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Bianchi L, Cangemi D, Farolfi A, Sgro CMP, Giorgio AD, Castellucci P, Gaudiano C, Corcioni B, Giunchi F, Degiovanni A, Pirelli V, Mignogna C, Rotaru V, Mottaran A, Piazza P, Droghetti M, Ragni M, Romei F, Mosconi C, Fiorentino M, Schiavina R, Fanti S, Brunocilla E. PSMA-Targeted Biopsy With Fusion Guidance for Detecting Clinically Significant Prostate Cancer in Men With Negative MRI-Feasibility and Diagnostic Performance of a Pilot Single-Center Prospective Study. Clin Genitourin Cancer 2025; 23:102348. [PMID: 40312220 DOI: 10.1016/j.clgc.2025.102348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2025] [Revised: 03/18/2025] [Accepted: 03/23/2025] [Indexed: 05/03/2025]
Abstract
INTRODUCTION Contemporary prostate biopsy utilizes multiparametric magnetic resonance (MRI) guidance; however, it may fail to identify a non-negligible proportion of men with clinically significant (csPCa). The main objective of this study was to assess the feasibility and diagnostic performance of Prostate Specific Membrane Antigen-Target biopsy (PSMA-TB) to diagnose csPCa in men with negative MRI and high clinical risk of PCa. PATIENTS AND METHODS Open-label, single-center, nonrandomized, prospective study. INCLUSION CRITERIA PSA density (PSAd) ≥0.2 ng/ml2 in men with PIRADS 1-2; PSA >10 ng/ml or abnormal digital rectal examination or strong familiar history for PCa or known genetic mutation. Each patients underwent PSMA-PET and transperineal fusion PSMA-TB ± systematic biopsy (SB). RESULTS Overall, 35 patients were enrolled; 23 (65.7%) men had positive PSMA-PET (PRIMARY score ≥3). Overall, 14 (40%) men had csPCA and 21 (60%) patients had any PCa at PSMA-TB+SB. Only 1 patient (8.3%) with negative PSMA-PET had csPCa (ISUP 3) at SB (92% Negative Predictive Value [NPV]). Fusion PSMA-TB alone detected csPCa in 12 out of 23 (52.2%) patients with positive PSMA-PET; fusion PSMA-TB with concomitant SB increased the detection of csPCa to 56.5% (added value of 4.3%). The sensitivity, specificity, Positive Predictive Value (PPV), NPV and AUC of PSMA-TB+SB were 93%, 57%, 59%, 92% and 0.75 for detection of csPCa and 91%, 79%, 86%, 95% and 0.84 for detection of any PCa, respectively. The main limitation of this study is its small sample size. CONCLUSIONS Fusion PSMA-TB is technically feasible and may improve the detection of csPCa in patients with negative MRI.
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Affiliation(s)
- Lorenzo Bianchi
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy.
| | - Danilo Cangemi
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Andrea Farolfi
- Nuclear Medicine, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | | | - Andrea Di Giorgio
- Nuclear Medicine, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Paolo Castellucci
- Nuclear Medicine, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Caterina Gaudiano
- Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Beniamino Corcioni
- Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Francesca Giunchi
- Department of Pathology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Alessio Degiovanni
- Department of Pathology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Valerio Pirelli
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Chiara Mignogna
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Valeria Rotaru
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Angelo Mottaran
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Pietro Piazza
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy
| | - Matteo Droghetti
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Matteo Ragni
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Francesco Romei
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Cristina Mosconi
- Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy
| | - Michelangelo Fiorentino
- Department of Pathology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy
| | - Riccardo Schiavina
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy
| | - Stefano Fanti
- Nuclear Medicine, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy
| | - Eugenio Brunocilla
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; University of Bologna, Bologna, Italy
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Zhou H, Xie M, Shi H, Shou C, Tang M, Zhang Y, Hu Y, Liu X. Integrating multimodal imaging and peritumoral features for enhanced prostate cancer diagnosis: A machine learning approach. PLoS One 2025; 20:e0323752. [PMID: 40373044 DOI: 10.1371/journal.pone.0323752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Accepted: 04/14/2025] [Indexed: 05/17/2025] Open
Abstract
BACKGROUND Prostate cancer is a common malignancy in men, and accurately distinguishing between benign and malignant nodules at an early stage is crucial for optimizing treatment. Multimodal imaging (such as ADC and T2) plays an important role in the diagnosis of prostate cancer, but effectively combining these imaging features for accurate classification remains a challenge. METHODS This retrospective study included MRI data from 199 prostate cancer patients. Radiomic features from both the tumor and peritumoral regions were extracted, and a random forest model was used to select the most contributive features for classification. Three machine learning models-Random Forest, XGBoost, and Extra Trees-were then constructed and trained on four different feature combinations (tumor ADC, tumor T2, tumor ADC+T2, and tumor + peritumoral ADC+T2). RESULTS The model incorporating multimodal imaging features and peritumoral characteristics showed superior classification performance. The Extra Trees model outperformed the others across all feature combinations, particularly in the tumor + peritumoral ADC+T2 group, where the AUC reached 0.729. The AUC values for the other combinations also exceeded 0.65. While the Random Forest and XGBoost models performed slightly lower, they still demonstrated strong classification abilities, with AUCs ranging from 0.63 to 0.72. SHAP analysis revealed that key features, such as tumor texture and peritumoral gray-level features, significantly contributed to the model's classification decisions. CONCLUSION The combination of multimodal imaging data with peritumoral features moderately improved the accuracy of prostate cancer classification. This model provides a non-invasive and effective diagnostic tool for clinical use and supports future personalized treatment decisions.
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Affiliation(s)
- Huadi Zhou
- Department of Radiology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
| | - Mei Xie
- Department of Radiology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
| | - Hemiao Shi
- Department of Radiology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
| | - Chenhan Shou
- Department of Radiology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
| | - Meng Tang
- Department of Pathology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
| | - Yue Zhang
- Department of Radiology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
| | - Yue Hu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiao Liu
- Department of Radiology, Zhejiang Hospital, Hangzhou, Zhejiang Province, China
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Xu J, Chen H, Chen L, Li T, Lin H, Bian S, Lin Q, Zhuang Y, Xue Y, Yang Y, Su X, Yao F. The predictive value of multiparametric MRI combined with [ 18F]PSMA-1007 PET/CT for the pathological upgrade in prostate cancer: a multicenter study. Eur J Nucl Med Mol Imaging 2025:10.1007/s00259-025-07311-1. [PMID: 40338303 DOI: 10.1007/s00259-025-07311-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2025] [Accepted: 04/23/2025] [Indexed: 05/09/2025]
Abstract
PURPOSE This study aimed to develop a predictive model that integrates parameters derived from preoperative multiparametric magnetic resonance imaging (mpMRI) and [18F]PSMA-1007 PET/CT for reliably predicting pathological upgrading from systematic biopsy (SB) to radical prostatectomy (RP) specimens. METHODS We ultimately retrospectively analyzed 163 patients with biopsy-confirmed localized prostate cancer (PCa) who underwent preoperative mpMRI and [18F]PSMA-1007 PET/CT scans between January 2019 and June 2022. Clinical and imaging characteristics were compared between patients with and without pathological upgrading. Predictive factors for pathological upgrading were evaluated through univariate and multivariable analyses. Predictive models were constructed based on the identified parameters. Receiver operating characteristic (ROC) curves were utilized to determine optimal cutoff values and to evaluate model performance. Additionally, patients from two external centers were selected as a validation cohort. RESULTS A total of 55 (33.7%) cases experienced pathological upgrading. Multivariate analysis revealed that ADCmean - ADCmin (P = 0.035); SUVmax (P = 0.003); highest tumor grade at SB, ISUP grade group (ISUP GG) 1 vs. 2 (P = 0.001), ISUP GG 1 vs. 3 (P < 0.001), ISUP GG 1 vs. 4 (P < 0.001); and multifocality on [18F]PSMA-1007 PET/CT (P = 0.007) were independent predictors for pathological upgrading. The combined model achieved an area under the curve (AUC) of 0.803 (95% CI: 0.734 to 0.861), indicating robust discriminative power. External validation confirmed the model's reliability and predictive ability. CONCLUSION Our predictive model, integrating mpMRI and [18F]PSMA-1007 PET/CT parameters, effectively forecasts pathological upgrading in PCa, allowing for more precise treatment risk stratification.
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Affiliation(s)
- Jian Xu
- The Department of Nuclear Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Haisong Chen
- The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Lixuan Chen
- The Department of Nuclear Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Tiancheng Li
- The Departments of Nuclear Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Heng Lin
- The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Shuying Bian
- The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Qi Lin
- The Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Yuandi Zhuang
- The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Yingnan Xue
- The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Yunjun Yang
- The Department of Nuclear Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Xinhui Su
- The Departments of Nuclear Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China.
| | - Fei Yao
- The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
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Russo T, Quarta L, Pellegrino F, Cosenza M, Camisassa E, Lavalle S, Apostolo G, Zaurito P, Scuderi S, Barletta F, Marzorati C, Stabile A, Montorsi F, De Cobelli F, Brembilla G, Gandaglia G, Briganti A. The added value of artificial intelligence using Quantib Prostate for the detection of prostate cancer at multiparametric magnetic resonance imaging. LA RADIOLOGIA MEDICA 2025:10.1007/s11547-025-02017-8. [PMID: 40332649 DOI: 10.1007/s11547-025-02017-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Accepted: 04/15/2025] [Indexed: 05/08/2025]
Abstract
PURPOSE Artificial intelligence (AI) has been proposed to assist radiologists in reporting multiparametric magnetic resonance imaging (mpMRI) of the prostate. We evaluate the diagnostic performance of radiologists with different levels of experience when reporting mpMRI with the support of available AI-based software (Quantib Prostate). MATERIAL AND METHODS This is a single-center study (NCT06298305) involving 110 patients. Those with a positive mpMRI (PI-RADS ≥ 3) underwent targeted plus systematic biopsy (TBx plus SBx), while those with a negative mpMRI but a high clinical suspicion of prostate cancer (PCa) underwent SBx. Three readers with different levels of experience, identified as R1, R2, and R3 reviewed all mpMRI. Inter-reader agreement among the three readers with or without the assistance of Quantib Prostate as well as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for the detection of clinically significant PCa (csPCa) were assessed. RESULTS 102 patients underwent prostate biopsy and the csPCa detection rate was 47%. Using Quantib Prostate resulted in an increased number of lesions identified for R3 (101 vs. 127). Inter-reader agreement slightly increased when using Quantib Prostate from 0.37 to 0.41 without vs. with Quantib Prostate, respectively. PPV, NPV and diagnostic accuracy (measured by the area under the curve [AUC]) of R3 improved (0.51 vs. 0.55, 0.65 vs.0.82 and 0.56 vs. 0.62, respectively). Conversely, no changes were observed for R1 and R2. CONCLUSIONS Using Quantib Prostate did not enhance the detection rate of csPCa for readers with some experience in prostate imaging. However, for an inexperienced reader, this AI-based software is demonstrated to improve the performance. TRIAL REGISTRATION Name of registry: clinicaltrials.gov. TRIAL REGISTRATION NUMBER NCT06298305. Date of registration: 2022-09.
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Affiliation(s)
- Tommaso Russo
- Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Leonardo Quarta
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy.
| | - Francesco Pellegrino
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
| | - Michele Cosenza
- Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Enrico Camisassa
- Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Salvatore Lavalle
- Department of Medicine and Surgery, University of Enna Kore, Enna, Italy
| | - Giovanni Apostolo
- Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Zaurito
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
| | - Simone Scuderi
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
| | - Francesco Barletta
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
| | - Clara Marzorati
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
| | - Armando Stabile
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
| | - Francesco Montorsi
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Francesco De Cobelli
- Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Giorgio Brembilla
- Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Giorgio Gandaglia
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Alberto Briganti
- Unit of Urology/Division of Oncology, Gianfranco Soldera Prostate Cancer Lab, URI, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
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Gelikman DG, Azar WS, Yilmaz EC, Lin Y, Shumaker LA, Fang AM, Harmon SA, Huang EP, Parikh SH, Hyman JA, Schuppe K, Nix JW, Galgano SJ, Merino MJ, Choyke PL, Gurram S, Wood BJ, Rais‐Bahrami S, Pinto PA, Turkbey B. A Prostate Imaging-Reporting and Data System version 2.1-based predictive model for clinically significant prostate cancer diagnosis. BJU Int 2025; 135:751-759. [PMID: 39654290 PMCID: PMC11975180 DOI: 10.1111/bju.16616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2025]
Abstract
OBJECTIVES To develop and validate a Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 (v2.1)-based predictive model for diagnosis of clinically significant prostate cancer (csPCa), integrating clinical and multiparametric magnetic resonance imaging (mpMRI) data, and compare its performance with existing models. PATIENTS AND METHODS We retrospectively analysed data from patients who underwent prospective mpMRI assessment using the PI-RADS v2.1 scoring system and biopsy at our institution between April 2019 and December 2023. A 'Clinical Baseline' model using patient demographics and laboratory results and an 'MRI Added' model additionally incorporating PI-RADS v2.1 scores and prostate volumes were created and validated on internal and external patients. Both models were compared against two previously published MRI-based algorithms for csPCa using area under the receiver operating characteristic curve (AUC) and decision curve analysis. RESULTS A total of 1319 patients across internal and external cohorts were included. Our 'MRI Added' model demonstrated significantly improved discriminative ability (AUCinternal 0.88, AUCexternal 0.79) compared to our 'Clinical Baseline' model (AUCinternal 0.75, AUCexternal 0.68) (P < 0.001). The 'MRI Added' model also showed higher net benefits across various clinical threshold probabilities and compared to a 'biopsy all' approach, it reduced unnecessary biopsies (defined as biopsies without Gleason Grade Group ≥2 csPCa) by 27% in the internal cohort and 10% in the external cohort at a risk threshold of 25%. However, there was no significant difference in predictive ability and reduction in unnecessary biopsies between our model and comparative ones developed for PI-RADS v2 and v1. CONCLUSION Our PI-RADS v2.1-based mpMRI model significantly enhances csPCa prediction, outperforming the traditional clinical model in accuracy and reduction of unnecessary biopsies. It proves promising across diverse patient populations, establishing an updated, integrated approach for detection and management of prostate cancer.
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Affiliation(s)
- David G. Gelikman
- Molecular Imaging Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - William S. Azar
- Urologic Oncology Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Enis C. Yilmaz
- Molecular Imaging Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Yue Lin
- Molecular Imaging Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Luke A. Shumaker
- Department of UrologyUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
| | - Andrew M. Fang
- Department of UrologyUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
| | - Stephanie A. Harmon
- Molecular Imaging Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Erich P. Huang
- Biometric Research Program, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Sahil H. Parikh
- Urologic Oncology Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Jason A. Hyman
- Urologic Oncology Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Kyle Schuppe
- Urologic Oncology Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Jeffrey W. Nix
- Department of UrologyUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
- O'Neal Comprehensive Cancer CenterUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
| | - Samuel J. Galgano
- O'Neal Comprehensive Cancer CenterUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
- Department of RadiologyUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
| | - Maria J. Merino
- Laboratory of Pathology, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Peter L. Choyke
- Molecular Imaging Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Sandeep Gurram
- Urologic Oncology Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Bradford J. Wood
- Center for Interventional Oncology, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
- Department of Radiology, Clinical CenterNational Institutes of HealthBethesdaMDUSA
| | - Soroush Rais‐Bahrami
- Department of UrologyUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
- O'Neal Comprehensive Cancer CenterUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
- Department of RadiologyUniversity of Alabama at Birmingham Heersink School of MedicineBirminghamALUSA
| | - Peter A. Pinto
- Urologic Oncology Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
| | - Baris Turkbey
- Molecular Imaging Branch, National Cancer InstituteNational Institutes of HealthBethesdaMDUSA
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Sun Z, Wang K, Gao G, Wang H, Wu P, Li J, Zhang X, Wang X. Assessing the Performance of Artificial Intelligence Assistance for Prostate MRI: A Two-Center Study Involving Radiologists With Different Experience Levels. J Magn Reson Imaging 2025; 61:2234-2245. [PMID: 39540567 DOI: 10.1002/jmri.29660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 10/22/2024] [Accepted: 10/22/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Artificial intelligence (AI) assistance may enhance radiologists' performance in detecting clinically significant prostate cancer (csPCa) on MRI. Further validation is needed for radiologists with different experiences. PURPOSE To assess the performance of experienced and less-experienced radiologists in detecting csPCa, with and without AI assistance. STUDY TYPE Retrospective. POPULATION Nine hundred patients who underwent prostate MRI and biopsy (median age 67 years; 356 with csPCa and 544 with non-csPCa). FIELD STRENGTH/SEQUENCE 3-T and 1.5-T, diffusion-weighted imaging using a single-shot gradient echo-planar sequence, turbo spin echo T2-weighted image. ASSESSMENT CsPCa regions based on biopsy results served as the reference standard. Ten less-experienced (<500 prostate MRIs) and six experienced (>1000 prostate MRIs) radiologists reviewed each case twice using Prostate Imaging Reporting and Data System v2.1, with and without AI, separated by 4-week intervals. Cases were equally distributed among less-experienced radiologists, and 90 cases were randomly assigned to each experienced radiologist. Reading time and diagnostic confidence were assessed. STATISTICAL TESTS Area under the curve (AUC), sensitivity, specificity, reading time, and diagnostic confidence were compared using the DeLong test, Chi-squared test, Fisher exact test, or Wilcoxon rank-sum test between the two sessions. A P-value <0.05 was considered significant. Adjusting threshold using Bonferroni correction was performed for multiple comparisons. RESULTS For less-experienced radiologists, AI assistance significantly improved lesion-level sensitivity (0.78 vs. 0.88), sextant-level AUC (0.84 vs. 0.93), and patient-level AUC (0.84 vs. 0.89). For experienced radiologists, AI assistance only improved sextant-level AUC (0.82 vs. 0.91). AI assistance significantly reduced median reading time (250 s [interquartile range, IQR: 157, 402] vs. 130 s [IQR: 88, 209]) and increased diagnostic confidence (5 [IQR: 4, 5] vs. 5 [IQR: 4, 5]) irrespective of experience and enhanced consistency among experienced radiologists (Fleiss κ: 0.53 vs. 0.61). DATA CONCLUSION AI-assisted reading improves the performance of detecting csPCa on MRI, particularly for less-experienced radiologists. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zhaonan Sun
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Kexin Wang
- School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - Ge Gao
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Huihui Wang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Pengsheng Wu
- Beijing Smart Tree Medical Technology Co. Ltd, Beijing, China
| | - Jialun Li
- Beijing Smart Tree Medical Technology Co. Ltd, Beijing, China
| | - Xiaodong Zhang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Xiaoying Wang
- Department of Radiology, Peking University First Hospital, Beijing, China
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Pylväläinen J, Talala K, Raitanen J, Rannikko A, Auvinen A. Association of prostate-specific antigen density with prostate cancer mortality after a benign systematic prostate biopsy result. BJU Int 2025; 135:841-850. [PMID: 39840544 PMCID: PMC11975165 DOI: 10.1111/bju.16641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2025]
Abstract
OBJECTIVE To assess the association between prostate-specific antigen (PSA) density (PSAD) and prostate cancer mortality after a benign result on systematic transrectal ultrasonography (TRUS)-guided prostate biopsy. PATIENTS AND METHODS This retrospective study used data from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC) collected between 1996 and 2020. We identified men aged 55-71 years randomised to the screening arm with PSA ≥4.0 ng/mL and a benign systematic TRUS-guided biopsy result. The cumulative prostate cancer mortality of men stratified by a PSAD cutoff of 0.15 ng/mL/cm3 was modelled with competing risk functions. The ability of PSAD, PSA, and base variables (age at biopsy, DRE result, socioeconomic status, 5α-reductase inhibitor usage, family history, and Charlson Comorbidity Index (CCI)) to predict prostate cancer death was compared using c-statistics and a likelihood ratio test. RESULTS After excluding 10 men without PSA data within 2 years of the biopsy and 65 without prostate volume data, 2276 men were eligible for inclusion in the study. A total of 50 men died from prostate cancer and 1028 from other causes during a median (interquartile range) follow-up of 17.4 (13.2-20.9) years. The cumulative prostate cancer mortality of men with PSAD <0.15 ng/mL/cm3 was significantly lower than that of men with PSAD ≥0.15 ng/mL/cm3: 0.5% (95% confidence interval [CI] 0.2%-1.1%) vs 2.0% (95% CI 1.2%-3.1%) at 15 years (Grey's test, P = 0.001). The model consisting of PSAD, PSA and the base variables predicted prostate cancer mortality (c-statistic 0.781) significantly better than either the base variables alone (c-statistic 0.737; likelihood-ratio test, P = 0.003) or the base variables and PSA (c-statistic 0.765; likelihood-ratio test, P = 0.039). CONCLUSION Prostate cancer mortality after a benign systematic TRUS-guided biopsy is low. In these patients, PSAD predicts prostate cancer mortality and provides additional value to other clinical variables. PSAD-based stratification can be used to guide follow-up strategy.
