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Garcia-Becerra CA, Arias-Gallardo MI, Soltero-Molinar V, Juarez-Garcia JE, Rivera-Rocha MI, Parra-Camaño LF, Garcia-Becerra N, Garcia-Gutierrez CM. Is biparametric MRI a feasible option for detecting clinically significant prostate cancer?: A systematic review and meta-analysis. Urol Oncol 2025; 43:396.e9-396.e17. [PMID: 39753482 DOI: 10.1016/j.urolonc.2024.12.262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2024] [Revised: 09/09/2024] [Accepted: 12/10/2024] [Indexed: 05/19/2025]
Abstract
BACKGROUND Multiparametric MRI (Mp-MRI) is a key tool to screen for Prostate Cancer (Pca) and Clinically Significant Prostate Cancer (CsPca). It primarily includes T2-Weighted imaging (T2w), diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced imaging (DCE). Despite its improvements in CsPca screening, concerns about the cost-effectiveness of DCE persist due to its associated side effects, increased cost, longer acquisition time, and limitations in patients with poor kidney function. Recent studies have explored Biparametric MRI (Bp-MRI) as an alternative that excludes DCE. OBJECTIVES The main objective of this study is to compile and evaluate updated results of Bp-MRI as a diagnostic alternative to detect CsPca. METHODS A systematic review was conducted using PubMed, Central Cochrane, and ClinicalTrialls.gov registry. Inclusion criteria was focused on observational and experimental studies that assessed a direct comparison of Bp-MRI and Mp-MRI for CsPca detection. The primary outcomes included were necessary to create a contingency 2×2 table and CsPca prevalence from each study. The secondary outcomes included were demographic data and imaging protocol features. The statistical analysis used a Bivariate Random-Effect model to estimate the pooled sensitivity, specificity, and area under the curve (AUC). An univariate random-effect model was conducted to estimate the positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies -2 tool. RESULTS From 534 articles initially identified, 19 studies met the inclusion criteria with a total of 5075 patients. The pooled sensitivity estimated was 0.89, pooled specificity was 0.73, and AUC was 0.90; these results showed a slight increase compared to previous studies. CONCLUSION The results obtained showed that Bp-MRI is a feasible alternative to detect CsPca, which demonstrates high diagnostic accuracy and avoids the drawbacks associated with DCE. REGISTRY This is a sub-analysis of the protocol registered at PROSPERO (CRD42024552125).
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Affiliation(s)
| | | | - Veronica Soltero-Molinar
- Basic Science Institute, School of Medicine, Autonomous University of Guadalajara, Guadalajara, México
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Gündoğdu H, Panç K, Sekmen S, Er H, Gürün E. Enhancing bone metastasis prediction in prostate cancer using quantitative mpMRI features, ISUP grade and PSA density: a machine learning approach. Abdom Radiol (NY) 2025; 50:2221-2231. [PMID: 39542946 DOI: 10.1007/s00261-024-04667-0] [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: 10/13/2024] [Revised: 10/27/2024] [Accepted: 10/28/2024] [Indexed: 11/17/2024]
Abstract
PURPOSE Bone metastasis is a critical complication in prostate cancer, significantly impacting patient prognosis and quality of life. This study aims to enhance bone metastasis prediction using machine learning (ML) techniques by integrating dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion features, International Society of Urological Pathology (ISUP) grade, and prostate-specific antigen (PSA) density. MATERIALS AND METHODS A retrospective analysis was conducted on 122 patients with histopathologically confirmed prostate cancer who underwent multiparametric prostate magnetic resonance imaging (mpMRI). Quantitative mpMRI features, PSA density, and ISUP grades were extracted and normalized. The dataset was balanced using oversampling and divided into training (70%) and test (30%) sets. Various ML models were developed and evaluated using area under the curve (AUC) metrics. RESULTS Bone metastases were present in 26 patients (21.3%) at diagnosis. IAUGC and MaxSlope showed a statistically significant association with bone metastasis (p = 0.035, p = 0.050 respectively). The optimal PSA density cut-off value of 0.24 yielded a sensitivity of 0.88, specificity of 0.60, and AUC of 0.77. Machine learning models were developed using the dataset created with IAUGC, MaxSlope, ISUP grade, and PSA density values. Among the ML models, XGBoost demonstrated superior performance with validation and test AUCs of 91.5% and 92.6%, respectively, along with high precision (93.3%) and recall (93.1%). CONCLUSION Integrating quantitative mpMRI features, ISUP grade, and PSA density through machine learning algorithms, particularly XGBoost, significantly improves the accuracy of bone metastasis prediction in prostate cancer patients. This approach can potentially reduce the need for additional imaging modalities and associated radiation exposure.
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Affiliation(s)
| | - Kemal Panç
- Karakoçan State Hospital, Elazig, Turkey
| | | | - Hüseyin Er
- Recep Tayyip Erdoğan University, Rize, Turkey
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Dhiman A, Kumar V, Das CJ. Quantitative magnetic resonance imaging in prostate cancer: A review of current technology. World J Radiol 2024; 16:497-511. [PMID: 39494137 PMCID: PMC11525833 DOI: 10.4329/wjr.v16.i10.497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 09/26/2024] [Accepted: 10/20/2024] [Indexed: 10/28/2024] Open
Abstract
Prostate cancer (PCa) imaging forms an important part of PCa clinical management. Magnetic resonance imaging is the modality of choice for prostate imaging. Most of the current imaging assessment is qualitative i.e., based on visual inspection and thus subjected to inter-observer disagreement. Quantitative imaging is better than qualitative assessment as it is more objective, and standardized, thus improving interobserver agreement. Apart from detecting PCa, few quantitative parameters may have potential to predict disease aggressiveness, and thus can be used for prognosis and deciding the course of management. There are various magnetic resonance imaging-based quantitative parameters and few of them are already part of PIRADS v.2.1. However, there are many other parameters that are under study and need further validation by rigorous multicenter studies before recommending them for routine clinical practice. This review intends to discuss the existing quantitative methods, recent developments, and novel techniques in detail.
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Affiliation(s)
- Ankita Dhiman
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India
| | - Virendra Kumar
- Department of NMR & MRI Facility, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India
| | - Chandan Jyoti Das
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India
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Klaassen L, Jaarsma-Coes MG, Marinkovic M, Luyten GPM, Rasch CRN, Ferreira TA, Beenakker JWM. Quantitative Perfusion-Weighted Magnetic Resonance Imaging in Uveal Melanoma. Invest Ophthalmol Vis Sci 2024; 65:17. [PMID: 39250118 PMCID: PMC11385876 DOI: 10.1167/iovs.65.11.17] [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: 09/10/2024] Open
Abstract
Purpose Perfusion-weighted imaging (PWI; magnetic resonance imaging [MRI]) has been shown to provide valuable biological tumor information in uveal melanoma (UM). Clinically used semiquantitative methods do not account for tumor pigmentation and eye movement. We hypothesize that a quantitative PWI method that incorporates these, provides a more accurate description of tumor perfusion than the current clinical method. The aim of this study was to test this in patients with UM before and after radiotherapy. Methods Perfusion-weighted 3T MRIs were retrospectively analyzed in 47 patients with UM before and after radiotherapy. Tofts pharmacokinetic modeling was performed to determine vascular permeability (Ktrans), extracellular extravascular space (ve), and reflux rate (kep). These were compared with semiquantitative clinical parameters including peak intensity and outflow percentage. Results The effect of tumor pigmentation on peak intensity and outflow percentage was statistically significant (P < 0.01) and relative peak intensity was significantly different between melanotic and amelanotic tumors (1.5 vs. 1.9, P < 0.01). Before radiotherapy, median tumor Ktrans was 0.63 min-1 (range = 0.06-1.42 min-1), median ve was 0.23 (range = 0.09-0.63), and median kep was 2.3 min-1 (range = 0.6-5.0 min-1). After radiotherapy, 85% showed a decrease in Ktrans and kep (P < 0.01). Changes in tumor pigmentation before and after radiotherapy were small and not significant (median increase in T1 of 33 ms, P = 0.55). Conclusions Quantitative PWI parameters decreased significantly after radiotherapy and can therefore can serve as an early biomarker for treatment response assessment. However, due to the nonsignificant changes in tumor pigmentation before and after radiotherapy, the current semiquantitative method appears to be sufficiently sensitive for detection of changes in tumor perfusion.
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Affiliation(s)
- Lisa Klaassen
- Leiden University Medical Center, Department of Ophthalmology, Leiden, The Netherlands
- Leiden University Medical Center, Department of Radiology, Leiden, The Netherlands
- Leiden University Medical Center, Department of Radiation Oncology, Leiden, The Netherlands
| | - Myriam G Jaarsma-Coes
- Leiden University Medical Center, Department of Ophthalmology, Leiden, The Netherlands
- Leiden University Medical Center, Department of Radiology, Leiden, The Netherlands
| | - Marina Marinkovic
- Leiden University Medical Center, Department of Ophthalmology, Leiden, The Netherlands
| | - Gregorius P M Luyten
- Leiden University Medical Center, Department of Ophthalmology, Leiden, The Netherlands
| | - Coen R N Rasch
- Leiden University Medical Center, Department of Radiation Oncology, Leiden, The Netherlands
- HollandPTC, Delft, The Netherlands
| | - Teresa A Ferreira
- Leiden University Medical Center, Department of Radiology, Leiden, The Netherlands
| | - Jan-Willem M Beenakker
- Leiden University Medical Center, Department of Ophthalmology, Leiden, The Netherlands
- Leiden University Medical Center, Department of Radiology, Leiden, The Netherlands
- Leiden University Medical Center, Department of Radiation Oncology, Leiden, The Netherlands
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Chen R, Zhou B, Liu W, Gan H, Liu X, Zhou L. Association of Pathological Features and Multiparametric MRI-Based Radiomics With TP53-Mutated Prostate Cancer. J Magn Reson Imaging 2024; 60:1134-1145. [PMID: 38153859 DOI: 10.1002/jmri.29186] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 11/30/2023] [Accepted: 12/02/2023] [Indexed: 12/30/2023] Open
Abstract
BACKGROUND TP53 mutations are associated with prostate cancer (PCa) prognosis and therapy. PURPOSE To develop TP53 mutation classification models for PCa using MRI radiomics and clinicopathological features. STUDY TYPE Retrospective. POPULATION 388 patients with PCa from two centers (Center 1: 281 patients; Center 2: 107 patients). Cases from Center 1 were randomly divided into training and internal validation sets (7:3). Cases from Center 2 were used for external validation. FIELD STRENGTH/SEQUENCE 3.0T/T2-weighted imaging, dynamic contrast-enhanced imaging, diffusion-weighted imaging. ASSESSMENT Each patient's index tumor lesion was manually delineated on the above MRI images. Five clinicopathological and 428 radiomics features were obtained from each lesion. Radiomics features were selected by least absolute shrinkage and selection operator and binary logistic regression (LR) analysis, while clinicopathological features were selected using Mann-Whitney U test. Radiomics models were constructed using LR, support vector machine (SVM), and random forest (RF) classifiers. Clinicopathological-radiomics combined models were constructed using the selected radiomics and clinicopathological features with the aforementioned classifiers. STATISTICAL TESTS Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC). P value <0.05 indicates statistically significant. RESULTS In the internal validation set, the radiomics model had an AUC of 0.74 with the RF classifier, which was significantly higher than LR (AUC = 0.61), but similar to SVM (AUC = 0.69; P = 0.422). For the combined model, the AUC of RF model was 0.84, which was significantly higher than LR (0.64), but similar to SVM (0.80; P = 0.548). Both the combined RF and combined SVM models showed significantly higher AUCs than the radiomics models. In the external validation set, the combined RF and combined SVM models showed AUCs of 0.83 and 0.82. DATA CONCLUSION Pathological-radiomics combined models with RF, SVM show the association of TP53 mutations and pathological-radiomics features of PCa. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ruchuan Chen
- Shanghai Institute of Medical imaging, Shanghai, China
- Department of Radiology, Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bingni Zhou
- Department of Radiology, Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Liu
- Department of Radiology, Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hualei Gan
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xiaohang Liu
- Department of Radiology, Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liangping Zhou
- Department of Radiology, Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Boland PA, Hardy NP, Moynihan A, McEntee PD, Loo C, Fenlon H, Cahill RA. Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art. Eur J Nucl Med Mol Imaging 2024; 51:3135-3148. [PMID: 38858280 PMCID: PMC11300525 DOI: 10.1007/s00259-024-06731-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 04/15/2024] [Indexed: 06/12/2024]
Abstract
Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major treatment modality for primary and, increasingly, secondary curative therapy. However, with more patients being diagnosed with early stage and premalignant disease manifesting as large polyps, greater accuracy in diagnostic and therapeutic precision is needed right from the time of first endoscopic encounter. Rapid advancements in the field of artificial intelligence (AI), coupled with widespread availability of near infrared imaging (currently based around indocyanine green (ICG)) can enable colonoscopic tissue classification and prognostic stratification for significant polyps, in a similar manner to contemporary dynamic radiological perfusion imaging but with the advantage of being able to do so directly within interventional procedural time frames. It can provide an explainable method for immediate digital biopsies that could guide or even replace traditional forceps biopsies and provide guidance re margins (both areas where current practice is only approximately 80% accurate prior to definitive excision). Here, we discuss the concept and practice of AI enhanced ICG perfusion analysis for rectal cancer surgery while highlighting recent and essential near-future advancements. These include breakthrough developments in computer vision and time series analysis that allow for real-time quantification and classification of fluorescent perfusion signals of rectal cancer tissue intraoperatively that accurately distinguish between normal, benign, and malignant tissues in situ endoscopically, which are now undergoing international prospective validation (the Horizon Europe CLASSICA study). Next stage advancements may include detailed digital characterisation of small rectal malignancy based on intraoperative assessment of specific intratumoral fluorescent signal pattern. This could include T staging and intratumoral molecular process profiling (e.g. regarding angiogenesis, differentiation, inflammatory component, and tumour to stroma ratio) with the potential to accurately predict the microscopic local response to nonsurgical treatment enabling personalised therapy via decision support tools. Such advancements are also applicable to the next generation fluorophores and imaging agents currently emerging from clinical trials. In addition, by providing an understandable, applicable method for detailed tissue characterisation visually, such technology paves the way for acceptance of other AI methodology during surgery including, potentially, deep learning methods based on whole screen/video detailing.
