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Kawase M, Goto T, Ebara S, Tatenuma T, Sasaki T, Ishihara T, Ikehata Y, Nakayama A, Toide M, Yoneda T, Sakaguchi K, Teishima J, Saito R, Kobayashi T, Makiyama K, Inoue T, Kitamura H, Saito K, Koga F, Urakami S, Koie T. External Validation of the Nomogram Predicting Locally Advanced Prostate Cancer in Patients Undergoing Robot-Assisted Radical Prostatectomy (the MSUG94 Group). Ann Surg Oncol 2025:10.1245/s10434-025-17385-8. [PMID: 40343587 DOI: 10.1245/s10434-025-17385-8] [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: 01/31/2025] [Accepted: 04/13/2025] [Indexed: 05/11/2025]
Abstract
PURPOSE A clinically applicable nomogram predicting locally advanced prostate cancer (PCa) (defined as pathological T stage ≥ 3) of patients with clinical T stage ≤ 2 was released (MSUG nomogram). We performed external validation, ensuring its applicability to patients undergoing robot-assisted radical prostatectomy (RARP). Therefore, we also compared the external validation for the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram. PATIENTS AND METHODS We collected the data for 8194 patients who underwent RARP at Daimonji Clinical Application Database Group (Dai-CAD) as the validation cohort and performed the external validation using this cohort. The primary endpoint was the accuracy of the MSUG nomogram, and the secondary endpoint was comparison with the MSKCC nomogram. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated to quantify the accuracy of the nomogram at predicting pT ≥ 3. A calibration plot was performed to evaluate the extent of over- and underestimation. RESULTS Locally advanced PCa was diagnosed in 677 of 2530 patients (26.8%) in the MSUG cohort and 1472 of 5799 patients (25.3%) in the validation cohort. The ROC curve for the validation cohorts fit to the MSUG nomogram and the MSKCC nomogram, with AUC of 0.66 and 0.65, respectively. For calibration plots, it overestimated the risk of locally advanced PCa when probability thresholds are over 70% in the MSUG nomogram, while it may overestimate when probability thresholds are over 30% in the MSKCC nomogram. CONCLUSIONS We conducted external validation of a clinically applicable nomogram that predicts the probability of locally advanced PCa in patients undergoing RARP using available clinical parameters.
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Affiliation(s)
- Makoto Kawase
- Department of Urology, Gifu University Graduate School of Medicine, Gifu, Japan.
| | - Takayuki Goto
- Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Shin Ebara
- Department of Urology, Hiroshima City Hiroshima Citizens Hospital, Hiroshima, Japan
| | | | - Takeshi Sasaki
- Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Japan
| | - Takuma Ishihara
- Innovative and Clinical Research Promotion Center, Gifu University Hospital, Gifu, Japan
| | | | - Akinori Nakayama
- Department of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Masahiro Toide
- Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Tatsuaki Yoneda
- Department of Urology, Seirei Hamamatsu General Hospital, Hamamatsu, Japan
| | | | - Jun Teishima
- Department of Urology, Kobe City Hospital Organization Kobe City Medical Center West Hospital, Kobe, Japan
| | - Ryoichi Saito
- Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takashi Kobayashi
- Department of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - Takahiro Inoue
- Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Japan
| | | | - Kazutaka Saito
- Department of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Fumitaka Koga
- Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | | | - Takuya Koie
- Department of Urology, Gifu University Graduate School of Medicine, Gifu, Japan
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Huang MM, Rac G, Felice M, Ellis JL, Handa N, Li EV, McCormick M, Bsatee A, Piyevsky B, Ross AE, Yonover PM, Gupta GN, Patel HD. Prostate magnetic resonance imaging to predict grade concordance, extra prostatic extension, and biochemical recurrence after radical prostatectomy. Urol Oncol 2025:S1078-1439(25)00039-0. [PMID: 40082107 DOI: 10.1016/j.urolonc.2025.02.013] [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] [Revised: 01/23/2025] [Accepted: 02/15/2025] [Indexed: 03/16/2025]
Abstract
OBJECTIVES To investigate whether preoperative prostate MRI findings predicted biopsy to radical prostate (RP) grade group concordance, presence of extraprostatic extension (EPE), and biochemical recurrence (BCR) after RP. MATERIAL AND METHODS We conducted a multi-institutional study (tertiary academic center and community practice) including patients who underwent RP (2014-2021) with preoperative MRI. Grade concordance for systematic, targeted, and combined prostate biopsy was compared to RP. Concordances were also compared for a contemporaneous RP cohort without prebiopsy MRI (No MRI cohort). We assessed association of extracapsular extension on MRI (MRI-ECE) with EPE and BCR after RP. RESULTS Among 768 men, concordance between biopsy and RP was 65.7% for combined, 58.3% for targeted, and 44.7% for systematic biopsy (P < 0.001). There was no difference in upgrading, concordance, and downgrading compared to 1014 men in the No MRI cohort (P = 0.6). Combined biopsy decreased upgrading to Grade Group ≥3 by 9.2%. EPE after RP was present in 292/768 (38%). MRI-ECE had 56% sensitivity, 74% specificity, 57% positive predictive value, and 73% negative predictive value. MRI-ECE was associated with EPE (OR: 2.25, P < 0.001) and BCR (HR: 1.77, P = 0.006). An MRI-based model improved EPE prediction in the development cohort (AUC 0.80) compared to a traditional nomogram but failed external validation (AUC 0.68). CONCLUSIONS Preoperative MRI findings predicted grade concordance, presence of EPE, and risk of BCR after RP. Variability in MRI-ECE interpretation limited generalizability of models to predict EPE indicating a need for more standardized reporting to increase clinical utility.
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Affiliation(s)
- Mitchell M Huang
- Department of Urology, Northwestern University, Feinberg School of Medicine, Chicago, IL.
| | - Goran Rac
- Department of Urology, Loyola University Medical Center, Maywood, IL
| | - Michael Felice
- Department of Urology, Loyola University Medical Center, Maywood, IL
| | - Jeffrey L Ellis
- Department of Urology, Loyola University Medical Center, Maywood, IL
| | - Nicole Handa
- Department of Urology, Northwestern University, Feinberg School of Medicine, Chicago, IL
| | - Eric V Li
- Department of Urology, Northwestern University, Feinberg School of Medicine, Chicago, IL
| | - Mallory McCormick
- Department of Urology, Loyola University Medical Center, Maywood, IL
| | - Aya Bsatee
- Department of Urology, Loyola University Medical Center, Maywood, IL
| | - Brandon Piyevsky
- Wright State University Boonshoft School of Medicine, Dayton, OH
| | - Ashley E Ross
- Department of Urology, Northwestern University, Feinberg School of Medicine, Chicago, IL
| | - Paul M Yonover
- UroPartners, LLC, Chicago, IL; Department of Urology, University of Illinois at Chicago, Chicago, IL
| | - Gopal N Gupta
- Department of Urology, Loyola University Medical Center, Maywood, IL; Department of Radiology, Loyola University Medical Center, Maywood, IL; Department of Surgery, Loyola University Medical Center, Maywood, IL
| | - Hiten D Patel
- Department of Urology, Northwestern University, Feinberg School of Medicine, Chicago, IL; Department of Urology, Loyola University Medical Center, Maywood, IL; Surgery Service, Jesse Brown VA Medical Center, Chicago, IL
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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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Gumus KZ, Menendez M, Baerga CG, Harmon I, Kumar S, Mete M, Hernandez M, Ozdemir S, Yuruk N, Balaji KC, Gopireddy DR. Investigation of radiomic features on MRI images to identify extraprostatic extension in prostate cancer. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2025; 259:108528. [PMID: 39615194 DOI: 10.1016/j.cmpb.2024.108528] [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: 01/30/2024] [Revised: 11/13/2024] [Accepted: 11/22/2024] [Indexed: 12/11/2024]
Abstract
BACKGROUND AND OBJECTIVE Detection of extraprostatic extension (EPE) preoperatively is of critical importance in the context of prostate cancer (PCa) management and outcomes. This study aimed to characterize the radiomic features of malignant prostate lesions based on multi-paramagnetic magnetic resonance imaging (mpMRI). METHODS We analyzed 20 patients who underwent mpMRI followed by radical prostatectomy. Two experienced radiologists manually segmented the 3D lesions using the T2-weighted (T2WI) and Apparent Diffusion Coefficient (ADC) imaging sequences. A total of 210 radiomic features were extracted from each lesion. We used the Recursive Feature Elimination with Cross-Validation to select key features. Using the selected radiomic features, we developed a Multilayer Perceptron (MLP) neural network to classify the EPE and non-EPE lesions. The pathology results were accepted as gold standard for EPE. We measured the performance of the classifier, calculating the area-under-curve (AUC), sensitivity, and specificity. RESULTS A total of 25 lesions were segmented, including 12 lesions with EPE and 13 lesions without EPE, based on the pathology reports. We selected 18 radiomic features (18/210). The MLP classifier using these features provided a good sensitivity (0.75), specificity (0.79), and AUC of 0.82, 95 % CL [0.59 - 0.96] in identifying the EPE lesions. CONCLUSIONS This pilot study presents 18 radiomic features derived from T2-weighted and ADC images and demonstrates their potential in the preoperative prediction of EPE in PCa using an MLP model.
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Affiliation(s)
- Kazim Z Gumus
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Manuel Menendez
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Carlos Gonzalez Baerga
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Ira Harmon
- Center for Data Solutions, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Sindhu Kumar
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Mutlu Mete
- Department of Information Science, University of North Texas, Denton, TX, USA.
| | - Mauricio Hernandez
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Savas Ozdemir
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
| | - Nurcan Yuruk
- Department of Computer Science, Southern Methodist University, Dallas, TX, USA.
| | - K C Balaji
- Department of Urology, University of Florida College of Medicine Jacksonville, FL, USA.
| | - Dheeraj R Gopireddy
- Department of Radiology, University of Florida, College of Medicine Jacksonville, FL, USA.
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Priester A, Mota SM, Grunden KP, Shubert J, Richardson S, Sisk A, Felker ER, Sayre J, Marks LS, Natarajan S, Brisbane WG. Extracapsular extension risk assessment using an artificial intelligence prostate cancer mapping algorithm. BJUI COMPASS 2024; 5:986-997. [PMID: 39416757 PMCID: PMC11479810 DOI: 10.1002/bco2.421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 07/17/2024] [Accepted: 07/17/2024] [Indexed: 10/19/2024] Open
Abstract
Objective The objective of this study is to compare detection rates of extracapsular extension (ECE) of prostate cancer (PCa) using artificial intelligence (AI)-generated cancer maps versus MRI and conventional nomograms. Materials and methods We retrospectively analysed data from 147 patients who received MRI-targeted biopsy and subsequent radical prostatectomy between September 2016 and May 2022. AI-based software cleared by the United States Food and Drug Administration (Unfold AI, Avenda Health) was used to map 3D cancer probability and estimate ECE risk. Conventional ECE predictors including MRI Likert scores, capsular contact length of MRI-visible lesions, PSMA T stage, Partin tables, and the "PRedicting ExtraCapsular Extension" nomogram were used for comparison.Postsurgical specimens were processed using whole-mount histopathology sectioning, and a genitourinary pathologist assessed each quadrant for ECE presence. ECE predictors were then evaluated on the patient (Unfold AI versus all comparators) and quadrant level (Unfold AI versus MRI Likert score). Receiver operator characteristic curves were generated and compared using DeLong's test. Results Unfold AI had a significantly higher area under the curve (AUC = 0.81) than other predictors for patient-level ECE prediction. Unfold AI achieved 68% sensitivity, 78% specificity, 71% positive predictive value, and 75% negative predictive value. At the quadrant level, Unfold AI exceeded the AUC of MRI Likert scores for posterior (0.89 versus 0.82, p = 0.003), anterior (0.84 versus 0.80, p = 0.34), and all quadrants (0.89 versus 0.82, p = 0.002). The false negative rate of Unfold AI was lower than MRI in both the anterior (-60%) and posterior prostate (-40%). Conclusions Unfold AI accurately predicted ECE risk, outperforming conventional methodologies. It notably improved ECE prediction over MRI in posterior quadrants, with the potential to inform nerve-spare technique and prevent positive margins. By enhancing PCa staging and risk stratification, AI-based cancer mapping may lead to better oncological and functional outcomes for patients.
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Affiliation(s)
- Alan Priester
- Avenda Health, Inc.United States
- Department of UrologyDavid Geffen School of MedicineUnited States
| | | | - Kyla P. Grunden
- Department of UrologyDavid Geffen School of MedicineUnited States
| | | | | | - Anthony Sisk
- Department of PathologyDavid Geffen School of MedicineUnited States
| | - Ely R. Felker
- Department of RadiologyDavid Geffen School of MedicineUnited States
| | - James Sayre
- Department of Radiological Sciences and BiostatisticsUniversity of California, Los AngelesUnited States
| | - Leonard S. Marks
- Department of UrologyDavid Geffen School of MedicineUnited States
| | - Shyam Natarajan
- Avenda Health, Inc.United States
- Department of UrologyDavid Geffen School of MedicineUnited States
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Ostau NEV, Handke AE, Wiesenfarth M, Albers P, Antoch G, Noldus J, Reis H, Cotarelo C, Preetz J, Umutlu L, Ingenwerth M, Radtke JP, Hadaschik B, Schimmöller L, Kesch C. Bicenter validation of a risk model for the preoperative prediction of extraprostatic extension of localized prostate cancer combining clinical and multiparametric MRI parameters. World J Urol 2024; 42:530. [PMID: 39302458 PMCID: PMC11415414 DOI: 10.1007/s00345-024-05232-6] [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: 02/22/2024] [Accepted: 08/16/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND This study aimed to validate a previously published risk model (RM) which combines clinical and multiparametric MRI (mpMRI) parameters to predict extraprostatic extension (EPE) of prostate cancer (PC) prior to radical prostatectomy (RP). MATERIALS AND METHODS A previously published RM combining clinical with mpMRI parameters including European Society of Urogenital Radiology (ESUR) classification for EPE was retrospectively evaluated in a cohort of two urological university hospitals in Germany. Consecutive patients (n = 205, January 2015 -June 2021) with available preoperative MRI images, clinical information including PSA, prostate volume, ESUR classification for EPE, histopathological results of MRI-fusion biopsy and RP specimen were included. Validation was performed by receiver operating characteristic analysis and calibration plots. The RM's performance was compared to ESUR criteria. RESULTS Histopathological T3 stage was detected in 43% of the patients (n = 89); 45% at Essen and 42% at Düsseldorf. Discrimination performance between pT2 and pT3 of the RM in the entire cohort was AUC = 0.86 (AUC = 0.88 at site 1 and AUC = 0.85 at site 2). Calibration was good over the entire probability range. The discrimination performance of ESUR classification alone was comparable (AUC = 0.87). CONCLUSIONS The RM showed good discriminative performance to predict EPE for decision-making for RP as a patient-tailored risk stratification. However, when experienced MRI reading is available, standardized MRI reading with ESUR scoring is comparable regarding information outcome. A main limitation is the potentially limited transferability to other populations because of the high prevalence of EPE in our subgroups.