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Affiliation(s)
- Juho Pylväläinen
- Department of Radiology, HUS Diagnostic CentreHelsinki University HospitalHelsinkiFinland
- Research Program in Systems Oncology, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
| | | | - Jani Raitanen
- Faculty of Social Sciences (Health Sciences), Prostate Cancer Research CenterTampere UniversityTampereFinland
- UKK Institute for Health Promotion ResearchTampereFinland
| | - Antti Rannikko
- Department of UrologyHelsinki University HospitalHelsinkiFinland
- Research Program in Systems Oncology, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
| | - Anssi Auvinen
- Faculty of Social Sciences (Health Sciences), Prostate Cancer Research CenterTampere UniversityTampereFinland
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8
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Baseilhac P, Romain-Scelle N, Klich A, Crouzet S, Colombel M, Ruffion A, Rabilloud M, Rouvière O. Relaxing the PI-RADS dominant sequence rule improves the characterization of high-grade prostate cancer on multiparametric MRI. Diagn Interv Imaging 2025:S2211-5684(25)00074-9. [PMID: 40246599 DOI: 10.1016/j.diii.2025.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2024] [Revised: 03/30/2025] [Accepted: 04/08/2025] [Indexed: 04/19/2025]
Abstract
PURPOSE The Prostate Imaging-Reporting and Data System 2.0 (PI-RADSv2.0) and 2.1 (PI-RADSv2.1) scores are deduced from the pulse sequence categories using the "dominant sequence" scoring rule. The purpose of this study was to develop and evaluate a new scoring rule that makes better use of non-dominant pulse sequence findings. MATERIAL AND METHODS The new scoring rule was developed using a single-center database of 1627 patients who underwent prostate multiparametric MRI and prostate biopsy. The combinations of PI-RADSv2.0 pulse sequence categories observed at sextant level were ranked based on their rate of high-grade (grade group ≥ 2) prostate cancer and assigned to one of the five levels of the new score. Then, a hidden evaluation dataset of 240 MRI lesions to which 21 readers of varying experience had assigned PI-RADSv2.1 pulse sequence categories was used. For each reader, the PI-RADSv2.1 score of the lesions (PI-RADSv2.1 dominant sequence rule) and the new score (scoring rule defined in the development cohort) were computed. The scores were compared using areas under the curve (AUC), sensitivities, specificities, reproducibility, and clinical utility. RESULTS Across all readers, the mean AUC of the new score (0.78; 95 % confidence interval [CI]: 0.73-0.83) was significantly greater than that of the PI-RADSv2.1 score (0.76; 95 % CI: 0.71-0.81; P < 0.01). The new score showed lower sensitivity, higher specificity and better inter-reader agreement in all reader experience subgroups. Across all readers, for a ≥ 3 dichotomization, it provided a higher net benefit than the PIRADSv2.1 score for risk thresholds > 0.15. CONCLUSION The new scoring rule outperformed the dominant sequence rule in characterizing high-grade prostate cancer regardless of reader experience.
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Affiliation(s)
- Pierre Baseilhac
- Hospices Civils de Lyon, Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Lyon, 69437, France; Université Lyon 1, Lyon, 69003, France
| | - Nicolas Romain-Scelle
- Université Lyon 1, Lyon, 69003, France; Pôle Santé Publique, Service de Biostatistique et Bioinformatique, Hospices Civils de Lyon, Lyon, 69003, France; CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, Équipe Biostatistique-Santé, Villeurbanne, 69100, France
| | - Amna Klich
- Pôle Santé Publique, Service de Biostatistique et Bioinformatique, Hospices Civils de Lyon, Lyon, 69003, France
| | - Sébastien Crouzet
- Université Lyon 1, Lyon, 69003, France; Hospices Civils de Lyon, Department of Urology, Hôpital Edouard Herriot, Lyon, 69437, France; INSERM, U1032, LabTau, Lyon, 69003, France
| | - Marc Colombel
- Université Lyon 1, Lyon, 69003, France; Hospices Civils de Lyon, Department of Urology, Hôpital Edouard Herriot, Lyon, 69437, France
| | - Alain Ruffion
- Université Lyon 1, Lyon, 69003, France; Hospices Civils de Lyon, Department of Urology, Centre Hospitalier Lyon Sud, Pierre Bénite, 69310, France
| | - Muriel Rabilloud
- Université Lyon 1, Lyon, 69003, France; Pôle Santé Publique, Service de Biostatistique et Bioinformatique, Hospices Civils de Lyon, Lyon, 69003, France; CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, Équipe Biostatistique-Santé, Villeurbanne, 69100, France
| | - Olivier Rouvière
- Hospices Civils de Lyon, Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Lyon, 69437, France; Université Lyon 1, Lyon, 69003, France; INSERM, U1032, LabTau, Lyon, 69003, France.
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9
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Kohada Y, Miyamoto S, Hayashi T, Tasaka R, Honda Y, Ishikawa A, Kobatake K, Sekino Y, Kitano H, Goto K, Ikeda K, Goriki A, Hieda K, Kitamura N, Awai K, Hinata N. Utility of tumor diameter-to-prostate volume ratio for predicting the outcome of magnetic resonance imaging/transrectal ultrasound fusion-targeted biopsy. Urol Oncol 2025:S1078-1439(25)00121-8. [PMID: 40234138 DOI: 10.1016/j.urolonc.2025.03.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 03/03/2025] [Accepted: 03/14/2025] [Indexed: 04/17/2025]
Abstract
OBJECTIVES To assess the impact of the tumor diameter-to-prostate volume ratio (TD/PV) on predicting prostate cancer (PCa) and clinically significant (cs) -PCa in magnetic resonance imaging (MRI) /transrectal ultrasound (TRUS) fusion-targeted biopsy based on prostate imaging-reporting and data system (PI-RADS) findings in MRI. MATERIALS AND METHODS Patients who underwent MRI/TRUS fusion-targeted biopsy for PI-RADS version 2.1 categories 3-5 lesions between 2017 and 2023 were retrospectively reviewed. TD/PV was calculated by dividing the tumor diameter by the total prostate volume. csPCa was defined as a Gleason score of ≥ 3 + 4. Univariable and multivariable logistic regression analyses were used to develop predictive nomograms for PCa and csPCa. A receiver operating characteristic curve was constructed to evaluate the predictive ability of the factors using the area under the curve (AUC). RESULTS A total of 565 patients were analyzed; the AUC of TD/PV was significantly superior to those of the prostate-specific antigen (PSA), tumor diameter, PSA density, and PI-RADS for predicting PCa (AUC: 0.840, P < 0.05) and csPCa (AUC: 0.819, P < 0.05). Multivariable analyses showed that TD/PV is a significant predictive factor for PCa and csPCa in MRI/TRUS fusion-targeted biopsy (P < 0.05). The predictive nomograms combining TD/PV and PI-RADS category were constructed and their AUCs for predicting PCa and csPCa were 0.861 and 0.845, respectively. CONCLUSIONS In this retrospective analysis, prediction of PCa and csPCa on MRI/TRUS fusion-targeted biopsy was improved when TD/PV was combined with PI-RADS category.
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Affiliation(s)
- Yuki Kohada
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Shunsuke Miyamoto
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan.
| | - Tetsutaro Hayashi
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Ryo Tasaka
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Yukiko Honda
- Department of Diagnostic Radiology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Akira Ishikawa
- Department of Molecular Pathology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Kohei Kobatake
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Yohei Sekino
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Hiroyuki Kitano
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Keisuke Goto
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Kenichiro Ikeda
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Akihiro Goriki
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Keisuke Hieda
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | | | - Kazuo Awai
- Department of Diagnostic Radiology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
| | - Nobuyuki Hinata
- Department of Urology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan
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10
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Qin F, Wu J, Ma J, Tian S, Li D, Chen S, Liu Y, Li X. Novel ultrasound scoring system to guide cognitive fusion-targeted biopsy: a prospective study. Abdom Radiol (NY) 2025:10.1007/s00261-025-04903-1. [PMID: 40220167 DOI: 10.1007/s00261-025-04903-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2024] [Revised: 02/23/2025] [Accepted: 03/16/2025] [Indexed: 04/14/2025]
Abstract
PURPOSE To develop and validate a novel ultrasound scoring system (USS) for assisting cognitive fusion-targeted biopsy (cTB). METHODS We prospectively collected a study cohort consisting of 452 patients with biopsy-naïve, PSA ≤ 20 ng/ml and their 531 Prostate Imaging Reporting and Data System (PI-RADS) v2.1 ≥ 3 lesions. All MRI regions of interest were scored as USS 0, 1, 2, and 3 for the corresponding lesion or region on TRUS. The cumulative cancer detection rate of the biopsy cores was assessed according to USS. Subgroup analysis was conducted to assess the csPCa detection rate following the re-stratification of PI-RADS using USS. Receiver operating characteristics (ROC) analysis was performed for USS, PI-RADS and USS + PI-RADS. The area under the curve (AUC), sensitivity, and specificity were calculated at the cut-off selected by the Youden index. RESULTS The overall cancer detection rates for USS scores of 0 to 3 were 0% (0/67), 66% (111/166), 83% (176/210), and 100% (59/59), respectively. For USS 2 and USS 3 lesions, the detection rates in targeting the 3rd core (79%, P = 0.774) and 2nd core (93%, P = 0.125) did not significantly increase with subsequent biopsy cores. In the subgroup analysis, the csPCa positive rate for USS 0 was zero across all PI-RADS categories. In contrast, USS 1, 2, and 3 enhanced the csPCa positive rate within each PI-RADS strata. In ROC analysis, the AUC (95% CI) for the combined USS + PI-RADS 0.85 (0.82-0.89) outperformed PI-RADS 0.77 (0.73-0.81) alone (P < 0.001). USS + PI-RADS sensitivity (95% CI) was 80.7% (75.6-84.9) compared to PI-RADS 72.5% (67.6-77.0). CONCLUSION In cTB, USS has good performance in cancer risk re-stratification, with higher USS scores correlating with an increased likelihood of cancer and improved diagnostic accuracy. CLINICAL TRIAL REGISTRATION No. 2023-272-002, July 14, 2023.
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Affiliation(s)
- Fei Qin
- Peking University First Hospital, Beijing, China
- The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jingyun Wu
- Peking University First Hospital, Beijing, China
| | - Jianguo Ma
- The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | | | - Derun Li
- Peking University First Hospital, Beijing, China
| | - Shuyuan Chen
- Peking University First Hospital, Beijing, China
| | - Yi Liu
- Peking University First Hospital, Beijing, China.
| | - Xuesong Li
- Peking University First Hospital, Beijing, China.
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11
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Lu F, Zhao Y, Wang Z, Feng N. Biparametric MRI-based radiomics for prediction of clinically significant prostate cancer of PI-RADS category 3 lesions. BMC Cancer 2025; 25:615. [PMID: 40188349 PMCID: PMC11972529 DOI: 10.1186/s12885-025-14022-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Accepted: 03/26/2025] [Indexed: 04/07/2025] Open
Abstract
PURPOSE We aimed to investigate the diagnostic performance of biparametric MRI (bpMRI)-based radiomics in differentiating clinically significant prostate cancer (csPCa) among lesions categorized as Prostate Imaging Reporting and Data System (PI-RADS) score 3. METHOD Between September 2020 and October 2023, a total of 233 patients with PI-RADS category 3 lesions were identified, which were divided into training cohort (n = 160) and validation cohort (n = 73). Radiomics features were extracted from T2-weighted imaging (T2) and diffusion-weighted imaging (DWI) for csPCa prediction. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to select the most useful radiomics features. Diagnostic performance was compared using the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS 34 robust radiomics features (incorporating 12 features from T2 and 22 features from DWI) were selected to construct the final radiomics signature. In the training group, the AUCs for prostate-specific antigen density (PSAD), radiomics, and combination were 0.658 (95% CI 0.550-0.766), 0.858 (95% CI 0.779-0.936), and 0.887 (95% CI 0.814-0.959), respectively, in the validation group were 0.690 (95% CI 0.524-0.855), 0.810 (95% CI 0.682-0.937), and 0.856 (95% CI 0.750-0.962). The combination model integrating radiomics and PSAD showed a significant improvement in diagnostic performance as compared to using these two parameters alone either in the training group (P < 0.001 and P = 0.024) or in the validation group (P = 0.024 and P = 0.048). CONCLUSION BpMRI-based radiomics had high diagnostic performance in predicting csPCa among PI-RADS 3 lesions, and combining it with PSAD could further improve the overall accuracy.
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Affiliation(s)
- Feng Lu
- Department of Radiology, Jiangnan University Medical Center, Wuxi, China
- Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Yanjun Zhao
- Department of Radiology, Jiangnan University Medical Center, Wuxi, China
| | - Zhongjuan Wang
- Department of Radiology, Jiangnan University Medical Center, Wuxi, China
| | - Ninghan Feng
- Department of Urological Surgical, Jiangnan University Medical Center, Wuxi, China.
- Wuxi School of Medicine, Jiangnan University, Wuxi, China.
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12
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Thijssen LCP, Twilt JJ, Barrett T, Giganti F, Schoots IG, Engels RRM, Broeders MJM, Barentsz JO, de Rooij M. Quality of prostate MRI in early diagnosis-a national survey and reading evaluation. Insights Imaging 2025; 16:82. [PMID: 40188300 PMCID: PMC11972232 DOI: 10.1186/s13244-025-01960-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2024] [Accepted: 03/25/2025] [Indexed: 04/07/2025] Open
Abstract
OBJECTIVES The reliability of image-based recommendations in the prostate cancer pathway is partially dependent on prostate MRI image quality. We evaluated the current compliance with PI-RADSv2.1 technical recommendations and the prostate MRI image quality in the Netherlands. To aid image quality improvement, we identified factors that possibly influence image quality. MATERIALS AND METHODS A survey was sent to 68 Dutch medical centres to acquire information on prostate MRI acquisition. The responding medical centres were requested to provide anonymised prostate MRI examinations of biopsy-naive men suspected of prostate cancer. The images were evaluated for quality by three expert prostate radiologists. The compliance with PI-RADSv2.1 technical recommendations and the PI-QUALv2 score was calculated. Relationships between hardware, education of personnel, technical parameters, and/or patient preparation and both compliance and image quality were analysed using Pearson correlation, Mann-Whitney U-test, or Student's t-test where appropriate. RESULTS Forty-four medical centres submitted their compliance with PI-RADSv2.1 technical recommendations, and 26 medical centres completed the full survey. Thirteen hospitals provided 252 usable images. The mean compliance with technical recommendations was 79%. Inadequate PI-QUALv2 scores were given in 30.9% and 50.6% of the mp-MRI and bp-MRI examinations, respectively. Multiple factors with a possible relationship with image quality were identified. CONCLUSION In the Netherlands, the average compliance with PI-RADSv2.1 technical recommendations is high. Prostate MRI image quality was inadequate in 30-50% of the provided examinations. Many factors not covered in the PI-RADSv2.1 technical recommendations can influence image quality. Improvement of prostate MRI image quality is needed. CRITICAL RELEVANCE STATEMENT It is essential to improve the image quality of prostate MRIs, which can be achieved by addressing factors not covered in the PI-RADSv2.1 technical recommendations. KEY POINTS Prostate MRI image quality influences the diagnostic accuracy of image-based decisions. Thirty to fifty percent of Dutch prostate MRI examinations were of inadequate image quality. We identified multiple factors with possible influence on image quality.
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Affiliation(s)
- Linda C P Thijssen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Jasper J Twilt
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Ivo G Schoots
- Department of Radiology & Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Rianne R M Engels
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mireille J M Broeders
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Maarten de Rooij
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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13
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Sridhar S, Abouelfetouh Z, Codreanu I, Gupta N, Zhang S, Efstathiou E, Karolyi DK, Shen SS, LaViolette PS, Miles B, Martin DR. The Role of Dynamic Contrast Enhanced Magnetic Resonance Imaging in Evaluating Prostate Adenocarcinoma: A Partially-Blinded Retrospective Study of a Prostatectomy Patient Cohort With Whole Gland Histopathology Correlation and Application of PI-RADS or TNM Staging. Prostate 2025; 85:413-423. [PMID: 39702937 PMCID: PMC11848987 DOI: 10.1002/pros.24843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Accepted: 11/11/2024] [Indexed: 12/21/2024]
Abstract
BACKGROUND Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in the current Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS v2.1) is considered optional, with primary scoring based on T2-weighted imaging (T2WI) and diffusion weighted imaging (DWI). Our study is designed to assess the relative contribution of DCE MRI in a patient-cohort with whole mount prostate histopathology and spatially-mapped prostate adenocarcinoma (PCa) for reference. METHODS We performed a partially-blinded retrospective review of 47 prostatectomy patients with recent multi-parametric MRI (mpMRI). Scans included T2WI, DWI with apparent diffusion coefficient (ADC) mapping, and DCE imaging. Lesion conspicuity was scored on a 10-point scale with ≥ 6 considered "positive," and image quality was assessed on a 4-point scale for each sequence. The diagnostic contribution of DCE images was evaluated on a 4-point scale. The mpMRI studies were assigned PI-RADS scores and tumor, node, metastasis (TNM) T-stage with blinded comparison to spatially-mapped whole-mount pathology. Results were compared to the prospective clinical reports, which used standardized PI-RADS templates that emphasize T2WI, DWI and ADC. RESULTS Per lesion sensitivity for PCa was 93.5%, 82.6%, 63.0%, and 58.7% on T2WI, DCE, ADC and DWI, respectively. Mean lesion conspicuity was 8.5, 7.9, 6.2, and 6.1, on T2W, DCE, ADC and DWI, respectively. The higher values on T2WI and DCE imaging were not significantly different from each other but were both significantly different from DWI and ADC (p < 0.001). DCE scans were determined to have a marked diagnostic contribution in 83% of patients, with the most common diagnostic yield being detection of contralateral peripheral zone tumor or delineating presence/absence of extra-prostatic extension (EPE), contributing to more accurate PCa staging by PI-RADS or TNM, as compared to histopathology. CONCLUSION We demonstrate that DCE may contribute to lesion detection and local staging as compared to T2WI plus DWI-ADC alone and that lesion conspicuity using DCE is markedly improved as compared to DWI-ADC. These findings support modification of PI-RADS v2.1 to include use of DCE acquisitions and that a TNM staging is feasible on mpMRI as compared to surgical pathology.