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Affiliation(s)
- Patrick A Boland
- UCD Centre for Precision Surgery, School of Medicine, University College Dublin, 47 Eccles Street, Dublin 7, Dublin, Ireland
- Department of Colorectal Surgery, Mater Misericordiae University Hospital, Dublin, Ireland
| | - N P Hardy
- UCD Centre for Precision Surgery, School of Medicine, University College Dublin, 47 Eccles Street, Dublin 7, Dublin, Ireland
- Department of Colorectal Surgery, Mater Misericordiae University Hospital, Dublin, Ireland
| | - A Moynihan
- UCD Centre for Precision Surgery, School of Medicine, University College Dublin, 47 Eccles Street, Dublin 7, Dublin, Ireland
- Department of Colorectal Surgery, Mater Misericordiae University Hospital, Dublin, Ireland
| | - P D McEntee
- UCD Centre for Precision Surgery, School of Medicine, University College Dublin, 47 Eccles Street, Dublin 7, Dublin, Ireland
- Department of Colorectal Surgery, Mater Misericordiae University Hospital, Dublin, Ireland
| | - C Loo
- UCD Centre for Precision Surgery, School of Medicine, University College Dublin, 47 Eccles Street, Dublin 7, Dublin, Ireland
| | - H Fenlon
- Department of Radiology, Mater Misericordiae University Hospital, Dublin, Ireland
| | - R A Cahill
- UCD Centre for Precision Surgery, School of Medicine, University College Dublin, 47 Eccles Street, Dublin 7, Dublin, Ireland.
- Department of Colorectal Surgery, Mater Misericordiae University Hospital, Dublin, Ireland.
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Trecarten S, Sunnapwar AG, Clarke GD, Liss MA. Prostate MRI for the detection of clinically significant prostate cancer: Update and future directions. Adv Cancer Res 2024; 161:71-118. [PMID: 39032957 DOI: 10.1016/bs.acr.2024.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
PURPOSE OF REVIEW In recent decades, there has been an increasing role for magnetic resonance imaging (MRI) in the detection of clinically significant prostate cancer (csPC). The purpose of this review is to provide an update and outline future directions for the role of MRI in the detection of csPC. RECENT FINDINGS In diagnosing clinically significant prostate cancer pre-biopsy, advances include our understanding of MRI-targeted biopsy, the role of biparametric MRI (non-contrast) and changing indications, for example the role of MRI in screening for prostate cancer. Furthermore, the role of MRI in identifying csPC is maturing, with emphasis on standardization of MRI reporting in active surveillance (PRECISE), clinical staging (EPE grading, MET-RADS-P) and recurrent disease (PI-RR, PI-FAB). Future directions of prostate MRI in detecting csPC include quality improvement, artificial intelligence and radiomics, positron emission tomography (PET)/MRI and MRI-directed therapy. SUMMARY The utility of MRI in detecting csPC has been demonstrated in many clinical scenarios, initially from simply diagnosing csPC pre-biopsy, now to screening, active surveillance, clinical staging, and detection of recurrent disease. Continued efforts should be undertaken not only to emphasize the reporting of prostate MRI quality, but to standardize reporting according to the appropriate clinical setting.
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Affiliation(s)
- Shaun Trecarten
- Department of Urology, UT Health San Antonio, San Antonio, TX, United States
| | - Abhijit G Sunnapwar
- Department of Radiology, UT Health San Antonio, San Antonio, TX, United States
| | - Geoffrey D Clarke
- Department of Radiology, UT Health San Antonio, San Antonio, TX, United States
| | - Michael A Liss
- Department of Urology, UT Health San Antonio, San Antonio, TX, United States.
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Wei Z, Iluppangama M, Qi J, Choi JW, Yu A, Gage K, Chumbalkar V, Dhilon J, Balaji KC, Venkataperumal S, Hernandez DJ, Park J, Yedjou C, Alo R, Gatenby RA, Pow-Sang J, Balagurunanthan Y. Quantitative DCE Dynamics on Transformed MR Imaging Discriminates Clinically Significant Prostate Cancer. Cancer Control 2024; 31:10732748241298539. [PMID: 39545376 PMCID: PMC11565616 DOI: 10.1177/10732748241298539] [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: 05/16/2024] [Revised: 09/26/2024] [Accepted: 10/23/2024] [Indexed: 11/17/2024] Open
Abstract
Dynamic contrast enhancement (DCE) imaging is a valuable sequence of multiparametric magnetic resonance imaging (mpMRI). A DCE sequence enhances the vasculature and complements T2-weighted (T2W) and Diffusion-weighted imaging (DWI), allowing early detection of prostate cancer. However, DCE assessment has remained primarily qualitative. The study proposes quantifying DCE characteristics (T1W sequences) using six time-dependent metrics computed on feature transformations (306 radiomic features) of abnormal image regions observed over time. We applied our methodology to prostate cancer patients with the DCE MRI images (n = 25) who underwent prostatectomy with confirmed pathological assessment of the disease using Gleason Score. Regions of abnormality were assessed on the T2W MRI, guided using the whole mount pathology. Preliminary analysis finds over six temporal DCE imaging features obtained on different transformations on the imaging regions showed significant differences compared to the indolent counterpart (P ≤ 0.05, q ≤ 0.01). We find classifier models using logistic regression formed on DCE features after feature-based transformation (Centre of Mass) had an AUC of 0.89-0.94. While using mean feature-based transformation, the AUC was in the range of 0.71-0.76, estimated using the 0.632 bootstrap cross-validation method and after applying sample balancing using the synthetic minority oversampling technique (SMOTE). Our study finds, radiomic transformation of DCE images (T1 sequences) provides better signal standardization. Their temporal characteristics allow improved discrimination of aggressive disease.
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Affiliation(s)
- Zhouping Wei
- Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA
| | - Malinda Iluppangama
- Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA
- Department of Mathematics and Statistics, University of South Florida, FL, USA
| | - Jin Qi
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Jung W. Choi
- Department of Diagnostic & Interventional Radiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Alice Yu
- Department of Genitourinary Cancer, Moffitt Cancer Center, Tampa, FL, USA
| | - Kenneth Gage
- Department of Diagnostic & Interventional Radiology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Jasreman Dhilon
- Department of Pathology, Moffitt Cancer Center, Tampa, FL, USA
| | - K. C. Balaji
- Department of Urology, University of Florida, Jacksonville, FL, USA
| | | | - David J. Hernandez
- Department of Urology, University of South Florida Health, Tampa, FL, USA
| | - Jong Park
- Department of Population Sciences, Moffitt Cancer Center, Tampa, FL, USA
| | - Clement Yedjou
- Department of Biology, College of Science and Technology, Florida A&M University, Tallahassee, FL, USA
| | - Richard Alo
- Department of Biology, College of Science and Technology, Florida A&M University, Tallahassee, FL, USA
| | - Robert A. Gatenby
- Department of Diagnostic & Interventional Radiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Julio Pow-Sang
- Department of Genitourinary Cancer, Moffitt Cancer Center, Tampa, FL, USA
| | - Yoganand Balagurunanthan
- Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA
- Department of Diagnostic & Interventional Radiology, Moffitt Cancer Center, Tampa, FL, USA
- Department of Genitourinary Cancer, Moffitt Cancer Center, Tampa, FL, USA
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9
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Shen L, Li Y, Huang H, Lu Z, Chen B. HER2 in Gastric Cancer: A Comprehensive Analysis Combining Meta-Analysis and DCE-MRI Radiomics. Cancer Control 2024; 31:10732748241293699. [PMID: 39448273 PMCID: PMC11528791 DOI: 10.1177/10732748241293699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 09/26/2024] [Accepted: 10/07/2024] [Indexed: 10/26/2024] Open
Abstract
OBJECTIVE Advanced gastric cancer (AGC) is a severe malignant tumor, and overexpression of HER2/ERBB2 may play a crucial role in its development. The purpose of this study is to investigate the overexpression of HER2/ERBB2 in gastric cancer through a meta-analysis and examine its relationship with perfusion parameters using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) technology. METHODS We conducted an extensive literature search and collected relevant studies for the meta-analysis. We used a random-effects model and assigned weights using the "inverse variance" method. Additionally, we included 95 AGC patients diagnosed pathologically between April 2018 and October 2021. They all underwent DCE-MRI scans, and the data were subsequently analyzed using the Omni kinetic software. HER2 expression was assessed using immunohistochemistry. RESULTS The meta-analysis revealed an overall odds ratio (OR) of .21 for HER2/ERBB2 overexpression in gastric cancer, with a 95% confidence interval of [.14, .30]. DCE-MRI results showed a significant association between high HER2 expression and poor tumor differentiation (P < .005). The extracellular volume fraction (Ecv) quantile, mean, relative deviation, median intensity, and difference entropy were significantly higher in the low HER2 expression group compared to the high HER2 expression group. Receiver operating characteristic (ROC) curve analysis demonstrated that the area under the curve (AUC) values of DCE-MRI radiomic parameters with significant differences were close to .7. CONCLUSION Overexpression of HER2/ERBB2 in gastric cancer is significantly associated with certain radiomic parameters of DCE-MRI, providing a valuable diagnostic tool for clinical practice. Furthermore, the meta-analysis further confirmed the critical role of HER2/ERBB2 in the development of gastric cancer.