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Affiliation(s)
- Nicola Edith von Ostau
- Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany.
| | - Analena Elisa Handke
- Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany
- Department of Urology, Ruhr-University Bochum, Marien Hospital, Herne, Germany
| | - Manuel Wiesenfarth
- Division of Biostatistics, German Cancer Research Center, Heidelberg, Germany
| | - Peter Albers
- Department of Urology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Gerald Antoch
- Medical Faculty, Department of Diagnostic and Interventional Radiology, University Düsseldorf, D-40225, Dusseldorf, Germany
| | - Joachim Noldus
- Department of Urology, Ruhr-University Bochum, Marien Hospital, Herne, Germany
| | - Henning Reis
- Division of Pathology, University Hospital Frankfurt, Frankfurt, Germany
| | - Cristina Cotarelo
- Department of Pathology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- Department of Pathology, University Hospital Mannheim, Mannheim, Germany
| | - Julia Preetz
- Department of Pathology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Lale Umutlu
- Division of Radiology, University Hospital Essen, Essen, Germany
| | - Marc Ingenwerth
- Department of Pathology, University Hospital Essen, Essen, Germany
| | - Jan Philipp Radtke
- Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany
- Department of Urology, University Hospital Düsseldorf, Düsseldorf, Germany
- Division of Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Boris Hadaschik
- Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany
| | - Lars Schimmöller
- Medical Faculty, Department of Diagnostic and Interventional Radiology, University Düsseldorf, D-40225, Dusseldorf, Germany
- Department of Diagnostic, Interventional Radiology and Nuclear Medicine, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum, Herne, Germany
| | - Claudia Kesch
- Department of Urology, University Hospital Essen, Hufelandstraße 55, 45147, Essen, Germany
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7
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Martini A, Wever L, Soeterik TFW, Rakauskas A, Fankhauser CD, Grogg JB, Checcucci E, Amparore D, Haiquel L, Rodriguez-Sanchez L, Ploussard G, Qiang P, Affentranger A, Marquis A, Marra G, Ettala O, Zattoni F, Falagario UG, De Angelis M, Kesch C, Apfelbeck M, Al-Hammouri T, Kretschmer A, Kasivisvanathan V, Preisser F, Lefebvre E, Olivier J, Radtke JP, Carrieri G, Moro FD, Boström P, Jambor I, Gontero P, Chiu PK, John H, Macek P, Porpiglia F, Hermanns T, van den Bergh RCN, van Basten JPA, Gandaglia G, Valerio M. An updated model for predicting side-specific extraprostatic extension in the era of MRI-targeted biopsy. Prostate Cancer Prostatic Dis 2024; 27:520-524. [PMID: 38182804 DOI: 10.1038/s41391-023-00776-x] [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: 09/03/2023] [Revised: 11/26/2023] [Accepted: 12/01/2023] [Indexed: 01/07/2024]
Abstract
PURPOSE Accurate prediction of extraprostatic extension (EPE) is pivotal for surgical planning. Herein, we aimed to provide an updated model for predicting EPE among patients diagnosed with MRI-targeted biopsy. MATERIALS AND METHODS We analyzed a multi-institutional dataset of men with clinically localized prostate cancer diagnosed by MRI-targeted biopsy and subsequently underwent prostatectomy. To develop a side-specific predictive model, we considered the prostatic lobes separately. A multivariable logistic regression analysis was fitted to predict side-specific EPE. The decision curve analysis was used to evaluate the net clinical benefit. Finally, a regression tree was employed to identify three risk categories to assist urologists in selecting candidates for nerve-sparing, incremental nerve sparing and non-nerve-sparing surgery. RESULTS Overall, data from 3169 hemi-prostates were considered, after the exclusion of prostatic lobes with no biopsy-documented tumor. EPE was present on final pathology in 1,094 (34%) cases. Among these, MRI was able to predict EPE correctly in 568 (52%) cases. A model including PSA, maximum diameter of the index lesion, presence of EPE on MRI, highest ISUP grade in the ipsilateral hemi-prostate, and percentage of positive cores in the ipsilateral hemi-prostate achieved an AUC of 81% after internal validation. Overall, 566, 577, and 2,026 observations fell in the low-, intermediate- and high-risk groups for EPE, as identified by the regression tree. The EPE rate across the groups was: 5.1%, 14.9%, and 48% for the low-, intermediate- and high-risk group, respectively. CONCLUSION In this study we present an update of the first side-specific MRI-based nomogram for the prediction of extraprostatic extension together with updated risk categories to help clinicians in deciding on the best approach to nerve-preservation.
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Affiliation(s)
- Alberto Martini
- Department of Urology, La Croix du Sud Hospital, Toulouse, France.
| | - Lieke Wever
- St. Antonius ziekenhuis, Nieuwegein, the Netherlands
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | | | - Arnas Rakauskas
- Department of Urology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Josias Bastian Grogg
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | | | - Luciano Haiquel
- Department of Urology, Institut Mutualiste Montsouris, Paris, France
| | | | | | - Peng Qiang
- SH Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China
| | | | - Alessandro Marquis
- Department of Urology, San Giovanni Battista Hospital, University of Turin, Turin, Italy
| | - Giancarlo Marra
- Department of Urology, San Giovanni Battista Hospital, University of Turin, Turin, Italy
| | - Otto Ettala
- Department of Urology, Turku University, Turku, Finland
| | - Fabio Zattoni
- Urology Unit, Academical Medical Centre Hospital, Udine, Italy
- Department of Surgery, Oncology, and Gastroenterology, Urology Clinic, University of Padua, Padua, Italy
| | | | - Mario De Angelis
- Unit of Urology/Division of Oncology, Urological Research Institute, IRCCS San Raffaele Hospital, Milan, Italy
| | - Claudia Kesch
- Department of Urology, University Hospital Essen, Essen, Germany
- German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | | | - Tarek Al-Hammouri
- Department of Urology, University College London and University College London Hospitals NHS Foundation Trust, London, UK
| | | | - Veeru Kasivisvanathan
- Department of Urology, University College London and University College London Hospitals NHS Foundation Trust, London, UK
| | - Felix Preisser
- Department of Urology, University Hospital Frankfurt, Frankfurt, Germany
| | | | | | - Jan Philipp Radtke
- Department of Urology, University Hospital Essen, Essen, Germany
- German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | | | - Fabrizio Dal Moro
- Urology Unit, Academical Medical Centre Hospital, Udine, Italy
- Department of Surgery, Oncology, and Gastroenterology, Urology Clinic, University of Padua, Padua, Italy
| | - Peter Boström
- Department of Urology, Turku University, Turku, Finland
| | - Ivan Jambor
- Department of Urology, Turku University, Turku, Finland
| | - Paolo Gontero
- Department of Urology, San Giovanni Battista Hospital, University of Turin, Turin, Italy
| | - Peter K Chiu
- SH Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China
| | - Hubert John
- Department of Urology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Petr Macek
- Department of Urology, Institut Mutualiste Montsouris, Paris, France
| | | | - Thomas Hermanns
- Department of Urology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Jean-Paul A van Basten
- St. Antonius ziekenhuis, Nieuwegein, the Netherlands
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Giorgio Gandaglia
- Unit of Urology/Division of Oncology, Urological Research Institute, IRCCS San Raffaele Hospital, Milan, Italy
| | - Massimo Valerio
- Department of Urology, Geneva University Hospital, Geneva, Switzerland.
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8
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Wieslander E, Jóhannesson V, Nilsson P, Kjellén E, Gunnlaugsson A. Ultrahypofractionated Radiation Therapy for Prostate Cancer Including Seminal Vesicles in the Target Volume: A Treatment-planning Study Based on the HYPO-RT-PC Fractionation Schedule. Adv Radiat Oncol 2024; 9:101531. [PMID: 38883997 PMCID: PMC11176962 DOI: 10.1016/j.adro.2024.101531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 04/25/2024] [Indexed: 06/18/2024] Open
Abstract
Purpose Ultrahypofractionated (UHF) radiation therapy (RT) has become a treatment alternative for patients with localized prostate cancer. In more advanced cases, seminal vesicles (SVs) are routinely included in the target volume. The Scandinavian HYPO-RT-PC trial, which compared 42.7 Gy in 7 fractions (fr) to conventional fractionation (CF), did not include SVs in the clinical target volume. The primary objective of the present work was to implement a ultrahypofractionated-simultaneous integrated boost (UHF-SIB) for prostate cancer RT, incorporating SVs into the target volume based on this fractionation schedule. A secondary objective was to analyze the unintentional dose coverage of SVs from state-of-the-art volumetric modulated arc therapy treatments to the prostate gland only. Methods and Materials Two different equieffective UHF-SIB treatment schedules to SVs were derived based on the CF clinical schedule (50.0 Gy/25 fr to elective SVs and 70.0 Gy/35 fr to verified SV-invasion (SVI)) using the linear quadric model with α/β = 2 Gy and 3 Gy. The dose to the prostate was 42.7 Gy/7 fr in both schedules, with 31.2 Gy/37.8 Gy (α/β = 2 Gy) and 32.7 Gy/40.1 Gy (α/β = 3 Gy) to elective SV/verified SVI. Volumetric modulated arc therapy plans to the proximal 10 mm and 20 mm were optimized, and dose-volume metrics for target volumes and organs at risk were evaluated. Results Dose metrics were overall lower for UHF-SIB compared with CF. QUANTEC-based volume criteria were 2% to 7% lower for the rectum and 2% to 4% lower for the bladder in the UHF-SIB. The D98% to elective SV was 7 to 12 Gy3 lower with UHF-SIB, and the corresponding data for verified SVI were approximately 2 to 3 Gy3. The SV(10 mm) V90%/(29.5 Gy) for prostate-only treatments (42.7 Gy) were as follows: median (IQR), 99% (87-100) and 78% (58-99) for the clinical target volume and planning target volume, respectively. Conclusions UHF RT based on the HYPO-RT-PC fractionation schedule, with a SIB technique, to the prostate and the base of the SV can be planned with lower doses (EQD2) to organs at risk, compared with CF. The unintentional dose to the proximal parts of SVs in prostate-only treatment can be substantial.
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Affiliation(s)
- Elinore Wieslander
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden
| | - Vilberg Jóhannesson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Oncology and Pathology, Lund, Sweden
| | - Per Nilsson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden
| | - Elisabeth Kjellén
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Oncology and Pathology, Lund, Sweden
| | - Adalsteinn Gunnlaugsson
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Oncology and Pathology, Lund, Sweden
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9
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Ponsiglione A, Gambardella M, Stanzione A, Green R, Cantoni V, Nappi C, Crocetto F, Cuocolo R, Cuocolo A, Imbriaco M. Radiomics for the identification of extraprostatic extension with prostate MRI: a systematic review and meta-analysis. Eur Radiol 2024; 34:3981-3991. [PMID: 37955670 PMCID: PMC11166859 DOI: 10.1007/s00330-023-10427-3] [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: 05/02/2023] [Revised: 09/10/2023] [Accepted: 09/27/2023] [Indexed: 11/14/2023]
Abstract
OBJECTIVES Extraprostatic extension (EPE) of prostate cancer (PCa) is predicted using clinical nomograms. Incorporating MRI could represent a leap forward, although poor sensitivity and standardization represent unsolved issues. MRI radiomics has been proposed for EPE prediction. The aim of the study was to systematically review the literature and perform a meta-analysis of MRI-based radiomics approaches for EPE prediction. MATERIALS AND METHODS Multiple databases were systematically searched for radiomics studies on EPE detection up to June 2022. Methodological quality was appraised according to Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and radiomics quality score (RQS). The area under the receiver operating characteristic curves (AUC) was pooled to estimate predictive accuracy. A random-effects model estimated overall effect size. Statistical heterogeneity was assessed with I2 value. Publication bias was evaluated with a funnel plot. Subgroup analyses were performed to explore heterogeneity. RESULTS Thirteen studies were included, showing limitations in study design and methodological quality (median RQS 10/36), with high statistical heterogeneity. Pooled AUC for EPE identification was 0.80. In subgroup analysis, test-set and cross-validation-based studies had pooled AUC of 0.85 and 0.89 respectively. Pooled AUC was 0.72 for deep learning (DL)-based and 0.82 for handcrafted radiomics studies and 0.79 and 0.83 for studies with multiple and single scanner data, respectively. Finally, models with the best predictive performance obtained using radiomics features showed pooled AUC of 0.82, while those including clinical data of 0.76. CONCLUSION MRI radiomics-powered models to identify EPE in PCa showed a promising predictive performance overall. However, methodologically robust, clinically driven research evaluating their diagnostic and therapeutic impact is still needed. CLINICAL RELEVANCE STATEMENT Radiomics might improve the management of prostate cancer patients increasing the value of MRI in the assessment of extraprostatic extension. However, it is imperative that forthcoming research prioritizes confirmation studies and a stronger clinical orientation to solidify these advancements. KEY POINTS • MRI radiomics deserves attention as a tool to overcome the limitations of MRI in prostate cancer local staging. • Pooled AUC was 0.80 for the 13 included studies, with high heterogeneity (84.7%, p < .001), methodological issues, and poor clinical orientation. • Methodologically robust radiomics research needs to focus on increasing MRI sensitivity and bringing added value to clinical nomograms at patient level.
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Affiliation(s)
- Andrea Ponsiglione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy
| | | | - Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy.
| | - Roberta Green
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy
| | - Valeria Cantoni
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy
| | - Carmela Nappi
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy
| | - Felice Crocetto
- Department of Neurosciences, Human Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy
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10
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Frego N, Contieri R, Fasulo V, Maffei D, Avolio PP, Arena P, Beatrici E, Sordelli F, De Carne F, Lazzeri M, Saita A, Hurle R, Buffi NM, Casale P, Lughezzani G. Development of a microultrasound-based nomogram to predict extra-prostatic extension in patients with prostate cancer undergoing robot-assisted radical prostatectomy. Urol Oncol 2024; 42:159.e9-159.e16. [PMID: 38423852 DOI: 10.1016/j.urolonc.2024.01.033] [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: 11/07/2023] [Revised: 01/12/2024] [Accepted: 01/26/2024] [Indexed: 03/02/2024]
Abstract
OBJECTIVES To develop a microultrasound-based nomogram including clinicopathological parameters and microultrasound findings to predict the presence of extra-prostatic extension and guide the grade of nerve-sparing. MATERIAL AND METHODS All patients underwent microultrasound the day before robot-assisted radical prostatectomy. Variables significantly associated with extra-prostatic extension at univariable analysis were used to build the multivariable logistic model, and the regression coefficients were used to develop the nomogram. The model was subjected to 1000 bootstrap resamples for internal validation. The performance of the microultrasound-based model was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA). RESULTS Overall, 122/295 (41.4%) patients had a diagnosis of extra-prostatic extension on definitive pathology. Microultrasound correctly identify extra-prostatic extension in 84/122 (68.9%) cases showing a sensitivity and a specificity of 68.9% and 84.4%, with an AUC of 76.6%. After 1000 bootstrap resamples, the predictive accuracy of the microultrasound-based model was 85.9%. The calibration plot showed a satisfactory concordance between predicted probabilities and observed frequencies of extra-prostatic extension. The DCA showed a higher clinical net-benefit compared to the model including only clinical parameters. Considering a 4% cut-off, nerve-sparing was recommended in 173 (58.6%) patients and extra-prostatic extension was detected in 32 (18.5%) of them. CONCLUSION We developed a microultrasound-based nomogram for the prediction of extra-prostatic extension that could aid in the decision whether to preserve or not neurovascular bundles. External validation and a direct comparison with mpMRI-based nomogram is crucial to corroborate our results.
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Affiliation(s)
- Nicola Frego
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Roberto Contieri
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Vittorio Fasulo
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Davide Maffei
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Pier Paolo Avolio
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Paola Arena
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Edoardo Beatrici
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Federica Sordelli
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Fabio De Carne
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
| | - Massimo Lazzeri
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy
| | - Alberto Saita
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy
| | - Rodolfo Hurle
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy
| | - Nicolò Maria Buffi
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy.
| | - Paolo Casale
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy
| | - Giovanni Lughezzani
- Department of Urology, IRCCS - Humanitas Research Hospital, Milan, Italy; Department of Biomedical Science, Humanitas University, Milan, Italy
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11
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Wen J, Liu W, Zhang Y, Shen X. MRI-based radiomics for prediction of extraprostatic extension of prostate cancer: a systematic review and meta-analysis. LA RADIOLOGIA MEDICA 2024; 129:702-711. [PMID: 38520649 DOI: 10.1007/s11547-024-01810-1] [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: 08/29/2023] [Accepted: 03/13/2024] [Indexed: 03/25/2024]
Abstract
PURPOSE We to systematically evaluate the diagnostic performance of MRI radiomics in detecting extracapsular extension (EPE) of prostate cancer (PCa). METHODS A literature search of online databases of PubMed, EMBASE, Cochrane Library, Web of Science, and Google Scholar online scientific publication databases was performed to identify studies published up to July 2023. The summary estimates were pooled with the hierarchical summary receiver-operating characteristic (HSROC) model. This study was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, the quality of included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool (QUADAS-2) and the radiomics quality score (RQS). Meta-regression and subgroup analyses were performed to explore the impact of varying clinical settings. RESULTS A total of ten studies met the inclusion criteria. The pooled sensitivity and specificity were 0.77 (95% CI 0.68-0.84, I2 = 83.5%) and 0.75 (95% CI 0.67-0.82, I2 = 83.5%), respectively, with an area under the HSROC curve of 0.88 (95% CI 0.85-0.91). Study quality was not high while assessing with the RQS. Substantial heterogeneity was observed between studies; however, meta-regression analysis did not reveal any significant contributing factors. CONCLUSIONS MRI radiomics demonstrated moderate sensitivity and specificity, offering similar diagnostic performance with previous risk stratifications and models that primarily based on radiologists' subjective experience. However, all studies included were retrospective, thus the performance of radiomics needs to validate in prospective, multicenter studies.