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Affiliation(s)
- Sajeev Sridhar
- Department of RadiologyHouston Methodist Research InstituteHoustonTexasUSA
| | - Zeyad Abouelfetouh
- Department of RadiologyHouston Methodist Research InstituteHoustonTexasUSA
| | - Ion Codreanu
- Department of Radiology, Houston Methodist Research InstituteNicolae Testemițanu State University of Medicine and PharmacyChișinăuMoldova
| | - Nakul Gupta
- Department of Radiology, Houston Methodist Hospital, Houston Methodist Research InstituteHouston Radiology AssociatedHoustonTexasUSA
| | - Shu Zhang
- Department of RadiologyHouston Methodist Research InstituteHoustonTexasUSA
| | - Eleni Efstathiou
- Department of Medicine, Houston Methodist HospitalHouston Methodist Oncology PartnersHoustonTexasUSA
| | - Daniel K. Karolyi
- Department of RadiologyVirginia Tech Carilion School of MedicineRoanokeVirginiaUSA
| | - Steven S. Shen
- Department of Pathology, Houston Methodist HospitalHouston Methodist Research InstituteHoustonTexasUSA
| | | | - Brian Miles
- Department of Urology, Houston Methodist HospitalHouston Methodist Urology AssociatesHoustonTexasUSA
| | - Diego R. Martin
- Department of Pathology, Houston Methodist HospitalHouston Methodist Research InstituteHoustonTexasUSA
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14
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Abbadi A, Eklund M, Lantz A, Discacciati A, Björnebo L, Palsdottir T, Chandra Engel J, Jäderling F, Falagario U, Grönberg H, Nordström T. Evaluating the performance of existing tools to predict clinically significant prostate cancer in men with indeterminate lesions on biparametric MRI and development of a novel multiplex model: a prospective cohort study. EClinicalMedicine 2025; 82:103191. [PMID: 40242565 PMCID: PMC12002877 DOI: 10.1016/j.eclinm.2025.103191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2024] [Revised: 03/17/2025] [Accepted: 03/20/2025] [Indexed: 04/18/2025] Open
Abstract
Background Indeterminate lesions on prostate MRI, such as PI-RADS 3, present a clinical challenge due to their equivocal nature, complicating biopsy decisions in men undergoing testing for prostate cancer. Understanding the predictive capacity of biomarkers and risk calculators is critical to improve clinical decision-making and reduce unnecessary biopsies. Methods In this prospective cohort study, men with PI-RADS 3 findings on biparametric MRI (bp-MRI) who underwent combined biopsy (fusion targeted and systematic) in the STHLM3-MRI randomised clinical trial (first- and second-rounds) and at Capio St Göran's Hospital (Capio PCC), Sweden were included, representing screening-by-invitation, repeat screening, and clinical practice cohorts, respectively. Data collection occurred between Feb 5th, 2018, and Mar 4th, 2020, for STHLM3-MRI first-round screening, between Nov 10th, 2021, and Feb 20th, 2023 for second-round screening, and between Jan 7th, 2017 and June 30th, 2023 for Capio PCC. The data was collected directly from the participating laboratories using standardized reporting forms, medical charts, and additional study-specific data collection forms filled by patients. The primary outcome was detection of clinically significant prostate cancer (csPCa; ISUP ≥2) in men with PSA ≥3 ng/mL confirmed by the combined biopsy. The predictive capacity of the evaluated biomarkers (PSA density, the Stockholm3 test, prostate volume, MRI lesion volume ratio, and Stockholm3 density), as well as seven risk calculators, was assessed via the area under the curve (AUC) computed using logistic regression. Sensitivity and specificity of detecting csPCa and high-grade prostate cancer (ISUP ≥3) were reported. Complete-case analysis was performed for men with complete data on their PSA, prostate volume, Stockholm3 test, MRI lesion volume, findings on the digital rectal examination, family history of prostate cancer, and previous biopsy. The findings were contrasted to the analysis from the imputed dataset. Findings Of the 6554 men included into the three cohorts, 1187 received PI-RADS score of 3 on the bp-MRI, and 1146 underwent combined biopsy. Of them, 900 had PSA ≥3 ng/mL, and 656 men were included in the complete-case analysis (169 from STHLM3-MRI first-round, 72 from the second-round, and 415 from Capio PCC). Overall, 370/900 men (41%) and 258/656 men (39%) had ISUP ≥2, but only 75/900 (8%) and 50/656 (8%) had ISUP ≥3. PSA density, tested risk calculators, and probability tests had low-to-moderate AUC (range 0.50-0.73; PSA density range 0.58-0.66, Stockholm3 range 0.59-0.67, lesion volume ratio range 0.54-0.63), and performed similarly across individual cohorts and the combined dataset in the complete-case and imputed dataset analysis. For detection of ISUP ≥2 based on STHLM3-MRI first-round, PSA density at 0.10 had a sensitivity of 69% (56%, 80%), specificity of 49% (39%, 58%), and missing 27% (6%, 61%) of ISUP ≥3, while a PSA density of 0.15 had a sensitivity of 37% (25%, 50%), specificity of 84% (76%, 90%), missing 45% (17%, 70%) of ISUP ≥3. The best-performing model based on STHLM3-MRI included age, prostate volume, Stockholm3 density and MRI lesion ratio, and reduced prostate biopsies by 33% (26%, 40%) while maintaining 98% (91%, 100%) sensitivity to detect ISUP ≥2 cancer, specificity of 50% (41%, 60%) and AUC of 0.82 (0.76, 0.87). Meanwhile, the best-performing model based on the complete-case combined dataset included age, prostate volume, PSA density, and Stockholm3 density, and reduce prostate biopsies by 26% (23%, 30%) with a sensitivity of 90% (85%, 93%), specificity of 36% (31%, 41%), and AUC of 0.70 (0.66, 0.74). Interpretation Current risk-stratification tools and individual biomarkers perform suboptimally for guiding biopsy decisions in men with PI-RADS 3 lesions. The findings highlight the limitations of relying on PSA density alone and emphasize the need for caution in clinical recommendations. However, multiplex models might offer possibility to reduce unnecessary biopsies while maintaining high sensitivity for clinically significant prostate cancer detection. These findings should be externally validated and evaluated for cost-effectiveness. Funding STHLM3-MRI clinical trial is funded by the Swedish Cancer Society (Cancerfonden), the Swedish Research Council (Vetenskapsrådet), the Swedish Research Council for Health Working Life and Welfare (FORTE), the Strategic Research Programme on Cancer (StratCan), Hagstrandska Minnesfonden, Region Stockholm, Svenska Druidorden, Åke Wibergs Stiftelse, the Swedish e-Science Research Centre, the Karolinska Institutet, and Prostatacancerförbundet.
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Affiliation(s)
- Ahmad Abbadi
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Martin Eklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Anna Lantz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
- Department of Molecular Medicine and Surgery (Solna), Karolinska Institutet, Stockholm, Sweden
| | - Andrea Discacciati
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Lars Björnebo
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Thorgerdur Palsdottir
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Jan Chandra Engel
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
- Department of Clinical Sciences at Danderyds Hospital, Karolinska Institutet, Solna, Sweden
| | - Fredrik Jäderling
- Department of Molecular Medicine and Surgery (Solna), Karolinska Institutet, Stockholm, Sweden
- Department of Radiology, Capio S:t Görans Hospital, Stockholm, Sweden
| | - Ugo Falagario
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
- Department of Urology and Kidney Transplantation, University of Foggia, Foggia, Italy
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
- Department of Oncology, Capio S:t Görans Hospital, Stockholm, Sweden
| | - Tobias Nordström
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
- Department of Clinical Sciences at Danderyds Hospital, Karolinska Institutet, Solna, Sweden
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Setya N, Ghagane SC, Nerli RB, Bokare A, Thakur ML, Gomella L. VPAC receptor positivity in comparison with mp-MRI in the diagnosis of prostate cancer: A preliminary study. BJUI COMPASS 2025; 6:e70006. [PMID: 40264829 PMCID: PMC12012386 DOI: 10.1002/bco2.70006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Revised: 01/27/2025] [Accepted: 02/05/2025] [Indexed: 04/24/2025] Open
Abstract
Objective The study aimed to prospectively evaluate the feasibility of diagnosing PCa using voided urine samples and by targeting the genomic VPAC (vasoactive intestinal peptide and pituitary adenylate cyclase-activating peptide) receptors in comparison with multiparametric magnetic resonance imaging (mp-MRI) in male patients (≥40 years of age) with lower urinary tract symptoms and having a serum PSA of >4 but <15 ng/ml. Patients and Methods Male patients attending urological services ≥40 years old, with lower urinary tract symptoms and serum PSA levels of >4 but <15 ng/ml formed the study group. Voided urine samples were collected to target VPAC receptors on malignant cells. All patients underwent mp-MRI. A 12-core transrectal ultrasound-guided prostate biopsy was performed in all, and the results were compared for the diagnosis of PCa. Results A total of 61 patients with a median age of 65.33 ± 8.11 years and with a median serum PSA of 9.56 ± 2.78 ng/ml were further evaluated with both urinary biomarker assessment and mp-MRI. Histopathological (HPR) confirmation of PCa was noted in 25 (40.98%) patients and benign prostatic hyperplasia in the remaining 36 (59.01%) patients. Of the 25 patients with histologically proven PCa, the urinary biomarker (VPAC positivity) was positive for malignancy in 24 (96%), one case showed false negative results (4%) and there were no false positive cases (0%). HPR confirming PCa was seen in 3/16 patients with a PIRADS 2 score, 7/21 patients with a PIRADS 3 score, 7/14 patients with a PIRADS 4 score and 8/8 patients with a PIRADS score of 5. Conclusions VPAC receptor positivity of prostate cancer cells is an easy test to perform using a voided urine sample. VPAC receptor positivity can be used as an indication for prostate biopsy in patients having a negative previous biopsy but highly suspicious of cancer, in patients with an elevated serum PSA but with a normal digital rectal examination and in patients with benign features and borderline elevation of serum PSA.
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Affiliation(s)
- Nishant Setya
- Department of Urology, J.N. Medical CollegeKLE Academy of Higher Education and Research (Deemed‐to‐be‐University)BelagaviIndia
| | - Shridhar C. Ghagane
- KAHER's Dr. Prabhakar Kore Basic Science Research CenterKLE Academy of Higher Education and Research (Deemed‐to‐be‐University)BelagaviIndia
- Division of Urologic‐oncology, Urinary Biomarkers Research CentreKLES Dr. Prabhakar Kore Hospital and Medical Research CentreBelagaviIndia
| | - Rajendra B. Nerli
- Department of Urology, J.N. Medical CollegeKLE Academy of Higher Education and Research (Deemed‐to‐be‐University)BelagaviIndia
- Division of Urologic‐oncology, Urinary Biomarkers Research CentreKLES Dr. Prabhakar Kore Hospital and Medical Research CentreBelagaviIndia
| | - Ashwin Bokare
- Department of Urology, J.N. Medical CollegeKLE Academy of Higher Education and Research (Deemed‐to‐be‐University)BelagaviIndia
| | - Madhukar L. Thakur
- Departments of Urology, RadiologyThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
- Departments of UrologyThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
- Sidney Kimmel Cancer CentreThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
| | - Leonard Gomella
- Departments of UrologyThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
- Sidney Kimmel Cancer CentreThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
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Shiraishi K, Nakaura T, Kobayashi N, Uetani H, Nagayama Y, Kidoh M, Yatsuda J, Kurahashi R, Kamba T, Yamahita Y, Hirai T. Enhancing thin slice 3D T2-weighted prostate MRI with super-resolution deep learning reconstruction: Impact on image quality and PI-RADS assessment. Magn Reson Imaging 2025; 117:110308. [PMID: 39667642 DOI: 10.1016/j.mri.2024.110308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 11/28/2024] [Accepted: 12/09/2024] [Indexed: 12/14/2024]
Abstract
PURPOSES This study aimed to assess the effectiveness of Super-Resolution Deep Learning Reconstruction (SR-DLR) -a deep learning-based technique that enhances image resolution and quality during MRI reconstruction- in improving the image quality of thin-slice 3D T2-weighted imaging (T2WI) and Prostate Imaging-Reporting and Data System (PI-RADS) assessment in prostate Magnetic Resonance Imaging (MRI). METHODS This retrospective study included 33 patients who underwent prostate MRI with SR-DLR between November 2022 and April 2023. Thin-slice 3D-T2WI of the prostate was obtained and reconstructed with and without SR-DLR (matrix: 720 × 720 and 240 × 240, respectively). We calculated the contrast and contrast-to-noise ratio (CNR) between the internal and external glands of the prostate, as well as the slope of pelvic bone and adipose tissue. Two radiologists evaluated qualitative image quality and assessed PI-RADS scores of each reconstruction. RESULTS The final analysis included 28 male patients (age range: 47-88 years; mean age: 70.8 years). The CNR with SR-DLR was significantly higher than without SR-DLR (1.93 [IQR: 0.79, 3.83] vs. 1.88 [IQR: 0.63, 3.82], p = 0.002). No significant difference in contrast was observed between images with and without SR-DLR (p = 0.864). The slope with SR-DLR was significantly higher than without SR-DLR (0.21 [IQR: 0.15, 0.25] vs. 0.15 [IQR: 0.12, 0.19], p < 0.01). Qualitative scores for contrast, sharpness, artifacts, and overall image quality were significantly higher with SR-DLR than without SR-DLR (p < 0.05 for all). The kappa values for 2D-T2WI and 3D-T2WI increased from 0.694 and 0.640 to 0.870 and 0.827 with SR-DLR for both readers. CONCLUSIONS SR-DLR has the potential to improve image quality and the ability to assess PI-RADS scores in thin-slice 3D-T2WI of the prostate without extending MRI acquisition time. SUMMARY Super-Resolution Deep Learning Reconstruction (SR-DLR) significantly improved image quality of thin-slice 3D T2-weighted imaging (T2WI) without extending the acquisition time. Additionally, the PI-RADS scores from 3D-T2WI with SR-DLR demonstrated higher agreement with those from 2D-T2WI.
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Affiliation(s)
- Kaori Shiraishi
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan.
| | - Naoki Kobayashi
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Hiroyuki Uetani
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Yasunori Nagayama
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Masafumi Kidoh
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Junji Yatsuda
- Department of Urology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Ryoma Kurahashi
- Department of Urology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Tomomi Kamba
- Department of Urology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Yuichi Yamahita
- MRI Systems Division, Canon Medical Systems Corporation, Japan
| | - Toshinori Hirai
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
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Long Depaquit T, Uleri A, Peyrottes A, Corral R, Toledano H, Chiron P, Bastide C, Baboudjian M. PI-RADS 3 MRI lesions: Are biopsies still necessary? THE FRENCH JOURNAL OF UROLOGY 2025; 35:102853. [PMID: 39755240 DOI: 10.1016/j.fjurol.2024.102853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 12/02/2024] [Accepted: 12/23/2024] [Indexed: 01/06/2025]
Abstract
INTRODUCTION A significant proportion of newly diagnosed prostate cancer (PCa) cases are slow growing with a low risk of metastatic progression. There is a lack of data concerning the optimal biopsy regimen for improving diagnosis yield in PI-RADS3 lesions. This study aimed to assess the diagnostic value of current biopsy regimens in PI-RADS 3 lesions and identify clinical predictors to improve clinically significant PCa (csPCa) detection. METHODS This retrospective study included patients from two academic centers between 2017 and 2024 who benefitted from prostate biopsies for a PI-RADS 3 lesion. Prostate biopsies were performed via either a transrectal or a transperineal route according to local resources. All patients underwent systematic and targeted cores. Targeted biopsies were performed using MRI-ultrasound fusion software or cognitive fusion. Patients were categorized based on biopsy results: benign, clinically insignificant (insignPCa, i.e. ISUP 1), or csPCa (ISUP≥2). The primary endpoint was to assess the detection rate of csPCa in MRI-targeted biopsies alone and in MRI-targeted+ipsilateral systematic cores in comparison to the gold standard MRI-targeted+systematic biopsies. Then, the percentage of csPCa missed and insignPCa diagnoses avoided were calculated referring to the gold standard MRI-targeted+systematic template. RESULTS A total of 163 men with at least one PI-RADS 3 index lesion were identified. Ninety-one (55.8%) lesions were benign, 52 (32%) were insignPCa and 20 (12.3%) were csPCa. Of the 20 patients with csPCa, the diagnosis was made with targeted cores in 12 patients and with systematic cores in 8 patients. If no biopsies were performed, 12.3% of csPCa would have gone undiagnosed. Targeted biopsies alone would have missed 4.9% of csPCa but avoided 24.5% of insignPCa. Targeted biopsies with systematic cores solely performed on the same side as the index lesion would have missed 3.8% of csPCa and avoided 12.9% of insignPCa. We reported no significant differences in detection rate of csPCa between MRI-targeted cores alone vs. the gold standard template (7.4% vs. 12.3%; P=0.9) and between MRI-targeted cores+ipsilateral systematic cores vs. the gold standard template (8.5% vs. 12.3%; P=1.2). At multivariable analysis age, clinical T stage, and mpMRI lesion size were predictors of csPCa. CONCLUSION As a small proportion of PI-RADS 3 lesions are associated with csPCa, the value of biopsies is questionable. Targeted biopsies with systematic cores on the same side as the index lesion may improve detection of csPCa and reduce overdiagnosis of indolent CaP. Clinical T stage and lesion size on MRI can potentially predict the presence of clinically significant CaP. LEVEL OF EVIDENCE: 4
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Affiliation(s)
- Thibaut Long Depaquit
- Department of Urology, HIA Sainte-Anne, Toulon, France; Department of Urology, North Hospital, AP-HM, Marseille, France.
| | | | - Arthur Peyrottes
- Department of Urology, Saint-Louis Hospital, Université Paris-Cité, Paris, France
| | - Renaud Corral
- Department of Urology, North Hospital, AP-HM, Marseille, France
| | - Harry Toledano
- Department of Urology, North Hospital, AP-HM, Marseille, France; Department of Urology, Martigues Hospital, Martigues, France
| | - Paul Chiron
- Department of Urology, HIA Begin, Saint-Mandé, France
| | - Cyrille Bastide
- Department of Urology, North Hospital, AP-HM, Marseille, France
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He J, Wei C, Su S, Luo Y, Li Y, Han K, Jiang L, Zhang J, Wang D. Frontiers and hotspots of 3D technology in prostatectomy from 1999 to 2024: a bibliometric analysis and visualization. Gland Surg 2025; 14:436-450. [PMID: 40256469 PMCID: PMC12004326 DOI: 10.21037/gs-2024-483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2024] [Accepted: 02/20/2025] [Indexed: 04/22/2025]
Abstract
Background Prostate cancer is a major global health issue. Radical prostatectomy is an effective treatment for prostate cancer. The integration of three-dimensional (3D) technology in prostatectomy offers numerous benefits. We intended to perform a bibliometric analysis of the role of 3D technology in prostatectomy. Methods Articles and review articles related to "3D" and "prostatectomy" were retrieved from Web of Science Core Collection. Microsoft Office Excel, CiteSpace, and VOSviewer were utilized for analysis and visualization. Results A total of 441 articles were collected. The annual publication volume and journal distribution were illustrated. Visualizations of collaborations among countries/regions, institutions, and authors were provided. Networks of reference co-citations and keyword co-occurrences, along with their respective clusters were plotted. Conclusions The number of published papers significantly increased over the last 25 years. The most productive and influential country was the USA, and The University of California System was the most influential institution. The journal with the highest number of publications was BJU International. Among all authors in this field, Wijkstra H has published the most papers. Porpiglia F was the most cited author. Previous hot topics included advanced imaging and clinical trials, whereas augmented reality (AR) and robotics are likely to be hot topics in the future.