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Affiliation(s)
- Liyijing Shen
- Department of Radiology, Shaoxing People’s Hospital, Shaoxing, P. R. China
| | - Yaoqing Li
- Department of Gastrointestinal Surgery, Shaoxing People’s Hospital, Shaoxing, P. R. China
| | - Huizhen Huang
- Department of Radiology, Shaoxing People’s Hospital, Shaoxing, P. R. China
| | - Zengxin Lu
- Department of Radiology, Shaoxing People’s Hospital, Shaoxing, P. R. China
| | - Bo Chen
- Department of Radiology, Shaoxing People’s Hospital, Shaoxing, P. R. China
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Spilseth B, Margolis DJA, Gupta RT, Chang SD. Interpretation of Prostate Magnetic Resonance Imaging Using Prostate Imaging and Data Reporting System Version 2.1: A Primer. Radiol Clin North Am 2024; 62:17-36. [PMID: 37973241 DOI: 10.1016/j.rcl.2023.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Prostate magnetic resonance imaging (MRI) is increasingly being used to diagnose and stage prostate cancer. The Prostate Imaging and Data Reporting System (PI-RADS) version 2.1 is a consensus-based reporting system that provides a standardized and reproducible method for interpreting prostate MRI. This primer provides an overview of the PI-RADS system, focusing on its current role in clinical interpretation. It discusses the appropriate use of PI-RADS and how it should be applied by radiologists in clinical practice to assign and report PI-RADS assessments. We also discuss the changes from prior versions and published validation studies on PI-RADS accuracy and reproducibility.
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Affiliation(s)
- Benjamin Spilseth
- Department of Radiology, University of Minnesota Medical School, MMC 292420, Delaware Street, Minneapolis, MN 55455, USA.
| | - Daniel J A Margolis
- Weill Cornell Medical College, Department of Radiology, 525 East 68th Street, Box 141, New York, NY 10068, USA
| | - Rajan T Gupta
- Department of Radiology, Duke University Medical Center, Duke Cancer Institute Center for Prostate & Urologic Cancers, DUMC Box 3808, Durham, NC 27710, USA; Department of Surgery, Duke University Medical Center, Duke Cancer Institute Center for Prostate & Urologic Cancers, DUMC Box 3808, Durham, NC 27710, USA
| | - Silvia D Chang
- Department of Radiology, University of British Columbia, Vancouver General Hospital, 899 West 12th Avenue, Vancouver B.C., Canada V5M 1M9
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Choi MH, Lee YJ, Han D, Kim DH. Quantitative Analysis of Prostate MRI: Correlation between Contrast-Enhanced Magnetic Resonance Fingerprinting and Dynamic Contrast-Enhanced MRI Parameters. Curr Oncol 2023; 30:10299-10310. [PMID: 38132384 PMCID: PMC10743035 DOI: 10.3390/curroncol30120750] [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: 10/30/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
This research aimed to assess the relationship between contrast-enhanced (CE) magnetic resonance fingerprinting (MRF) values and dynamic contrast-enhanced (DCE) MRI parameters including (Ktrans, Kep, Ve, and iAUC). To evaluate the correlation between the MRF-derived values (T1 and T2 values, CE T1 and T2 values, T1 and T2 change) and DCE-MRI parameters and the differences in the parameters between prostate cancer and noncancer lesions in 68 patients, two radiologists independently drew regions-of-interest (ROIs) at the focal prostate lesions. Prostate cancer was identified in 75% (51/68) of patients. The CE T2 value was significantly lower in prostate cancer than in noncancer lesions in the peripheral zone and transition zone. Ktrans, Kep, and iAUC were significantly higher in prostate cancer than noncancer lesions in the peripheral zone (p < 0.05), but not in the transition zone. The CE T1 value was significantly correlated with Ktrans, Ve, and iAUC in prostate cancer, and the CE T2 value was correlated to Ve in noncancer. Some CE MRF values are different between prostate cancer and noncancer tissues and correlate with DCE-MRI parameters. Prostate cancer and noncancer tissues may have different characteristics regarding contrast enhancement.
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Affiliation(s)
- Moon-Hyung Choi
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea;
| | - Young-Joon Lee
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea;
| | - Dongyeob Han
- Siemens Healthineers Ltd., Seoul 06620, Republic of Korea;
| | - Dong-Hyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea;
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12
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Guljaš S, Dupan Krivdić Z, Drežnjak Madunić M, Šambić Penc M, Pavlović O, Krajina V, Pavoković D, Šmit Takač P, Štefančić M, Salha T. Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review. Diagnostics (Basel) 2023; 13:3488. [PMID: 37998624 PMCID: PMC10670922 DOI: 10.3390/diagnostics13223488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 10/30/2023] [Accepted: 11/16/2023] [Indexed: 11/25/2023] Open
Abstract
The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.
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Affiliation(s)
- Silva Guljaš
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (S.G.); (Z.D.K.)
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
| | - Zdravka Dupan Krivdić
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (S.G.); (Z.D.K.)
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
| | - Maja Drežnjak Madunić
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Oncology, University Hospital Centre, 31000 Osijek, Croatia
| | - Mirela Šambić Penc
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Oncology, University Hospital Centre, 31000 Osijek, Croatia
| | - Oliver Pavlović
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Urology, University Hospital Centre, 31000 Osijek, Croatia
| | - Vinko Krajina
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Urology, University Hospital Centre, 31000 Osijek, Croatia
| | - Deni Pavoković
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Urology, University Hospital Centre, 31000 Osijek, Croatia
| | - Petra Šmit Takač
- Clinical Department of Surgery, Osijek University Hospital Centre, 31000 Osijek, Croatia;
| | - Marin Štefančić
- Department of Radiology, National Memorial Hospital Vukovar, 32000 Vukovar, Croatia;
| | - Tamer Salha
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Teleradiology and Artificial Intelligence, Health Centre Osijek-Baranja County, 31000 Osijek, Croatia
- Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
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13
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Zhong J, Kobus M, Maitre P, Datta A, Eccles C, Dubec M, McHugh D, Buckley D, Scarsbrook A, Hoskin P, Henry A, Choudhury A. MRI-guided Pelvic Radiation Therapy: A Primer for Radiologists. Radiographics 2023; 43:e230052. [PMID: 37796729 DOI: 10.1148/rg.230052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
Radiation therapy (RT) is a core pillar of oncologic treatment, and half of all patients with cancer receive this therapy as a curative or palliative treatment. The recent integration of MRI into the RT workflow has led to the advent of MRI-guided RT (MRIgRT). Using MRI rather than CT has clear advantages for guiding RT to pelvic tumors, including superior soft-tissue contrast, improved organ motion visualization, and the potential to image tumor phenotypic characteristics to identify the most aggressive or treatment-resistant areas, which can be targeted with a more focal higher radiation dose. Radiologists should be familiar with the potential uses of MRI in planning pelvic RT; the various RT techniques used, such as brachytherapy and external beam RT; and the impact of MRIgRT on treatment paradigms. Current clinical experience with and the evidence base for MRIgRT in the settings of prostate, cervical, and bladder cancer are discussed, and examples of treated cases are illustrated. In addition, the benefits of MRIgRT, such as real-time online adaptation of RT (during treatment) and interfraction and/or intrafraction adaptation to organ motion, as well as how MRIgRT can decrease toxic effects and improve oncologic outcomes, are highlighted. MRIgRT is particularly beneficial for treating mobile pelvic structures, and real-time adaptive RT for tumors can be achieved by using advanced MRI-guided linear accelerator systems to spare organs at risk. Future opportunities for development of biologically driven adapted RT with use of functional MRI sequences and radiogenomic approaches also are outlined. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Jim Zhong
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Marta Kobus
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Priyamvada Maitre
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Anubhav Datta
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Cynthia Eccles
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Michael Dubec
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Damien McHugh
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - David Buckley
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Andrew Scarsbrook
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Peter Hoskin
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Ann Henry
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
| | - Ananya Choudhury
- From the Leeds Institute of Medical Research (J.Z., A.S., A.H.) and Department of Biomedical Imaging (D.B.), University of Leeds, 6 Clarendon Way, Woodhouse, Leeds LS2 9LH, England; Leeds Cancer Centre, St James's University Hospital, Leeds, England (J.Z., A.S., A.H.); Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany (M.K.); Radiation Therapy Research Group (M.K., P.M., A.D., C.E., M.D., P.H., A.C.) and Division of Cancer Sciences (D.M.), University of Manchester, Manchester, England; and The Christie NHS Foundation Trust, Manchester, England (P.M., C.E., M.D., D.M., P.H., A.C.)
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Chauvie S, Mazzoni LN, O’Doherty J. A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation. Tomography 2023; 9:1876-1902. [PMID: 37888741 PMCID: PMC10610870 DOI: 10.3390/tomography9050149] [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: 08/16/2023] [Revised: 10/10/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023] Open
Abstract
Imaging biomarkers (IBs) have been proposed in medical literature that exploit images in a quantitative way, going beyond the visual assessment by an imaging physician. These IBs can be used in the diagnosis, prognosis, and response assessment of several pathologies and are very often used for patient management pathways. In this respect, IBs to be used in clinical practice and clinical trials have a requirement to be precise, accurate, and reproducible. Due to limitations in imaging technology, an error can be associated with their value when considering the entire imaging chain, from data acquisition to data reconstruction and subsequent analysis. From this point of view, the use of IBs in clinical trials requires a broadening of the concept of quality assurance and this can be a challenge for the responsible medical physics experts (MPEs). Within this manuscript, we describe the concept of an IB, examine some examples of IBs currently employed in clinical practice/clinical trials and analyze the procedure that should be carried out to achieve better accuracy and reproducibility in their use. We anticipate that this narrative review, written by the components of the EFOMP working group on "the role of the MPEs in clinical trials"-imaging sub-group, can represent a valid reference material for MPEs approaching the subject.
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Affiliation(s)
- Stephane Chauvie
- Medical Physics Division, Santa Croce e Carle Hospital, 12100 Cuneo, Italy;
| | | | - Jim O’Doherty
- Siemens Medical Solutions, Malvern, PA 19355, USA;
- Department of Radiology & Radiological Sciences, Medical University of South Carolina, Charleston, SC 20455, USA
- Radiography & Diagnostic Imaging, University College Dublin, D04 C7X2 Dublin, Ireland
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15
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Zhou X, Fan X, Chatterjee A, Yousuf A, Antic T, Oto A, Karczmar GS. Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard tofts model in the diagnosis of prostate cancer. Phys Eng Sci Med 2023; 46:1215-1226. [PMID: 37432557 DOI: 10.1007/s13246-023-01289-6] [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: 02/01/2023] [Accepted: 06/14/2023] [Indexed: 07/12/2023]
Abstract
The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data and compared with the standard Tofts model. A total of 29 patients with biopsy-confirmed prostate cancer were included in this IRB-approved study. MRI data were acquired on a Philips Achieva 3T-TX scanner. After T2-weighted and diffusion-weighted imaging, DCE data using 3D T1-FFE mDIXON sequence were acquired pre- and post-contrast media injection (0.1 mmol/kg Multihance) for 60 dynamic scans with temporal resolution of 8.3 s/image. The 2TCM has one fast ([Formula: see text] and [Formula: see text]) and one slow ([Formula: see text] and [Formula: see text]) exchanging compartment, compared with the standard Tofts model parameters (Ktrans and kep). On average, prostate cancer had significantly higher values (p < 0.01) than normal prostate tissue for all calculated parameters. There was a strong correlation (r = 0.94, p < 0.001) between Ktrans and [Formula: see text] for cancer, but weak correlation (r = 0.28, p < 0.05) between kep and [Formula: see text]. Average root-mean-square error (RMSE) in fits from the 2TCM was significantly smaller (p < 0.001) than the RMSE in fits from the Tofts model. Receiver operating characteristic (ROC) analysis showed that fast [Formula: see text] had the highest area under the curve (AUC) than any other individual parameter. The combined four parameters from the 2TCM had a considerably higher AUC value than the combined two parameters from the Tofts model. The 2TCM is useful for quantitative analysis of prostate DCE-MRI data and provides new information in the diagnosis of prostate cancer.