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Affiliation(s)
- Jing Wen
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China.
| | - Wei Liu
- Department of Radiology, Yancheng Tinghu District People's Hospital, Yancheng, China
| | - Yilan Zhang
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Xiaocui Shen
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
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12
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Sanguedolce F, Tedde A, Granados L, Hernández J, Robalino J, Suquilanda E, Tedde M, Palou J, Breda A. Defining the role of multiparametric MRI in predicting prostate cancer extracapsular extension. World J Urol 2024; 42:37. [PMID: 38217693 PMCID: PMC10787875 DOI: 10.1007/s00345-023-04720-5] [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: 06/20/2023] [Accepted: 10/24/2023] [Indexed: 01/15/2024] Open
Abstract
OBJECTIVES To identify the predictive factors of prostate cancer extracapsular extension (ECE) in an institutional cohort of patients who underwent multiparametric MRI of the prostate prior to radical prostatectomy (RP). PATIENTS AND METHODS Overall, 126 patients met the selection criteria, and their medical records were retrospectively collected and analysed; 2 experienced radiologists reviewed the imaging studies. Logistic regression analysis was conducted to identify the variables associated to ECE at whole-mount histology of RP specimens; according to the statistically significant variables associated, a predictive model was developed and calibrated with the Hosmer-Lomeshow test. RESULTS The predictive ability to detect ECE with the generated model was 81.4% by including the length of capsular involvement (LCI) and intraprostatic perineural invasion (IPNI). The predictive accuracy of the model at the ROC curve analysis showed an area under the curve (AUC) of 0.83 [95% CI (0.76-0.90)], p < 0.001. Concordance between radiologists was substantial in all parameters examined (p < 0.001). Limitations include the retrospective design, limited number of cases, and MRI images reassessment according to PI-RADS v2.0. CONCLUSION The LCI is the most robust MRI factor associated to ECE; in our series, we found a strong predictive accuracy when combined in a model with the IPNI presence. This outcome may prompt a change in the definition of PI-RADS score 5.
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Affiliation(s)
- Francesco Sanguedolce
- Department of Medicine, Surgery and Pharmacy, Universitá degli Studi di Sassari, Sassari, Italy.
- Department of Urology, Fundació Puigvert, Barcelona, Spain.
- Institut Reserca Sant Pau, Institut Reserca Sant Pau, Barcelona, Spain.
| | - Alessandro Tedde
- Department of Medicine, Surgery and Pharmacy, Universitá degli Studi di Sassari, Sassari, Italy
- Department of Urology, Fundació Puigvert, Barcelona, Spain
| | - Luisa Granados
- Department of Radiology, Fundació Puigvert, Autonoma University of Barcelona, Barcelona, Spain
| | - Jonathan Hernández
- Department of Radiology, Fundació Puigvert, Autonoma University of Barcelona, Barcelona, Spain
| | - Jorge Robalino
- Department of Urology, Fundació Puigvert, Barcelona, Spain
| | | | - Matteo Tedde
- Department of Urology, Università degli Studi di Sassari, Sassari, Italy
| | - Joan Palou
- Department of Urology, Fundació Puigvert, Autonoma University of Barcelona, Barcelona, Spain
- Institut Reserca Sant Pau, Institut Reserca Sant Pau, Barcelona, Spain
| | - Alberto Breda
- Department of Urology, Fundació Puigvert, Barcelona, Spain
- Institut Reserca Sant Pau, Institut Reserca Sant Pau, Barcelona, Spain
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13
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Cheng X, Chen Y, Xu J, Cai D, Liu Z, Zeng H, Yao J, Song B. Development and validation of a predictive model based on clinical and MpMRI findings to reduce additional systematic prostate biopsy. Insights Imaging 2024; 15:3. [PMID: 38185753 PMCID: PMC10772021 DOI: 10.1186/s13244-023-01544-0] [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: 05/03/2023] [Accepted: 10/21/2023] [Indexed: 01/09/2024] Open
Abstract
OBJECTIVES To develop and validate a predictive model based on clinical features and multiparametric magnetic resonance imaging (mpMRI) to reduce unnecessary systematic biopsies (SBs) in biopsy-naïve patients with suspected prostate cancer (PCa). METHODS A total of 274 patients who underwent combined cognitive MRI-targeted biopsy (MRTB) with SB were retrospectively enrolled and temporally split into development (n = 201) and validation (n = 73) cohorts. Multivariable logistic regression analyses were used to determine independent predictors of clinically significant PCa (csPCa) on cognitive MRTB, and the clinical, MRI, and combined models were established respectively. Area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses were assessed. RESULTS Prostate imaging data and reporting system (PI-RADS) score, index lesion (IL) on the peripheral zone, age, and prostate-specific antigen density (PSAD) were independent predictors and included in the combined model. The combined model achieved the best discrimination (AUC 0.88) as compared to both the MRI model incorporated by PI-RADS score, IL level, and zone (AUC 0.86) and the clinical model incorporated by age and PSAD (AUC 0.70). The combined model also showed good calibration and enabled great net benefit. Applying the combined model as a reference for performing MRTB alone with a cutoff of 60% would reduce 43.8% of additional SB, while missing 2.9% csPCa. CONCLUSIONS The combined model based on clinical and mpMRI findings improved csPCa prediction and might be useful in making a decision about which patient could safely avoid unnecessary SB in addition to MRTB in biopsy-naïve patients. CRITICAL RELEVANCE STATEMENT The combined model based on clinical and mpMRI findings improved csPCa prediction and might be useful in making a decision about which patient could safely avoid unnecessary SB in addition to MRTB in biopsy-naïve patients. KEY POINTS • Age, PSAD, PI-RADS score, and peripheral index lesion were independent predictors of csPCa. • Risk models were used to predict the probability of detecting csPCa on cognitive MRTB. • The combined model might reduce 43.8% of unnecessary SBs, while missing 2.9% csPCa.
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Affiliation(s)
- Xueqing Cheng
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Street, Chengdu, 610041, Sichuan, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yuntian Chen
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Street, Chengdu, 610041, Sichuan, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Jinshun Xu
- Department of Ultrasound, Sichuan Cancer Hospital, Chengdu, Sichuan, China
| | - Diming Cai
- Department of Ultrasound, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Zhenhua Liu
- Department of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Hao Zeng
- Department of Urology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Jin Yao
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Street, Chengdu, 610041, Sichuan, China.
| | - Bin Song
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Street, Chengdu, 610041, Sichuan, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
- Department of Radiology, Sanya People's Hospital, Sanya, Hainan, China.
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14
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Furrer MA, Sathianathen N, Gahl B, Corcoran NM, Soliman C, Rodriguez Calero JA, Ineichen GB, Gahl M, Kiss B, Thalmann GN. Oncological outcomes after attempted nerve-sparing radical prostatectomy (NSRP) in patients with high-risk prostate cancer are comparable to standard non-NSRP: a longitudinal long-term propensity-matched single-centre study. BJU Int 2024; 133:53-62. [PMID: 37548822 DOI: 10.1111/bju.16126] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
OBJECTIVE To assess the long-term safety of nerve-sparing radical prostatectomy (NSRP) in men with high-risk prostate cancer (PCa) by comparing survival outcomes, disease recurrence, the need for additional therapy, and perioperative outcomes of patients undergoing NSRP to those having non-NSRP. PATIENTS AND METHODS We included consecutive patients at a single, academic centre who underwent open RP for high-risk PCa, defined as preoperative prostate-specific antigen level of > 20 ng/mL and/or postoperative International Society of Urological Pathology Grade Group 4 or 5 (i.e., Gleason score ≥ 8) and/or ≥pT3 and/or pN1 assessing the RP and lymph node specimen. We calculated a propensity score and used inverse probability of treatment weighting to match baseline characteristics of patients with high-risk PCa who underwent NSRP vs non-NSRP. We analysed oncological outcome as time-to-event and calculated hazard ratios (HRs). RESULTS A total of 726 patients were included in this analysis of which 84% (n = 609) underwent NSRP. There was no evidence for the positive surgical margin rate being different between the NSRP and non-NSRP groups (47% vs 49%, P = 0.64). Likewise, there was no evidence for the need for postoperative radiotherapy being different in men who underwent NSRP from those who underwent non-NSRP (HR 0.78, 95% confidence interval [CI] 0.53-1.15). NSRP did not impact the risk of any recurrence (HR 0.99, 95% CI 0.73-1.34, P = 0.09) and there was no evidence for survival being different in men who underwent NSRP to those who underwent non-NSRP (HR 0.65, 95% CI 0.39-1.08). There was also no evidence for the cancer-specific survival (HR 0.56, 95% CI 0.29-1.11) or progression-free survival (HR 0.99, 95% CI 0.73-1.34) being different between the groups. CONCLUSION In patients with high-risk PCa, NSRP can be attempted without compromising long-term oncological outcomes provided a comprehensive assessment of objective (e.g., T Stage) and subjective (e.g., intraoperative appraisal of tissue planes) criteria are conducted.
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Affiliation(s)
- Marc A Furrer
- Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Urology, Solothurner Spitäler AG, Kantonsspital Olten and Bürgerspital Solothurn, Biberist, Switzerland
- Department of Urology, Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | - Niranjan Sathianathen
- Department of Urology, Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Clinical Trials Unit Bern, University of Bern, Bern, Switzerland
| | - Brigitta Gahl
- Clinical Trials Unit Bern, University of Bern, Bern, Switzerland
| | - Niall M Corcoran
- Department of Urology, Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Urology, Western Health, St Albans, Victoria, Australia
| | - Christopher Soliman
- Department of Urology, Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Clinical Trials Unit Bern, University of Bern, Bern, Switzerland
| | | | - Gallus B Ineichen
- Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Miriam Gahl
- Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Bernhard Kiss
- Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - George N Thalmann
- Department of Urology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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15
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Wu S, Jiang Y, Liang Z, Chen S, Sun G, Ma S, Chen K, Liu R. Comprehensive analysis of predictive factors for upstaging in intraprostatic cancer after radical prostatectomy: Different patterns of spread exist in lesions at different locations. Cancer Med 2023; 12:17776-17787. [PMID: 37537798 PMCID: PMC10524000 DOI: 10.1002/cam4.6401] [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: 03/08/2023] [Revised: 07/14/2023] [Accepted: 07/22/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Accurate assessment of the clinical staging is crucial for determining the need for radical prostatectomy (RP) in prostate cancer (PCa). However, the current methods for PCa staging may yield incorrect results. This study aimed to comprehensively analyze independent predictors of postoperative upstaging of intraprostatic cancer. METHODS We conducted a retrospective analysis of data from intraprostatic cancer patients who underwent radical surgery between March 2019 and December 2022. Intraprostatic cancer was defined as a lesion confined to the prostate, excluding cases where multiparameter magnetic resonance imaging (mpMRI) showed the lesion in contact with the prostatic capsule. We assessed independent predictors of extraprostatic extension (EPE) and analyzed their association with positive surgical margin (PSM) status. In addition, based on the distance of the lesion from the capsule on mpMRI, we divided the patients into non-transition zone and transition zone groups for further analysis. RESULTS A total of 500 patients were included in our study. Logistic regression analysis revealed that biopsy Gleason grade group (GG) (odds ratio, OR: 1.370, 95% confidence interval, CI: 1.093-1.718) and perineural invasion (PNI) (OR: 2.746, 95% CI: 1.420-5.309) were predictive factors for postoperative EPE. Both biopsy GG and PNI were associated with lateral (GG: OR: 1.270, 95% CI: 1.074-1.501; PNI: OR: 2.733, 95% CI: 1.521-4.911) and basal (GG: OR: 1.491, 95% CI: 1.194-1.862; PNI: OR: 3.730, 95% CI: 1.929-7.214) PSM but not with apex PSM (GG: OR: 1.176, 95% CI: 0.989-1.399; PNI: OR: 1.204, 95% CI: 0.609-2.381) after RP. Finally, PNI was an independent predictor of EPE in the transition zone (OR: 11.235, 95% CI: 2.779-45.428) but not in the non-transition zone (OR: 1.942, 95% CI: 0.920-4.098). CONCLUSION PNI and higher GG may indicate upstaging of tumors in patients with intraprostatic carcinoma. These two factors are associated with PSM in locations other than the apex of the prostate. Importantly, cancer in the transition zone of the prostate is more likely to spread externally through nerve invasion than cancer in the non-transition zone.
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Affiliation(s)
- Shangrong Wu
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Yuchen Jiang
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Zhengxin Liang
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Shuaiqi Chen
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Guangyu Sun
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Shenfei Ma
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Kaifei Chen
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
| | - Ranlu Liu
- Department of UrologyThe Second Hospital of Tianjin Medical UniversityTianjinChina
- Tianjin Institute of UrologyTianjinChina
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16
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Ponsiglione A, Stanzione A, Califano G, De Giorgi M, Collà Ruvolo C, D'Iglio I, Morra S, Longo N, Imbriaco M, Cuocolo R. MR image quality in local staging of prostate cancer: Role of PI-QUAL in the detection of extraprostatic extension. Eur J Radiol 2023; 166:110973. [PMID: 37453275 DOI: 10.1016/j.ejrad.2023.110973] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 06/23/2023] [Accepted: 07/10/2023] [Indexed: 07/18/2023]
Abstract
PURPOSE To assess the impact of prostate MRI image quality by means of the Prostate Imaging Quality (PI-QUAL) score, on the identification of extraprostatic extension of disease (EPE), predicted using the EPE Grade Score, Likert Scale Score (LSS) and a clinical nomogram (MSKCCn). METHODS We retrospectively included 105 patients with multiparametric prostate MRI prior to prostatectomy. Two radiologists evaluated image quality using PI-QUAL (≥4 was considered high quality) in consensus. All cases were also scored using the EPE Grade, the LSS, and the MSKCCn (dichotomized). Inter-rater reproducibility for each score was also assessed. Accuracy was calculated for the entire population and by image quality, considering two thresholds for EPE Grade (≥2 and = 3) and LSS (≥3 and ≥ 4) and using McNemar's test for comparison. RESULTS Overall, 66 scans achieved high quality. The accuracy of EPE Grade ranged from 0.695 to 0.743, while LSS achieved values between 0.705 and 0.733. Overall sensitivity for the radiological scores (range = 0.235-0.529) was low irrespective of the PI-QUAL score, while specificity was higher (0.775-0.986). The MSKCCn achieved an AUC of 0.76, outperforming EPE Grade (=3 threshold) in studies with suboptimal image quality (0.821 vs 0.564, p = 0.016). EPE Grade (=3 threshold) accuracy was also better in high image quality studies (0.849 vs 0.564, p = 0.001). Reproducibility was good to excellent overall (95 % Confidence Interval range = 0.782-0.924). CONCLUSION Assessing image quality by means of PI-QUAL is helpful in the evaluation of EPE, as a scan of low quality makes its performance drop compared to clinical staging tools.
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Affiliation(s)
- Andrea Ponsiglione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
| | - Gianluigi Califano
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Marco De Giorgi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Claudia Collà Ruvolo
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Imma D'Iglio
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Simone Morra
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Nicola Longo
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery, and Dentistry, University of Salerno, Baronissi, Italy
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17
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Calimano-Ramirez LF, Virarkar MK, Hernandez M, Ozdemir S, Kumar S, Gopireddy DR, Lall C, Balaji KC, Mete M, Gumus KZ. MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review. Abdom Radiol (NY) 2023; 48:2379-2400. [PMID: 37142824 DOI: 10.1007/s00261-023-03924-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/13/2023] [Accepted: 04/18/2023] [Indexed: 05/06/2023]
Abstract
PURPOSE Prediction of extraprostatic extension (EPE) is essential for accurate surgical planning in prostate cancer (PCa). Radiomics based on magnetic resonance imaging (MRI) has shown potential to predict EPE. We aimed to evaluate studies proposing MRI-based nomograms and radiomics for EPE prediction and assess the quality of current radiomics literature. METHODS We used PubMed, EMBASE, and SCOPUS databases to find related articles using synonyms for MRI radiomics and nomograms to predict EPE. Two co-authors scored the quality of radiomics literature using the Radiomics Quality Score (RQS). Inter-rater agreement was measured using the intraclass correlation coefficient (ICC) from total RQS scores. We analyzed the characteristic s of the studies and used ANOVAs to associate the area under the curve (AUC) to sample size, clinical and imaging variables, and RQS scores. RESULTS We identified 33 studies-22 nomograms and 11 radiomics analyses. The mean AUC for nomogram articles was 0.783, and no significant associations were found between AUC and sample size, clinical variables, or number of imaging variables. For radiomics articles, there were significant associations between number of lesions and AUC (p < 0.013). The average RQS total score was 15.91/36 (44%). Through the radiomics operation, segmentation of region-of-interest, selection of features, and model building resulted in a broader range of results. The qualities the studies lacked most were phantom tests for scanner variabilities, temporal variability, external validation datasets, prospective designs, cost-effectiveness analysis, and open science. CONCLUSION Utilizing MRI-based radiomics to predict EPE in PCa patients demonstrates promising outcomes. However, quality improvement and standardization of radiomics workflow are needed.