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Affiliation(s)
| | | | - Shuai Su
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yu Luo
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yunfan Li
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Kun Han
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lincen Jiang
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Morote J, Miró B, Hernando P, Paesano N, Picola N, Muñoz-Rodriguez J, Ruiz-Plazas X, Muñoz-Rivero MV, Celma A, García-de Manuel G, Servian P, Abascal JM, Trilla E, Méndez O. Developing a Predictive Model for Significant Prostate Cancer Detection in Prostatic Biopsies from Seven Clinical Variables: Is Machine Learning Superior to Logistic Regression? Cancers (Basel) 2025; 17:1101. [PMID: 40227611 PMCID: PMC11987821 DOI: 10.3390/cancers17071101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2025] [Revised: 03/24/2025] [Accepted: 03/25/2025] [Indexed: 04/15/2025] Open
Abstract
Objective: This study compares machine learning (ML) and logistic regression (LR) algorithms in developing a predictive model for sPCa using the seven predictive variables from the Barcelona (BCN-MRI) predictive model. Method: A cohort of 5005 men suspected of having PCa who underwent MRI and targeted and/or systematic biopsies was used for training, testing, and validation. A feedforward neural network (FNN)-based SimpleNet model (GMV) and a logistic regression-based model (BCN) were developed. The models were evaluated for discrimination ability, precision-recall, net benefit, and clinical utility. Both models demonstrated strong predictive performance. Results: The GMV model achieved an area under the curve of 0.88 in training and 0.85 in test cohorts (95% CI: 0.83-0.90), while the BCN model reached 0.85 and 0.84 (95% CI: 0.82-0.87), respectively (p > 0.05). The GMV model exhibited higher recall, making it more suitable for clinical scenarios prioritizing sensitivity, whereas the BCN model demonstrated higher precision and specificity, optimizing the reduction of unnecessary biopsies. Both models provided similar clinical benefit over biopsying all men, reducing unnecessary procedures by 27.5-29% and 27-27.5% of prostate biopsies at 95% sensitivity, respectively (p > 0.05). Conclusions: Our findings suggest that both ML and LR models offer high accuracy in sPCa detection, with ML exhibiting superior recall and LR optimizing specificity. These results highlight the need for model selection based on clinical priorities.
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Affiliation(s)
- Juan Morote
- Department of Urology, Vall Hebron University Hospital, 08035 Barcelona, Spain; (A.C.); (E.T.)
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;
- Research Group in Urology, Vall Hebron Research Institute, 08035 Barcelona, Spain
| | - Berta Miró
- Statistics and Bioinformatics Unit, Vall d’Hebron Research Institute, 08035 Barcelona, Spain;
| | - Patricia Hernando
- Department of Artificial Intelligence and Big Data, GMV Innovative Solutions Inc., 28760 Madrid, Spain;
| | - Nahuel Paesano
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;
- Clínica Creu Blanca, 08018 Barcelona, Spain
| | - Natàlia Picola
- Department of Urology, Hospital Universitari de Bellvitge, 08907 Hospitalet de Llobregat, Spain;
| | | | - Xavier Ruiz-Plazas
- Department of Urology, Hospital Universitari Joan XXIII, 43005 Tarragona, Spain;
| | - Marta V. Muñoz-Rivero
- Department of Urology, Hospital Universitari Arnau de Vilanova, 25198 Lleida, Spain;
| | - Ana Celma
- Department of Urology, Vall Hebron University Hospital, 08035 Barcelona, Spain; (A.C.); (E.T.)
- Research Group in Urology, Vall Hebron Research Institute, 08035 Barcelona, Spain
| | | | - Pol Servian
- Department of Urology, Hospital Universitari Germans Trias i Pujol, 08916 Badalona, Spain;
| | - José M. Abascal
- Department of Urology, Parc de Salut Mar, 08003 Barcelona, Spain;
- Department of Medicine and Health Sciences, Universitat Pompeu Fabra, 08002 Barcelona, Spain
| | - Enrique Trilla
- Department of Urology, Vall Hebron University Hospital, 08035 Barcelona, Spain; (A.C.); (E.T.)
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;
- Research Group in Urology, Vall Hebron Research Institute, 08035 Barcelona, Spain
| | - Olga Méndez
- Research Group in Urology, Vall Hebron Research Institute, 08035 Barcelona, Spain
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Schaudinn A, Busse H, Ehrengut C, Linder N, Ludwig J, Franz T, Horn LC, Stolzenburg JU, Denecke T. Prostate cancer detection with transrectal in-bore MRI biopsies: impact of prostate volume and lesion features. Insights Imaging 2025; 16:69. [PMID: 40121573 PMCID: PMC11930903 DOI: 10.1186/s13244-025-01942-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 03/01/2025] [Indexed: 03/25/2025] Open
Abstract
OBJECTIVES To systematically analyze the diagnostic outcome of transrectal in-bore MRI-guided biopsies as a function of prostate volume and lesion features. METHODS This single-center study retrospectively included 184 consecutive patients with transrectal in-bore MRI biopsies and histological analysis after multiparametric MRI diagnostics of at least one PI-RADS ≥ 3 lesion. Diagnostic and biopsy MRI data were analyzed for a number of patient and imaging features, specifically prostate volume, lesion size, lesion location (longitudinal, sagittal and segmental) and lesion depth. Features were then compared for statistically significant differences in the cancer detection rate (CDR) of clinically significant (cs-PCa) and any prostate cancer (any-PCa) using categorical and continuous variables. RESULTS A total of 201 lesions were biopsied detecting cs-PCa in 26% and any-PCa in 68%, respectively. In subgroup analyses of all features, the CDR of cs-PCa differed significantly between ranges of lesion size only (p < 0.001, largest for large lesions). In multivariable analysis, however, only PI-RADS score and PSA showed a significant association with a higher risk of cs-PCa. CONCLUSIONS The cancer detection rates of transrectal in-bore MRI-guided biopsies did not vary significantly for prostate volume, lesion size or lesion location. This suggests that the diagnostic performance of such an approach is not necessarily compromised for challenging biopsy settings like large glands, small lesions or eccentric locations. A translation of these findings to other cohorts might be limited by the low detection rate for clinically significant cancer. CRITICAL RELEVANCE STATEMENT This systematic analysis indicates that the diagnostic performance of transrectal in-bore biopsies might not be substantially impaired by patient-specific factors like prostate volume, lesion size, and lesion location, making it a viable option for challenging biopsy cases as well. KEY POINTS The impact of prostate and lesion features on in-bore MRI biopsy performance is controversial. Neither prostate volume, lesion size, nor location showed significant impact on cancer detection. In-bore biopsy does not seem to be limited by challenging sampling geometries.
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Affiliation(s)
- Alexander Schaudinn
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany.
- Center of Radiology and Nuclear Medicine (ZRN) Leipzig, Leipzig, Germany.
| | - Harald Busse
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
| | - Constantin Ehrengut
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
- Department of Diagnostic and Interventional Radiology, Section of Pediatric Radiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nicolas Linder
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
- Division of Radiology and Nuclear Medicine, HOCH Health Ostschweiz, St. Gallen, Switzerland
| | - Jonna Ludwig
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
| | - Toni Franz
- Department of Urology, University Hospital Leipzig, Leipzig, Germany
| | | | | | - Timm Denecke
- Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
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Zwolski M, Kupilas A, Cnota P. Review of different convolutional neural networks used in segmentation of prostate during fusion biopsy. Cent European J Urol 2025; 78:23-39. [PMID: 40371421 PMCID: PMC12073522 DOI: 10.5173/ceju.2024.0064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 10/16/2024] [Indexed: 05/16/2025] Open
Abstract
Introduction The incidence of prostate cancer is increasing in Poland, particularly due to the aging population. This review explores the potential of deep learning algorithms to accelerate prostate contouring during fusion biopsies, a time-consuming but crucial process for the precise diagnosis and appropriate therapeutic decision-making in prostate cancer. Implementing convolutional neural networks (CNNs) can significantly improve segmentation accuracy in multiparametric magnetic resonance imaging (mpMRI). Material and methods A comprehensive literature review was conducted using PubMed and IEEE Xplore, focusing on open-access studies from the past five years, and following PRISMA 2020 guidelines. The review evaluates the enhancement of prostate contouring and segmentation in MRI for fusion biopsies using CNNs. Results The results indicate that CNNs, particularly those utilizing the U-Net architecture, are predominantly selected for advanced medical image analysis. All the reviewed algorithms achieved a Dice similarity coefficient (DSC) above 74%, indicating high precision and effectiveness in automatic prostate segmentation. However, there was significant heterogeneity in the methods used to evaluate segmentation outcomes across different studies. Conclusions This review underscores the need for developing and optimizing segmentation algorithms tailored to the specific needs of urologists performing fusion biopsies. Future research with larger cohorts is recommended to confirm these findings and further enhance the practical application of CNN-based segmentation tools in clinical settings.
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Affiliation(s)
- Maciej Zwolski
- Department of Urology and Urooncology, Municipal Hospital No. 4 in Gliwice, Poland
| | - Andrzej Kupilas
- Department of Urology and Urooncology, Municipal Hospital No. 4 in Gliwice, Poland
| | - Przemysław Cnota
- Department of Urology and Urooncology, Municipal Hospital No. 4 in Gliwice, Poland
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22
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Pisotskyi O, Petrasz P, Zorga P, Gałęski M, Szponar P, Koper K, Brzeźniakiewicz-Janus K, Drewa T, Kaczmarek K, Cezary Czarnogórski M, Adamowicz J. The potential of gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography as a main diagnostic tool in prostate cancer staging. Cent European J Urol 2025; 78:52-60. [PMID: 40371428 PMCID: PMC12073512 DOI: 10.5173/ceju.2025.0014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2025] [Accepted: 02/09/2025] [Indexed: 05/16/2025] Open
Abstract
Introduction Prostate cancer (PC) remains a significant global health burden, necessitating accurate staging for optimal treatment planning. Conventional imaging methods, including multiparametric magnetic resonance imaging (mpMRI), computed tomography (CT), and bone scintigraphy (BS), exhibit limitations in sensitivity and specificity. Gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (68Ga PSMA-PET/CT) has emerged as a promising alternative, with potential advantages in staging accuracy. Material and methods A comprehensive review of current literature was conducted to assess the role of 68Ga PSMA-PET/CT in primary PC staging. The diagnostic performance of PSMA-PET/CT was compared with conventional imaging techniques in detecting locoregional and distant metastases. Studies evaluating sensitivity, specificity, and clinical utility in treatment decision-making were analyzed. Results 68Ga PSMA-PET/CT demonstrated superior sensitivity and specificity in detecting lymph node and distant metastases compared to conventional imaging. It enables earlier and more precise disease staging, potentially reducing the need for multiple imaging modalities. Emerging evidence suggests its role in guiding therapeutic strategies, particularly in high-risk and recurrent PC cases. Despite its advantages, limitations such as accessibility, cost, and occasional false-negative findings must be considered. Conclusions 68Ga PSMA-PET/CT represents a transformative diagnostic tool for PC staging, offering enhanced accuracy compared to traditional imaging. Its integration into clinical practice could streamline diagnostic pathways, improve treatment selection, and potentially optimize patient outcomes. Further research and cost-effectiveness analyses are needed to establish its widespread implementation.
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Affiliation(s)
- Oleksii Pisotskyi
- Urology and Urological Oncology Department, Multidisciplinary Regional Hospital, Gorzow Wielkopolski, Poland
| | - Piotr Petrasz
- Urology and Urological Oncology Department, Multidisciplinary Regional Hospital, Gorzow Wielkopolski, Poland
| | - Piotr Zorga
- Department and Chair of Urology and Andrology, University Hospital No. 1 in Bydgoszcz, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
| | - Marcin Gałęski
- Urology and Urological Oncology Department, Multidisciplinary Regional Hospital, Gorzow Wielkopolski, Poland
| | - Paweł Szponar
- Urology and Urological Oncology Department, Multidisciplinary Regional Hospital, Gorzow Wielkopolski, Poland
| | - Krzysztof Koper
- Clinical Oncology and Nursing Department, Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland
| | - Katarzyna Brzeźniakiewicz-Janus
- Haematology, Oncology, and Radiotherapy Department and Clinic, University of Zielona Gora, Multidisciplinary Regional Hospital, Gorzow Wielkopolski, Poland
| | - Tomasz Drewa
- Department and Chair of Urology and Andrology, University Hospital No. 1 in Bydgoszcz, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
| | - Krzysztof Kaczmarek
- Urology and Urological Oncology Department, Multidisciplinary Regional Hospital, Gorzow Wielkopolski, Poland
| | - Michał Cezary Czarnogórski
- Department and Chair of Urology and Andrology, University Hospital No. 1 in Bydgoszcz, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
| | - Jan Adamowicz
- Department and Chair of Urology and Andrology, University Hospital No. 1 in Bydgoszcz, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
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23
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Viana PCC, Pinto PVA, Horvat N, Queiroz MA, Cordeiro MD, Coelho RF, Cardili L, Pontes J, Cerri GG, Nahas WC. The presence of prostate MRI-visible lesions at follow-up biopsy as a risk factor for histopathological upgrading during active surveillance. Abdom Radiol (NY) 2025:10.1007/s00261-025-04871-6. [PMID: 40072539 DOI: 10.1007/s00261-025-04871-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2025] [Revised: 02/27/2025] [Accepted: 03/02/2025] [Indexed: 03/14/2025]
Abstract
OBJECTIVE To prospectively determine the ability of visible lesions on multiparametric MRI (PI-RADS 4-5) and commonly used biomarkers to predict disease upgrading on rebiopsy in men with low-risk prostate cancer (PCa) enrolled in active surveillance (AS). MATERIALS AND METHODS For this prospective study, approved by the Institutional Review Board (IRB), we selected consecutive patients with low-risk, low-grade, and localized prostate cancer (PCa) from our active surveillance (AS) program, who were enrolled between March 2014 and December 2020. Patients who had undergone previous prostate surgery, hormonal treatment, had contraindications for mpMRI, or transrectal ultrasound-guided (TRUS) biopsy were excluded from this study. All eligible patients underwent mpMRI at least 3 months after the initial biopsy, followed by MRI-targeted TRUS-guided re-biopsy within 12 months after enrollment. The mpMRI studies were evaluated by an experienced radiologist using the PI-RADS v2 classification. Statistical significance was determined by comparing the results from the MRI with the pathology data from rebiopsy. RESULTS There were 240 patients included. Overall upgrading rate was 41.2% (99/240), higher among patients classified as PIRADS 4 or 5 (77%). MRI sensitivity was 77.7% and specificity was 83.6% on re-biopsy. Visible lesion on mpMRI, PSA density and 3 + /12 positive cores at the first biopsy were good predictors of disease upgrade on rebiopsy. On our predictive model, patients with PI-RADS 4 or 5, PSA density > 0.15 ng/mL/cm3, and 3 + /12 positive cores at first biopsy had 92.4% chance of having clinically significant PCa. CONCLUSION Patients in AS with PI-RADS 4 or 5 lesions, PSA density > 0.15 ng/mL/cm3 and 3 + /12 positive cores at first biopsy have a high probability of having significant PCa on re-biopsy.
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Affiliation(s)
| | | | | | | | | | | | | | - Jose Pontes
- Universidade de São Paulo, São Paulo, Brazil
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24
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Porões F, Karampa P, Sartoretti T, Najberg H, Froehlich JM, Reischauer C, Thoeny HC. Additional findings in prostate MRI. Cancer Imaging 2025; 25:29. [PMID: 40069885 PMCID: PMC11895278 DOI: 10.1186/s40644-025-00846-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2024] [Accepted: 02/24/2025] [Indexed: 03/15/2025] Open
Abstract
BACKGROUND Despite the increasing interest in abbreviated protocols, we adopted an extended protocol for all prostate MRIs. In this study, we assessed the benefits of an extended prostate MRI protocol, measured by the number and the clinical importance of additional findings (AFs) and their impact on patient management. METHODS In a single-center study, we retrospectively included 1282 patients undergoing prostate MRI between 01.10.2018 and 30.04.2022. Additional findings were defined as any pathology not located in the prostate or the seminal vesicles. These were classified as related or unrelated to prostate cancer (PCa). The latter were divided into groups based on low, moderate, or high clinical significance (group 1, 2, and 3). A finding unrelated to PCa was judged to be clinically significant (group 2: moderate, group 3: high) if further diagnostic investigations, or treatment was necessary. The degree of urgency of the latter determined moderate and high significance. For group 3 findings, a change in management was defined as further workup. RESULTS A total of 5206 AFs was recorded in 1240/1282 patients. One hundred and twenty-three (2.4% of all findings) extra-prostatic PCa related AFs were found in 106 (8.3% of all patients) patients. The remaining 5083 (97.6% of all findings) findings were not related to PCa, of which 3155 (60.6%), 1770 (34.0%), and 158 (3.0%) were assigned to groups 1, 2, and 3, respectively. A management shift was identified in 49 (3.8% of all patients) patients of group 3. CONCLUSION The extended prostate MRI protocol shows a considerable prevalence of AFs of which more than a third are clinically significant, related or unrelated to PCa (groups 2 and 3). A substantial percentage (8.3%) of patients have extra-prostatic PCa-related AFs that change the patient's disease stage and management. However, a change in management due to AFs unrelated to PCA that belong to group 3 is observed in less than 4% of all patients. The choice between extended and abbreviated prostate MRI protocols should be made based on available resources.