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Affiliation(s)
- Xueyan Zhou
- School of Technology, Harbin University, Harbin, China.
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA.
| | - Xiaobing Fan
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA
| | | | - Ambereen Yousuf
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA
| | - Tatjana Antic
- Department of Pathology, University of Chicago, Chicago, IL, 60637, USA
| | - Aytekin Oto
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA
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16
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Thulasi Seetha S, Garanzini E, Tenconi C, Marenghi C, Avuzzi B, Catanzaro M, Stagni S, Villa S, Chiorda BN, Badenchini F, Bertocchi E, Sanduleanu S, Pignoli E, Procopio G, Valdagni R, Rancati T, Nicolai N, Messina A. Stability of Multi-Parametric Prostate MRI Radiomic Features to Variations in Segmentation. J Pers Med 2023; 13:1172. [PMID: 37511785 PMCID: PMC10381192 DOI: 10.3390/jpm13071172] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Stability analysis remains a fundamental step in developing a successful imaging biomarker to personalize oncological strategies. This study proposes an in silico contour generation method for simulating segmentation variations to identify stable radiomic features. Ground-truth annotation provided for the whole prostate gland on the multi-parametric MRI sequences (T2w, ADC, and SUB-DCE) were perturbed to mimic segmentation differences observed among human annotators. In total, we generated 15 synthetic contours for a given image-segmentation pair. One thousand two hundred twenty-four unfiltered/filtered radiomic features were extracted applying Pyradiomics, followed by stability assessment using ICC(1,1). Stable features identified in the internal population were then compared with an external population to discover and report robust features. Finally, we also investigated the impact of a wide range of filtering strategies on the stability of features. The percentage of unfiltered (filtered) features that remained robust subjected to segmentation variations were T2w-36% (81%), ADC-36% (94%), and SUB-43% (93%). Our findings suggest that segmentation variations can significantly impact radiomic feature stability but can be mitigated by including pre-filtering strategies as part of the feature extraction pipeline.
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Affiliation(s)
- Sithin Thulasi Seetha
- Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (S.T.S.); (R.V.)
- Department of Precision Medicine, GROW—School for Oncology and Developmental Biology, Maastricht University, 6211 LK Maastricht, The Netherlands
| | - Enrico Garanzini
- Department of Radiology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (E.G.); (A.M.)
| | - Chiara Tenconi
- Department of Medical Physics, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy;
- Department of Oncology and Hematooncology, Università degli Studi di Milano, 20133 Milan, Italy
| | - Cristina Marenghi
- Unit of Genito-Urinary Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (C.M.); (F.B.); (E.B.); (G.P.)
| | - Barbara Avuzzi
- Department of Radiation Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (B.A.); (S.V.); (B.N.C.)
| | - Mario Catanzaro
- Department of Urology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (M.C.); (S.S.); (N.N.)
| | - Silvia Stagni
- Department of Urology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (M.C.); (S.S.); (N.N.)
| | - Sergio Villa
- Department of Radiation Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (B.A.); (S.V.); (B.N.C.)
| | - Barbara Noris Chiorda
- Department of Radiation Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (B.A.); (S.V.); (B.N.C.)
| | - Fabio Badenchini
- Unit of Genito-Urinary Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (C.M.); (F.B.); (E.B.); (G.P.)
| | - Elena Bertocchi
- Unit of Genito-Urinary Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (C.M.); (F.B.); (E.B.); (G.P.)
| | - Sebastian Sanduleanu
- Department of Precision Medicine, GROW—School for Oncology and Developmental Biology, Maastricht University, 6211 LK Maastricht, The Netherlands
| | - Emanuele Pignoli
- Department of Medical Physics, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy;
| | - Giuseppe Procopio
- Unit of Genito-Urinary Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (C.M.); (F.B.); (E.B.); (G.P.)
| | - Riccardo Valdagni
- Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (S.T.S.); (R.V.)
- Department of Oncology and Hematooncology, Università degli Studi di Milano, 20133 Milan, Italy
| | - Tiziana Rancati
- Data Science Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Nicola Nicolai
- Department of Urology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (M.C.); (S.S.); (N.N.)
| | - Antonella Messina
- Department of Radiology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy; (E.G.); (A.M.)
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Stamatelatou A, Sima DM, van Huffel S, van Asten JJA, Heerschap A, Scheenen TWJ. Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate. Magn Reson Med 2023; 89:1741-1753. [PMID: 36572967 DOI: 10.1002/mrm.29565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 11/23/2022] [Accepted: 12/08/2022] [Indexed: 12/28/2022]
Abstract
PURPOSE To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites. METHODS Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI. RESULTS The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed 1 H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D 1 H-MRSI of the prostate showed expected spatial variations in metabolite levels. CONCLUSION We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.
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Affiliation(s)
- Angeliki Stamatelatou
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | | | - Sabine van Huffel
- STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering (ESAT), Leuven, Belgium
| | - Jack J A van Asten
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
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18
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Asif A, Nathan A, Ng A, Khetrapal P, Chan VWS, Giganti F, Allen C, Freeman A, Punwani S, Lorgelly P, Clarke CS, Brew-Graves C, Muirhead N, Emberton M, Agarwal R, Takwoingi Y, Deeks JJ, Moore CM, Kasivisvanathan V. Comparing biparametric to multiparametric MRI in the diagnosis of clinically significant prostate cancer in biopsy-naive men (PRIME): a prospective, international, multicentre, non-inferiority within-patient, diagnostic yield trial protocol. BMJ Open 2023; 13:e070280. [PMID: 37019486 PMCID: PMC10083803 DOI: 10.1136/bmjopen-2022-070280] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/07/2023] Open
Abstract
INTRODUCTION Prostate MRI is a well-established tool for the diagnostic work-up for men with suspected prostate cancer (PCa). Current recommendations advocate the use of multiparametric MRI (mpMRI), which is composed of three sequences: T2-weighted sequence (T2W), diffusion-weighted sequence (DWI) and dynamic contrast-enhanced sequence (DCE). Prior studies suggest that a biparametric MRI (bpMRI) approach, omitting the DCE sequences, may not compromise clinically significant cancer detection, though there are limitations to these studies, and it is not known how this may affect treatment eligibility. A bpMRI approach will reduce scanning time, may be more cost-effective and, at a population level, will allow more men to gain access to an MRI than an mpMRI approach. METHODS Prostate Imaging Using MRI±Contrast Enhancement (PRIME) is a prospective, international, multicentre, within-patient diagnostic yield trial assessing whether bpMRI is non-inferior to mpMRI in the diagnosis of clinically significant PCa. Patients will undergo the full mpMRI scan. Radiologists will be blinded to the DCE and will initially report the MRI using only the bpMRI (T2W and DWI) sequences. They will then be unblinded to the DCE sequence and will then re-report the MRI using the mpMRI sequences (T2W, DWI and DCE). Men with suspicious lesions on either bpMRI or mpMRI will undergo prostate biopsy. The main inclusion criteria are men with suspected PCa, with a serum PSA of ≤20 ng/mL and without prior prostate biopsy. The primary outcome is the proportion of men with clinically significant PCa detected (Gleason score ≥3+4 or Gleason grade group ≥2). A sample size of at least 500 patients is required. Key secondary outcomes include the proportion of clinically insignificant PCa detected and treatment decision. ETHICS AND DISSEMINATION Ethical approval was obtained from the National Research Ethics Committee West Midlands, Nottingham (21/WM/0091). Results of this trial will be disseminated through peer-reviewed publications. Participants and relevant patient support groups will be informed about the results of the trial. TRIAL REGISTRATION NUMBER NCT04571840.
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Affiliation(s)
- Aqua Asif
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Arjun Nathan
- Division of Surgery and Interventional Science, University College London, London, UK
- Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK
| | - Alexander Ng
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Pramit Khetrapal
- Division of Surgery and Interventional Science, University College London, London, UK
- Department of Urology, Whipps Cross University Hospital, London, UK
| | - Vinson Wai-Shun Chan
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Francesco Giganti
- Division of Surgery and Interventional Science, University College London, London, UK
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Clare Allen
- Division of Surgery and Interventional Science, University College London, London, UK
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Alex Freeman
- Department of Histopathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Shonit Punwani
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
- Centre for Medical Imaging, University College London, London, UK
| | - Paula Lorgelly
- Institute of Epidemiology and Health Care, University College London, London, UK
- School of Population Health, The University of Auckland, Auckland, New Zealand
| | - Caroline S Clarke
- Research Department of Primary Care and Population Health, University College London, London, UK
| | - Chris Brew-Graves
- National Cancer Imaging Translational Accelerator, University College London, London, UK
| | - Nicola Muirhead
- National Cancer Imaging Translational Accelerator, University College London, London, UK
| | - Mark Emberton
- Division of Surgery and Interventional Science, University College London, London, UK
- Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Ridhi Agarwal
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Yemisi Takwoingi
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Jonathan J Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Caroline M Moore
- Division of Surgery and Interventional Science, University College London, London, UK
- Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Veeru Kasivisvanathan
- Division of Surgery and Interventional Science, University College London, London, UK
- Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
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19
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Hu W, Chen L, Lin L, Wang J, Wang N, Liu A. Three-dimensional amide proton transfer-weighted and intravoxel incoherent motion imaging for predicting bone metastasis in patients with prostate cancer: A pilot study. Magn Reson Imaging 2023; 96:8-16. [PMID: 36375760 DOI: 10.1016/j.mri.2022.11.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 10/25/2022] [Accepted: 11/07/2022] [Indexed: 11/13/2022]
Abstract
PURPOSE To explore the value of 3-dimensional amide proton transfer-weighted (APTw) and intravoxel incoherent motion (IVIM) imaging in predicting bone metastasis (BM) of prostate cancer (PCa) in addition to routine diffusion-weighted imaging (DWI). METHODS The clinical and imaging data of 39 PCa patients who were pathologically confirmed in our hospital from March 2019 to February 2022 were retrospectively analyzed, and they were divided into BM-negative (27 patients) and BM-positive (12 patients) groups. MR examination included APTw, DWI and IVIM imaging. The IVIM data was fitted by single-exponential IVIM model (IVIMmono) and double-exponential IVIM model (IVIMbi), respectively. The APTw, ADC, IVIMmono (Dmono, D*mono, and fmono), and IVIMbi (Dbi, D*bi, and fbi) parameters were independently measured by two radiologists. The synthetic minority oversampling technique (SMOTE) was conducted to balance the minority group. Mann-Whitney U test or Student's t-test was used to compare above values between the BM-negative and BM-positive groups. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. The Delong test was used for ROC curve comparison.The relationship between APTw and IVIM was explored through Spearman's rank correlation analysis. RESULTS The APTw and D*mono values were higher, and the ADC, fmono, and fbi values were lower in the BM-positive group than in the BM-negative group (all P < 0.05). Among the individual parameters, the AUC of fmono was the highest (AUC = 0.865), and AUC (fmono) was significantly higher than AUC (fbi), AUC (D*mono), and AUC (ADC) (all P < 0.05). The AUC (IVIMmono) was higher than the AUC (IVIMbi) (P = 0.0068). The combination of APTw and IVIMmono further improved diagnostic capability, and the AUC of APTw+IVIMmono was significantly higher than those of APTw and DWI (all P < 0.05). No correlation was found between IVIM-derived parameters and APTw value. CONCLUSION Both 3D APTw and IVIM imaging could predict BM of PCa. IVIM showed better performance than APTw and DWI, and the single-exponential IVIM model was superior to the double-exponential IVIM model. The combination of APTw and IVIM could further improve diagnostic performance.