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Affiliation(s)
- Luis F Calimano-Ramirez
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Mayur K Virarkar
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Mauricio Hernandez
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Savas Ozdemir
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Sindhu Kumar
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Dheeraj R Gopireddy
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Chandana Lall
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - K C Balaji
- Department of Urology, University of Florida College of Medicine, Jacksonville, FL, 32209, USA
| | - Mutlu Mete
- Department of Computer Science and Information System, Texas A&M University-Commerce, Commerce, TX, 75428, USA
| | - Kazim Z Gumus
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA.
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18
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Pedraza AM, Parekh S, Joshi H, Grauer R, Wagaskar V, Zuluaga L, Gupta R, Barthe F, Nasri J, Pandav K, Patel D, Gorin MA, Menon M, Tewari AK. Side-specific, Microultrasound-based Nomogram for the Prediction of Extracapsular Extension in Prostate Cancer. EUR UROL SUPPL 2022; 48:72-81. [PMID: 36743400 PMCID: PMC9895764 DOI: 10.1016/j.euros.2022.12.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/01/2022] [Indexed: 12/29/2022] Open
Abstract
Background Prediction of extracapsular extension (ECE) is essential to achieve a balance between oncologic resection and neural tissue preservation. Microultrasound (MUS) is an attractive alternative to multiparametric magnetic resonance imaging (mpMRI) in the staging scenario. Objective To create a side-specific nomogram integrating clinicopathologic parameters and MUS findings to predict ipsilateral ECE and guide nerve sparing. Design setting and participants Prospective data were collected from consecutive patients who underwent robotic-assisted radical prostatectomy from June 2021 to May 2022 and had preoperative MUS and mpMRI. A total of 391 patients and 612 lobes were included in the analysis. Outcome measurements and statistical analysis ECE on surgical pathology was the primary outcome. Multivariate regression analyses were carried out to identify predictors for ECE. The resultant multivariable model's performance was visualized using the receiver-operating characteristic curve. A nomogram was developed based on the coefficients of the logit function for the MUS-based model. A decision curve analysis (DCA) was performed to assess clinical utility. Results and limitations The areas under the receiver-operating characteristic curve (AUCs) of the MUS-based model were 81.4% and 80.9% (95% confidence interval [CI] 75.6, 84.6) after internal validation. The AUC of the mpMRI-model was also 80.9% (95% CI 77.2, 85.7). The DCA demonstrated the net clinical benefit of the MUS-based nomogram and its superiority compared with MUS and MRI alone for detecting ECE. Limitations of our study included its sample size and moderate inter-reader agreement. Conclusions We developed a side-specific nomogram to predict ECE based on clinicopathologic variables and MUS findings. Its performance was comparable with that of a mpMRI-based model. External validation and prospective trials are required to corroborate our results. Patient summary The integration of clinical parameters and microultrasound can predict extracapsular extension with similar results to models based on magnetic resonance imaging findings. This can be useful for tailoring the preservation of nerves during surgery.
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Affiliation(s)
- Adriana M. Pedraza
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.,Corresponding authors at: Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA. Tel. +1 2122416500
| | - Sneha Parekh
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Himanshu Joshi
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.,Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ralph Grauer
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Vinayak Wagaskar
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Laura Zuluaga
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Raghav Gupta
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Flora Barthe
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Jordan Nasri
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Krunal Pandav
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Dhruti Patel
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Michael A. Gorin
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Mani Menon
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Ashutosh K. Tewari
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.,Corresponding authors at: Department of Urology, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA. Tel. +1 2122416500
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19
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Li PI, Chen SJ, Chen YH, Chen WC, Huang CP. Comparative Outcomes of Robotic Radical Prostatectomy in Patients with Locally Advanced Prostate Cancer. Medicina (B Aires) 2022; 58:medicina58121820. [PMID: 36557022 PMCID: PMC9782116 DOI: 10.3390/medicina58121820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 12/14/2022] Open
Abstract
The effectiveness of radical prostatectomy alone for locally advanced prostate cancer is controversial owing to an increased complication rate and treatment-related morbidity. With technical advances and refinements in surgical techniques, robotic-assisted radical prostatectomy (RARP) has improved the outcomes of patients with locally advanced prostate cancer. RARP therefore plays a role in the treatment of locally advanced prostate cancer. In this study, we enrolled a total of 76 patients with pathologic stage pT3a, pT3b, pT4, or pN1. All patients were followed from surgery to June 2022, and their characteristics, perioperative outcomes, complications, adjuvant therapies and outcomes were analyzed. The median age of the patients was 69 years, and the initial PSA level was 20.5 (IQR 10.8-31.6) ng/mL. The median operative time was 205 (IQR 182-241) minutes. Sixty-six patients (86.8%) regained continence within 1 year, and the continence rate within 3 years of follow-up was 90.8% (69 patients). The overall survival rate was 100%. Twenty-two patients had BCR, of whom 13 received salvage androgen deprivation therapy (ADT), 2 received salvage external beam radiation therapy (EBRT) alone, and 7 received combined ADT and EBRT. No patient had disease progression to castration-resistant prostate cancer during a median 36 months of follow-up after salvage therapy. Our results suggest that RARP can also decrease tumor burden and allow for accurate and precise pathological staging with the need for subsequent treatment. Therefore, we recommend that RARP represents a well-standardized, safe, and oncologically effective option for patients with locally advanced prostate cancer.
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Affiliation(s)
- Po-I Li
- Department of Urology, China Medical University Hospital, Taichung 40447, Taiwan
| | - Szu-Ju Chen
- Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung 40705, Taiwan
| | - Yung-Hsiang Chen
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung 40402, Taiwan
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung 41354, Taiwan
| | - Wen-Chi Chen
- Department of Urology, China Medical University Hospital, Taichung 40447, Taiwan
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung 40402, Taiwan
| | - Chi-Ping Huang
- Department of Urology, China Medical University Hospital, Taichung 40447, Taiwan
- School of Medicine, College of Medicine, China Medical University, Taichung 40402, Taiwan
- Correspondence:
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20
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Nocera L, Stolzenbach LF, Collà Ruvolo C, Wenzel M, Wurnschimmel C, Tian Z, Gandaglia G, Fossati N, Mirone V, Chun FKH, Shariat SF, Graefen M, Saad F, Montorsi F, Briganti A, Karakiewicz PI. Predicting the probability of pT3 or higher pathological stage at radical prostatectomy: COVID19-specific considerations. Front Oncol 2022; 12:990851. [PMID: 36561531 PMCID: PMC9763886 DOI: 10.3389/fonc.2022.990851] [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: 07/16/2022] [Accepted: 11/16/2022] [Indexed: 12/12/2022] Open
Abstract
Background We tested whether a model identifying prostate cancer (PCa) patients at risk of pT3-4/pN1 can be developed for use during COVID19 pandemic, in order to guarantee appropriate treatment to patients harboring advanced disease patients without compromising sustainability of care delivery. Methods Within the Surveillance, Epidemiology and End Results database 2010-2016, we identified 27,529 patients with localized PCa and treated with radical prostatectomy. A multivariable logistic regression model predicting presence of pT3-4/pN1 disease was fitted within a development cohort (n=13,977, 50.8%). Subsequently, external validation (n=13,552, 49.2%) and head-to-head comparison with NCCN risk group stratification was performed. Results In model development, age, PSA, biopsy Gleason Grade Group (GGG) and percentage of positive biopsy cores were independent predictors of pT3-4/pN1 stage. In external validation, prediction of pT3-4/pN1 with novel nomogram was 74% accurate versus 68% for NCCN risk group stratification. Nomogram achieved better calibration and showed net-benefit over NCCN risk group stratification in decision curve analyses. The use of nomogram cut-off of 49% resulted in pT3-4/pN1 rate of 65%, instead of the average 35%. Conclusion The newly developed, externally validated nomogram predicts presence of pT3-4/pN1 better than NCCN risk group stratification and allows to focus radical prostatectomy treatment on individuals at highest risk of pT3-4/pN1.
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Affiliation(s)
- Luigi Nocera
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada,Division of Experimental Oncology/Unit of Urology, URI, Urological Research Institute, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy,*Correspondence: Luigi Nocera,
| | - Lara F. Stolzenbach
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada,Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Claudia Collà Ruvolo
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada,Department of Urology, University of Naples Federico II, Naples, Italy
| | - Mike Wenzel
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada,Department of Urology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Christoph Wurnschimmel
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada,Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Zhe Tian
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada
| | - Giorgio Gandaglia
- Division of Experimental Oncology/Unit of Urology, URI, Urological Research Institute, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
| | - Nicola Fossati
- Division of Experimental Oncology/Unit of Urology, URI, Urological Research Institute, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
| | - Vincenzo Mirone
- Department of Urology, University of Naples Federico II, Naples, Italy
| | - Felix K. H. Chun
- Department of Urology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Shahrokh F. Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria,Departments of Urology, Weill Cornell Medical College, New York, NY, United States,Department of Urology, University of Texas Southwestern, Dallas, TX, United States,Department of Urology, Second Faculty of Medicine, Charles University, Prag, Czechia,Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia,Division of Urology, Department of Special Surgery, Jordan University Hospital, The University of Jordan, Amman, Jordan
| | - Markus Graefen
- Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Fred Saad
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada
| | - Francesco Montorsi
- Division of Experimental Oncology/Unit of Urology, URI, Urological Research Institute, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
| | - Alberto Briganti
- Division of Experimental Oncology/Unit of Urology, URI, Urological Research Institute, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
| | - Pierre I. Karakiewicz
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, QC, Canada
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21
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Washino S, Ito K, Miyagawa T. Prostate-specific antigen level, biopsy grade group, and tumor-capsular contact length on magnetic resonance imaging are independently associated with an extraprostatic extension. Int J Urol 2022; 29:1455-1461. [PMID: 36001632 DOI: 10.1111/iju.15012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 07/21/2022] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To define the clinicopathological and radiological factors independently associated with the existence of an extraprostatic extension in radical prostatectomy specimens. METHODS A total of 202 patients who underwent robotic prostatectomy following biparametric magnetic resonance imaging were assessed. We evaluated the clinicopathological and magnetic resonance imaging variables. We performed receiver-operating characteristic curve analyses to identify factors associated with extraprostatic extension. We engaged in multivariate analysis to identify factors independently associated with such extension. RESULTS Extraprostatic extensions were apparent in the final prostatectomy specimens of 62 patients (31%). The areas under the curves of the prostate-specific antigen level, the biopsy grade group, and the tumor-capsular contact length on magnetic resonance imaging were 0.76, 0.71, and 0.70, respectively, in receiver-operating characteristic analysis when used to predict extraprostatic extension; thus, higher than the areas under the curves of the other variables (0.61-0.68). The prostate-specific antigen level (odds ratio 1.090, p = 0.004), the biopsy grade group (odds ratios 2.678 and 6.358, p = 0.017 and p < 0.001 for grade group 3-4 and 5), and the tumor-capsular contact length (odds ratio 1.079, p = 0.001) were independently associated with extraprostatic extension. When the three factors were combined, the area under the receiver-operator characteristic curve increased to 0.79. CONCLUSIONS The prostate-specific antigen level, the biopsy grade group, and the tumor-capsular contact length on magnetic resonance imaging were independently associated with extracapsular extension.
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Affiliation(s)
- Satoshi Washino
- Department of Urology, Jichi Medical University Saitama Medical Center, Saitama, Japan
| | - Koichi Ito
- Department of Radiology, Jichi Medical University Saitama Medical Center, Saitama, Japan
| | - Tomoaki Miyagawa
- Department of Urology, Jichi Medical University Saitama Medical Center, Saitama, Japan
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22
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A side-specific nomogram for extraprostatic extension may reduce the positive surgical margin rate in radical prostatectomy. World J Urol 2022; 40:2919-2924. [DOI: 10.1007/s00345-022-04191-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 10/08/2022] [Indexed: 11/09/2022] Open
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23
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Song XQ, Liu ZX, Kong QY, He ZH, Zhang S. Nomogram for prediction of peritoneal metastasis risk in colorectal cancer. Front Oncol 2022; 12:928894. [PMID: 36419892 PMCID: PMC9676355 DOI: 10.3389/fonc.2022.928894] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 10/24/2022] [Indexed: 09/09/2023] Open
Abstract
OBJECTIVE Peritoneal metastasis is difficult to diagnose using traditional imaging techniques. The main aim of the current study was to develop and validate a nomogram for effectively predicting the risk of peritoneal metastasis in colorectal cancer (PMCC). METHODS A retrospective case-control study was conducted using clinical data from 1284 patients with colorectal cancer who underwent surgery at the First Affiliated Hospital of Guangxi Medical University from January 2010 to December 2015. Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize feature selection of the PMCC risk prediction model and multivariate logistic regression analysis conducted to determine independent risk factors. Using the combined features selected in the LASSO regression model, we constructed a nomogram model and evaluated its predictive value via receiver operating characteristic (ROC) curve analysis. The bootstrap method was employed for repeated sampling for internal verification and the discrimination ability of the prediction models evaluated based on the C-index. The consistency between the predicted and actual results was assessed with the aid of calibration curves. RESULTS Overall, 96 cases of PMCC were confirmed via postoperative pathological diagnosis. Logistic regression analysis showed that age, tumor location, perimeter ratio, tumor size, pathological type, tumor invasion depth, CEA level, and gross tumor type were independent risk factors for PMCC. A nomogram composed of these eight factors was subsequently constructed. The calibration curve revealed good consistency between the predicted and actual probability, with a C-index of 0.882. The area under the curve (AUC) of the nomogram prediction model was 0.882 and its 95% confidence interval (CI) was 0.845-0.919. Internal validation yielded a C-index of 0.868. CONCLUSION We have successfully constructed a highly sensitive nomogram that should facilitate early diagnosis of PMCC, providing a robust platform for further optimization of clinical management strategies.
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Affiliation(s)
- Xian-qing Song
- General Surgery Department, Ningbo Fourth Hospital, Ningbo, Zhejiang, China
| | - Zhi-xian Liu
- Proctology Department, Beilun People’s Hospital of Ningbo, Ningbo, Zhejiang, China
| | - Qing-yuan Kong
- General Surgery Department, Baoan People’s Hospital of Shenzhen, Shenzhen, Guangdong, China
| | - Zhen-hua He
- General Surgery Department, Hezhou People’s Hospital, Hezhou, Guangxi, China
| | - Sen Zhang
- Department of Colorectal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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24
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Diamand R, Roche JB, Lievore E, Lacetera V, Chiacchio G, Beatrici V, Mastroianni R, Simone G, Windisch O, Benamran D, Favre MM, Fourcade A, Nguyen TA, Fournier G, Fiard G, Ploussard G, Roumeguère T, Peltier A, Albisinni S. External Validation of Models for Prediction of Side-specific Extracapsular Extension in Prostate Cancer Patients Undergoing Radical Prostatectomy. Eur Urol Focus 2022; 9:309-316. [PMID: 36153227 DOI: 10.1016/j.euf.2022.09.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/29/2022] [Accepted: 09/08/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND Predicting the risk of side-specific extracapsular extension (ECE) is essential for planning nerve-sparing radical prostatectomy (RP) in patients with prostate cancer (PCa). OBJECTIVE To externally validate available models for prediction of ECE. DESIGN, SETTING, AND PARTICIPANTS Sixteen models were assessed in a cohort of 737 consecutive PCa patients diagnosed via multiparametric magnetic resonance imaging (MRI)-targeted and systematic biopsies and treated with RP between January 2016 and November 2021 at eight referral centers. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Model performance was evaluated in terms of discrimination using area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). RESULTS AND LIMITATIONS Overall, ECE was identified in 308/1474 (21%) prostatic lobes. Prostatic lobes with ECE had higher side-specific clinical stage on digital rectal examination and MRI, number of positive biopsy cores, and International Society of Urological Pathology grade group in comparison to those without ECE (all p < 0.0001). Less optimistic performance was observed in comparison to previous published studies, although the models described by Pak, Patel, Martini, and Soeterik achieved the highest accuracy (AUC ranging from 0.73 to 0.77), adequate calibration for a probability threshold <40%, and the highest net benefit for a probability threshold >8% on DCA. Inclusion of MRI-targeted biopsy data and MRI information in models improved patient selection and clinical usefulness. Using model-derived cutoffs suggested by their authors, approximately 15% of positive surgical margins could have been avoided. Some available models were not included because of missing data, which constitutes a limitation of the study. CONCLUSIONS We report an external validation of models predicting ECE and identified the four with the best performance. These models should be applied for preoperative planning and patient counseling. PATIENT SUMMARY We validated several tools for predicting extension of prostate cancer outside the prostate gland. These tools can improve patient selection for surgery that spares nerves affecting recovery of sexual potency after removal of the prostate. They could potentially reduce the risk of finding cancer cells at the edge of specimens taken for pathology, a finding that suggests that not all of the cancer has been removed.