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Affiliation(s)
- Fabio Porões
- University of Fribourg, Fribourg, Switzerland.
- Department of Radiology, Cantonal Hospital of Fribourg, Chemin des Pensionnats 2-6 Case postale, Fribourg, CH-1708, Switzerland.
| | - Paraskevi Karampa
- University of Fribourg, Fribourg, Switzerland
- Department of Radiology, Cantonal Hospital of Fribourg, Chemin des Pensionnats 2-6 Case postale, Fribourg, CH-1708, Switzerland
| | | | - Hugo Najberg
- University of Fribourg, Fribourg, Switzerland
- Department of Radiology, Cantonal Hospital of Fribourg, Chemin des Pensionnats 2-6 Case postale, Fribourg, CH-1708, Switzerland
| | | | | | - Harriet C Thoeny
- University of Fribourg, Fribourg, Switzerland
- Department of Radiology, Cantonal Hospital of Fribourg, Chemin des Pensionnats 2-6 Case postale, Fribourg, CH-1708, Switzerland
- Department of Urology, Inselspital, University of Bern, Bern, Switzerland
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25
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Onishi K, Nakai Y, Miyamoto T, Maesaka F, Tomizawa M, Shimizu T, Hori S, Gotoh D, Miyake M, Tachiiri T, Marugami N, Fujimoto K, Tanaka N. The Utility of Transperineal Template Saturation Biopsy in the Detection of Clinically Significant Prostate Cancer. Adv Urol 2025; 2025:9961847. [PMID: 40224212 PMCID: PMC11991765 DOI: 10.1155/aiu/9961847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Accepted: 02/10/2025] [Indexed: 04/15/2025] Open
Abstract
Aim: We investigated the role of transperineal template saturation biopsy (TTSB) in detecting clinically significant prostate cancer (csPCa). We compared the TTSB findings with multiparametric magnetic resonance imaging (mpMRI) findings in suspected prostate cancer patients. Methods: This retrospective study included 124 patients who underwent TTSB following mpMRI at our institute. We examined factors contributing to csPCa detection in these patients. We examined the association between the Prostate Imaging-Reporting and Data System (PI-RADS) Version 2.1 category and csPCa detection. Results: The median age at TTSB was 68 (interquartile range: 62-73) years, and the median prostate-specific antigen level was 9.9 (6.1-15.5) ng/mL. Herein, 61.3% (76/124) of the patients who underwent TTSB had cancer and 35.5% (44/124) had csPCa. Abnormal digital rectal examination findings (p=0.006) and PI-RADS category ≥ 4 (p < 0.001) were independent factors for csPCa detection. Among patients categorized as PI-RADS ≥ 4, 64.8% (35/54) had csPCa; csPCa frequency increased with increasing PI-RADS categories (p < 0.001). Cancer was detected in 38.3% (23/60) of the patients categorized as PI-RADS ≤ 2; among them, 10% (6) had csPCa. Only 3.2% (4/124) of the patients had TTSB-related adverse events ≥ grade 2, 0.8% (1/124) suffered from hematuria, and 2.4% (3/124) had acute urinary retention. All patients were treated conservatively. Conclusions: Patients with a higher PI-RADS category tended to have csPCa. However, the PI-RADS category alone may not be sufficient for csPCa detection. TTSB detected csPCa in 10% of the patients with negative mpMRI findings. TTSB is a safe and crucial technique for accurately diagnosing prostate cancer.
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Affiliation(s)
- Kenta Onishi
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Yasushi Nakai
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Tatsuki Miyamoto
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Fumisato Maesaka
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Mitsuru Tomizawa
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Takuto Shimizu
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Shunta Hori
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Daisuke Gotoh
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Makito Miyake
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Tetsuya Tachiiri
- Departments of Radiology and Nuclear Medicine, Nara Medical University, Kashihara, Nara, Japan
| | - Nagaaki Marugami
- Departments of Radiology and Nuclear Medicine, Nara Medical University, Kashihara, Nara, Japan
| | - Kiyohide Fujimoto
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
| | - Nobumichi Tanaka
- Departments of Urology, Nara Medical University, Kashihara, Nara, Japan
- Departments of Prostate Brachytherapy, Nara Medical University, Kashihara, Nara, Japan
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26
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Lambert L, Macova I, Wagnerova M, Jurka M, Burgetova R, Capoun O, Burgetova A. The impact of modifiable factors on image quality of prostate magnetic resonance imaging and PI-RADS scores. Quant Imaging Med Surg 2025; 15:2433-2443. [PMID: 40160644 PMCID: PMC11948393 DOI: 10.21037/qims-24-1776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2024] [Accepted: 02/07/2025] [Indexed: 04/02/2025]
Abstract
Background The diagnostic accuracy of prostate magnetic resonance imaging (MRI) is highly dependent on image quality. Although the effects of spasmolytics and rectal preparation have been previously studied, the findings remain inconsistent and fail to address other critical modifiable factors. This study aimed to evaluate the impact of various modifiable factors on prostate MRI image quality and their subsequent influence on Prostate Imaging Reporting and Data System (PI-RADS) scoring. Methods Fifty-six consecutive patients who underwent 3T multiparametric MRI (mpMRI) with the administration of hyoscine butylbromide (HB+) and at least one 3T mpMRI without HB (HB-) ≤3 years earlier were retrospectively evaluated. Two radiologists performed morphometry of the prostate, bladder, rectum, and abdomen and evaluated image quality, artifacts, and motion on a five-point scale and T2 and diffusion-weighted imaging (DWI) PI-RADS v2.1 scores. The influence of HB, rectum and bladder distension, breathing motion, and examination hour were analyzed. Results The sharpness and overall image quality of T2 images were significantly better in HB+ compared to HB- (P=0.0047 and P=0.013). T2 motion artifacts were reduced earlier in the day (ρ=0.32, P=0.017). DWI susceptibility artifact correlated with patient diameter (ρ=0.40, P=0.002), but not with rectum diameter (ρ=0.09, P=0.51) or gas content (ρ=0.13, P=0.33). Examinations later in the day were associated with increased motion artifacts on T2 [hazard ratio (HR) =1.36]. T2 and DWI scores were influenced by bladder volume, breathing motion, and rectal air, but not by HB. Breathing motion negatively impacted overall image quality (HR =1.24), and DWI susceptibility artifacts (HR =1.22). Conclusions HB administration, daytime, and breathing motion have significant influence on image quality of prostate MRI. The gas content of the rectum influences T2 image quality and T2 scores. Bladder filling is associated with reduced breathing motion, subsequently affecting DWI scores.
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Affiliation(s)
- Lukas Lambert
- Department of Imaging Methods, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czech Republic
| | - Iva Macova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Monika Wagnerova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Martin Jurka
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Romana Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Department of Radiology, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Otakar Capoun
- Department of Urology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Andrea Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
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27
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Orsini A, Ferretti S, Porreca A, Castellan P, Litterio G, Ciavarella D, De Palma A, Berardinelli F, Pizzi AD, D'Angelo E, di Nicola M, Schips L, Marchioni M. PI-RADS in Predicting csPCa: A Comparison Between Academic and Nonacademic Centers. Prostate 2025; 85:337-343. [PMID: 39709541 PMCID: PMC11776442 DOI: 10.1002/pros.24832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 11/18/2024] [Accepted: 11/19/2024] [Indexed: 12/23/2024]
Abstract
INTRODUCTION The introduction of multiparametric prostate magnetic resonance imaging (mpMRI) has revolutionized prostate cancer (PCa) diagnosis, enhancing the localization of clinically significant prostate cancer (csPCa) and guiding targeted biopsies. However, significant disparities in the execution, interpretation, and reporting of prostate MRI examinations across centers necessitate greater standardization and accuracy. This study compares the diagnostic efficacy of mpMRI from academic and nonacademic centers in detecting csPCa and identifies factors associated with csPCa detection. MATERIALS AND METHODS Between July 2018 and October 2023, we prospectively followed 810 men at SS. Annunziata Hospital of Chieti who underwent MRI/US fusion biopsies due to elevated prostate-specific antigen (PSA) and/or abnormal digital rectal examination (DRE). Patients with mpMRI-documented suspicious lesions classified as PI-RADS ≥ 3 were included. Patients were divided into two groups based on the source of their mpMRI (academic or nonacademic centers). All biopsies were conducted using the MRI/US fusion technique. Clinical, mpMRI, and pathological data were collected and analyzed. Statistical analyses were performed using R software. RESULTS The cohort included 354 patients from academic centers and 456 from nonacademic centers. There were no significant differences in patient demographics, such as age and PSA levels, between the groups. Patients at academic centers were more likely to receive a higher number of elevated PI-RADS scores compared to those at nonacademic centers (PI-RADS > 3: 72.6% vs. 62.3%, p = 0.003). Histopathological analysis revealed no significant differences in the ISUP grade distribution between groups. Increased age, PSA levels, and positive DRE were significantly associated with higher odds of detecting csPCa. Median PSA density was significantly higher in patients with csPCa compared to those without csPCa (0.14 vs. 0.11 ng/mL/cm³, p < 0.001). Academic centers exhibited a higher odds ratio for csPCa detection in patients with PI-RADS scores > 3 compared to nonacademic centers. CONCLUSION Our study highlights significant variability in PI-RADS score assignments between academic and nonacademic centers, affecting csPCa detection rates. This variability underscores the need for greater standardization in PI-RADS scoring to reduce disparities and improve diagnostic uniformity across centers.
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Affiliation(s)
- Angelo Orsini
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
| | - Simone Ferretti
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
| | - Annamaria Porreca
- Department of Medical Oral Science and BiotechnologyG. d'Annunzio UniversityChietiItaly
| | - Pietro Castellan
- Department of UrologyUniversita degli Studi Gabriele d'Annunzio Chieti Pescara Dipartimento di Scienze Mediche Orali e BiotecnologicheChietiItaly
| | - Giulio Litterio
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
| | - Davide Ciavarella
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
| | - Antonio De Palma
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
| | - Francesco Berardinelli
- Department of UrologyUniversita degli Studi Gabriele d'Annunzio Chieti Pescara Dipartimento di Scienze Mediche Orali e BiotecnologicheChietiItaly
| | - Andrea D. Pizzi
- Department of Innovative Technologies in Medicine and DentistryG. D'Annunzio UniversityChietiItaly
- ITAB Institute for Advanced Biomedical TechnologiesGabriele d'Annunzio University of ChietiChietiItaly
| | - Emanuela D'Angelo
- Diagnostic Molecular Pathology, Unit of Anatomic Pathology, SS Annunziata HospitalChietiItaly
| | - Marta di Nicola
- Department of Medical Oral Science and BiotechnologyG. d'Annunzio UniversityChietiItaly
| | - Luigi Schips
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
- Department of UrologyUniversita degli Studi Gabriele d'Annunzio Chieti Pescara Dipartimento di Scienze Mediche Orali e BiotecnologicheChietiItaly
| | - Michele Marchioni
- Urology Unit, Department of Medical, Oral and Biotechnological Sciences‘G. d'Annunzio University’ChietiItaly
- Department of UrologyUniversita degli Studi Gabriele d'Annunzio Chieti Pescara Dipartimento di Scienze Mediche Orali e BiotecnologicheChietiItaly
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28
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Avolio PP, Hassan T, Addar A, Alshamsi H, McPherson V, Buffi NM, Lughezzani G, Loutochin O, Rompré-Brodeur A, Anidjar M, Sanchez-Salas R. The Role of Tumor Volume Ratio in Predicting Clinically Significant Prostate Cancer on Transperineal Biopsy. J Endourol 2025; 39:S47-S53. [PMID: 39587895 DOI: 10.1089/end.2024.0428.fts24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2024] Open
Abstract
Objectives: Multiparametric magnetic resonance imaging (mpMRI) has made dramatic inroads into the management of localized prostate cancer (PCa); however, not all suspicious lesions represent clinically significant (cs) PCa. We aimed to analyze the hypothetical effect of incorporating tumor volume ratio (TVR) into prostate biopsy (PBx) decision-making. Materials and Methods: Two hundred and fifty-two patients with suspicious lesions at mpMRI undergoing transperineal PBx under local anesthesia between 2019 and 2022 were retrospectively evaluated. TVR was calculated by dividing the tumor volume by the prostate volume. A regression model was used to assess predictors of csPCa. Descriptive statistics were applied to evaluate the effect of including TVR in PBx decision-making. Results: Overall, 119 patients (47%) were found to have csPCa. Age (p < 0.001), prior negative PBx (p = 0.011), and TVR (p < 0.001) were found to be independent predictors of csPCa. Applying the TVR cutoff of 0.23, a total of 117/252 (46%) PBx would have been avoided at the cost of missing csPCa in 26 (10%) men. Conclusions: Age, previous biopsy status, and TVR were found to be independent predictors of csPCa in men with suspicious lesions at mpMRI. Implementation of TVR into PBx decision-making improves the accuracy of mpMRI. Future studies are required to validate our findings and evaluate the role of TVR in avoiding unnecessary PBx.
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Affiliation(s)
- Pier Paolo Avolio
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Toufic Hassan
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Abdulmalik Addar
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Hend Alshamsi
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Victor McPherson
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | | | | | - Oleg Loutochin
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Alexis Rompré-Brodeur
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Maurice Anidjar
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
| | - Rafael Sanchez-Salas
- Division of Urology, Department of Surgery, McGill University Health Centre, Montreal, Canada
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29
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Baboudjian M, Leni R, Oderda M, Peyrottes A, Kesch C, Al-Nader M, Uleri A, Dariane C, Baud H, Olivier J, Rios AR, Sanguedolce F, Benard V, Windisch O, Valerio M, Gandaglia G, Ploussard G. Active Surveillance of Grade Group 2 Prostate Cancer: Oncological Outcomes from a Contemporary European Cohort. Eur Urol Oncol 2025:S2588-9311(25)00027-6. [PMID: 39965999 DOI: 10.1016/j.euo.2025.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Revised: 01/07/2025] [Accepted: 01/16/2025] [Indexed: 02/20/2025]
Abstract
BACKGROUND AND OBJECTIVE Uptake of active surveillance for patients with Gleason grade group (GG) 2 prostate cancer (PCa) remains low. Magnetic resonance imaging (MRI) before biopsy would allow better patient selection, but there are no published data on this strategy. Our aim was to report one of the first European AS series of patients with GG 2 PCa selected via MRI before image-guided biopsy. METHODS This multicenter study enrolled patients with GG 2 PCa managed with AS between 2016 and 2024 in ten reference centers in France, Spain, Italy, Switzerland, and Germany. Patients deemed unsuitable for curative treatment (ie, watchful waiting) were excluded. The primary endpoint was metastasis-free survival. KEY FINDINGS AND LIMITATIONS A total of 139 patients with GG 2 PCa were included. Baseline MRI revealed a lesion with a Prostate Imaging-Reporting and Data System score of 4-5 in 81 patients (59%). Median event-free follow-up was 38 mo (interquartile range 20-63). Two cases of metastasis were observed, and there were no deaths due to PCa. The estimated 3-yr metastasis-free survival rate was 98.1% (95% confidence interval 95.5-100%). Overall, 56 patients underwent definitive treatment and 26 were reclassified as having GG 3 PCa during follow-up. Among the 28 patients who underwent radical prostatectomy, final pathology revealed adverse features (GG 3 and/or pT3a) in 13 cases (46%), but very aggressive disease (GG ≥4 and/or ≥pT3b and/or pN1) was noted in only two cases (7%). There were no statistically significant differences in outcomes between groups that did and did not meet the European Association of Urology inclusion criteria for AS (all log-rank tests p > 0.05). CONCLUSIONS AND CLINICAL IMPLICATIONS In the era of prebiopsy MRI and image-guided biopsy, AS is a safe management option for selected patients with GG 2 PCa. Future studies should focus on redefining current inclusion criteria for AS in the targeted biopsy era, as many patients with GG 2 PCa are at low absolute risk of distant progression.
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Affiliation(s)
- Michael Baboudjian
- Department of Urology Aix-Marseille University North Hospital AP-HM Marseille France.
| | - Riccardo Leni
- Division of Experimental Oncology Department of Urology IRCCS San Raffaele Scientific Institute Milan Italy; Vita-Salute San Raffaele University Milan Italy
| | - Marco Oderda
- Division of Urology Department of Surgical Sciences Molinette Hospital University of Turin Turin Italy
| | - Arthur Peyrottes
- Department of Urology and Renal transplantation Université de Paris St. Louis Hospital AP-HP Paris France
| | - Claudia Kesch
- Department of Urology University Hospital Essen Essen Germany
| | - Mulham Al-Nader
- Department of Urology University Hospital Essen Essen Germany
| | - Alessandro Uleri
- Department of Urology Aix-Marseille University North Hospital AP-HM Marseille France
| | - Charles Dariane
- Department of Urology Hôpital Européen Georges-Pompidou Université Paris Cité Paris France
| | - Helene Baud
- Department of Urology Hôpital Européen Georges-Pompidou Université Paris Cité Paris France
| | - Jonathan Olivier
- Urology Department Claude Huriez Hospital CHU Lille Lille France
| | | | | | - Vincent Benard
- Division of Urology Geneva University Hospitals Geneva Switzerland
| | - Olivier Windisch
- Division of Urology Geneva University Hospitals Geneva Switzerland
| | - Massimo Valerio
- Division of Urology Geneva University Hospitals Geneva Switzerland
| | - Giorgio Gandaglia
- Division of Experimental Oncology Department of Urology IRCCS San Raffaele Scientific Institute Milan Italy; Vita-Salute San Raffaele University Milan Italy
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Torres CVDS, Gouvea GDL, Secaf ADF, Vieira DFM, Morgado ASDM, Palma MDM, Ramos GA, Elias J, Muglia VF. Imaging Assessment of Prostate Cancer Extra-prostatic Extension: From Histology to Controversies. Semin Ultrasound CT MR 2025; 46:45-55. [PMID: 39586413 DOI: 10.1053/j.sult.2024.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2024]
Abstract
Prostate cancer (PCa) is the most common non-skin malignancy among men and the fourth leading cause of cancer-related deaths globally. Accurate staging of PCa, particularly the assessment of extra-prostatic extension (EPE), is critical for prognosis and treatment planning. EPE, typically evaluated using magnetic resonance imaging (MRI), is associated with higher risks of positive surgical margins, biochemical recurrence, metastasis, and reduced overall survival. Despite the widespread use of MRI, there is no consensus on diagnosing EPE via imaging. There are 2 main scores assessing EPE by MRI: the European Society of Urogenital Radiology score and an MRI-based EPE grading system from an American group. While both are widely recognized, their differences can lead to varying interpretations in specific cases. This paper clarifies the anatomical considerations in diagnosing locally advanced PCa, explores EPE's impact on treatment and prognosis, and evaluates the relevance of MRI findings according to different criteria. Accurate EPE diagnosis remains challenging due to MRI limitations and inconsistencies in interpretation. Understanding these variations is crucial for optimal patient management.
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Affiliation(s)
- Cecília Vidal de Souza Torres
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Gabriel de Lion Gouvea
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - André de Freitas Secaf
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - David Freire Maia Vieira
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | | | - Matheus de Moraes Palma
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Gabriel Andrade Ramos
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Jorge Elias
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil
| | - Valdair F Muglia
- Department of Imaging, Oncology and Hematology, Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo, Brazil.