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Affiliation(s)
- Wenjun Hu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China
| | - Lihua Chen
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China; Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging, Dalian, Liaoning, 116011, PR China
| | | | | | - Nan Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China; Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging, Dalian, Liaoning, 116011, PR China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116011, PR China; Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging, Dalian, Liaoning, 116011, PR China.
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20
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Bergen RV, Ryner L, Essig M. Comparison of DCE-MRI parametric mapping using MP2RAGE and variable flip angle T1 mapping. Magn Reson Imaging 2023; 95:103-109. [PMID: 32646633 DOI: 10.1016/j.mri.2020.01.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 12/23/2019] [Accepted: 01/03/2020] [Indexed: 12/15/2022]
Abstract
Quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) measures the rate of transfer of contrast agent from the vascular space to the tissue space by fitting signal-time data to pharmacokinetic models. However, these models are very sensitive to errors in T1 mapping. Accurate T1 mapping is necessary for high quality quantitative DCE-MRI studies. This study compares magnetization prepared rapid (two) gradient echo sequence (MP2RAGE) T1-mapping accuracy to the conventional variable flip angle (VFA) approach, and also determines the effect of the new T1-mapping method on the Ktrans parameter. VFA and MP2RAGE T1 values were compared to the gold standard inverse recovery (IR) method in phantom over manually drawn ROIs. In vivo, ROIs were manually drawn over prostate and prostatic lesions. Average T1 values over ROIs were compared and Ktrans maps for each method were calculated via the extended Tofts model. VFA-T1 maps overestimated T1 values by up to 50% compared to gold standard IR T1 values in phantom. MP2RAGE differed by up to 9%. MP2RAGE-T1 and Ktrans values were significantly different from VFA values over prostatic lesions (p < 0.05). Ktrans was consistently underestimated using VFA compared to MP2RAGE (p < 0.05). MP2RAGE T1 maps are shown to be more accurate, leading to more reliable pharmacokinetic modeling. This can potentially lead to better lesion characterization and improve clinical outcomes.
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Affiliation(s)
- Robert V Bergen
- Department of Physics & Astronomy, University of Manitoba, Canada; Medical Physics, CancerCare Manitoba, Canada
| | - Lawrence Ryner
- Department of Physics & Astronomy, University of Manitoba, Canada; Medical Physics, CancerCare Manitoba, Canada.
| | - Marco Essig
- Department of Radiology, University of Manitoba, Canada
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21
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Matani H, Patel AK, Horne ZD, Beriwal S. Utilization of functional MRI in the diagnosis and management of cervical cancer. Front Oncol 2022; 12:1030967. [PMID: 36439416 PMCID: PMC9691646 DOI: 10.3389/fonc.2022.1030967] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 10/13/2022] [Indexed: 09/15/2023] Open
Abstract
Introduction Imaging is integral part of cervical cancer management. Currently, MRI is used for staging, follow up and image guided adaptive brachytherapy. The ongoing IQ-EMBRACE sub-study is evaluating the use of MRI for functional imaging to aid in the assessment of hypoxia, metabolism, hemodynamics and tissue structure. This study reviews the current and potential future utilization of functional MRI imaging in diagnosis and management of cervical cancer. Methods We searched PubMed for articles characterizing the uses of functional MRI (fMRI) for cervical cancer. The current literature regarding these techniques in diagnosis and outcomes for cervical cancer were then reviewed. Results The most used fMRI techniques identified for use in cervical cancer include diffusion weighted imaging (DWI) and dynamic contrast enhancement (DCE). DCE-MRI indirectly reflects tumor perfusion and hypoxia. This has been utilized to either characterize a functional risk volume of tumor with low perfusion or to characterize at-risk tumor voxels by analyzing signal intensity both pre-treatment and during treatment. DCE imaging in these situations has been associated with local control and disease-free survival and may have predictive/prognostic significance, however this has not yet been clinically validated. DWI allows for creation of ADC maps, that assists with diagnosis of local malignancy or nodal disease with high sensitivity and specificity. DWI findings have also been correlated with local control and overall survival in patients with an incomplete response after definitive chemoradiotherapy and thus may assist with post-treatment follow up. Other imaging techniques used in some instances are MR-spectroscopy and perfusion weighted imaging. T2-weighted imaging remains the standard technique used for diagnosis and radiation treatment planning. In many instances, it is unclear what additional information functional-MRI techniques provide compared to standard MRI imaging. Conclusions Functional MRI provides potential for improved diagnosis, prediction of treatment response and prognostication in cervical cancer. Specific sequences such as DCE, DWI and ADC need to be validated in a large prospective setting prior to widespread use. The ongoing IQ-EMBRACE study will provide important clinical information regarding these imaging modalities.
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Affiliation(s)
- Hirsch Matani
- Division of Radiation Oncology, Allegheny Health Network Cancer Institute, Pittsburgh, PA, United States
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22
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Ziayee F, Schimmöller L, Blondin D, Boschheidgen M, Wilms LM, Vach M, Arsov C, Albers P, Antoch G, Ullrich T. Impact of dynamic contrast-enhanced MRI in 1.5 T versus 3 T MRI for clinically significant prostate cancer detection. Eur J Radiol 2022; 156:110520. [PMID: 36116141 DOI: 10.1016/j.ejrad.2022.110520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/21/2022] [Accepted: 09/06/2022] [Indexed: 11/03/2022]
Abstract
PURPOSE This study analyzes the value of dynamic contrast-enhanced MRI (DCE) of the prostate on 1.5 T and 3 T examinations in patients within PI-RADS category 4. METHODS In this retrospective, bi-centric, cohort study all consecutive patients classified as PI-RADS 4 in mpMRI with 100 verified prostate cancers (PCa) in subsequent MRI/US-guided fusion biopsy were included for 1.5 T and 3 T, each. PCa detection in index lesions (IL) upgraded to PI-RADS 4 based on positive DCE findings was compared between 1.5 T and 3 T. Secondary objectives are subgroup analysis of PZ lesions and comparison of ISUP grade group distribution between 1.5 T and 3 T. RESULTS In total, 293 patients within PI-RADS category 4, including 152 (mean 66 ± 8y; median PSA 6.4 ng/ml;116 PZ IL) in the 1.5 T group and 141 (mean 65 ± 8y; median PSA 7.2 ng/ml;100 PZ IL) in the 3 T group were included. Overall amount of PCa (66 % vs 71 %; p = 0.346) and portion of upgraded IL (28 % vs 21 %; p = 0.126) did not differ significantly. At 1.5 T PCa detection was higher in upgraded PZ lesions compared to 3 T (23 % vs 14 %; p = 0.048). The amount of upgraded PZ lesions with ISUP grade group 2-5 PCa was significantly higher at 1.5 T versus 3 T (13.8 % vs 4.0 %; p = 0.007). 33 % (11/33; 1.5 T) and 32 % (10/31; 3 T) of the ISUP grade group 1 PCa of the PZ lesions were detected in upgraded lesions (10% of all PZ index lesions, respectively). CONCLUSION DCE enabled the detection of a substantial amount of additional clinically significant PCa in prostate mpMRI at 1.5 T. The effect was smaller at 3 T and was accompanied in relation to 1.5 T by higher risk of overdiagnosis due to detection of additional low-risk PCa.
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Affiliation(s)
- F Ziayee
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - L Schimmöller
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - D Blondin
- Community Hospital Moenchengladbach GmbH, Elisabeth-Hospital Rheydt, Department of Radiology, Vascular Radiology, and Nuclear Medicine, D-41239 Moenchengladbach, Germany.
| | - M Boschheidgen
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - L M Wilms
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - M Vach
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - C Arsov
- University Dusseldorf, Medical Faculty, Department of Urology, D-40225 Dusseldorf, Germany.
| | - P Albers
- University Dusseldorf, Medical Faculty, Department of Urology, D-40225 Dusseldorf, Germany.
| | - G Antoch
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - T Ullrich
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
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23
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Bottero M, Faiella A, Giannarelli D, Farneti A, D'Urso P, Bertini L, Landoni V, Vici P, Sanguineti G. A prospective study assessing the pattern of response of local disease at DCE-MRI after salvage radiotherapy for prostate cancer. Clin Transl Radiat Oncol 2022; 35:21-26. [PMID: 35516461 PMCID: PMC9065465 DOI: 10.1016/j.ctro.2022.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/18/2022] [Accepted: 04/25/2022] [Indexed: 10/29/2022] Open
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24
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Guljaš S, Benšić M, Krivdić Dupan Z, Pavlović O, Krajina V, Pavoković D, Šmit Takač P, Hranić M, Salha T. Dynamic Contrast Enhanced Study in Multiparametric Examination of the Prostate—Can We Make Better Use of It? Tomography 2022; 8:1509-1521. [PMID: 35736872 PMCID: PMC9231365 DOI: 10.3390/tomography8030124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/18/2022] [Accepted: 06/04/2022] [Indexed: 11/16/2022] Open
Abstract
We sought to investigate whether quantitative parameters from a dynamic contrast-enhanced study can be used to differentiate cancer from normal tissue and to determine a cut-off value of specific parameters that can predict malignancy more accurately, compared to the obturator internus muscle as a reference tissue. This retrospective study included 56 patients with biopsy proven prostate cancer (PCa) after multiparametric magnetic resonance imaging (mpMRI), with a total of 70 lesions; 39 were located in the peripheral zone, and 31 in the transition zone. The quantitative parameters for all patients were calculated in the detected lesion, morphologically normal prostate tissue and the obturator internus muscle. Increase in the Ktrans value was determined in lesion-to-muscle ratio by 3.974368, which is a cut-off value to differentiate between prostate cancer and normal prostate tissue, with specificity of 72.86% and sensitivity of 91.43%. We introduced a model to detect prostate cancer that combines Ktrans lesion-to-muscle ratio value and iAUC lesion-to-muscle ratio value, which is of higher accuracy compared to individual variables. Based on this model, we identified the optimal cut-off value with 100% sensitivity and 64.28% specificity. The use of quantitative DCE pharmacokinetic parameters compared to the obturator internus muscle as reference tissue leads to higher diagnostic accuracy for prostate cancer detection.
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Affiliation(s)
- Silva Guljaš
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (Z.K.D.); (M.H.)
- Correspondence:
| | - Mirta Benšić
- Department of Mathematics, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
| | - Zdravka Krivdić Dupan
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (Z.K.D.); (M.H.)