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Affiliation(s)
- Romain Diamand
- Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium.
| | | | - Elena Lievore
- Department of Urology, Clinique Saint-Augustin, Bordeaux, France; Department of Urology, IRCCS IEO Istituto Europeo di Oncologia, Milan, Italy
| | - Vito Lacetera
- Department of Urology, Azienda Ospedaliera Ospedali Riuniti Marche Nord, Pesaro, Italy
| | - Giuseppe Chiacchio
- Department of Urology, Azienda Ospedaliera Ospedali Riuniti Marche Nord, Pesaro, Italy
| | - Valerio Beatrici
- Department of Urology, Azienda Ospedaliera Ospedali Riuniti Marche Nord, Pesaro, Italy
| | - Riccardo Mastroianni
- Department of Urology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Giuseppe Simone
- Department of Urology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Olivier Windisch
- Department of Urology, Hôpitaux Universitaires de Genève, Geneva, Switzerland
| | - Daniel Benamran
- Department of Urology, Hôpitaux Universitaires de Genève, Geneva, Switzerland
| | | | - Alexandre Fourcade
- Department of Urology, Hôpital Cavale Blanche, CHRU Brest, Brest, France
| | - Truong An Nguyen
- Department of Urology, Hôpital Cavale Blanche, CHRU Brest, Brest, France
| | - Georges Fournier
- Department of Urology, Hôpital Cavale Blanche, CHRU Brest, Brest, France
| | - Gaelle Fiard
- Department of Urology, Grenoble Alpes University Hospital, Université Grenoble Alpes, CNRS, Grenoble INP, TIMC, Grenoble, France
| | | | - Thierry Roumeguère
- Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Alexandre Peltier
- Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Simone Albisinni
- Department of Urology, Jules Bordet Institute-Erasme Hospital, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
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Multiparametric MRI for Staging of Prostate Cancer: A Multicentric Analysis of Predictive Factors to Improve Identification of Extracapsular Extension before Radical Prostatectomy. Cancers (Basel) 2022; 14:cancers14163966. [PMID: 36010963 PMCID: PMC9406654 DOI: 10.3390/cancers14163966] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 07/29/2022] [Accepted: 08/10/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary In this multicentric study, we tested the accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting extracapsular extension (ECE) out of the prostate in order to plan surgical sparing of neurovascular bundles in radical prostatectomy. Univariate and multivariate logistic regression analyses were performed to identify other risk factors for ECE. We found that it has a good ability to exclude extracapsular extension but a poor ability to identify it correctly. Risk factors other than mpMRI that predicted ECE were as follows: prostatic specific antigen, digital rectal examination, ratio of positive cores, and biopsy grade group. We suggest that using mpMRI exclusively should not be recommended to decide on surgical approaches. Abstract The correct identification of extracapsular extension (ECE) of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI) is crucial for surgeons in order to plan the nerve-sparing approach in radical prostatectomy. Nerve-sparing strategies allow for better outcomes in preserving erectile function and urinary continence, notwithstanding this can be penalized with worse oncologic results. The aim of this study was to assess the ability of preoperative mpMRI to predict ECE in the final prostatic specimen (PS) and identify other possible preoperative predictive factors of ECE as a secondary end-point. We investigated a database of two high-volume hospitals to identify men who underwent a prostate biopsy with a pre-biopsy mpMRI and a subsequent RP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting ECE were calculated. A univariate analysis was performed to find the association between image staging and pathological staging. A multivariate logistic regression was performed to investigate other preoperative predictive factors. A total of 1147 patients were selected, and 203 out of the 1147 (17.7%) patients were classified as ECE according to the mpMRI. ECE was reported by pathologists in 279 out of the 1147 PS (24.3%). The PPV was 0.58, the NPV was 0.72, the sensitivity was 0.32, and the specificity was 0.88. The multivariate analysis found that PSA (OR 1.057, C.I. 95%, 1.016–1.100, p = 0.006), digital rectal examination (OR 0.567, C.I. 95%, 0.417–0.770, p = 0.0001), ratio of positive cores (OR 9.687, C.I. 95%, 3.744–25.006, p = 0.0001), and biopsy grade in prostate biopsy (OR 1.394, C.I. 95%, 1.025–1.612, p = 0.0001) were independent factors of ECE. The mpMRI has a great ability to exclude ECE, notwithstanding that low sensitivity is still an important limitation of the technique.
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Sorce G, Flammia RS, Hoeh B, Chierigo F, Hohenhorst L, Panunzio A, Stabile A, Gandaglia G, Tian Z, Tilki D, Terrone C, Gallucci M, Chun FKH, Antonelli A, Saad F, Shariat SF, Montorsi F, Briganti A, Karakiewicz PI. Grade and stage misclassification in intermediate unfavorable-risk prostate cancer radiotherapy candidates. Prostate 2022; 82:1040-1050. [PMID: 35365851 PMCID: PMC9325037 DOI: 10.1002/pros.24349] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/20/2022] [Accepted: 03/22/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND We tested for upgrading (Gleason grade group [GGG] ≥ 4) and/or upstaging to non-organ-confined stage ([NOC] ≥ pT3/pN1) in intermediate unfavorable-risk (IU) prostate cancer (PCa) patients treated with radical prostatectomy, since both change the considerations for dose and/or type of radiotherapy (RT) and duration of androgen deprivation therapy (ADT). METHODS We relied on Surveillance, Epidemiology, and End Results (2010-2015). Proportions of (a) upgrading, (b) upstaging, or (c) upgrading and/or upstaging were tabulated and tested in multivariable logistic regression models. RESULTS We identified 7269 IU PCa patients. Upgrading was recorded in 479 (6.6%) and upstaging in 2398 (33.0%), for a total of 2616 (36.0%) upgraded and/or upstaged patients, who no longer fulfilled the IU grade and stage definition. Prostate-specific antigen, clinical stage, biopsy GGG, and percentage of positive cores, neither individually nor in multivariable logistic regression models, discriminated between upgraded and/or upstaged patients versus others. CONCLUSIONS IU PCa patients showed very high (36%) upgrading and/or upstaging proportion. Interestingly, the overwhelming majority of those were upstaged to NOC. Conversely, very few were upgraded to GGG ≥ 4. In consequence, more than one-third of IU PCa patients treated with RT may be exposed to suboptimal dose and/or type of RT and to insufficient duration of ADT, since their true grade and stage corresponded to high-risk PCa definition, instead of IU PCa. Data about magnetic resonance imaging were not available but may potentially help with better stage discrimination.
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Affiliation(s)
- Gabriele Sorce
- Department of Urology, Division of Experimental OncologyURI, Urological Research Institute, IRCCS San Raffaele Scientific InstituteMilanItaly
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
| | - Rocco Simone Flammia
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
- Department of Maternal‐Child and Urological Sciences, Policlinico Umberto I HospitalSapienza University of RomeRomeItaly
| | - Benedikt Hoeh
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
- Department of UrologyUniversity Hospital FrankfurtFrankfurt am MainGermany
| | - Francesco Chierigo
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
- Department of Surgical and Diagnostic Integrated Sciences (DISC)University of GenovaGenovaItaly
| | - Lukas Hohenhorst
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
- Department of UrologyMartini‐Klinik Prostate Cancer Center, University Hospital Hamburg‐EppendorfHamburgGermany
| | - Andrea Panunzio
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
- Department of UrologyUniversity of Verona, Azienda Ospedaliera Universitaria Integrata di VeronaVeronaItaly
| | - Armando Stabile
- Department of Urology, Division of Experimental OncologyURI, Urological Research Institute, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Giorgio Gandaglia
- Department of Urology, Division of Experimental OncologyURI, Urological Research Institute, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Zhe Tian
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
| | - Derya Tilki
- Department of UrologyMartini‐Klinik Prostate Cancer Center, University Hospital Hamburg‐EppendorfHamburgGermany
- Department of UrologyUniversity Hospital Hamburg‐EppendorfHamburgGermany
- Department of UrologyKoc University HospitalInstanbulTurkey
| | - Carlo Terrone
- Department of Surgical and Diagnostic Integrated Sciences (DISC)University of GenovaGenovaItaly
| | - Michele Gallucci
- Department of Maternal‐Child and Urological Sciences, Policlinico Umberto I HospitalSapienza University of RomeRomeItaly
| | - Felix K. H. Chun
- Department of UrologyUniversity Hospital FrankfurtFrankfurt am MainGermany
| | - Alessandro Antonelli
- Department of UrologyUniversity of Verona, Azienda Ospedaliera Universitaria Integrata di VeronaVeronaItaly
| | - Fred Saad
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
| | - Shahrokh F. Shariat
- Departments of UrologyWeill Cornell Medical CollegeNew YorkNew YorkUSA
- Department of UrologyUniversity of Texas SouthwesternDallasTexasUSA
- Department of Urology, Second Faculty of MedicineCharles UniversityPragaCzech Republic
- Department of Urology, Institute for Urology and Reproductive HealthI.M. Sechenov First Moscow State Medical UniversityMoscowRussia
- Division of Urology, Hourani Center for Applied Scientific ResearchAl‐Ahliyya Amman UniversityAmmanJordan
- Department of Urology, Comprehensive Cancer CenterMedical University of ViennaViennaAustria
| | - Francesco Montorsi
- Department of Urology, Division of Experimental OncologyURI, Urological Research Institute, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Alberto Briganti
- Department of Urology, Division of Experimental OncologyURI, Urological Research Institute, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Pierre I. Karakiewicz
- Division of Urology, Cancer Prognostics and Health Outcomes UnitUniversity of Montréal Health CenterMontréalQuébecCanada
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Prostate-specific antigen nomogram to predict advanced prostate cancer using area under the receiver operating characteristic curve boosting. Urol Oncol 2022; 40:162.e9-162.e16. [DOI: 10.1016/j.urolonc.2021.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/27/2021] [Accepted: 12/21/2021] [Indexed: 11/18/2022]
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Gatti M, Faletti R, Gentile F, Soncin E, Calleris G, Fornari A, Oderda M, Serafini A, Strazzarino GA, Vissio E, Bergamasco L, Cirillo S, Papotti MG, Gontero P, Fonio P. mEPE-score: a comprehensive grading system for predicting pathologic extraprostatic extension of prostate cancer at multiparametric magnetic resonance imaging. Eur Radiol 2022; 32:4942-4953. [PMID: 35290508 PMCID: PMC9213375 DOI: 10.1007/s00330-022-08595-9] [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: 10/11/2021] [Revised: 01/18/2022] [Accepted: 01/20/2022] [Indexed: 11/24/2022]
Abstract
Objective To investigate the diagnostic accuracy of the PI-RADS v2.1 multiparametric magnetic resonance imaging (mpMRI) features in predicting extraprostatic extension (mEPE) of prostate cancer (PCa), as well as to develop and validate a comprehensive mpMRI-derived score (mEPE-score). Methods We retrospectively reviewed all consecutive patients admitted to two institutions for radical prostatectomy for PCa with available records of mpMRI performed between January 2015 and December 2020. Data from one institution was used for investigating diagnostic performance of each mEPE feature using radical prostatectomy specimens as benchmark. The results were implemented in a mEPE-score as follows: no mEPE features: 1; capsular abutment: 2; irregular or spiculated margin: 3; bulging prostatic contour, or asymmetry of the neurovascular bundles, or tumor-capsule interface > 1.0 cm: 4; ≥ 2 of the previous three parameters or measurable extraprostatic disease: 5. The performance of mEPE features was evaluated using the five diagnostic parameters and ROC curve analysis. Results Two-hundred patients were enrolled at site 1 and 76 at site 2. mEPE features had poor sensitivities ranging from 0.08 (0.00–0.15) to 0.71 (0.59–0.83), whereas specificity ranged from 0.68 (0.58–0.79) to 1.00. mEPE-score showed excellent discriminating ability (AUC > 0.8) and sensitivity = 0.82 and specificity = 0.77 with a threshold of 3. mEPE-score had AUC comparable to ESUR-score (p = 0.59 internal validation; p = 0.82 external validation), higher than or comparable to mEPE-grade (p = 0.04 internal validation; p = 0.58 external validation), and higher than early-and-late-EPE (p < 0.0001 internal and external validation). There were no significant differences between readers having different expertise with EPE-score (p = 0.32) or mEPE-grade (p = 0.45), but there were significant differences for ESUR-score (p = 0.02) and early-versus-late-EPE (p = 0.03). Conclusions The individual mEPE features have low sensitivity and high specificity. The use of mEPE-score allows for consistent and reliable assessment for pathologic EPE. Key Points • Individual PI-RADS v2.1 mpMRI features had poor sensitivities ranging from 0.08 (0.00–0.15) to 0.71 (0.59–0.83), whereas Sp ranged from 0.68 (0.58–0.79) to 1.00. • mEPE-score is an all-inclusive score for the assessment of pEPE with excellent discriminating ability (i.e., AUC > 0.8) and Se = 0.82, Sp = 0.77, PPV = 0.74, and NPV = 0.84 with a threshold of 3. • The diagnostic performance of the expert reader and beginner reader with pEPE-score was comparable (p = 0.32). Supplementary Information The online version contains supplementary material available at 10.1007/s00330-022-08595-9.
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Affiliation(s)
- Marco Gatti
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy.
| | - Riccardo Faletti
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | - Francesco Gentile
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | - Enrico Soncin
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | - Giorgio Calleris
- Urology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Alberto Fornari
- Radiology Unit, Mauriziano Umberto I Hospital, 10128, Turin, Italy
| | - Marco Oderda
- Urology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Alessandro Serafini
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | | | - Elena Vissio
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Laura Bergamasco
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Stefano Cirillo
- Radiology Unit, Mauriziano Umberto I Hospital, 10128, Turin, Italy
| | - Mauro Giulio Papotti
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Paolo Gontero
- Urology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Paolo Fonio
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
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Caglic I, Sushentsev N, Shah N, Warren AY, Lamb BW, Barrett T. Integration of Prostate Biopsy Results with Pre-Biopsy Multiparametric Magnetic Resonance Imaging Findings Improves Local Staging of Prostate Cancer. Can Assoc Radiol J 2022; 73:515-523. [PMID: 35199583 DOI: 10.1177/08465371211073158] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
PURPOSE To assess the added value of histological information for local staging of prostate cancer (PCa) by comparing the accuracy of multiparametric MRI alone (mpMRI) and mpMRI with biopsy Gleason grade (mpMRI+Bx). METHODS 133 consecutive patients who underwent preoperative 3T-MRI and subsequent radical prostatectomy for PCa were included in this single-centre retrospective study. mpMRI imaging was reviewed independently by two uroradiologists for the presence of extracapsular extension (ECE) and seminal vesicle invasion (SVI) on a 5-point Likert scale. For second reads, the radiologists received results of targeted fused MR/US biopsy (mpMRI+Bx) prior to re-staging. RESULTS The median patient age was 63 years (interquartile range (IQR) 58-67 years) and median PSA was 6.5 ng/mL (IQR 5.0-10.0 ng/mL). Extracapsular extension was present in 85/133 (63.9%) patients and SVI was present in 22/133 (16.5%) patients. For ECE prediction, mpMRI showed sensitivity and specificity of 63.5% and 81.3%, respectively, compared to 77.7% and 81.3% achieved by mpMRI+Bx. At an optimal cut-off value of Likert score ≥ 3, areas under the curves (AUCs) was .85 for mpMRI+Bx and .78 for mpMRI, P < .01. For SVI prediction, AUC was .95 for mpMRI+Bx compared to .92 for mpMRI; P = .20. Inter-reader agreement for ECE and SVI prediction was substantial for mpMRI (k range, .78-.79) and mpMRI+Bx (k range, .74-.79). CONCLUSIONS MpMRI+Bx showed superior diagnostic performance with an increased sensitivity for ECE prediction but no significant difference for SVI prediction. Inter-reader agreement was substantial for both protocols. Integration of biopsy information adds value when staging prostate mpMRI.