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Esengur OT, Gelikman DG, Law YM, Yilmaz EC, Harmon SA, Merino MJ, Gurram S, Choyke PL, Wood BJ, Pinto PA, Turkbey B. Comparison of Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) and Prostate Imaging after Focal Ablation (PI-FAB) for Detecting Recurrent Prostate Cancer at Prostate MRI. Acad Radiol 2025; 32:855-863. [PMID: 39426916 PMCID: PMC11810585 DOI: 10.1016/j.acra.2024.09.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2024] [Revised: 09/23/2024] [Accepted: 09/23/2024] [Indexed: 10/21/2024]
Abstract
RATIONALE AND OBJECTIVES The increasing use of focal therapy (FT) in localized prostate cancer (PCa) management requires a standardized MRI interpretation system to detect recurrent clinically significant PCa (csPCa). This pilot study evaluates the novel Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) and compares its performance to that of the Prostate Imaging after Focal Ablation (PI-FAB) system. MATERIALS AND METHODS This retrospective study included 38 patients who underwent primary FT for localized PCa, with follow-up multiparametric MRI (mpMRI) and biopsy. Two radiologists assessed the mpMRIs using both PI-FAB and TARGET independently. Diagnostic performance metrics and area under the receiver operating characteristic curve (AUC) were calculated. Inter-reader and intrareader agreement were assessed using Cohen's κ and Kendall's τ. RESULTS 14 patients had recurrent csPCa. PI-FAB showed high sensitivity (92.9% for both readers) and NPV (reader 1: 93.8%, reader 2: 92.9%) but moderate specificity (reader 1: 62.5%, reader 2: 54.2%). TARGET demonstrated lower sensitivity for one reader (reader 1: 78.6%, reader 2: 92.9%) but higher specificity (reader 1: 79.2%, reader 2: 62.5%) for both readers. Both systems displayed moderate inter-reader agreement (κ = 0.56 for PI-FAB, 0.57 for TARGET). CONCLUSION PI-FAB and TARGET exhibit similar performances in post-FT MRI. While PI-FAB had consistently high sensitivity, TARGET offered higher specificity for one reader. Moderate agreement levels demonstrate the viability of these systems in clinical settings and a promise for improvement.
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Affiliation(s)
- Omer Tarik Esengur
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - David G Gelikman
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Yan Mee Law
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore
| | - Enis C Yilmaz
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Stephanie A Harmon
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Maria J Merino
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Sandeep Gurram
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Peter L Choyke
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Bradford J Wood
- Center for Interventional Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD; Department of Radiology, Clinical Center, National Institutes of Health, Bethesda, MD
| | - Peter A Pinto
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Baris Turkbey
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD.
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Paesano N, Catalá V, Tcholakian L, Alomar X, Barranco MÁ, Hernández-Mancera J, Miró B, Trilla E, Morote J. Validation of the Barcelona Magnetic Resonance Imaging Predictive Model for Significant Prostate Cancer Detection in Men Undergoing Mapping per 0.5 Mm-Core Targeted Biopsies of Suspicious Lesions and Perilesional Areas. Cancers (Basel) 2025; 17:473. [PMID: 39941840 PMCID: PMC11815984 DOI: 10.3390/cancers17030473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2024] [Revised: 01/07/2025] [Accepted: 01/28/2025] [Indexed: 02/16/2025] Open
Abstract
Background/Objectives: Validation of predictive models (PMs) is crucial to be implemented in new populations or when advances in diagnostic approaches occurred. The aim of this study is to validate the BCN-MRI PM for sPCa when a highly effective prostate biopsy protocol is used. Methods: A prospective cohort of 457 men suspected of having PCa, for whom MRI results were reported with the Prostate Imaging-Reporting and Data System (PI-RADS) v 2.1, underwent a per 0.5 mm-core mapping targeted biopsy of suspicious lesions and perilesional areas, followed by a 12-core-systematic biopsy. These procedures took place between 1 February 2022, and 29 February 2024, at a reference center for prostate biopsy. The individual likelihood of sPCa was assessed through the BCN-MRI risk calculator. Results: The overall sPCa detection rate was 58.3%. The calibration curve of the BCN-MRI PM showed an appropriate accuracy between expected and observed probabilities with a discrimination ability for sPCa yielding an area under the curve (AUC) of 0.862 (95% CI 0.828-0.896) comparable to the AUC of 0.858 (95% CI 0.833-0.883) observed in the development cohort. The application of the BCN-MRI PM provided a net benefit over performing biopsies on all men, avoiding 24.9% of prostate biopsies at 95% sensitivity for sPCa, compared to the 23.7% reduction observed in the development cohort. Conclusions: We conclude that the BCN-MRI PM is ready to be implemented when this biopsy protocol is employed.
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Affiliation(s)
- Nahuel Paesano
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
- Clínica Creu Blanca, 08034 Barcelona, Spain; (V.C.); (L.T.); (X.A.)
| | - Violeta Catalá
- Clínica Creu Blanca, 08034 Barcelona, Spain; (V.C.); (L.T.); (X.A.)
- Uroima, 08005 Barcelona, Spain
| | - Larisa Tcholakian
- Clínica Creu Blanca, 08034 Barcelona, Spain; (V.C.); (L.T.); (X.A.)
- Uroima, 08005 Barcelona, Spain
| | - Xavier Alomar
- Clínica Creu Blanca, 08034 Barcelona, Spain; (V.C.); (L.T.); (X.A.)
| | | | | | - Berta Miró
- Statistics Unit, Vall d’Hebron Research Institute, 08035 Barcelona, Spain;
| | - Enrique Trilla
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain
| | - Juan Morote
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain
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Jin Y, Chen F, Xu G, Wei C, Dong C. Transition zone-based prostate-specific antigen density for differentiating clinically significant prostate cancer in PI-RADS score 3 lesions. Sci Rep 2025; 15:3258. [PMID: 39863696 PMCID: PMC11762996 DOI: 10.1038/s41598-025-87311-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Accepted: 01/17/2025] [Indexed: 01/27/2025] Open
Abstract
We intended to investigate the potential of several transitional zone (TZ) volume-related variables for the detection of clinically significant prostate cancer (csPCa) among lesions scored as Prostate Imaging Reporting and Data System (PI-RADS) category 3. Between September 2018 and August 2023, patients who underwent mpMRI examination and scored as PI-RADS 3 were queried from our institution. The diagnostic performances of prostate-specific antigen density (PSAD), TZ-adjusted PSAD (TZPSAD), and TZ-ratio (TZ volume/whole gland prostate volume) were analyzed. We calculated the sensitivity and specificity for each variable, the overall accuracy was evaluated with the area under the receiver operating characteristic curve (AUC). The best cutoff value was determined by the Youden index, and differences between diagnostic performances were compared with the Delong test. A total of 154 TZ lesions were included, of them 28 were diagnosed with csPCa. The AUC for PSAD, TZPSAD, and TZ-ratio were 0.644 (95% CI 0.538-0.751), 0.714 (95% CI 0.607-0.821), and 0.746 (95% CI 0.636-0.856), with corresponding optimal cutoff values of 0.11 ng/ml/ml, 0.21 ng/ml/ml, and 0.66 ng/ml/ml, respectively. PSAD was significantly inferior to either TZPSAD (P = 0.03) or TZ-ratio (P = 0.03). The combination model including TZPSAD, TZ-ratio, and age generated an AUC of 0.838 (95% CI 0.759-0.917), significantly higher than use of these variables alone, with P values of 0.001 and 0.035 for the TZPSAD and TZ-ratio, respectively. TZPSAD and TZ-ratio were found to be independent predictors for differentiating csPCa among TZ lesions categorized as PI-RADS score 3. Furthermore, by combining these two variables with others, the diagnostic performance can be improved significantly.
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Affiliation(s)
- Yongming Jin
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng Third People's Hospital, Yancheng, China
| | - Fei Chen
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng Third People's Hospital, Yancheng, China
| | - Gang Xu
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng Third People's Hospital, Yancheng, China
| | - Chaogang Wei
- Department of Radiology, Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Congsong Dong
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng Third People's Hospital, Yancheng, China.
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Utzat F, Herrmann S, May M, Moersler J, Wolff I, Lermer J, Gregor M, Fodor K, Groß V, Kravchuk A, Elgeti T, Degener S, Gilfrich C. Meeting Cancer Detection Benchmarks in MRI/Ultrasound Fusion Biopsy for Prostate Cancer: Insights from a Retrospective Analysis of Experienced Urologists. Cancers (Basel) 2025; 17:277. [PMID: 39858061 PMCID: PMC11764349 DOI: 10.3390/cancers17020277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Revised: 11/18/2024] [Accepted: 01/14/2025] [Indexed: 01/27/2025] Open
Abstract
BACKGROUND The relationship between case volume and clinical outcomes is well established for most urological procedures but remains underexplored in prostate ultrasound/MRI fusion biopsy (UMFB). UMFB aims to detect clinically significant prostate cancer (csPCa) by adhering to cancer detection benchmarks for PI-RADS lesions identified via multiparametric MRI (mpMRI). These benchmarks, defined by Ahmed et al., include cumulative cancer detection rate (C-CDR) targets of >80% for PI-RADS 5, >50% for PI-RADS 4, and <20% for PI-RADS 1-3. METHODS This retrospective, single-center study analyzed the case volumes required for two experienced urologists (U1 and U2, each with >15 years of practice) to consistently achieve the Ahmed-defined C-CDR benchmarks for csPCa (ISUP grade ≥ 2) using UMFB. Both transrectal and transperineal approaches were included to enable comprehensive learning curve analysis. Data from 2017 to 2023 were reviewed, encompassing 157 UMFBs performed by U1 and 242 by U2, with a transrectal-to-perineal ratio of 7:3. RESULTS Both urologists achieved Ahmed-defined C-CDR targets from the outset. Over a median follow-up of 30 months, patients with initial PI-RADS 4 or 5 ratings and negative primary biopsies remained prostate cancer-free in 77% of cases for U1 and 91.2% for U2 (p = 0.152). CONCLUSIONS This study demonstrates that experienced urologists can achieve high diagnostic accuracy and maintain patient safety immediately upon implementing UMFB, meeting established benchmarks without requiring additional procedural learning.
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Affiliation(s)
- Fabian Utzat
- Department of Urology, University of Witten/Herdecke, 42283 Wuppertal, Germany; (F.U.); (S.D.)
| | - Stefanie Herrmann
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
| | - Matthias May
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
| | - Johannes Moersler
- Department of Radiology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany;
| | - Ingmar Wolff
- Department of Urology, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Johann Lermer
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
| | - Mate Gregor
- Institute of Pathology, Hospital Deggendorf, 94469 Deggendorf, Germany;
| | - Katharina Fodor
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
| | - Verena Groß
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
| | - Anton Kravchuk
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
| | - Thomas Elgeti
- Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 12203 Berlin, Germany;
| | - Stephan Degener
- Department of Urology, University of Witten/Herdecke, 42283 Wuppertal, Germany; (F.U.); (S.D.)
| | - Christian Gilfrich
- Department of Urology, St. Elisabeth Hospital Straubing, 94315 Straubing, Germany; (M.M.); (J.L.); (K.F.); (V.G.); (A.K.); (C.G.)
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Chai JG, Li YH, Ke CX. Development of novel nomograms for predicting prostate cancer in biopsy-naive patients with PSA < 10 ng/ml and PI-RADS ≤ 3 lesions. Front Oncol 2025; 14:1500010. [PMID: 39839793 PMCID: PMC11746004 DOI: 10.3389/fonc.2024.1500010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2024] [Accepted: 12/12/2024] [Indexed: 01/23/2025] Open
Abstract
Purpose To develop novel nomograms for predicting prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in patients with prostate-specific antigen (PSA) < 10 ng/ml and PI-RADS v2.1 score ≤ 3. Methods We retrospectively collected data from 327 men with PSA < 10 ng/ml and PI-RADS score ≤ 3 from June 2020 to June 2024 in our hospital. Clinical data were compared among the PI-RADS scores 1-3 population, PI-RADS scores 1-2 population, and PI-RADS score 3 population. Logistic regression analyses were conducted to identify independent risk factors for PCa or csPCa, and nomograms were subsequently developed. The nomograms were evaluated via receiver operating curves (ROC), calibration curves, and decision curve analysis (DCA). Internal validation was conducted using bootstrap methods. Results Among the 327 patients, 224 (68.50%) were diagnosed with benign, 65 (19.87%) with csPCa, and 38 (11.62%) with clinically insignificant prostate cancer (cisPCa). Prostate-specific antigen density (PSAD), lesion volume (LV), lesion location, and apparent diffusion coefficient (ADC) were found to be independent risk factors for PCa and csPCa in PI-RADS scores 1-3 population. PSAD and lesion location were independent risk factors for PCa in the PI-RADS scores 1-2 population, while PSAD, lesion location and ADC were independent risk factors for PCa in the PI-RADS score 3 population. Four nomograms were established based on these variables. For the population with PI-RADS scores 1-3, the area under the ROC (AUC) for predicting PCa and csPCa was 0.78 and 0.79, respectively. For patients with PI-RADS scores 1-2, the AUC for predicting PCa was 0.75. For patients with PI-RADS score 3, the AUC for predicting PCa was 0.78. The calibration curves revealed good concordance between the predicted probability and the actual probability. DCA demonstrated the net benefit of nomograms. Internal validation revealed strong discrimination of the nomograms. Conclusion We developed novel nomograms with acceptable discriminability for predicting PCa and csPCa in patients with PSA < 10 ng/ml and PI-RADS score ≤ 3. These models can assist urologists in determining the necessity of prostate biopsy.
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Affiliation(s)
| | | | - Chang-xing Ke
- Department of Urology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
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Launer BM, Ellis TA, Scarpato KR. A contemporary review: mpMRI in prostate cancer screening and diagnosis. Urol Oncol 2025; 43:15-22. [PMID: 39129080 DOI: 10.1016/j.urolonc.2024.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/29/2024] [Accepted: 05/18/2024] [Indexed: 08/13/2024]
Abstract
Prostate cancer (PCa) screening has evolved beyond PSA and digital rectal exam to include multiparametric prostate MRI (mpMRI). Incorporating this advanced imaging tool has further limited the well-established problem of overdiagnosis, aiding in the identification of higher grade, clinically significant cancers. For this reason, mpMRI has become an important part of the diagnostic pathway and is recommended across guidelines in biopsy naïve patients or for patients with prior negative biopsy. This contemporary review evaluates the most recent literature on the role of mpMRI in the screening and diagnosis of prostate cancer. Barriers to utilization of mpMRI still exist including variable access, high cost, and requisite expertise, encouraging evaluation of novel techniques such as biparametric MRI. Future screening and diagnostic practice patterns will undoubtedly evolve as our understanding of novel biomarkers and artificial intelligence improves.
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Affiliation(s)
- Bryn M Launer
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Taryn A Ellis
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kristen R Scarpato
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, United States.
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Esen B, Gürses B, Sekmen M, Kordan Y, Kiremit MC, Vural M, Tilki D, Esen T. Natural history of PIRADS-2 lesions on serial multiparametric magnetic resonance imaging: Real-life data from an Academic Center. Urol Oncol 2025; 43:65.e9-65.e15. [PMID: 39256146 DOI: 10.1016/j.urolonc.2024.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 08/03/2024] [Accepted: 08/15/2024] [Indexed: 09/12/2024]
Abstract
INTRODUCTION/BACKGROUND The natural history of prostate imaging reporting and data system (PIRADS) score 2 lesions on serial mpMRIs is largely unknown. Herein, we aimed to evaluate the patients with PIRADS-2 index lesions by using serial mpMRI scans to reveal the rates of mpMRI upgrade in PIRADS score and prostate cancer (PCa) detection. METHODS/MATERIALS All mpMRI scans with a PIRADS-2 index lesion from our mpMRI database were evaluated retrospectively. Data from 214 biopsy-naïve patients with a PIRADS-2 index lesion on the initial mpMRI who then underwent at least 1 follow-up mpMRI were reevaluated by an experienced uroradiologist and only those (n = 172) who had a PIRADS-2 index lesion on the initial mpMRI according to PIRADS v2.1 were included in the study. mpMRI progression was defined as the detection of any PIRADS ≥3 lesion at follow-up mpMRI. Histopathological results were evaluated in patients undergoing biopsy upon mpMRI progression. RESULTS A total of 172 patients with a mean age of 60.1 ± 8.6 years were evaluated. The median PSA at baseline mpMRI was 4.7 (IQR; 3.3-6.7) ng/dl. Overall mpMRI progression was detected in 54 patients (31.4%), 37 were upgraded to PIRADS-3, 16 to PIRADS-4, and one to PIRADS-5. Multivariate logistic regression analysis revealed that a PSA increase of ≥25% during follow-up was the only predictor of mpMRI upgrade (P = 0.019, OR: 2.384). 30 out of 54 patients underwent a prostate biopsy and PCa was detected in 15 patients; 5 with ISUP grade 1, 10 with ISUP grade 2. CONCLUSIONS Almost half of the patients with a PIRADS-2 index lesion were upgraded to PIRADS ≥3 when evaluated with serial mpMRI when a PSA increase of ≥25% was observed during follow-up. PCa was detected in half of the patients who underwent a biopsy. Serial mpMRI can be recommended when monitoring patients with elevating PSA ≥25%, a prostate biopsy can be considered upon a mpMRI progression.
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Affiliation(s)
- Barış Esen
- Department of Urology, Koc University, School of Medicine, Istanbul, Türkiye.
| | - Bengi Gürses
- Department of Radiology, Koc University, School of Medicine, Istanbul, Türkiye
| | - Mert Sekmen
- Department of Urology, Koc University, School of Medicine, Istanbul, Türkiye
| | - Yakup Kordan
- Department of Urology, Koc University, School of Medicine, Istanbul, Türkiye
| | - Murat Can Kiremit
- Department of Urology, Koc University, School of Medicine, Istanbul, Türkiye
| | - Metin Vural
- Radiology Clinic, VKF American Hospital, Istanbul, Türkiye
| | - Derya Tilki
- Department of Urology, Koc University, School of Medicine, Istanbul, Türkiye; Department of Urology, Hamburg University, School of Medicine, Hamburg, Germany; Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Tarık Esen
- Department of Urology, Koc University, School of Medicine, Istanbul, Türkiye
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Morote J, Celma A, Semidey ME, Antolín A, Miró B, Méndez O, Trilla E. Analysis of Inflammatory Features in Suspicious Lesions for Significant Prostate Cancer on Magnetic Resonance Imaging-Are They Mimickers of Prostate Cancer? Cancers (Basel) 2024; 17:53. [PMID: 39796682 PMCID: PMC11718908 DOI: 10.3390/cancers17010053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Revised: 12/19/2024] [Accepted: 12/23/2024] [Indexed: 01/13/2025] Open
Abstract
BACKGROUND Inflammatory features can mimic PCa in suspicious MRI-lesions. OBJECTIVES To assess the incidence of inflammatory features in targeted biopsies to suspicious lesions. METHODS A prospective analysis was conducted of 531 MRI-suspicious lesions with Prostate Imaging-Reporting and Data System (PI-RADS) scores of 3 to 5 in 364 men suspected of having PCa. RESULTS The incidence of inflammatory features in the MRI-suspicious lesions without PCa was 69.6%, compared to 48.1% in those with PCa (p < 0.001). Among the suspicious lesions without PCa, the incidence of inflammatory features ranged from 68.6% to 71.2% across the PI-RADS categories (p = 0.870). Mild chronic prostatitis increased with higher PI-RADS scores, while acute prostatitis decreased, and granulomatous prostatitis was exclusively observed in patients with PI-RADS scores of 4 and 5. The incidence of inflammatory features in the lesions with insignificant PCa (grade group 1) was 66.7%, compared to 42.7% in those with significant PCa (grade group 2 to 5; p = 0.027). The detection of inflammatory features in MRI-suspicious lesions was identified as an independent predictor of a lower likelihood of significant PCa detection, with an odds ratio (OR) of 0.326 (95% CI 0.196-0.541). Mild chronic prostatitis was the only type of prostatitis which was an independent predictor of a lower likelihood of significant PCa, with an OR of 0.398 (95% CI 0.268-0.590). CONCLUSIONS These data suggest that inflammatory features may be considered mimickers of significant PCa on MRI.