- Department of Radiology, Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
| | - Oliver Pavlović
- Department of Urology, University Hospital Centre Osijek, 31000 Osijek, Croatia; (O.P.); (V.K.); (D.P.)
| | - Vinko Krajina
- Department of Urology, University Hospital Centre Osijek, 31000 Osijek, Croatia; (O.P.); (V.K.); (D.P.)
| | - Deni Pavoković
- Department of Urology, University Hospital Centre Osijek, 31000 Osijek, Croatia; (O.P.); (V.K.); (D.P.)
| | - Petra Šmit Takač
- Clinical Department of Surgery, Osijek University Hospital Centre, 31000 Osijek, Croatia;
| | - Matija Hranić
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (Z.K.D.); (M.H.)
| | - Tamer Salha
- Department of Radiology, Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
- Department of Teleradiology and Artificial Intelligence, Health Centre Osijek-Baranja County, 31000 Osijek, Croatia
- Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
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25
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Synthetic correlated diffusion imaging hyperintensity delineates clinically significant prostate cancer. Sci Rep 2022; 12:3376. [PMID: 35232991 PMCID: PMC8888633 DOI: 10.1038/s41598-022-06872-7] [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: 09/05/2021] [Accepted: 02/08/2022] [Indexed: 11/08/2022] Open
Abstract
Prostate cancer (PCa) is the second most common cancer in men worldwide and the most frequently diagnosed cancer among men in more developed countries. The prognosis of PCa is excellent if detected at an early stage, making early screening crucial for detection and treatment. In recent years, a new form of diffusion magnetic resonance imaging called correlated diffusion imaging (CDI) was introduced, and preliminary results show promise as a screening tool for PCa. In the largest study of its kind, we investigate the relationship between PCa presence and a new variant of CDI we term synthetic correlated diffusion imaging (CDI\documentclass[12pt]{minimal}
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\begin{document}$$^s$$\end{document}s), as well as its performance for PCa delineation compared to current standard MRI techniques [T2-weighted (T2w) imaging, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging] across a cohort of 200 patient cases. Statistical analyses reveal that hyperintensity in CDI\documentclass[12pt]{minimal}
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\begin{document}$$^s$$\end{document}s is a strong indicator of PCa presence and achieves strong delineation of clinically significant cancerous tissue compared to T2w, DWI, and DCE. These results suggest that CDI\documentclass[12pt]{minimal}
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\begin{document}$$^s$$\end{document}s hyperintensity may be a powerful biomarker for the presence of PCa, and may have a clinical impact as a diagnostic aid for improving PCa screening.
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26
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Fan X, Xie N, Chen J, Li T, Cao R, Yu H, He M, Wang Z, Wang Y, Liu H, Wang H, Yin X. Multiparametric MRI and Machine Learning Based Radiomic Models for Preoperative Prediction of Multiple Biological Characteristics in Prostate Cancer. Front Oncol 2022; 12:839621. [PMID: 35198452 PMCID: PMC8859464 DOI: 10.3389/fonc.2022.839621] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 01/11/2022] [Indexed: 01/18/2023] Open
Abstract
Objectives This study aims to develop and evaluate multiparametric MRI (MP-MRI)-based radiomic models as a noninvasive diagnostic method to predict several biological characteristics of prostate cancer. Methods A total of 252 patients were retrospectively included who underwent radical prostatectomy and MP-MRI examinations. The prediction characteristics of this study were as follows: Ki67, S100, extracapsular extension (ECE), perineural invasion (PNI), and surgical margin (SM). Patients were divided into training cohorts and validation cohorts in the ratio of 4:1 for each group. After lesion segmentation manually, radiomic features were extracted from MP-MRI images and some clinical factors were also included. Max relevance min redundancy (mRMR) and recursive feature elimination (RFE) based on random forest (RF) were adopted to select features. Six classifiers were included (SVM, KNN, RF, decision tree, logistic regression, XGBOOST) to find the best diagnostic performance among them. The diagnostic efficiency of the construction models was evaluated by ROC curves and quantified by AUC. Results RF performed best among the six classifiers for the four groups according to AUC values (Ki67 = 0.87, S100 = 0.80, ECE = 0.85, PNI = 0.82). The performance of SVM was relatively the best for SM (AUC = 0.77). The number and importance of DCE features ranked first in the models of each group. The combined models of MP-MRI and clinical characteristics showed no significant difference compared with MP-MRI models according to Delong’s tests. Conclusions Radiomics models based on MP-MRI have the potential to predict biological characteristics and are expected to be a noninvasive method to evaluate the risk stratification of prostate cancer.
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Affiliation(s)
- Xuhui Fan
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ni Xie
- Institution for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingwen Chen
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiewen Li
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong Cao
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongwei Yu
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Meijuan He
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zilin Wang
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yihui Wang
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hao Liu
- Department of Research and Development, Yizhun Medical AI Technology Co. Ltd., Beijing, China
| | - Han Wang
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Institution for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Radiology, Jiading Branch of Shanghai General Hospital, Shanghai, China
| | - Xiaorui Yin
- Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Yuan J, Poon DMC, Lo G, Wong OL, Cheung KY, Yu SK. A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer. Quant Imaging Med Surg 2022; 12:1585-1607. [PMID: 35111651 PMCID: PMC8739116 DOI: 10.21037/qims-21-697] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 08/20/2021] [Indexed: 08/24/2023]
Abstract
Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.
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Affiliation(s)
- Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Darren M. C. Poon
- Comprehensive Oncology Centre, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Gladys Lo
- Department of Diagnostic & Interventional Radiology, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
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Urakami A, Arimura H, Takayama Y, Kinoshita F, Ninomiya K, Imada K, Watanabe S, Nishie A, Oda Y, Ishigami K. Stratification of prostate cancer patients into low- and high-grade groups using multiparametric magnetic resonance radiomics with dynamic contrast-enhanced image joint histograms. Prostate 2022; 82:330-344. [PMID: 35014713 DOI: 10.1002/pros.24278] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 11/09/2021] [Accepted: 11/23/2021] [Indexed: 01/04/2023]
Abstract
PURPOSE This study aimed to investigate the potential of stratification of prostate cancer patients into low- and high-grade groups (GGs) using multiparametric magnetic resonance (mpMR) radiomics in conjunction with two-dimensional (2D) joint histograms computed with dynamic contrast-enhanced (DCE) images. METHODS A total of 101 prostate cancer regions extracted from the MR images of 44 patients were identified and divided into training (n = 31 with 72 cancer regions) and test datasets (n = 13 with 29 cancer regions). Each dataset included low-grade tumors (International Society of Urological Pathology [ISUP] GG ≤ 2) and high-grade tumors (ISUP GG ≥ 3). A total of 137,970 features consisted of mpMR image (16 types of images in four sequences)-based and joint histogram (DCE images at 10 phases)-based features for each cancer region. Joint histogram features can visualize temporally changing perfusion patterns in prostate cancer based on the joint histograms between different phases or subtraction phases of DCE images. Nine signatures (a set of significant features related to GGs) were determined using the best combinations of features selected using the least absolute shrinkage and selection operator. Further, support vector machine models with the nine signatures were built based on a leave-one-out cross-validation for the training dataset and evaluated with receiver operating characteristic (ROC) curve analysis. RESULTS The signature showing the best performance was constructed using six features derived from the joint histograms, DCE original images, and apparent diffusion coefficient maps. The areas under the ROC curves for the training and test datasets were 1.00 and 0.985, respectively. CONCLUSION This study suggests that the proposed approach with mpMR radiomics in conjunction with 2D joint histogram computed with DCE images could have the potential to stratify prostate cancer patients into low- and high-GGs.
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Affiliation(s)
- Akimasa Urakami
- Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hidetaka Arimura
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yukihisa Takayama
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Fumio Kinoshita
- Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kenta Ninomiya
- Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kenjiro Imada
- Department of Urology, Prostate, Kidney, Adrenal Surgery, Kyushu University Hospital, Fukuoka, Japan
| | - Sumiko Watanabe
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Akihiro Nishie
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoshinao Oda
- Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kousei Ishigami
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Greenberg JW, Koller CR, Casado C, Triche BL, Krane LS. A narrative review of biparametric MRI (bpMRI) implementation on screening, detection, and the overall accuracy for prostate cancer. Ther Adv Urol 2022; 14:17562872221096377. [PMID: 35531364 PMCID: PMC9073105 DOI: 10.1177/17562872221096377] [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: 12/30/2021] [Accepted: 03/31/2022] [Indexed: 11/17/2022] Open
Abstract
Prostate cancer is the most common malignancy in American men following skin cancer, with approximately one in eight men being diagnosed during their lifetime. Over the past several decades, the treatment of prostate cancer has evolved rapidly, so too has screening. Since the mid-2010s, magnetic resonance imaging (MRI)-guided biopsies or 'targeted biopsies' has been a rapidly growing topic of clinical research within the field of urologic oncology. The aim of this publication is to provide a review of biparametric MRI (bpMRI) utilization for the diagnosis of prostate cancer and a comparison to multiparametric MRI (mpMRI). Through single-centered studies and meta-analysis across all identified pertinent published literature, bpMRI is an effective tool for the screening and diagnosis of prostate cancer. When compared with the diagnostic accuracy of mpMRI, bpMRI identifies prostate cancer at comparable rates. In addition, when omitting dynamic contrast-enhanced (DCE) protocol to the MRI, patients incur reduced costs and shorter imaging time while providers can offer more tests to their patient population.
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Affiliation(s)
- Jacob W. Greenberg
- Department of Urology, Tulane University School of Medicine, New Orleans, LA, USA
| | | | - Crystal Casado
- Department of Urology, Tulane University School of Medicine, New Orleans, LA, USA
| | - Benjamin L. Triche
- Department of Radiology, Tulane University School of Medicine, New Orleans, LA, USA
| | - L. Spencer Krane
- Southeastern Louisiana Veterans Health Care System, 2400 Canal St., New Orleans, LA 70119, USA
- Department of Urology, Tulane University School of Medicine, New Orleans, LA, USA
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Holland MD, Morales A, Simmons S, Smith B, Misko SR, Jiang X, Hormuth DA, Christenson C, Koomullil RP, Morgan DE, Li Y, Xu J, Yankeelov TE, Kim H. Disposable point-of-care portable perfusion phantom for quantitative DCE-MRI. Med Phys 2021; 49:271-281. [PMID: 34802148 DOI: 10.1002/mp.15372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 10/12/2021] [Accepted: 11/05/2021] [Indexed: 12/30/2022] Open
Abstract
PURPOSE To develop a disposable point-of-care portable perfusion phantom (DP4) and validate its clinical utility in a multi-institutional setting for quantitative dynamic contrast-enhanced magnetic resonance imaging (qDCE-MRI). METHODS The DP4 phantom was designed for single-use and imaged concurrently with a human subject so that the phantom data can be utilized as the reference to detect errors in qDCE-MRI measurement of human tissues. The change of contrast-agent concentration in the phantom was measured using liquid chromatography-mass spectrometry. The repeatability of the contrast enhancement curve (CEC) was assessed with five phantoms in a single MRI scanner. Five healthy human subjects were recruited to evaluate the reproducibility of qDCE-MRI measurements. Each subject was imaged concurrently with the DP4 phantom at two institutes using three 3T MRI scanners from three different vendors. Pharmacokinetic (PK) parameters in the regions of liver, spleen, pancreas, and paravertebral muscle were calculated based on the Tofts model (TM), extended Tofts model (ETM), and shutter speed model (SSM). The reproducibility of each PK parameter over three measurements was evaluated with the intraclass correlation coefficient (ICC) and compared before and after DP4-based error correction. RESULTS The contrast-agent concentration in the DP4 phantom was linearly increased over 10 min (0.17 mM/min, measurement accuracy: 96%) after injecting gadoteridol (100 mM) at a constant rate (0.24 ml/s, 4 ml). The repeatability of the CEC within the phantom was 0.997 when assessed by the ICC. The reproducibility of the volume transfer constant, Ktrans , was the highest of the PK parameters regardless of the PK models. The ICCs of Ktrans in the TM, ETM, and SSM before DP4-based error correction were 0.34, 0.39, and 0.72, respectively, while those increased to 0.93, 0.98, and 0.86, respectively, after correction. CONCLUSIONS The DP4 phantom is reliable, portable, and capable of significantly improving the reproducibility of qDCE-MRI measurements.