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Affiliation(s)
- Iztok Caglic
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Radiology, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Faculty of Medicine, University of Ljubljana, Slovenia
| | - Nikita Sushentsev
- Department of Radiology, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Nimish Shah
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Urology, 573020Addenbrooke's Hospital, Cambridge, UK
| | - Anne Y Warren
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Pathology, 573020Addenbrooke's Hospital, Cambridge, UK
| | - Benjamin W Lamb
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Urology, 573020Addenbrooke's Hospital, Cambridge, UK
| | - Tristan Barrett
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Radiology, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
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Kurose H, Ueda K, Ogasawara N, Chikui K, Nakiri M, Nishihara K, Matsuo M, Suekane S, Kusano H, Akiba J, Yano H, Igawa T. Impact of Gleason score of the tumor at the positive surgical margin as a prognostic factor. Mol Clin Oncol 2022; 16:82. [PMID: 35251633 PMCID: PMC8892462 DOI: 10.3892/mco.2022.2515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 10/27/2021] [Indexed: 11/19/2022] Open
Abstract
Although numerous studies have reported that a positive surgical margin (PSM) is the most important predictive factor for biochemical recurrence (BCR) of prostate cancer (PCa), only a small number of studies have evaluated the predictive value of the Gleason score (GS) of the tumor at the margin in radical prostatectomy (RP). The present study aimed to investigate the preoperative factors that predict PSM and the significant predictive factors for BCR in cases with PSM. In addition, it was examined whether documenting the GS of the tumor at the margin in pathological reports is useful as a predictive factor for BCR. Data of 241 patients with PCa who underwent RP at Kurume University Hospital (Kurume, Japan) between January 2007 and December 2011 were retrospectively reviewed. The median follow-up period was 72 months and 122 patients had at least one PSM. The time to BCR was significantly shorter in patients with PSM than in those with a negative surgical margin. Multivariate analysis demonstrated that >10 ng/ml prostate-specific antigen at diagnosis (P=0.024) and >25% positive core at biopsy (P=0.041) were independent prognostic preoperative factors for PSM. The GS of the tumor at the margin was equal, lower and higher than those of the main tumor in 74 (60.7%), 16 (13.1%) and 32 (26.2%) RPs, respectively. The BCR rates were 35.7, 55.1 and 82.1% in patients whose GS of the tumor at the margin was 6, 7 and 8-10, respectively (P=0.0017). The GS of the tumor at the PSM (P=0.038) and anatomic location of the PSM (P=0.04) were identified as independent prognostic preoperative factors for BCR, whereas the GS of the main tumor and margin length were not. These results suggest that documenting the GS at the margin in pathological reports is useful as a predictive factor for BCR.
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Affiliation(s)
- Hirofumi Kurose
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Kosuke Ueda
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Naoyuki Ogasawara
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Katsuaki Chikui
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Makoto Nakiri
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Kiyoaki Nishihara
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Mitsunori Matsuo
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Shigetaka Suekane
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Hironori Kusano
- Department of Pathology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Jun Akiba
- Department of Pathology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Hirohisa Yano
- Department of Pathology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
| | - Tsukasa Igawa
- Department of Urology, Kurume University School of Medicine, Kurume, Fukuoka 830‑0011, Japan
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Li W, Shang W, Lu F, Sun Y, Tian J, Wu Y, Dong A. Diagnostic Performance of Extraprostatic Extension Grading System for Detection of Extraprostatic Extension in Prostate Cancer: A Diagnostic Systematic Review and Meta-Analysis. Front Oncol 2022; 11:792120. [PMID: 35145904 PMCID: PMC8824228 DOI: 10.3389/fonc.2021.792120] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
PURPOSE To evaluate the diagnostic performance of the extraprostatic extension (EPE) grading system for detection of EPE in patients with prostate cancer (PCa). MATERIALS AND METHODS We performed a literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar to identify eligible articles published before August 31, 2021, with no language restrictions applied. We included studies using the EPE grading system for the prediction of EPE, with histopathological results as the reference standard. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic odds ratio (DOR) were calculated with the bivariate model. Quality assessment of included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS A total of 4 studies with 1,294 patients were included in the current systematic review. The pooled sensitivity and specificity were 0.82 (95% CI 0.76-0.87) and 0.63 (95% CI 0.51-0.73), with the area under the hierarchical summary receiver operating characteristic (HSROC) curve of 0.82 (95% CI 0.79-0.85). The pooled LR+, LR-, and DOR were 2.20 (95% CI 1.70-2.86), 0.28 (95% CI 0.22-0.36), and 7.77 (95% CI 5.27-11.44), respectively. Quality assessment for included studies was high, and Deeks's funnel plot indicated that the possibility of publication bias was low (p = 0.64). CONCLUSION The EPE grading system demonstrated high sensitivity and moderate specificity, with a good inter-reader agreement. However, this scoring system needs more studies to be validated in clinical practice.
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Affiliation(s)
- Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Wenwen Shang
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Feng Lu
- Department of Radiology, Wuxi No. 2 People’s Hospital, Wuxi, China
| | - Yuan Sun
- Department of Burn and Plastic Surgery, 71st Group Army Hospital of People’s Liberation Army of China, Xuzhou, China
| | - Jun Tian
- Department of Basic Medicine, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Yiman Wu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Anding Dong
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
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Brinkley GJ, Fang AM, Rais-Bahrami S. Integration of magnetic resonance imaging into prostate cancer nomograms. Ther Adv Urol 2022; 14:17562872221096386. [PMID: 35586139 PMCID: PMC9109484 DOI: 10.1177/17562872221096386] [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: 12/28/2021] [Accepted: 04/05/2022] [Indexed: 11/16/2022] Open
Abstract
The decision whether to undergo prostate biopsy must be carefully weighed. Nomograms have widely been utilized as risk calculators to improve the identification of prostate cancer by weighing several clinical factors. The recent inclusion of multiparametric magnetic resonance imaging (mpMRI) findings into nomograms has drastically improved their nomogram's accuracy at identifying clinically significant prostate cancer. Several novel nomograms have incorporated mpMRI to aid in the decision-making process in proceeding with a prostate biopsy in patients who are biopsy-naïve, have a prior negative biopsy, or are on active surveillance. Furthermore, novel nomograms have incorporated mpMRI to aid in treatment planning of definitive therapy. This literature review highlights how the inclusion of mpMRI into prostate cancer nomograms has improved upon their performance, potentially reduce unnecessary procedures, and enhance the individual risk assessment by improving confidence in clinical decision-making by both patients and their care providers.
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Affiliation(s)
- Garrett J Brinkley
- Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Andrew M Fang
- Department of Urology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Soroush Rais-Bahrami
- Department of Urology, The University of Alabama at Birmingham, Faculty Office Tower 1107, 510 20th Street South, Birmingham, AL 35294, USA
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Zapała P, Fus Ł, Lewandowski Z, Garbas K, Zapała Ł, Górnicka B, Radziszewski P. E-Cadherin, Integrin Alpha2 (Cd49b), and Transferrin Receptor-1 (Tfr1) Are Promising Immunohistochemical Markers of Selected Adverse Pathological Features in Patients Treated with Radical Prostatectomy. J Clin Med 2021; 10:jcm10235587. [PMID: 34884287 PMCID: PMC8658679 DOI: 10.3390/jcm10235587] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 11/13/2021] [Accepted: 11/24/2021] [Indexed: 11/17/2022] Open
Abstract
In patients treated for prostate cancer (PCa) with radical prostatectomy (RP), determining the risk of extraprostatic extension (EPE) and nodal involvement (NI) remains crucial for planning nerve-sparing and extended lymphadenectomy. The study aimed to determine proteins that could serve as immunohistochemical markers of locally advanced PCa. To select candidate proteins associated with adverse pathologic features (APF) reverse-phase protein array data of 498 patients was retrieved from The Cancer Genome Atlas. The analysis yielded 6 proteins which were then validated as predictors of APF utilizing immunohistochemistry in a randomly selected retrospective cohort of 53 patients. For univariate and multivariate analysis, logistic regression was used. Positive expression of TfR1 (OR 13.74; p = 0.015), reduced expression of CD49b (OR 10.15; p = 0.013), and PSA (OR 1.29; p = 0.013) constituted independent predictors of EPE, whereas reduced expression of e-cadherin (OR 10.22; p = 0.005), reduced expression of CD49b (OR 24.44; p = 0.017), and PSA (OR 1.18; p = 0.002) were independently associated with NI. Both models achieved high discrimination (AUROC 0.879 and 0.888, respectively). Immunohistochemistry constitutes a straightforward tool that might be easily utilized before RP. Expression of TfR1 and CD49b is associated with EPE, whereas expression of e-cadherin and CD49b is associated with NI. Since following immunohistochemical markers predicts respective APFs independently from PSA, in the future they might supplement existing preoperative nomograms or be implemented in novel tools.
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Affiliation(s)
- Piotr Zapała
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, 02-091 Warsaw, Poland; (P.Z.); (K.G.); (Ł.Z.); (P.R.)
| | - Łukasz Fus
- Department of Pathology, Medical University of Warsaw, 02-091 Warsaw, Poland;
- Correspondence: ; Tel.: +48-22-57-20-710
| | - Zbigniew Lewandowski
- Department of Epidemiology and Biostatistics, Medical University of Warsaw, 02-091 Warsaw, Poland;
| | - Karolina Garbas
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, 02-091 Warsaw, Poland; (P.Z.); (K.G.); (Ł.Z.); (P.R.)
| | - Łukasz Zapała
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, 02-091 Warsaw, Poland; (P.Z.); (K.G.); (Ł.Z.); (P.R.)
| | - Barbara Górnicka
- Department of Pathology, Medical University of Warsaw, 02-091 Warsaw, Poland;
| | - Piotr Radziszewski
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, 02-091 Warsaw, Poland; (P.Z.); (K.G.); (Ł.Z.); (P.R.)
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Li W, Sun Y, Wu Y, Lu F, Xu H. The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis. Front Oncol 2021; 11:771864. [PMID: 34881183 PMCID: PMC8645791 DOI: 10.3389/fonc.2021.771864] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 10/28/2021] [Indexed: 11/13/2022] Open
Abstract
PURPOSE To investigate the diagnostic performance of using quantitative assessment with multiparametric MRI (mpMRI) for prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa). METHODS We performed a computerized search of MEDLINE, Embase, Cochrane Library, Web of Science, and Google Scholar from inception until July 31, 2021. Summary estimates of sensitivity and specificity were pooled with the bivariate model, and quality assessment of included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2. We plotted forest plots to graphically present the results. Multiple subgroup analyses and meta-regression were performed to explore the variate clinical settings and heterogeneity. RESULTS A total of 23 studies with 3,931 participants were included. The pooled sensitivity and specificity for length of capsular contact (LCC) were 0.79 (95% CI 0.75-0.83) and 0.77 (95% CI 0.73-0.80), for apparent diffusion coefficient (ADC) were 0.71 (95% CI 0.50-0.86) and 0.71 (95% CI 059-0.81), for tumor size were 0.62 (95% CI 0.57-0.67) and 0.75 (95% CI 0.67-0.82), and for tumor volume were 0.77 (95% CI 0.68-0.84) and 0.72 (95% CI 0.56-0.83), respectively. Substantial heterogeneity was presented among included studies, and meta-regression showed that publication year (≤2017 vs. >2017) was the significant factor in studies using LCC as the quantitative assessment (P=0.02). CONCLUSION Four quantitative assessments of LCC, ADC, tumor size, and tumor volume showed moderate to high diagnostic performance of predicting EPE. However, the optimal cutoff threshold varied widely among studies and needs further investigation to establish.
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Affiliation(s)
- Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Yuan Sun
- Department of Burn and Plastic Surgery, 71st Group Army Hospital of People’s Liberation Army of China, Xuzhou, China
| | - Yiman Wu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Feng Lu
- Department of Radiology, Wuxi No. 2 People’s Hospital, Wuxi, China
| | - Hongtao Xu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
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Vis AN, Bergh RCN, Poel HG, Mottrie A, Stricker PD, Graefen M, Patel V, Rocco B, Lissenberg‐Witte B, Leeuwen PJ. Selection of patients for nerve sparing surgery in robot‐assisted radical prostatectomy. BJUI COMPASS 2021; 3:6-18. [PMID: 35475150 PMCID: PMC8988739 DOI: 10.1002/bco2.115] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/13/2021] [Accepted: 09/18/2021] [Indexed: 11/09/2022] Open
Abstract
Context Robot‐assisted radical prostatectomy (RARP) has become the standard surgical procedure for localized prostate‐cancer (PCa). Nerve‐sparing surgery (NSS) during RARP has been associated with improved erectile function and continence rates after surgery. However, it remains unclear what are the most appropriate indications for NSS. Objective The objective of this study is to systematically review the available parameters for selection of patients for NSS. The weight of different clinical variables, multiparametric magnetic‐resonance‐imaging (mpMRI) findings, and the impact of multiparametric‐nomograms in the decision‐making process on (side‐specific) NSS were assessed. Evidence acquisition This systematic review searched relevant databases and included studies performed from January 2000 until December 2020 and recruited a total of 15 840 PCa patients. Studies were assessed that defined criteria for (side‐specific) NSS and associated them with oncological safety and/or functional outcomes. Risk of bias assessment was performed. Evidence synthesis Nineteen articles were eligible for full‐text review. NSS is primarily recommended in men with adequate erectile function, and with low‐risk of extracapsular extension (ECE) on the side‐of NSS. Separate clinical and radiological variables have low accuracy for predicting ECE, whereas nomograms optimize the risk‐stratification and decision‐making process to perform or to refrain from NSS when oncological safety (organ‐confined disease, PSM rates) and functional outcomes (erectile function and continence rates) were assessed. Conclusions Consensus exists that patients who are at high risk of ECE should refrain from NSS. Several multiparametric preoperative nomograms were developed to predict ECE with increased accuracy compared with single clinical, pathological, or radiological variables, but controversy exists on risk thresholds and decision rules on a conservative versus a less‐conservative surgical approach. An individual clinical judgment on the possibilities of NSS set against the risks of ECE is warranted. Patient summary NSS is aimed at sparing the nerves responsible for erection. NSS may lead to unfavorable tumor control if the risk of capsule penetration is high. Nomograms predicting extraprostatic tumor‐growth are probably most helpful.
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Affiliation(s)
- André N. Vis
- Department of Urology Amsterdam UMC, Location VUmc Amsterdam The Netherlands
- Prostate Cancer Network Netherlands
| | | | - Henk G. Poel
- Prostate Cancer Network Netherlands
- Department of Urology NKI/AVL Amsterdam The Netherlands
| | | | | | - Marcus Graefen
- Martini‐Klinik University Hospital Hamburg‐Eppendorf Hamburg Germany
| | - Vipul Patel
- Global Robotics Institute Florida Hospital Celebration Health Orlando Florida USA
| | - Bernardo Rocco
- Department of Urology University of Modena and Reggio Emilia Modena Italy
| | - Birgit Lissenberg‐Witte
- Department of Epidemiology and Data Science Amsterdam UMC, Location VUmc Amsterdam The Netherlands
| | - Pim J. Leeuwen
- Prostate Cancer Network Netherlands
- Department of Urology NKI/AVL Amsterdam The Netherlands
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Zapała P, Kozikowski M, Dybowski B, Zapała Ł, Dobruch J, Radziszewski P. External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer. Cent European J Urol 2021; 74:327-333. [PMID: 34729221 PMCID: PMC8552930 DOI: 10.5173/ceju.2021.0128.r2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 09/07/2021] [Accepted: 09/10/2021] [Indexed: 01/22/2023] Open
Abstract
Introduction Recently developed algorithm for prediction of side-specific extracapsular extension (ECE) of prostate cancer required validation before being recommended to use. The algorithm assumed that ECE on a particular side was not likely with same side maximum tumor diameter (MTD) <15 mm AND cancerous tissue in ipsilateral biopsy <15% AND PSA <20 ng/mL (both sides condition). The aim of the study was to validate this predictive tool in patients from another department. Material and methods Data of 154 consecutive patients (308 prostatic lateral lobes) were used for validation. Predictive factors chosen in the development set of patients were assessed together with other preoperative parameters using logistic regression to check for their significance. Sensitivity, specificity, negative and positive predictive values were calculated for bootstrapped risk-stratified validation dataset. Results Validation cohort did not differ significantly from development cohort regarding PSA, PSA density, Gleason score (GS), MTD, age, ECE and seminal vesicle invasion rate. In bootstrapped data set (n = 200 random sampling) algorithm revealed 70.2% sensitivity (95% confidence interval (CI) 58.8–83.0%), 49.9% specificity (95%CI: 42.0–57.7%), 83.9% negative predictive value (NPV; 95%CI: 76.1–91.4%) and 31.1% positive predictive value (PPV; 95%CI: 19.6–39.7%). When limiting analysis to high-risk patients (Gleason score >7) the algorithm improved its performance: sensitivity 91%, specificity 47%, PPV 53%, NPV 89%. Conclusions Analyzed algorithm is useful for identifying prostate lobes without ECE and deciding on ipsilateral nerve-sparing technique during radical prostatectomy, especially in patients with GS >7. Due to significant number of false positives in case of: MTD ≥15 mm OR cancer in biopsy ≥15% OR PSA ≥20 ng/mL additional evaluation is necessary to aid decision-making.