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Affiliation(s)
- Juan Morote
- Department of Urology, Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain; (A.C.); (E.T.)
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;
- Urology Research Group, Vall d’Hebron Research Institute, 08035 Barcelona, Spain; (M.E.S.); (O.M.)
| | - Ana Celma
- Department of Urology, Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain; (A.C.); (E.T.)
- Urology Research Group, Vall d’Hebron Research Institute, 08035 Barcelona, Spain; (M.E.S.); (O.M.)
| | - María E. Semidey
- Urology Research Group, Vall d’Hebron Research Institute, 08035 Barcelona, Spain; (M.E.S.); (O.M.)
- Department of Pathology, Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain
| | - Andreu Antolín
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;
- Department of Radiology, Institut de Diagnòstic per la Imatge, Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain
| | - Berta Miró
- Statistics Unit, Vall d’Hebron Research Institute, 08035 Barcelona, Spain;
| | - Olga Méndez
- Urology Research Group, Vall d’Hebron Research Institute, 08035 Barcelona, Spain; (M.E.S.); (O.M.)
| | - Enrique Trilla
- Department of Urology, Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain; (A.C.); (E.T.)
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;
- Urology Research Group, Vall d’Hebron Research Institute, 08035 Barcelona, Spain; (M.E.S.); (O.M.)
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Liu WQ, Wei Y, Ke ZB, Lin B, Wu XH, Huang XY, Chen ZJ, Chen JY, Chen SH, Xue YT, Lin F, Chen DN, Zheng QS, Xue XY, Xu N. Radiomics of Periprostatic Fat and Tumor Lesion Based on MRI Predicts the Pathological Upgrading of Prostate Cancer from Biopsy to Radical Prostatectomy. Acad Radiol 2024:S1076-6332(24)00890-0. [PMID: 39730248 DOI: 10.1016/j.acra.2024.11.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 09/04/2024] [Accepted: 11/16/2024] [Indexed: 12/29/2024]
Abstract
RATIONALE AND OBJECTIVES To assess the predictive value of MRI-based radiomics of periprostatic fat (PPF) and tumor lesions for predicting Gleason score (GS) upgrading from biopsy to radical prostatectomy (RP) in prostate cancer (PCa). METHODS A total of 314 patients with pathologically confirmed prostate cancer (PCa) after radical prostatectomy (RP) were included in the study. The patients were randomly assigned to the training cohort (n = 157) and the validating cohort (n = 157) in a 1:1 ratio. All had pre-surgery MRI followed by transrectal ultrasound-guided prostate biopsy. Radiological features were extracted from T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) sequences for PPF and tumors. Univariate and multivariate logistic regression identified independent clinical risk factors, and a combined model was established by integrating radiomic features of PPF and PCa. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration, and decision curve analysis. RESULTS The combined model, incorporating radiomic features of PPF, PCa, and clinical data, predicted GS upgrading from biopsy to RP excellently (AUC=0.925, 95%CI0.872-0.979) in the training cohort. The Hosmer-Lemeshow test confirmed model fit (χ2 = 9.316, P = 0.316). The nomogram was validated in the validating cohort; it showed good accuracy (AUC= 0.937, 95% CI, 0.891-0.983) and was well calibrated (χ2 = 12.871, P = 0.116). Decision curve analysis indicated good clinical utility of the radiomic nomogram. CONCLUSION The combined model incorporating PPF, PCa, and clinical data showed excellent performance in predicting GS upgrading from biopsy to RP in PCa patients. This offers a novel and reliable noninvasive tool for GS upgrading risk stratification.
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Affiliation(s)
- Wen-Qi Liu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Yong Wei
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Zhi-Bin Ke
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Bin Lin
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Xiao-Hui Wu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Xu-Yun Huang
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Ze-Jia Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Jia-Yin Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Shao-Hao Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Yu-Ting Xue
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Fei Lin
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Dong-Ning Chen
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Qing-Shui Zheng
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.)
| | - Xue-Yi Xue
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China (X-Y.X., N.X.)
| | - Ning Xu
- Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 35005, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China (W-Q.L., Y.W., Z-B.K., B.L., X-H.W., X-Y.H., Z-J.C., J-Y.C., S-H.C., Y-T.X., F.L., D-N.C., Q-S.Z., X-Y.X., N.X.); Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China (X-Y.X., N.X.).
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Qin F, Liu Z, Ma J, Wu J, Shen Q, Liu Y, Li X. Visibility of mpMRI region of interest on ultrasound during cognitive fusion targeted biopsy predicts prostate cancer detection: a prospective single-center study. Abdom Radiol (NY) 2024:10.1007/s00261-024-04750-6. [PMID: 39710761 DOI: 10.1007/s00261-024-04750-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2024] [Revised: 11/08/2024] [Accepted: 12/05/2024] [Indexed: 12/24/2024]
Abstract
PURPOSE The purpose of this study was to evaluate the nature of ultrasound characteristics during mpMRI/TRUS cognitive fusion targeted biopsy (cTB). METHODS From 2023 to 2024, data from 502 lesions in 426 men who underwent targeted combined systematic biopsy were analyzed. All lesions had a Prostate Imaging Reporting and Data System (PI-RADS) score of ≥ 3. The primary endpoint was the detection rate of prostate cancer (PCa) according to the PI-RADS score/ultrasound characteristics, categorized as benign or invisible (Bi), hypoechoic only (Ho), and hypoechoic with microcalcification (Hm), assessed through cross-stratification. The secondary endpoints included the distribution of ultrasound characteristics across PI-RADS scores, prostate zones, and histological types. Finally, associations between ultrasound characteristics and clinically significant PCa (csPCa) were assessed using multivariate logistic regression analysis (MVA). RESULTS Among lesions, 233 (46%) were Bi, 210 (42%) Ho, and 59 (12%) Hm. First, Bi lesions had a 64% (103/161) non-cancer rate in PI-RADS 3, while Ho + Hm lesions showed the highest csPCa rate in PI-RADS 5 at 82% (102/124). Additionally, Ho + Hm lesions were predominantly observed in PI-RADS 5 (92% [114/124]) and in the peripheral zone (64% [179/278]). Notably, Hm lesions had a significantly higher percentage of cribriform morphology than Ho lesions (32% vs. 14%, P = 0.001). Finally, MVA confirmed Ho ([Ref Bi] OR 4.95, P < 0.001) and Hm ([Ref Bi] OR 27.7, P < 0.001) as independent predictors of csPCa. CONCLUSION In cTB, the identification of Ho and Hm lesions on TRUS enhances the diagnostic yield of csPCa by facilitating more precise localization compared to Bi lesions. CLINICAL TRIAL REGISTRATION No. 2023-272-002, July 14, 2023.
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Affiliation(s)
- Fei Qin
- Peking University First Hospital, 8 Xishiku Street, Xicheng, Beijing, 100034, China
- The Third Hospital of Hebei Medical University, 139 Ziqiang Road, Qiaoxi, Shijiazhuang, 050000, China
| | - Zhijian Liu
- Peking University First Hospital, 8 Xishiku Street, Xicheng, Beijing, 100034, China
| | - Jianguo Ma
- The Third Hospital of Hebei Medical University, 139 Ziqiang Road, Qiaoxi, Shijiazhuang, 050000, China
| | - Jingyun Wu
- Peking University First Hospital, 8 Xishiku Street, Xicheng, Beijing, 100034, China
| | - Qi Shen
- Peking University First Hospital, 8 Xishiku Street, Xicheng, Beijing, 100034, China
| | - Yi Liu
- Peking University First Hospital, 8 Xishiku Street, Xicheng, Beijing, 100034, China.
| | - Xuesong Li
- Peking University First Hospital, 8 Xishiku Street, Xicheng, Beijing, 100034, China.
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Tamada T, Takeuchi M, Watanabe H, Higaki A, Moriya K, Kanki A, Fukukura Y, Yamamoto A. Differentiating clinically significant prostate cancer from clinically insignificant prostate cancer using qualitative and semi-quantitative indices of dynamic contrast-enhanced MRI. Discov Oncol 2024; 15:770. [PMID: 39692850 DOI: 10.1007/s12672-024-01668-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 12/03/2024] [Indexed: 12/19/2024] Open
Abstract
PURPOSE To investigate the utility of qualitative and semi-quantitative evaluation of DCE-MRI for detecting clinically significant prostate cancer (csPC). METHODS This retrospective study analyzed 307 lesions in 231 patients who underwent 3.0T MRI. Experienced radiologists assessed PI-RADS v 2.1 assessment category, qualitative contrast enhancement (QCE), contrast enhancement pattern (CEP: type 1, 2, 3), tumor contrast ratio, and tumor size of PC lesions in consensus. Mean and 0-10th-percentile ADC value of the lesion (ADCmean and ADC0-10) were calculated. Specimens obtained from MRI-ultrasound fusion-guided prostate biopsy were used as the pathological reference standard. RESULTS In assessment of tumor aggressiveness, PI-RADS assessment category, QCE, tumor size, and ratio of CEP 2 + 3 were significantly higher in PC with Gleason score (GS) ≥ 3 + 4 (n = 256) than in PC with GS = 6 (n = 51) (P ≤ 0.001). Tumor ADCmean and tumor ADC0-10 were comparable between PC with GS ≥ 3 + 4 and PC with GS = 6 (P = 0.164 to 0.504). Regarding diagnostic performance of csPC in 45 PI-RADS 3 transition zone lesions, only ratio of CEP 2 + 3 was significantly higher in PC with GS ≥ 3 + 4 (n = 31) than in PC with GS = 6 (n = 14) (P = 0.008). CONCLUSION Qualitative DCE-MRI indices may contribute to PC aggressiveness and improve detection of csPC in PI-RADS assessment category 3 lesions.
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Affiliation(s)
- Tsutomu Tamada
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan.
| | - Mitsuru Takeuchi
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
- Department of Radiology, Radiolonet Tokai, Nagoya, Japan
| | - Hiroyuki Watanabe
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | - Atsushi Higaki
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | - Kazunori Moriya
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | - Akihiko Kanki
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | - Yoshihiko Fukukura
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | - Akira Yamamoto
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
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Mehawed G, Roberts MJ, Bugeja J, Dowling J, Stewart K, Gunasena R, Malczewski F, Rukin NJ, Murray R. A Pilot Study of PSMA PET/CT and MRI Fusion for Prostate Cancer: Software to Replace PET/MRI Hardware. J Clin Med 2024; 13:7384. [PMID: 39685842 DOI: 10.3390/jcm13237384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Revised: 11/26/2024] [Accepted: 11/27/2024] [Indexed: 12/18/2024] Open
Abstract
Introduction: Prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT), in combination with magnetic resonance imaging (MRI), may enhance the diagnosis and staging of prostate cancer. Image fusion of separately acquired PET/CT and MRI images serve to facilitate clinical integration and treatment planning. This study aimed to investigate different PSMA PET/CT and MRI image fusion workflows for prostate cancer visualisation. Methods: Eighteen patients with prostate cancer who underwent PSMA PET/CT and MRI prior to radical prostatectomy were retrospectively selected. Alignment of the prostate was performed between PET/CT and MRI via three techniques: semi-automatic rigid, automatic rigid, and automatic non-rigid. Image fusion accuracy was evaluated through boundary and volume agreement, quantified by the Dice Similarity Coefficient (DSC), 95% Hausdorff Distance (HD), and Mean Surface Distance (MSD), with comparison against reconstructed histopathology slices. Results: Image fusion using all techniques resulted in clear lesion visualisation from PSMA PET/CT overlay and anatomical detail afforded by the MRI base and was consistent with histopathology tumour location. Image fusion accuracy was within the recommended range based on a DSC of 0.8-0.9. The automatic non-rigid registration method had the highest volume agreement (DSC: 0.96 ± <0.01) and boundary agreement (HD: 1.17 ± 0.35 mm) when compared to automatic rigid (DSC 0.88 ± 0.02, HD 3.18 ± 0.29 mm) and semi-automatic rigid (DSC 0.80 ± 0.06, HD 5.25 ± 1.68 mm). Conclusions: Image fusion of clinically obtained PET/CT and MRI is feasible and clinically acceptable for use in prostate cancer diagnosis and surgical management. While the best accuracy was observed with the automatic non-rigid technique, which requires further validation, image fusion with clinically accessible methods (semi-automatic rigid) may currently aid patient education, pre-operative planning, and intra-operative guidance.
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Affiliation(s)
- Georges Mehawed
- Herston Biofabrication Institute, Metro North Health, Herston, QLD 4029, Australia
- Urology Department, Redcliffe Hospital, Metro North Health, Redcliffe, QLD 4020, Australia
- School of Medicine, University of Queensland, Herston, QLD 4029, Australia
- Australian Institute of Bioengineering and Nanotechnology, University of Queensland, St. Lucia, QLD 4067, Australia
| | - Matthew J Roberts
- School of Medicine, University of Queensland, Herston, QLD 4029, Australia
- Urology Department, Royal Brisbane and Women's Hospital, Metro North Health, Herston, QLD 4029, Australia
- University of Queensland Centre for Clinical Research, University of Queensland, Herston, QLD 4029, Australia
| | - Jessica Bugeja
- Commonwealth Scientific and Industrial Research Organisation, Australian E-Health Research Centre, Herston, QLD 4029, Australia
| | - Jason Dowling
- Commonwealth Scientific and Industrial Research Organisation, Australian E-Health Research Centre, Herston, QLD 4029, Australia
- Information Technology and Electrical Engineering, University of Queensland, St. Lucia, QLD 4067, Australia
| | - Kate Stewart
- Department of Radiation Oncology, Royal Brisbane and Women's Hospital, Metro North Health, Herston, QLD 4029, Australia
| | - Rivindi Gunasena
- Department of Radiology, Royal Brisbane and Women's Hospital, Metro North Health, Herston, QLD 4029, Australia
| | - Frances Malczewski
- Department of Pathology, Royal Brisbane and Women's Hospital, Metro North Health, Herston, QLD 4029, Australia
| | - Nicholas J Rukin
- Herston Biofabrication Institute, Metro North Health, Herston, QLD 4029, Australia
- Urology Department, Redcliffe Hospital, Metro North Health, Redcliffe, QLD 4020, Australia
- School of Medicine, University of Queensland, Herston, QLD 4029, Australia
| | - Rebecca Murray
- Herston Biofabrication Institute, Metro North Health, Herston, QLD 4029, Australia
- Urology Department, Redcliffe Hospital, Metro North Health, Redcliffe, QLD 4020, Australia
- Australian Institute of Bioengineering and Nanotechnology, University of Queensland, St. Lucia, QLD 4067, Australia
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Zandie F, Salehi M, Maziar A, Bayatiani MR, Paydar R. Radiomics based Machine Learning Models for Classification of Prostate Cancer Grade Groups from Multi Parametric MRI Images. JOURNAL OF MEDICAL SIGNALS & SENSORS 2024; 14:33. [PMID: 39741789 PMCID: PMC11687675 DOI: 10.4103/jmss.jmss_47_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 08/24/2024] [Accepted: 09/13/2024] [Indexed: 01/03/2025]
Abstract
Purpose This study aimed to investigate the performance of multiparametric magnetic resonance imaging (mpMRI) radiomic feature-based machine learning (ML) models in classifying the Gleason grade group (GG) of prostate cancer. Methods In this retrospective study, a total of 203 patients with histopathologically confirmed prostate cancer who underwent mpMRI before prostate biopsy were included. After manual segmentation, radiomic features (RFs) were extracted from T2-weighted, apparent diffusion coefficient, and high b-value diffusion-weighted magnetic resonance imaging (DWMRI). Patients were split into training sets and testing sets according to a ratio of 8:2. A pipeline considering combinations of two feature selection (FS) methods and six ML classifiers was developed and evaluated. The performance of models was assessed using the accuracy, sensitivity, precision, F1-measure, and the area under curve (AUC). Results On high b-value DWMRI-derived features, a combination of FS method recursive feature elimination (RFE) and classifier random forest achieved the highest performance for classification of prostate cancer into five GGs, with 97.0% accuracy, 98.0% sensitivity, 98.0% precision, and 97.0% F1-measure. The method also achieved an average AUC for GG of 98%. Conclusion Preoperative mpMRI radiomic analysis based on ML, as a noninvasive approach, showed good performance for classification of prostate cancer into five GGs. Advances in Knowledge Herein, radiomic models based on preoperative mpMRI and ML were developed to classify prostate cancer into 5 GGs. Our study provides evidence that analysis of quantitative RFs extracted from high b-value DWMRI images based on a combination of FS method RFE and classifier random forest can be applied for multiclass grading of prostate cancer with an accuracy of 97.0%.
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Affiliation(s)
- Fatemeh Zandie
- Department of Radiation Sciences, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mohammad Salehi
- Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Asghar Maziar
- Department of Radiation Sciences, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Bayatiani
- Department of Radiotherapy and Medical Physics, Faculty of Para Medicine, Arak University of Medical Sciences and Khansari Hospital, Arak, Iran
| | - Reza Paydar
- Department of Radiation Sciences, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran
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Le Bihan D. From Brownian motion to virtual biopsy: a historical perspective from 40 years of diffusion MRI. Jpn J Radiol 2024; 42:1357-1371. [PMID: 39289243 PMCID: PMC11588775 DOI: 10.1007/s11604-024-01642-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Accepted: 08/07/2024] [Indexed: 09/19/2024]
Abstract
Diffusion MRI was introduced in 1985, showing how the diffusive motion of molecules, especially water, could be spatially encoded with MRI to produce images revealing the underlying structure of biologic tissues at a microscopic scale. Diffusion is one of several Intravoxel Incoherent Motions (IVIM) accessible to MRI together with blood microcirculation. Diffusion imaging first revolutionized the management of acute cerebral ischemia by allowing diagnosis at an acute stage when therapies can still work, saving the outcomes of many patients. Since then, the field of diffusion imaging has expanded to the whole body, with broad applications in both clinical and research settings, providing insights into tissue integrity, structural and functional abnormalities from the hindered diffusive movement of water molecules in tissues. Diffusion imaging is particularly used to manage many neurologic disorders and in oncology for detecting and classifying cancer lesions, as well as monitoring treatment response at an early stage. The second major impact of diffusion imaging concerns the wiring of the brain (Diffusion Tensor Imaging, DTI), allowing to obtain from the anisotropic movement of water molecules in the brain white-matter images in 3 dimensions of the brain connections making up the Connectome. DTI has opened up new avenues of clinical diagnosis and research to investigate brain diseases, neurogenesis and aging, with a rapidly extending field of application in psychiatry, revealing how mental illnesses could be seen as Connectome spacetime disorders. Adding that water diffusion is closely associated to neuronal activity, as shown from diffusion fMRI, one may consider that diffusion MRI is ideally suited to investigate both brain structure and function. This article retraces the early days and milestones of diffusion MRI which spawned over 40 years, showing how diffusion MRI emerged and expanded in the research and clinical fields, up to become a pillar of modern clinical imaging.