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Affiliation(s)
- Martin D Holland
- Interdisciplinary Engineering, University of Alabama, Birmingham, Alabama, USA
| | - Andres Morales
- Engineering and Innovative Technology Development, University of Alabama, Birmingham, Alabama, USA
| | | | - Brandon Smith
- Engineering and Innovative Technology Development, University of Alabama, Birmingham, Alabama, USA
| | - Samuel R Misko
- Engineering and Innovative Technology Development, University of Alabama, Birmingham, Alabama, USA
| | - Xiaoyu Jiang
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - David A Hormuth
- The Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas, USA
| | - Chase Christenson
- The Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas, USA
| | - Roy P Koomullil
- Department of Mechanical Engineering, University of Alabama, Birmingham, Alabama, USA
| | - Desiree E Morgan
- Department of Radiology, University of Alabama, Birmingham, Alabama, USA
| | - Yufeng Li
- Department of Preventive Medicine, University of Alabama, Birmingham, Alabama, USA
| | - Junzhong Xu
- Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Thomas E Yankeelov
- The Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas, USA
| | - Harrison Kim
- Department of Radiology, University of Alabama, Birmingham, Alabama, USA
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Tan J, Sun X, Wang S, Ma B, Chen Z, Shi Y, Zhang L, Shah MA. Evaluation of Angiogenesis and Pathological Classification of Extrahepatic Cholangiocarcinoma by Dynamic MR Imaging for E-Healthcare. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:8666498. [PMID: 34671450 PMCID: PMC8523230 DOI: 10.1155/2021/8666498] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 08/07/2021] [Accepted: 09/01/2021] [Indexed: 12/16/2022]
Abstract
For staging cholangiocarcinoma and determining respectability, MR is an accurate noninvasive method which provides size of tumor and vascular patency information. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive inspection method for evaluating the vascular structure and functional characteristics of tumor tissue. However, some limitations should be noted about the technology. At present, the technology cannot be used alone, which is just an assisted method during the conventional MRI examination. 50 ECC patients, admitted to Indira Gandhi Medical College and Hospital between 2016 and 2019, were selected as research subjects. They were classified pathologically according to the Steiner classification system. After image processing, regions of interest (ROIs) were selected from the image to measure the rate constant (Kep), extravascular space volume fraction (Ve), and tissue volume transfer constant (Ktrans). There were 15 cases with highly differentiated carcinoma, 23 cases with moderately differentiated carcinoma, and 12 cases with lowly differentiated carcinoma. Non-VEGF expression was noted in 21 cases, with low expression noted in 15 cases, moderate expression noted in 14 cases, and no high expression case noted. The relevant parameters in the dynamic MRI image can quantitatively reflect the angiogenesis and pathological classification of ECC, which is suggested in the clinical treatment of ECC. The Ktrans, Kep, and Ve values of the ECC patients were all not associated with the pathological classification, with no significant difference (P < 0.05). Besides, due to the fact that the patient cannot completely hold his breath, the air leak reduces the image quality.
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Affiliation(s)
- Jinyun Tan
- Department of Hepatobiliary and Pancreatic Surgery, Lanzhou Second People's Hospital, Lanzhou, Gansu Province, China
| | - Xijun Sun
- Department of Medical Imaging, The Second People's Hospital of Lanzhou, Lanzhou, Gansu Province, China
| | - Shaoyu Wang
- MR Scientific Marketing,Siemens Healthineers, Shanghai, China
| | - Baoqin Ma
- Department of Medical Imaging, The Second People's Hospital of Lanzhou, Lanzhou, Gansu Province, China
| | - Zhaohui Chen
- Department of Medical Imaging, The Second People's Hospital of Lanzhou, Lanzhou, Gansu Province, China
| | - Yaowei Shi
- Department of Hepatobiliary and Pancreatic Surgery, Lanzhou Second People's Hospital, Lanzhou, Gansu Province, China
| | - Li Zhang
- Department of Medical Imaging, The Second People's Hospital of Lanzhou, Lanzhou, Gansu Province, China
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Pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI in PI-RADS category 3 peripheral zone lesions: preliminary study evaluating DCE-MRI as an imaging biomarker for detection of clinically significant prostate cancers. Abdom Radiol (NY) 2021; 46:4370-4380. [PMID: 33818626 DOI: 10.1007/s00261-021-03035-6] [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: 10/25/2020] [Revised: 02/25/2021] [Accepted: 03/03/2021] [Indexed: 01/21/2023]
Abstract
PURPOSE To determine if pharmacokinetic modeling of DCE-MRI can diagnose CS-PCa in PI-RADS category 3 PZ lesions with subjective negative DCE-MRI. MATERIALS AND METHODS In the present IRB approved, bi-institutional, retrospective, case-control study, we identified 73 men with 73 PZ PI-RADS version 2.1 category 3 lesions with MRI-directed-TRUS-guided targeted biopsy yielding: 12 PZ CS-PCa (ISUP Grade Group 2; N = 9, ISUP 3; N = 3), 27 ISUP 1 PCa and 34 benign lesions. An expert blinded radiologist segmented lesions on ADC and DCE images; segmentations were overlayed onto pharmacokinetic DCE-MRI maps. Mean values were compared between groups using univariate analysis. Diagnostic accuracy was assessed by ROC. RESULTS There were no differences in age, PSA, PSAD or clinical stage between groups (p = 0.265-0.645). Mean and 10th percentile ADC did not differ comparing CS-PCa to ISUP 1 PCa and benign lesions (p = 0.376 and 0.598) but was lower comparing ISUP ≥ 1 PCa to benign lesions (p < 0.001). Mean Ktrans (p = 0.003), Ve (p = 0.003) but not Kep (p = 0.387) were higher in CS-PCa compared to ISUP 1 PCa and benign lesions. There were no differences in DCE-MRI metrics comparing ISUP ≥ 1 PCa and benign lesions (p > 0.05). AUC for diagnosis of CS-PCa using Ktrans and Ve were: 0.69 (95% CI 0.52-0.87) and 0.69 (0.49-0.88). CONCLUSION Pharmacokinetic modeling of DCE-MRI parameters in PI-RADS category 3 lesions with subjectively negative DCE-MRI show significant differences comparing CS-PCa to ISUP 1 PCa and benign lesions, in this study outperforming ADC. Studies are required to further evaluate these parameters to determine which patients should undergo targeted biopsy for PI-RADS 3 lesions.
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Challenges in the Use of Artificial Intelligence for Prostate Cancer Diagnosis from Multiparametric Imaging Data. Cancers (Basel) 2021; 13:cancers13163944. [PMID: 34439099 PMCID: PMC8391234 DOI: 10.3390/cancers13163944] [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: 06/29/2021] [Revised: 08/02/2021] [Accepted: 08/02/2021] [Indexed: 11/18/2022] Open
Abstract
Simple Summary Prostate Cancer is one of the main threats to men’s health. Its accurate diagnosis is crucial to properly treat patients depending on the cancer’s level of aggressiveness. Tumor risk-stratification is still a challenging task due to the difficulties met during the reading of multi-parametric Magnetic Resonance Images. Artificial Intelligence models may help radiologists in staging the aggressiveness of the equivocal lesions, reducing inter-observer variability and evaluation time. However, these algorithms need many high-quality images to work efficiently, bringing up overfitting and lack of standardization and reproducibility as emerging issues to be addressed. This study attempts to illustrate the state of the art of current research of Artificial Intelligence methods to stratify prostate cancer for its clinical significance suggesting how widespread use of public databases could be a possible solution to these issues. Abstract Many efforts have been carried out for the standardization of multiparametric Magnetic Resonance (mp-MR) images evaluation to detect Prostate Cancer (PCa), and specifically to differentiate levels of aggressiveness, a crucial aspect for clinical decision-making. Prostate Imaging—Reporting and Data System (PI-RADS) has contributed noteworthily to this aim. Nevertheless, as pointed out by the European Association of Urology (EAU 2020), the PI-RADS still has limitations mainly due to the moderate inter-reader reproducibility of mp-MRI. In recent years, many aspects in the diagnosis of cancer have taken advantage of the use of Artificial Intelligence (AI) such as detection, segmentation of organs and/or lesions, and characterization. Here a focus on AI as a potentially important tool for the aim of standardization and reproducibility in the characterization of PCa by mp-MRI is reported. AI includes methods such as Machine Learning and Deep learning techniques that have shown to be successful in classifying mp-MR images, with similar performances obtained by radiologists. Nevertheless, they perform differently depending on the acquisition system and protocol used. Besides, these methods need a large number of samples that cover most of the variability of the lesion aspect and zone to avoid overfitting. The use of publicly available datasets could improve AI performance to achieve a higher level of generalizability, exploiting large numbers of cases and a big range of variability in the images. Here we explore the promise and the advantages, as well as emphasizing the pitfall and the warnings, outlined in some recent studies that attempted to classify clinically significant PCa and indolent lesions using AI methods. Specifically, we focus on the overfitting issue due to the scarcity of data and the lack of standardization and reproducibility in every step of the mp-MR image acquisition and the classifier implementation. In the end, we point out that a solution can be found in the use of publicly available datasets, whose usage has already been promoted by some important initiatives. Our future perspective is that AI models may become reliable tools for clinicians in PCa diagnosis, reducing inter-observer variability and evaluation time.