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Affiliation(s)
- Piotr Zapała
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, Poland
| | - Mieszko Kozikowski
- Department of Urology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Bartosz Dybowski
- Department of Urology, Roefler Memorial Hospital, Pruszków, Poland.,Faculty of Medicine, Lazarski University, Warsaw, Poland
| | - Łukasz Zapała
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, Poland
| | - Jakub Dobruch
- Department of Urology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Piotr Radziszewski
- Department of General, Oncological and Functional Urology, Medical University of Warsaw, Poland
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Semen as a rich source of diagnostic biomarkers for prostate cancer: latest evidence and implications. Mol Cell Biochem 2021; 477:213-223. [PMID: 34655417 DOI: 10.1007/s11010-021-04273-4] [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: 05/11/2021] [Accepted: 10/01/2021] [Indexed: 12/24/2022]
Abstract
Prostate cancer (PCa) is one of the most common cancers in men and the cause of numerous cancer deaths in the world. Nowadays, based on diagnostic criteria, prostate-specific antigen (PSA) evaluation and rectal examination are used to diagnose prostate-related malignancies. However, due to the different types of PCa, there are several doubts about the diagnostic value of PSA. On the other hand, semen is considered an appropriate source and contains various biomarkers in non-invasive diagnosing several autoimmune disorders and malignancies. Evidence suggests that analysis of semen biomarkers could be helpful in PCa diagnosis. Therefore, due to the invasiveness of most diagnostic methods in PCa, the use of semen as a biologic sample containing various biomarkers can lead to the emergence of novel and non-invasive diagnostic approaches. This review summarized recent studies on the use of various seminal biomarkers for diagnosis, prognosis and prediction of PCa.
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Prostate Magnetic Resonance Imaging Analyses, Clinical Parameters, and Preoperative Nomograms in the Prediction of Extraprostatic Extension. Clin Pract 2021; 11:763-774. [PMID: 34698089 PMCID: PMC8544353 DOI: 10.3390/clinpract11040091] [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: 07/25/2021] [Revised: 08/27/2021] [Accepted: 09/30/2021] [Indexed: 11/25/2022] Open
Abstract
Introduction: Proper planning of laparoscopic radical prostatectomy (RP) in patients with prostate cancer (PCa) is crucial to achieving good oncological results with the possibility of preserving potency and continence. Aim: The aim of this study was to identify the radiological and clinical parameters that can predict the risk of extraprostatic extension (EPE) for a specific site of the prostate. Predictive models and multiparametric magnetic resonance imaging (mpMRI) data from patients qualified for RP were compared. Material and methods: The study included 61 patients who underwent laparoscopic RP. mpMRI preceded transrectal systematic and cognitive fusion biopsy. Martini, Memorial Sloan-Kettering Cancer Center (MSKCC), and Partin Tables nomograms were used to assess the risk of EPE. The area under the curve (AUC) was calculated for the models and compared. Univariate and multivariate logistic regression analyses were used to determine the combination of variables that best predicted EPE risk based on final histopathology. Results: The combination of mpMRI indicating or suspecting EPE (odds ratio (OR) = 7.49 (2.31–24.27), p < 0.001) and PSA ≥ 20 ng/mL (OR = 12.06 (1.1–132.15), p = 0.04) best predicted the risk of EPE for a specific side of the prostate. For the prediction of ipsilateral EPE risk, the AUC for Martini’s nomogram vs. mpMRI was 0.73 (p < 0.001) vs. 0.63 (p = 0.005), respectively (p = 0.131). The assessment of a non-specific site of EPE by MSKCC vs. Partin Tables showed AUC values of 0.71 (p = 0.007) vs. 0.63 (p = 0.074), respectively (p = 0.211). Conclusions: The combined use of mpMRI, the results of the systematic and targeted biopsy, and prostate-specific antigen baseline can effectively predict ipsilateral EPE (pT3 stage).
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Li W, Dong A, Hong G, Shang W, Shen X. Diagnostic performance of ESUR scoring system for extraprostatic prostate cancer extension: A meta-analysis. Eur J Radiol 2021; 143:109896. [PMID: 34416449 DOI: 10.1016/j.ejrad.2021.109896] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 07/28/2021] [Accepted: 08/03/2021] [Indexed: 11/18/2022]
Abstract
PURPOSE We aimed to evaluate the diagnostic performance of the European Society of Urogenital Radiology (ESUR) scoring system for detection of extraprostatic extension (EPE) in prostate cancer (PCa) by performing a meta-analysis. MATERIALS AND METHODS A literature search of MEDLINE, EMBASE, Cochrane Library, Web of Science, and Google Scholar was performed to identify relevant studies from January 2012 to December 2020. We included diagnostic accuracy studies using ESUR scoring system for detection of EPE, and with prostatectomy histopathological results as the reference standard. Quality assessment was performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The summary estimates of sensitivity and specificity were pooled using bivariate random-effects modeling. We conducted multiple subgroup analyses and meta-regression to explore varied clinical settings. RESULTS 10 studies with a total of 1698 participants were included in this meta-analysis. Pooled sensitivity and specificity were 0.71 (95% CI 0.61-0.80) and 0.76 (95% CI 0.67-0.84), respectively, with the area under ROC of 0.80 (95% CI 0.77-0.84). The Higgins I2 statistics demonstrated substantial heterogeneity in both sensitivity (I2 = 86.5%) and specificity (I2 = 91.6%), meta-regression revealed that the cutoff values (ESUR score ≥ 3 vs. ESUR score ≥ 4, P = 0.02) and malignancy rate (<40% vs. ≥40%, P = 0.04) were significant factors responsible for heterogeneity. Using endorectal coil and higher field strength (3.0 T) showed no additional benefit for EPE detection. CONCLUSION The evidence available for ESUR scoring system tends to show moderate diagnostic performance for detection of EPE, and the cutoff values (P = 0.02) and malignancy rate (P = 0.04) were significant factors contributed to the heterogeneity.
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Affiliation(s)
- Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Anding Dong
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Guohui Hong
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China.
| | - Wenwen Shang
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Xiaocui Shen
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
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He D, Wang X, Fu C, Wei X, Bao J, Ji X, Bai H, Xia W, Gao X, Huang Y, Hou J. MRI-based radiomics models to assess prostate cancer, extracapsular extension and positive surgical margins. Cancer Imaging 2021; 21:46. [PMID: 34225808 PMCID: PMC8259026 DOI: 10.1186/s40644-021-00414-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/10/2021] [Indexed: 01/01/2023] Open
Abstract
Purpose To investigate the performance of magnetic resonance imaging (MRI)-based radiomics models for benign and malignant prostate lesion discrimination and extracapsular extension (ECE) and positive surgical margins (PSM) prediction. Methods and materials In total, 459 patients who underwent multiparametric MRI (mpMRI) before prostate biopsy were included. Radiomic features were extracted from both T2-weighted imaging (T2WI) and the apparent diffusion coefficient (ADC). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. Radiomics signatures were built using radiomic features on the training set, and integrated models were built by adding clinical characteristics. The areas under the receiver operating characteristic curves (AUCs) were calculated to assess the classification performance on the testing sets. Results The radiomics signatures for benign and malignant lesion discrimination achieved AUCs of 0.775 (T2WI), 0.863 (ADC) and 0.855 (ADC + T2WI). The corresponding integrated models improved the AUC to 0.851/0.912/0.905, respectively. The radiomics signatures for ECE achieved the highest AUC of 0.625 (ADC), and the corresponding integrated model achieved the highest AUC (0.728). The radiomics signatures for PSM prediction achieved AUCs of 0.614 (T2WI) and 0.733 (ADC). The corresponding integrated models reached AUCs of 0.680 and 0.766, respectively. Conclusions The MRI-based radiomics models, which took advantage of radiomic features on ADC and T2WI scans, showed good performance in discriminating benign and malignant prostate lesions and predicting ECE and PSM. Combining radiomics signatures and clinical factors enhanced the performance of the models, which may contribute to clinical diagnosis and treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s40644-021-00414-6.
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Affiliation(s)
- Dong He
- Department of Urology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China
| | - Ximing Wang
- Department of Radiology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China
| | - Chenchao Fu
- Department of Urology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China
| | - Xuedong Wei
- Department of Urology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China
| | - Jie Bao
- Department of Radiology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China
| | - Xuefu Ji
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No.88 Keling Road, Suzhou New District, 215163, Jiangsu, China.,The School of Electro-Optical Engineering, Changchun University of Science and Technology, 130013, Changchun, China
| | - Honglin Bai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No.88 Keling Road, Suzhou New District, 215163, Jiangsu, China
| | - Wei Xia
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No.88 Keling Road, Suzhou New District, 215163, Jiangsu, China
| | - Xin Gao
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No.88 Keling Road, Suzhou New District, 215163, Jiangsu, China
| | - Yuhua Huang
- Department of Urology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China.
| | - Jianquan Hou
- Department of Urology, The First Affiliated Hospital of SooChow University, No.188, Shizi St, Canglang District, 215006, Suzhou, Jiangsu, China. .,Department of Urology, Dushu Lake Hospital affiliated to SooChow University, No.9, Chongwen Road, Suzhou Industrial Park District, Suzhou, Jiangsu, 215000, China.
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Bai H, Xia W, Ji X, He D, Zhao X, Bao J, Zhou J, Wei X, Huang Y, Li Q, Gao X. Multiparametric Magnetic Resonance Imaging-Based Peritumoral Radiomics for Preoperative Prediction of the Presence of Extracapsular Extension With Prostate Cancer. J Magn Reson Imaging 2021; 54:1222-1230. [PMID: 33970517 DOI: 10.1002/jmri.27678] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 04/17/2021] [Accepted: 04/19/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Preoperative prediction of extracapsular extension (ECE) of prostate cancer (PCa) is important to guide clinical decision-making and improve patient prognosis. PURPOSE To investigate the value of multiparametric magnetic resonance imaging (mpMRI)-based peritumoral radiomics for preoperative prediction of the presence of ECE. STUDY TYPE Retrospective. POPULATION Two hundred eighty-four patients with PCa from two centers (center 1: 226 patients; center 2: 58 patients). Cases from center 1 were randomly divided into training (158 patients) and internal validation (68 patients) sets. Cases from center 2 were assigned to the external validation set. FIELD STRENGTH/SEQUENCE A 3.0 T MRI scanners (three vendors). Sequence: Pelvic T2-weighted turbo/fast spin echo sequence and diffusion weighted echo planar imaging sequence. ASSESSMENT The peritumoral region (PTR) was obtained by 3-12 mm (half of the tumor length) 3D dilatation of the intratumoral region (ITR). Single-MRI radiomics signatures, mpMRI radiomics signatures, and integrated models, which combined clinical characteristics with the radiomics signatures were built. The discrimination ability was assessed by area under the receiver operating characteristic curve (AUC) in the internal and external validation sets. STATISTICAL TESTS Fisher's exact test, Mann-Whitney U-test, DeLong test. RESULTS The PTR radiomics signatures demonstrated significantly better performance than the corresponding ITR radiomics signatures (AUC: 0.674 vs. 0.554, P < 0.05 on T2-weighted, 0.652 vs. 0.546, P < 0.05 on apparent diffusion coefficient, 0.682 vs. 0.556 on mpMRI in the external validation set). The integrated models combining the PTR radiomics signature with clinical characteristics performed better than corresponding radiomics signatures in the internal validation set (eg. AUC: 0.718 vs. 0.671, P < 0.05 on mpMRI) but performed similar in the external validation set (eg. AUC: 0.684, vs. 0.682, P = 0.45 on mpMRI). DATA CONCLUSION The peritumoral radiomics can better predict the presence of ECE preoperatively compared with the intratumoral radiomics and may have better generalization than clinical characteristics. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: 2.
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Affiliation(s)
- Honglin Bai
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, China.,Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Wei Xia
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Xuefu Ji
- The School of Electro-Optical Engineering, Changchun University of Science and Technology, Changchun, 130013, China
| | - Dong He
- Department of Urology, The First Affiliated Hospital of SooChow University, Suzhou, 215006, China
| | - Xingyu Zhao
- School of Biomedical Engineering (Suzhou), Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230026, China.,Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Jie Bao
- Department of Radiology, The First Affiliated Hospital of SooChow University, Suzhou, 215006, China
| | - Jian Zhou
- Department of Radiology, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Xuedong Wei
- Department of Urology, The First Affiliated Hospital of SooChow University, Suzhou, 215006, China
| | - Yuhua Huang
- Department of Urology, The First Affiliated Hospital of SooChow University, Suzhou, 215006, China
| | - Qiong Li
- Department of Radiology, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Xin Gao
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.,Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Medical University, Taiyuan, 030013, China
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Xu L, Zhang G, Zhang X, Bai X, Yan W, Xiao Y, Sun H, Jin Z. External Validation of the Extraprostatic Extension Grade on MRI and Its Incremental Value to Clinical Models for Assessing Extraprostatic Cancer. Front Oncol 2021; 11:655093. [PMID: 33869062 PMCID: PMC8047629 DOI: 10.3389/fonc.2021.655093] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 03/17/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives To externally validate the extraprostatic extension (EPE) grade criteria on MRI and analyze the incremental value of EPE grade to clinical models of prostate cancer. Methods A consecutive 130 patients who underwent preoperative prostate MRI followed by radical prostatectomy between January 2015 to January 2020 in our institution were retrospectively enrolled. The EPE grade, Cancer of the Prostate Risk Assessment (CAPRA), and Memorial Sloan Kettering Cancer Center nomogram (MSKCCn) score for each patient were assigned. Significant clinicopathological factors in univariate and multivariate analyses were combined with EPE grade to build the Clinical + EPE grade model, and the CAPRA and MSKCCn score were also combined with EPE grade to build the CAPRA + EPE grade and MSKCCn + EPE grade model, respectively. The area under the curve (AUC), sensitivity and specificity of these models were calculated to evaluate their diagnostic performance. Calibration and decision curve analyses were used to analyze their calibration performance and clinical utility. Results The AUC for predicting EPE was 0.767–0.778 for EPE grade, 0.704 for CAPRA, and 0.723 for MSKCCn. After combination with EPE grade, the AUCs of these clinical models increased significantly than using clinical models along (P < 0.05), but was comparable with using EPE grade alone (P > 0.05). The calibration curves of EPE grade, clinical models and combined models showed that these models are well-calibrated for EPE. In the decision curve analysis, EPE grade showed slightly higher net benefit than MSKCCn and CAPRA. Conclusion The EPE grade showed good performance for evaluating EPE in our cohort and possessed well clinical utility. Further combinations with the EPE grade could improve the diagnostic performance of clinical models.
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Affiliation(s)
- Lili Xu
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Gumuyang Zhang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoxiao Zhang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xin Bai
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Weigang Yan
- Department of Urology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yu Xiao
- Department of Pathology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Hao Sun
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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Ravi C, Sanjeevan KV, Thomas A, Pooleri GK. Development of an Indian nomogram for predicting extracapsular extension in prostate cancer. INDIAN JOURNAL OF UROLOGY : IJU : JOURNAL OF THE UROLOGICAL SOCIETY OF INDIA 2021; 37:65-71. [PMID: 33850358 PMCID: PMC8033245 DOI: 10.4103/iju.iju_200_20] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 08/01/2020] [Accepted: 08/23/2020] [Indexed: 11/04/2022]
Abstract
Introduction The aim of our study was to develop a new Indian nomogram to estimate pathologic extracapsular extension (ECE) risk in prostate cancer, by including PI-RADS v1-based magnetic resonance imaging (MRI) ECE risk score to the clinical variables used in the Partin nomogram (PN). Materials and Methods We analyzed 273 patients who underwent MRI of prostate and radical prostatectomy (RP). Univariate and multivariate logistic regression analyses were performed to identify predictors of ECE. We calculated the area under the receiver operating characteristic curve (AUC) for three variables used in PN and MRI ECE risk score, and a new nomogram was designed using binary logistic regression. Calibration curves assessed the agreement between the actual ECE risk and the predicted probability of the new nomogram. Results Out of 273 patients, 123 patients (45.1) had ECE on MRI, whereas 136 patients (49.8) had ECE on final pathology. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI for predicting ECE were 76.6, 66.9, 70.0, 73.9, and 71.7 (confidence interval 95), respectively. Multivariate logistic regression analyses showed that clinical T-stage (cT), Gleason score (GS), and MRI ECE risk score remained significant. The highest and the lowest values of the AUC for single variables were 0.748 (MRI ECE risk score) and 0.636 (cT stage), respectively, and AUC for PN was 0.67. New nomogram designed using R statistical package has higher predictive accuracy (0.826) compared to PN (0.67) and good calibration. Conclusions MRI adds incremental value to PN. A new Indian nomogram can help in the decision-making process of nerve-sparing RP. This nomogram should be used with caution as validation is pending and will require further studies.