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Affiliation(s)
- Denis Le Bihan
- NeuroSpin, CEA, Paris-Saclay University, Bât 145, CEA-Saclay Center, 91191, Gif-sur-Yvette, France.
- Human Brain Research Center, Kyoto University, Kyoto, Japan.
- Department of System Neuroscience, National Institutes for Physiological Sciences, Okazaki, Japan.
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Straat KR, Hagens MJ, Cools Paulino Pereira LJ, van den Bergh RC, Mazel JW, Noordzij MA, Rynja SP. Risk Calculator Strategy Before Magnetic Resonance Imaging Stratification for Biopsy-naïve Men with Suspicion for Prostate Cancer: A Cost-effectiveness Analysis. EUR UROL SUPPL 2024; 70:52-57. [PMID: 39483520 PMCID: PMC11525455 DOI: 10.1016/j.euros.2024.08.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/30/2024] [Indexed: 11/03/2024] Open
Abstract
Background and objective Current guidelines on prostate cancer (PCa) diagnosis recommend risk stratification before prostate biopsy, using either a risk calculator (RC) or magnetic resonance imaging (MRI). The aim of our study was to assess the effectiveness and cost effectiveness of an RC strategy and a direct MRI (dMRI) strategy. Methods Data for biopsy-naïve men suspected of having PCa on the basis of elevated prostate specific antigen (PSA) and/or abnormal digital rectal examination (DRE) were retrospectively collected from two large teaching hospitals. The RC and dMRI strategies were evaluated for PCa detection, effectiveness, and costs. The RC strategy used the Rotterdam prostate cancer risk calculator 3/4 and MRI for stratification, while the dMRI strategy directly used MRI findings. Clinically significant (cs)PCa was defined as a Gleason score ≥3 + 4. Key findings and limitations In total, 1458 men were included for analysis, of whom 944 were in the RC group and 514 were in the dMRI group. The RC strategy significantly reduced MRI use by 47.8% (52.2% vs 99.8%; p < 0.001) and reduced costs by 14.3% (€422.45 vs €492.77; p < 0.001) in comparison to the dMRI strategy. The number of patients who underwent prostate biopsy (36.5% vs. 40.9%; p = 0.11) and the csPCa detection rate (43.5% vs 45.2%; p = 0.69) were similar between the groups. The study is limited by its retrospective nature, so the findings should be interpreted with caution. Conclusions and clinical implications Both the RC strategy and the dMRI strategy are viable options for PCa diagnosis, with the former significantly reducing MRI use and overall diagnostic costs per person. Therefore, the RC strategy might be preferred over dMRI, particularly in contexts aiming for sustainable health care practices that optimize resource allocation and cost effectiveness. Patient summary We compared two different approaches for men with a suspicion of prostate cancer. One uses a risk calculator to decide on whether to perform an MRI (magnetic resonance imaging) scan, and the other proceeds directly to MRI. In both cases, prostate biopsy is performed in cases with positive MRI findings. The number of patients who needed a biopsy and the cancer detection rate were similar for the two approaches.
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Affiliation(s)
| | - Marinus J. Hagens
- Department of Urology, VUmc site, Amsterdam University Medical Centers, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
- Department of Urology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | | | - Roderick C.N. van den Bergh
- Department of Urology, Sint Antonius Hospital, Urology, Nieuwegein, The Netherlands
- Department of Urology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jan Willem Mazel
- Department of Urology, Spaarne Gasthuis, Hoofddorp, The Netherlands
- Department of Urology, VUmc site, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - M. Arjen Noordzij
- Department of Urology, Spaarne Gasthuis, Hoofddorp, The Netherlands
- Department of Urology, VUmc site, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Sybren P. Rynja
- Department of Urology, Spaarne Gasthuis, Hoofddorp, The Netherlands
- Department of Urology, VUmc site, Amsterdam University Medical Centers, Amsterdam, The Netherlands
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Jung G, Song B, Ahn H, Hwang SI, Lee HJ, Huh KY, Song SH, Lee S, Byun SS, Hong SK. Oncological outcomes after radical prostatectomy of localized prostate cancer: stratified by magnetic resonance imaging and risk classification. Prostate Int 2024; 12:224-230. [PMID: 39735202 PMCID: PMC11681324 DOI: 10.1016/j.prnil.2024.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Revised: 09/19/2024] [Accepted: 09/25/2024] [Indexed: 12/31/2024] Open
Abstract
Background We investigated whether combining T2-weighted magnetic resonance imaging (MRI) findings and clinical risk categories improves upon established prognostic indicators of oncological outcomes in prostate cancer. Methods Patients who underwent radical prostatectomy, but not preoperative hormone therapy, radiotherapy, or chemotherapy, for localized prostate cancer at Seoul National University Bundang Hospital from October 2007 to April 2016 were included. MRIs were classified according to the Prostate Imaging-Reporting and Data System (PI-RADS). Patients were divided into the following five groups: 1, no focal suspicious lesion; 2, organ-confined suspicious lesion PI-RADS ≤3; 3, organ-confined suspicious lesion PI-RADS 4 or 5; 4, suspicious lesion with extraprostatic extension (EPE), no seminal vesicle invasion (SVI); 5, suspicious lesion with EPE and SVI. Risk classified according to the National Comprehensive Cancer Network (NCCN) and MRI findings were combined to analyze survival curves for biochemical recurrence (BCR)-free and metastasis-free survival. The area under a time-dependent receiver operating characteristic was analyzed for event prediction after 5 years. Results We analyzed 1,290 patients. In multivariate Cox regression models, PI-RADS ≥4 (hazard ratio [HR] 2.33, P < 0.001), EPE (HR 1.46, P = 0.027), SVI (HR 5.03, P < 0.001) and NCCN high-risk (HR 2.33, 95% CI 1.66-3.26, P < 0.001) were associated with BCR. For metastasis, EPE (HR 2.33, P = 0.047), SVI (HR 13.08, P < 0.001) and NCCN high-risk (HR 2.78, P = 0.026) were independent risk factors. Depending on MRI group, BCR-free survival significantly decreased in NCCN intermediate-risk (P = 0.001) and high-risk (P < 0.001) groups, and metastasis-free survival decreased in the intermediate-risk group (P = 0.39) and significantly decreased in the high-risk (P < 0.001) group. Adding MRI group to NCCN risk classification significantly improved the predictive accuracy for BCR in comparison with NCCN risk classification alone (P = 0.042), but not for metastasis (P = 0.012). Conclusion Combining prostate MRI with NCCN risk classification improves the prediction value of BCR following radical prostatectomy for localized prostate cancer.
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Affiliation(s)
- Gyoohwan Jung
- Department of Urology, Hanyang University College of Medicine, Seoul, Korea
| | - Byeongdo Song
- Department of Urology, Hanyang University Guri Hospital, Guri, Kyunggi-Do, Korea
| | - Hyungwoo Ahn
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sung Il Hwang
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Hak Jong Lee
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Ki Young Huh
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Korea
| | - Sang Hun Song
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sangchul Lee
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Urology, Seoul National University College of Medicine, Seoul, Korea
| | - Seok-Soo Byun
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea
| | - Sung Kyu Hong
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Urology, Seoul National University College of Medicine, Seoul, Korea
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Coelho FMA, Baroni RH. Strategies for improving image quality in prostate MRI. Abdom Radiol (NY) 2024; 49:4556-4573. [PMID: 38940911 DOI: 10.1007/s00261-024-04396-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 05/15/2024] [Accepted: 05/17/2024] [Indexed: 06/29/2024]
Abstract
Prostate magnetic resonance imaging (MRI) stands as the cornerstone in diagnosing prostate cancer (PCa), offering superior detection capabilities while minimizing unnecessary biopsies. Despite its critical role, global disparities in MRI diagnostic performance persist, stemming from variations in image quality and radiologist expertise. This manuscript reviews the challenges and strategies for enhancing image quality in prostate MRI, spanning patient preparation, MRI unit optimization, and radiology team engagement. Quality assurance (QA) and quality control (QC) processes are pivotal, emphasizing standardized protocols, meticulous patient evaluation, MRI unit workflow, and radiology team performance. Additionally, artificial intelligence (AI) advancements offer promising avenues for improving image quality and reducing acquisition times. The Prostate-Imaging Quality (PI-QUAL) scoring system emerges as a valuable tool for assessing MRI image quality. A comprehensive approach addressing technical, procedural, and interpretative aspects is essential to ensure consistent and reliable prostate MRI outcomes.
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Affiliation(s)
| | - Ronaldo Hueb Baroni
- Department of Radiology, Hospital Israelita Albert Einstein, 627 Albert Einstein Ave., Sao Paulo, SP, 05652-900, Brazil.
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Schrader A, Netzer N, Hielscher T, Görtz M, Zhang KS, Schütz V, Stenzinger A, Hohenfellner M, Schlemmer HP, Bonekamp D. Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms. Eur Radiol 2024; 34:7909-7920. [PMID: 38955845 PMCID: PMC11557625 DOI: 10.1007/s00330-024-10818-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/15/2024] [Accepted: 04/21/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVES Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) analyzes MRI data independently, and has been shown to be on par with clinical radiologists, but has yet to be incorporated into RCs. The goal of this study is to re-assess the diagnostic quality of RCs, the impact of replacing PI-RADS with DL predictions, and potential performance gains by adding DL besides PI-RADS. MATERIAL AND METHODS One thousand six hundred twenty-seven consecutive examinations from 2014 to 2021 were included in this retrospective single-center study, including 517 exams withheld for RC testing. Board-certified radiologists assessed PI-RADS during clinical routine, then systematic and MRI/Ultrasound-fusion biopsies provided histopathological ground truth for significant prostate cancer (sPC). nnUNet-based DL ensembles were trained on biparametric MRI predicting the presence of sPC lesions (UNet-probability) and a PI-RADS-analogous five-point scale (UNet-Likert). Previously published RCs were validated as is; with PI-RADS substituted by UNet-Likert (UNet-Likert-substituted RC); and with both UNet-probability and PI-RADS (UNet-probability-extended RC). Together with a newly fitted RC using clinical data, PI-RADS and UNet-probability, existing RCs were compared by receiver-operating characteristics, calibration, and decision-curve analysis. RESULTS Diagnostic performance remained stable for UNet-Likert-substituted RCs. DL contained complementary diagnostic information to PI-RADS. The newly-fitted RC spared 49% [252/517] of biopsies while maintaining the negative predictive value (94%), compared to PI-RADS ≥ 4 cut-off which spared 37% [190/517] (p < 0.001). CONCLUSIONS Incorporating DL as an independent diagnostic marker for RCs can improve patient stratification before biopsy, as there is complementary information in DL features and clinical PI-RADS assessment. CLINICAL RELEVANCE STATEMENT For patients with positive prostate screening results, a comprehensive diagnostic workup, including prostate MRI, DL analysis, and individual classification using nomograms can identify patients with minimal prostate cancer risk, as they benefit less from the more invasive biopsy procedure. KEY POINTS The current MRI-based nomograms result in many negative prostate biopsies. The addition of DL to nomograms with clinical data and PI-RADS improves patient stratification before biopsy. Fully automatic DL can be substituted for PI-RADS without sacrificing the quality of nomogram predictions. Prostate nomograms show cancer detection ability comparable to previous validation studies while being suitable for the addition of DL analysis.
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Affiliation(s)
- Adrian Schrader
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Heidelberg University Medical School, Heidelberg, Germany
| | - Nils Netzer
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Heidelberg University Medical School, Heidelberg, Germany
| | - Thomas Hielscher
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Magdalena Görtz
- Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany
- Junior Clinical Cooperation Unit 'Multiparametric Methods for Early Detection of Prostate Cancer', German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Kevin Sun Zhang
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Viktoria Schütz
- Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Albrecht Stenzinger
- Institute of Pathology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Markus Hohenfellner
- Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - David Bonekamp
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Heidelberg University Medical School, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany.
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Liu WQ, Xue YT, Huang XY, Lin B, Li XD, Ke ZB, Chen DN, Chen JY, Wei Y, Zheng QS, Xue XY, Xu N. Development and Validation of an MRI-Based Radiomics Nomogram to Predict the Prognosis of De Novo Oligometastatic Prostate Cancer Patients. Cancer Med 2024; 13:e70481. [PMID: 39704412 DOI: 10.1002/cam4.70481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 11/16/2024] [Accepted: 11/28/2024] [Indexed: 12/21/2024] Open
Abstract
OBJECTIVE We aimed to develop and validate a nomogram based on MRI radiomics to predict overall survival (OS) for patients with de novo oligometastatic prostate cancer (PCa). METHODS A total of 165 patients with de novo oligometastatic PCa were included in the study (training cohort, n = 115; validating cohort, n = 50). Among them, MRI scans were conducted and T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) sequences were collected for radiomics features along with their clinicopathological features. Radiological features were extracted from T2WI and ADC sequences for prostate tumors. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) combined with 10-fold cross-validation were used to select the optimal features on each sequence. Then, a weighted radiomics score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration, and decision curve analysis (DCA). RESULTS Eastern Cooperative Oncology Group (ECOG) score, absolute neutrophil count (ANC) and Rad-score were included in the nomogram as independent risk factors for OS in de novo oligometastatic PCa patients. We found that the areas under the curves (AUCs) in the training cohort were 0.734, 0.851, and 0.773 for predicting OS at 1, 2, and 3 years, respectively. In the validating cohort, the AUCs were 0.703, 0.799, and 0.833 for predicting OS at 1, 2, and 3 years, respectively. Furthermore, the clinical relevance of the predictive nomogram was confirmed through the analysis of DCA and calibration curve analysis. CONCLUSION The MRI-based nomogram incorporating Rad-score and clinical data was developed to guide the OS assessment of oligometastatic PCa. This helps in understanding the prognosis and improves the shared decision-making process.
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Affiliation(s)
- Wen-Qi Liu
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Yu-Ting Xue
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Xu-Yun Huang
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Bin Lin
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Xiao-Dong Li
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Zhi-Bin Ke
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Dong-Ning Chen
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Jia-Yin Chen
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Yong Wei
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Qing-Shui Zheng
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Xue-Yi Xue
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Ning Xu
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
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Girometti R, Peruzzi V, Polizzi P, De Martino M, Cereser L, Casarotto L, Pizzolitto S, Isola M, Crestani A, Giannarini G, Zuiani C. Case-by-case combination of the prostate imaging reporting and data system version 2.1 with the Likert score to reduce the false-positives of prostate MRI: a proof-of-concept study. Abdom Radiol (NY) 2024; 49:4273-4285. [PMID: 39079991 PMCID: PMC11522071 DOI: 10.1007/s00261-024-04506-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 07/17/2024] [Accepted: 07/21/2024] [Indexed: 10/30/2024]
Abstract
OBJECTIVES To retrospectively investigate whether a case-by-case combination of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS) with the Likert score improves the diagnostic performance of mpMRI for clinically significant prostate cancer (csPCa), especially by reducing false-positives. METHODS One hundred men received mpMRI between January 2020 and April 2021, followed by prostate biopsy. Reader 1 (R1) and reader 2 (R2) (experience of > 3000 and < 200 mpMRI readings) independently reviewed mpMRIs with the PI-RADS version 2.1. After unveiling clinical information, they were free to add (or not) a Likert score to upgrade or downgrade or reinforce the level of suspicion of the PI-RADS category attributed to the index lesion or, rather, identify a new index lesion. We calculated sensitivity, specificity, and predictive values of R1/R2 in detecting csPCa when biopsying PI-RADS ≥ 3 index-lesions (strategy 1) versus PI-RADS ≥ 3 or Likert ≥ 3 index-lesions (strategy 2), with decision curve analysis to assess the net benefit. In strategy 2, the Likert score was considered dominant in determining biopsy decisions. RESULTS csPCa prevalence was 38%. R1/R2 used combined PI-RADS and Likert categorization in 28%/18% of examinations relying mainly on clinical features such as prostate specific antigen level and digital rectal examination than imaging findings. The specificity/positive predictive values were 66.1/63.1% for R1 (95%CI 52.9-77.6/54.5-70.9) and 50.0/51.6% (95%CI 37.0-63.0/35.5-72.4%) for R2 in the case of PI-RADS-based readings, and 74.2/69.2% for R1 (95%CI 61.5-84.5/59.4-77.5%) and 56.6/54.2% (95%CI 43.3-69.0/37.1-76.6%) for R2 in the case of combined PI-RADS/Likert readings. Sensitivity/negative predictive values were unaffected. Strategy 2 achieved greater net benefit as a trigger of biopsy for R1 only. CONCLUSION Case-by-case combination of the PI-RADS version 2.1 with Likert score translated into a mild but measurable impact in reducing the false-positives of PI-RADS categorization, though greater net benefit in reducing unnecessary biopsies was found in the experienced reader only.
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Affiliation(s)
- Rossano Girometti
- Institute of Radiology, Department of Medicine (DMED), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy.
| | - Valeria Peruzzi
- Institute of Radiology, Department of Medicine (DMED), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
| | - Paolo Polizzi
- Institute of Radiology, Department of Medicine (DMED), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
- UOC Radiologia, Ospedale Civile SS. Giovanni e Paolo, ULSS 3 Serenissima, 6776 - 30122, Castello, Venezia, Italy
| | - Maria De Martino
- Division of Medical Statistics, Department of Medicine (DMED), University of Udine, pl.le Kolbe, 4 - 33100, Udine, Italy
| | - Lorenzo Cereser
- Institute of Radiology, Department of Medicine (DMED), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
| | - Letizia Casarotto
- Pathology Unit, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
| | - Stefano Pizzolitto
- Pathology Unit, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
| | - Miriam Isola
- Division of Medical Statistics, Department of Medicine (DMED), University of Udine, pl.le Kolbe, 4 - 33100, Udine, Italy
| | - Alessandro Crestani
- Urology Unit, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
| | - Gianluca Giannarini
- Urology Unit, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
| | - Chiara Zuiani
- Institute of Radiology, Department of Medicine (DMED), University of Udine, University Hospital S. Maria della Misericordia - Azienda Sanitaria-Universitaria Friuli Centrale (ASU FC), p.le S. Maria della Misericordia, 15 - 33100, Udine, Italy
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