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Affiliation(s)
- Chandran Ravi
- Department of Urology, Amrita Institute of Medical Sciences, Kochi, Kerala, India
| | | | - Appu Thomas
- Department of Urology, Amrita Institute of Medical Sciences, Kochi, Kerala, India
| | - Ginil Kumar Pooleri
- Department of Urology, Amrita Institute of Medical Sciences, Kochi, Kerala, India
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Huebner NA, Shariat SF. Clinical Impact and Statistical Significance of Multiparametric Magnetic Resonance Imaging for Local Staging of Prostate Cancer. Eur Urol 2020; 79:186-187. [PMID: 33246667 DOI: 10.1016/j.eururo.2020.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 11/03/2020] [Indexed: 11/24/2022]
Affiliation(s)
- Nicolai A Huebner
- Department of Urology, Medical University of Vienna, Vienna, Austria; Working Group for Diagnostic imaging in Urology, Austrian Association of Urology, Vienna, Austria
| | - Shahrokh F Shariat
- Department of Urology, Medical University of Vienna, Vienna, Austria; Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria; Division of Urology, Department of Urology, University of Jordan, Aman, Jordan; Institute of Urology and Reproductive Health, Sechenov University, Moscow, Russia; Department of Urology, Weill Cornell Medical Centre, New York, NY, USA; Department of Urology, University of Texas Southwestern, Dallas, TX, USA.
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Losnegård A, Reisæter LAR, Halvorsen OJ, Jurek J, Assmus J, Arnes JB, Honoré A, Monssen JA, Andersen E, Haldorsen IS, Lundervold A, Beisland C. Magnetic resonance radiomics for prediction of extraprostatic extension in non-favorable intermediate- and high-risk prostate cancer patients. Acta Radiol 2020; 61:1570-1579. [PMID: 32108505 DOI: 10.1177/0284185120905066] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND To investigate whether magnetic resonance (MR) radiomic features combined with machine learning may aid in predicting extraprostatic extension (EPE) in high- and non-favorable intermediate-risk patients with prostate cancer. PURPOSE To investigate the diagnostic performance of radiomics to detect EPE. MATERIAL AND METHODS MR radiomic features were extracted from 228 patients, of whom 86 were diagnosed with EPE, using prostate and lesion segmentations. Prediction models were built using Random Forest. Further, EPE was also predicted using a clinical nomogram and routine radiological interpretation and diagnostic performance was assessed for individual and combined models. RESULTS The MR radiomic model with features extracted from the manually delineated lesions performed best among the radiomic models with an area under the curve (AUC) of 0.74. Radiology interpretation yielded an AUC of 0.75 and the clinical nomogram (MSKCC) an AUC of 0.67. A combination of the three prediction models gave the highest AUC of 0.79. CONCLUSION Radiomic analysis combined with radiology interpretation aid the MSKCC nomogram in predicting EPE in high- and non-favorable intermediate-risk patients.
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Affiliation(s)
- Are Losnegård
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Norway
| | - Lars A. R. Reisæter
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Norway
| | - Ole J. Halvorsen
- Department of Pathology, Haukeland University Hospital, Bergen, Norway
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen, Norway
| | - Jakub Jurek
- Institute of Electronics, Technical University of Lodz, Poland
| | - Jörg Assmus
- Centre for Clinical Research, Haukeland University Hospital, Norway
| | - Jarle B. Arnes
- Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Alfred Honoré
- Department of Urology, Haukeland University Hospital, Bergen, Norway
| | - Jan A. Monssen
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Erling Andersen
- Department of Clinical Engineering, Haukeland University Hospital, Norway
| | - Ingfrid S. Haldorsen
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Norway
| | - Arvid Lundervold
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Biomedicine, University of Bergen, Norway
| | - Christian Beisland
- Department of Clinical Medicine, University of Bergen, Norway
- Department of Urology, Haukeland University Hospital, Bergen, Norway
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Soeterik TFW, van Melick HHE, Dijksman LM, Küsters-Vandevelde H, Stomps S, Schoots IG, Biesma DH, Witjes JA, van Basten JPA. Development and External Validation of a Novel Nomogram to Predict Side-specific Extraprostatic Extension in Patients with Prostate Cancer Undergoing Radical Prostatectomy. Eur Urol Oncol 2020; 5:328-337. [PMID: 32972895 DOI: 10.1016/j.euo.2020.08.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 08/04/2020] [Accepted: 08/18/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Prediction of side-specific extraprostatic extension (EPE) is crucial in selecting patients for nerve-sparing radical prostatectomy (RP). OBJECTIVE To develop and externally validate nomograms including multiparametric magnetic resonance imaging (mpMRI) information to predict side-specific EPE. DESIGN, SETTING, AND PARTICIPANTS A retrospective analysis of 1870 consecutive prostate cancer patients who underwent robot-assisted RP from 2014 to 2018 at three institutions. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Four multivariable logistic regression models were established, including combinations of patient-based and side-specific variables: prostate-specific antigen (PSA) density, highest ipsilateral International Society of Urological Pathology (ISUP) biopsy grade, ipsilateral percentage of positive cores on systematic biopsy, and side-specific clinical stage assessed by both digital rectal examination and mpMRI. Discrimination (area under the curve [AUC]), calibration, and net benefit of these models were assessed in the development cohort and two external validation cohorts. RESULTS AND LIMITATIONS On external validation, AUCs of the four models ranged from 0.80 (95% confidence interval [CI] 0.68-0.88) to 0.83 (95% CI 0.72-0.90) in cohort 1 and from 0.77 (95% CI 0.62-0.87) to 0.78 (95% CI 0.64-0.88) in cohort 2. The three models including mpMRI staging information resulted in relatively higher AUCs compared with the model without mpMRI information. No major differences between the four models regarding net benefit were established. The model based on PSA density, ISUP grade, and mpMRI T stage was superior in terms of calibration. Using this model with a cut-off of 20%, 1980/2908 (68%) prostatic lobes without EPE would be found eligible for nerve sparing, whereas non-nerve sparing would be advised in 642/832 (77%) lobes with EPE. CONCLUSIONS Our analysis resulted in a simple and robust nomogram for the prediction of side-specific EPE, which should be used to select patients for nerve-sparing RP. PATIENT SUMMARY We developed a prediction model that can be used to assess accurately the likelihood of tumour extension outside the prostate. This tool can guide patient selection for safe nerve-sparing surgery.
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Affiliation(s)
- Timo F W Soeterik
- Department of Value-Based Healthcare, Santeon Group, Utrecht, The Netherlands; Department of Urology, St. Antonius Hospital, Nieuwegein/Utrecht, Netherlands.
| | - Harm H E van Melick
- Department of Urology, St. Antonius Hospital, Nieuwegein/Utrecht, Netherlands
| | - Lea M Dijksman
- Department of Value-Based Healthcare, St. Antonius Hospital, Nieuwegein/Utrecht, The Netherlands
| | | | - Saskia Stomps
- Department of Urology, Hospital Group Twente, Hengelo/Almelo, The Netherlands
| | - Ivo G Schoots
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Douwe H Biesma
- Department of Value-Based Healthcare, Santeon Group, Utrecht, The Netherlands
| | - J A Witjes
- Department of Urology, Radboud University Medical centre, Nijmegen, The Netherlands
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Woo S, Ghafoor S, Becker AS, Han S, Wibmer AG, Hricak H, Burger IA, Schöder H, Vargas HA. Prostate-specific membrane antigen positron emission tomography (PSMA-PET) for local staging of prostate cancer: a systematic review and meta-analysis. Eur J Hybrid Imaging 2020; 4:16. [PMID: 34191215 PMCID: PMC8218057 DOI: 10.1186/s41824-020-00085-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 08/05/2020] [Indexed: 12/21/2022] Open
Abstract
Purpose Prostate-specific membrane antigen positron emission tomography (PSMA-PET) has shown promise for detecting nodal and distant prostate cancer (PCa) metastases. However, its performance for local tumor staging is not as well established. The purpose of this study was to review the diagnostic performance of PSMA-PET for determining seminal vesical invasion (SVI) and extraprostatic extension (EPE). Methods Pubmed and Embase databases were searched until January 12, 2020. Studies assessing accuracy of PSMA-PET in determining SVI and EPE were included. Study quality was evaluated with the revised Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity and specificity were calculated using hierarchical summary receiver operating characteristics modeling. Heterogeneity was explored using meta-regression analyses for anatomical imaging component (MRI vs CT) and by testing for a threshold effect. Results Twelve studies (615 patients) were included. Pooled sensitivity and specificity were 0.68 (95% CI 0.53-0.81) and 0.94 (95% CI 0.90-0.96) for SVI and 0.72 (95% CI 0.56-0.84) and 0.87 (95% CI 0.72-0.94) for EPE. Meta-regression analyses showed that for SVI, PET/MRI demonstrated greater sensitivity than PET/CT (0.87 [95% CI 0.75-0.98] vs 0.60 [95% CI 0.47-0.74]; p = 0.02 for joint model) while specificity was comparable (0.91 [95% CI 0.84-0.97] vs. 0.96 [95% CI 0.93-0.99]) but not for EPE (p = 0.08). A threshold effect was present for studies assessing EPE (correlation coefficient = 0.563 [95% CI, −0.234-0.908] between sensitivity and false-positive rate). Conclusion PSMA-PET has moderate sensitivity and excellent specificity for assessing local tumor extent in patients with PCa. PET/MRI showed potential for greater sensitivity than PET/CT in assessing SVI.
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Affiliation(s)
- Sungmin Woo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
| | - Soleen Ghafoor
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Anton S Becker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Sangwon Han
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Andreas G Wibmer
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Hedvig Hricak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Irene A Burger
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland.,Department of Nuclear Medicine, Kantonsspital Baden, Baden, Switzerland
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | - Hebert Alberto Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
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Mohler JL, Antonarakis ES, Armstrong AJ, D'Amico AV, Davis BJ, Dorff T, Eastham JA, Enke CA, Farrington TA, Higano CS, Horwitz EM, Hurwitz M, Ippolito JE, Kane CJ, Kuettel MR, Lang JM, McKenney J, Netto G, Penson DF, Plimack ER, Pow-Sang JM, Pugh TJ, Richey S, Roach M, Rosenfeld S, Schaeffer E, Shabsigh A, Small EJ, Spratt DE, Srinivas S, Tward J, Shead DA, Freedman-Cass DA. Prostate Cancer, Version 2.2019, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw 2020; 17:479-505. [PMID: 31085757 DOI: 10.6004/jnccn.2019.0023] [Citation(s) in RCA: 905] [Impact Index Per Article: 181.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The NCCN Guidelines for Prostate Cancer include recommendations regarding diagnosis, risk stratification and workup, treatment options for localized disease, and management of recurrent and advanced disease for clinicians who treat patients with prostate cancer. The portions of the guidelines included herein focus on the roles of germline and somatic genetic testing, risk stratification with nomograms and tumor multigene molecular testing, androgen deprivation therapy, secondary hormonal therapy, chemotherapy, and immunotherapy in patients with prostate cancer.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Joseph E Ippolito
- Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine
| | | | | | | | - Jesse McKenney
- Case Comprehensive Cancer Center/University Hospitals Seidman Cancer Center and Cleveland Clinic Taussig Cancer Institute
| | - George Netto
- University of Alabama at Birmingham Comprehensive Cancer Center
| | | | | | | | | | - Sylvia Richey
- St. Jude Children's Research Hospital/The University of Tennessee Health Science Center
| | - Mack Roach
- UCSF Helen Diller Family Comprehensive Cancer Center
| | | | - Edward Schaeffer
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University
| | - Ahmad Shabsigh
- The Ohio State University Comprehensive Cancer Center - James Cancer Hospital and Solove Research Institute
| | - Eric J Small
- UCSF Helen Diller Family Comprehensive Cancer Center
| | | | | | - Jonathan Tward
- Huntsman Cancer Institute at the University of Utah; and
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Rho MJ, Park J, Moon HW, Lee C, Nam S, Kim D, Kim CS, Jeon SS, Kang M, Lee JY. Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service. PLoS One 2020; 15:e0236553. [PMID: 32756597 PMCID: PMC7406030 DOI: 10.1371/journal.pone.0236553] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 07/08/2020] [Indexed: 11/25/2022] Open
Abstract
Objectives The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, we proposed a “Dr. Answer” AI software based on the clinical outcome prediction model for prostate cancer treated with radical prostatectomy. Methods The Dr. Answer AI was developed based on a clinical outcome prediction model, with a user-friendly interface. We used 7,128 clinical data of prostate cancer treated with radical prostatectomy from three hospitals. An outcome prediction model was developed to calculate the probability of occurrence of 1) tumor, node, and metastasis (TNM) staging, 2) extracapsular extension, 3) seminal vesicle invasion, and 4) lymph node metastasis. Random forest and k-nearest neighbors algorithms were used, and the proposed system was compared with previous algorithms. Results Random forest exhibited good performance for TNM staging (recall value: 76.98%), while k-nearest neighbors exhibited good performance for extracapsular extension, seminal vesicle invasion, and lymph node metastasis (80.24%, 98.67%, and 95.45%, respectively). The Dr. Answer AI software consisted of three primary service structures: 1) patient information, 2) clinical outcome prediction, and outcomes according to the National Comprehensive Cancer Network guideline. Conclusion The proposed clinical outcome prediction model could function as an effective CDSS, supporting the decisions of the physicians, while enabling the patients to understand their treatment outcomes. The Dr. Answer AI software for prostate cancer helps the doctors to explain the treatment outcomes to the patients, allowing the patients to be more confident about their treatment plans.
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Affiliation(s)
- Mi Jung Rho
- Catholic Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jihwan Park
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Department of Urology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyong Woo Moon
- Department of Urology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | | | - Sejin Nam
- LifeSemantics, Seoul, Republic of Korea
| | | | - Choung-Soo Kim
- Department of Urology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Seong Soo Jeon
- Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Minyong Kang
- Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Ji Youl Lee
- Department of Urology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- * E-mail:
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Wang B, Gao J, Zhang Q, Fu Y, Liu G, Zhang C, Wei W, Huang H, Shi J, Li D, Guo H. Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy. Oncol Lett 2020; 20:2797-2805. [PMID: 32782597 PMCID: PMC7400272 DOI: 10.3892/ol.2020.11861] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 04/16/2020] [Indexed: 01/23/2023] Open
Abstract
The aim of the present study was to develop a novel nomogram that incorporated clinical factors, imaging parameters and biopsy pathological factors (including cribriform morphology) to predict adverse pathology in prostate cancer (PCa). A total of 223 patients with PCa, who had undergone preoperative multi-parametric magnetic resonance imaging and had a biopsy of Gleason pattern (GP) 4, absence of GP 5 and pure Grade Group (GG) 3 [Gleason score (GS) 3+4, GS 4+3, GS 4+4], were retrospectively enrolled onto the study. The contribution of GG to the biopsy and Prostate Imaging Reporting and Data System (PI-RADS) score for PCa harboring adverse pathology were analyzed. Univariate and multivariate logistic regression analyses were performed to determine significant pathology predictors of adverse pathology for nomogram development. The nomogram was internally validated using bootstrapping with 1,000 iterations. The diagnostic performance of the nomogram was analyzed by receiver operating characteristics (ROC) analysis and decision curve analysis (DCA). A higher biopsy GG and PI-RADS score were associated with an increased likelihood of adverse pathology. Prostate specific antigen density (PSAD), biopsy GG, cribriform morphology on biopsy and PI-RADS score were significant predictors and were included in the nomogram. The ROC area under the curve of the nomogram was 0.88 (95% confidence interval, 0.84-0.91), with a high specificity (0.91) and moderate sensitivity (0.72). The novel nomogram was shown to have a higher net benefit for the prediction of adverse pathology in PCa, compared with any individual factors determined by DCA. Overall, a novel nomogram incorporating PSAD, PI-RADS score, biopsy GG and cribriform morphology on biopsy was shown to perform well in the prediction of PCa harboring adverse pathology at the time of radical prostatectomy.
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Affiliation(s)
- Baojun Wang
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Jie Gao
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Qing Zhang
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Yao Fu
- Department of Pathology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Guangxiang Liu
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Chengwei Zhang
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Wang Wei
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Haifeng Huang
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Jiong Shi
- Department of Pathology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Danyan Li
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
| | - Hongqian Guo
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu 210008, P.R. China
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