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Sathiadoss P, Schieda N, Haroon M, Osman H, Alrasheed S, Flood TA, Melkus G. Utility of Quantitative T2-Mapping Compared to Conventional and Advanced Diffusion Weighted Imaging Techniques for Multiparametric Prostate MRI in Men with Hip Prosthesis. J Magn Reson Imaging 2021; 55:265-274. [PMID: 34223675 DOI: 10.1002/jmri.27803] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/11/2021] [Accepted: 06/11/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Diffusion weighted imaging (DWI) is fundamental for prostate cancer (PCa) detection with MRI; however, limited by susceptibility artifact from hip prosthesis. PURPOSE To evaluate image quality and ability to detect PCa with quantitative T2-mapping and DWI in men with hip prosthesis undergoing prostate MRI. STUDY TYPE Prospective, cross-sectional study. POPULATION Thirty consecutive men with hip replacement (18 unilateral, 12 bilateral) undergoing prostate MRI from 2019 to 2021. FIELD STRENGTH/SEQUENCE 3-T; multiparametric MRI (T2W, DCE-MRI, echo-planar [EPI]-DWI), T2-mapping (Carr-Purcell-Meiboom-Gill), FOCUS-EPI-DWI, PROPELLER-DWI. ASSESSMENT Five blinded radiologists independently evaluated MRI image quality using a 5-point Likert scale. PI-RADS v2.1 scores were applied in four interpretation strategies: 1) T2W-FSE+DCE-MRI+EPI-DWI, 2) T2W-FSE+DCE-MRI+EPI-DWI+FOCUS-EPI-DWI, 3) T2W-FSE+DCE-MRI+EPI-DWI+PROPELLER-DWI, 4) T2W-FSE+DCE-MRI+EPI-DWI+T2-maps. Five-point confidence scores were recorded. STATISTICAL ANALYSIS ANOVA, Kruskal-Wallis with pair-wise comparisons by Wilcoxon sign-rank, and paired t-tests, P < 0.05 was considered significant. Cohen's Kappa (k) for PI-RADSv2.1 scoring and proportion of correctly classified lesions tabulated for pathology-confirmed cases with 95% confidence intervals (CIs). RESULTS For all radiologists, T2-map image quality was significantly higher than EPI-DWI, FOCUS-EPI-DWI, and PROPELLER-DWI and similar (P = 0.146-0.706) or significantly better (for two readers) than T2W-FSE and DCE-MRI. PI-RADS v2.1 agreement improved comparing strategy A (k = 0.46) to strategy B (k = 0.58) to strategy C (k = 0.58) and was highest with strategy D which included T2-maps (k = 1.00). Radiologists' confidence was significantly highest with strategy D. Strategies B and C had similar confidence (P = 0.051-0.063) both significantly outperforming strategy A. Twelve men with 17 lesions had pathology confirmed diagnoses (13 PCa, 4 benign). Strategy D had the highest proportion of correctly classified lesions (76.5-82.4%) with overlapping 95% confidence intervals. DATA CONCLUSION T2-mapping may be a valuable adjunct to prostate MRI in men with hip replacement resulting in improved image quality, higher reader confidence, interobserver agreement, and accuracy in PI-RADS scoring. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Paul Sathiadoss
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Mohammad Haroon
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Heba Osman
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Sumaya Alrasheed
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Trevor A Flood
- Department of Anatomical Pathology, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Gerd Melkus
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
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Wei M, Bo F, Cao H, Zhou W, Shan W, Bai G. Diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging for malignant ovarian tumors: a systematic review and meta-analysis. Acta Radiol 2021; 62:966-978. [PMID: 32741199 DOI: 10.1177/0284185120944916] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Accurate preoperative diagnosis of malignant ovarian tumors (MOTs) is particularly important for selecting the optimal treatment strategy and avoiding overtreatment. PURPOSE To evaluate the diagnostic efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for MOTs. MATERIAL AND METHODS A systematic search was performed in PubMed, Embase, the Cochrane Library, and Web of Science databases to find relevant original articles up to October 2019. The included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Studies on the diagnosis of MOTs with quantitative or semi-quantitative DCE-MRI were analyzed separately. The bivariate random-effects model was used to assess the diagnostic authenticity. Meta-regression analyses were performed to analyze the potential heterogeneity. RESULTS For semi-quantitative DCE-MRI, the pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic curves (AUC) were 85% (95% confidence interval [CI] 0.75-0.92), 85% (95% CI 0.77-0.91), 5.8 (95% CI 3.8-8.8), 0.17 (95% CI 0.10-0.30), 33 (95% CI 18-61), and 0.92 (95% CI 0.89-0.94), respectively. For quantitative DCE-MRI, the pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 88% (95% CI 0.65-0.96), 93% (95% CI 0.78-0.98), 12.3 (95% CI 3.4-43.9), 0.13 (95% CI 0.04-0.45), 91 (95% CI 10-857), and 0.96 (95% CI 0.94-0.98), respectively. CONCLUSION DCE-MRI has great diagnostic value for MOTs. Semi-quantitative DCE-MRI may be a relatively mature approach; however, quantitative DCE-MRI appears to be more promising than semi-quantitative DCE-MRI.
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Affiliation(s)
- Mingxiang Wei
- Department of Radiology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China
| | - Fan Bo
- Department of Radiology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China
| | - Hui Cao
- Department of Radiology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China
| | - Wei Zhou
- Department of Radiology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China
| | - Wenli Shan
- Department of Radiology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China
| | - Genji Bai
- Department of Radiology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China
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Wu J, Zhu Y, Zhang X, Wang X, Zhang J. An automatic framework for evaluating the vascular permeability of bone metastases from prostate cancer. Phys Med Biol 2021; 66. [PMID: 34010811 DOI: 10.1088/1361-6560/ac02d3] [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: 04/29/2021] [Accepted: 05/19/2021] [Indexed: 11/11/2022]
Abstract
Objectives.Vascular permeability can reflect tumorigenesis and metastasis. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess microvascular permeability by pharmacokinetic parameter estimation. Most estimation methods require manually selected arterial input function (AIF) or reference regions. However, the result will be unstable due to the annotation, which relies on personal experience. In this study, we propose an automatic framework for evaluating vascular permeability of bone metastases from prostate cancer without selecting AIF.Materials and methods.This retrospective study comprised of 15 prostate cancer patients with bone metastases. Based on clinical consensus for three typical DCE-MRI curve patterns, three characteristic curves as regularization constraints were introduced to the extended Tofts model (ETM) using clustering strategy, and the clustering-based blind identification of multichannel (CBM) framework was then proposed for pharmacokinetic parameter estimation. With automatic segmentation of the whole bone area, we obtained the estimation of the pharmacokinetic parameters in the bone area and quantified for bone metastases. Two experienced radiologists compared the CBM estimations with the diagnostic results and we compared the estimations with those of the ETM in bone metastasis regions to evaluate the feasibility of the CBM framework.Results.The higher signal regions ofKtransandKepindicated the metastasis of prostate cancer, which is consistent with the cancer area marked by the radiologists. In addition, theKtransandKepin bone metastasis regions were significantly higher than in normal bone regions (P < 0.001,P < 0.001). The consistency of estimation by using the CBM framework and conventional ETM method was confirmed by Bland-Altman analysis.Conclusion.The proposed CBM framework can provide a fully automatic and reliable quantitative estimation of vascular permeability for bone metastases in prostate cancer patients.
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Affiliation(s)
- Junjie Wu
- College of Engineering, Peking University, Beijing, People's Republic of China
| | - Yi Zhu
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Xiaodong Zhang
- Department of Radiology, Peking University First Hospital, Beijing, People's Republic of China
| | - Xiaoying Wang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China.,Department of Radiology, Peking University First Hospital, Beijing, People's Republic of China
| | - Jue Zhang
- College of Engineering, Peking University, Beijing, People's Republic of China.,Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
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Wang YF, Tadimalla S, Hayden AJ, Holloway L, Haworth A. Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment. J Med Imaging Radiat Oncol 2021; 65:612-626. [PMID: 34060219 DOI: 10.1111/1754-9485.13242] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/18/2021] [Accepted: 05/02/2021] [Indexed: 12/15/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.
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Affiliation(s)
- Yu-Feng Wang
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Sirisha Tadimalla
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Amy J Hayden
- Sydney West Radiation Oncology, Westmead Hospital, Wentworthville, New South Wales, Australia
- Faculty of Medicine, Western Sydney University, Sydney, New South Wales, Australia
- Faculty of Medicine, Health & Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
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Zhao J, Kader A, Mangarova DB, Brangsch J, Brenner W, Hamm B, Makowski MR. Dynamic Contrast-Enhanced MRI of Prostate Lesions of Simultaneous [ 68Ga]Ga-PSMA-11 PET/MRI: Comparison between Intraprostatic Lesions and Correlation between Perfusion Parameters. Cancers (Basel) 2021; 13:1404. [PMID: 33808685 PMCID: PMC8003484 DOI: 10.3390/cancers13061404] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 02/25/2021] [Accepted: 03/16/2021] [Indexed: 11/29/2022] Open
Abstract
We aimed to retrospectively compare the perfusion parameters measured from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of prostate benign lesions and malignant lesions to determine the relationship between perfusion parameters. DCE-MRI was performed in patients with PCa who underwent simultaneous [68Ga]Ga-prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/MRI. Six perfusion parameters (arrival time (AT), time to peak (TTP), wash-in slope (W-in), wash-out slope (W-out), peak enhancement intensity (PEI), and initial area under the 60-s curve (iAUC)), and a semi-quantitative parameter, standardized uptake values maximum (SUVmax) were calculated by placing regions of interest in the largest area of the lesions. The DCE-MRI parameters between prostate benign and malignant lesions were compared. The DCE-MRI parameters in both the benign and malignant lesions subgroup with SUVmax ≤ 3.0 and SUVmax > 3.0 were compared. The correlation of DCE-MRI parameters was investigated. Malignant lesions demonstrated significantly shorter TTP and higher SUVmax than did benign lesions. In the benign and malignant lesions subgroup, perfusion parameters of lesions with SUVmax ≤ 3.0 show no significant difference to those with SUVmax > 3.0. DCE-MRI perfusion parameters show a close correlation with each other. DCE-MRI parameters reflect the perfusion characteristics of intraprostatic lesions with malignant lesions, demonstrating significantly shorter TTP. There is a moderate to strong correlation between DCE-MRI parameters. Semi-quantitative analysis reflects that malignant lesions show a significantly higher SUVmax than benign lesions.
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Affiliation(s)
- Jing Zhao
- Institute of Radiology and Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (A.K.); (D.B.M.); (J.B.); (B.H.); (M.R.M.)
| | - Avan Kader
- Institute of Radiology and Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (A.K.); (D.B.M.); (J.B.); (B.H.); (M.R.M.)
- Department of Biology, Chemistry and Pharmacy, Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, 14195 Berlin, Germany
| | - Dilyana B. Mangarova
- Institute of Radiology and Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (A.K.); (D.B.M.); (J.B.); (B.H.); (M.R.M.)
- Department of Veterinary Medicine, Institute of Veterinary Pathology, Freie Universität Berlin, Robert-von-Ostertag-Str. 15, Building 12, 14163 Berlin, Germany
| | - Julia Brangsch
- Institute of Radiology and Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (A.K.); (D.B.M.); (J.B.); (B.H.); (M.R.M.)
| | - Winfried Brenner
- Department of Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Augustenburger Platz 1, 13353 Berlin, Germany;
| | - Bernd Hamm
- Institute of Radiology and Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (A.K.); (D.B.M.); (J.B.); (B.H.); (M.R.M.)
| | - Marcus R. Makowski
- Institute of Radiology and Nuclear Medicine, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany; (A.K.); (D.B.M.); (J.B.); (B.H.); (M.R.M.)
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 Munich, Germany
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Kamsut S, Reid K, Tan N. Roundtable: arguments in support of using multi-parametric prostate MRI protocol. Abdom Radiol (NY) 2020; 45:3990-3996. [PMID: 32385623 DOI: 10.1007/s00261-020-02543-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
There is increasing evidence to suggest the value of bi-parametric prostate MRI to replace multi-parametric MRI, which includes the dynamic contrast enhancement (DCE) sequence. In this review, we discuss the value of DCE in select scenarios, specifically in resolving equivocal cases, improving the diagnostic accuracy in the inexperienced reader, rescuing exams in the settings of failed T2W and DWI, detecting biochemical recurrence, while imposing minimal to no risk to the patient with respect to IV gadolinium use, specifically group II agents.
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Affiliation(s)
- Sirisin Kamsut
- Loma Linda University School of Medicine, Loma Linda, CA, USA
| | - Kimberly Reid
- Loma Linda University School of Medicine, Loma Linda, CA, USA
| | - Nelly Tan
- Loma Linda University School of Medicine, Loma Linda, CA, USA.
- Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ, 85054, USA.
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40
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Udayakumar N, Porter KK. How Fast Can We Go: Abbreviated Prostate MR Protocols. Curr Urol Rep 2020; 21:59. [PMID: 33135121 DOI: 10.1007/s11934-020-01008-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/15/2020] [Indexed: 12/27/2022]
Abstract
PURPOSE OF REVIEW Multiparametric MRI (mpMRI), composed of T2WI, DWI, and DCE sequences, is effective in identifying prostate cancer (PCa), but length and cost preclude its application as a PCa screening tool. Here we review abbreviated MRI protocols that shorten or omit conventional mpMRI components to reduce scan time and expense without forgoing diagnostic accuracy. RECENT FINDINGS The DCE sequence, which plays a limited diagnostic role in PI-RADS, is eliminated in variations of the biparametric MRI (bpMRI). T2WI, the lengthiest sequence, is truncated by only acquiring the axial plane or utilizing 3D acquisition with subsequent 2D reconstruction. DW-EPISMS further accelerates DWI acquisition. The fastest protocol described to date consists of just DW-EPISMS and axial-only 2D T2WI and runs less than 5 min. Abbreviated protocols can mitigate scan expense and increase scan access, allowing prostate MRI to become an efficient PCa screening tool.
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Affiliation(s)
- Neha Udayakumar
- University of Alabama at Birmingham School of Medicine, 1720 2nd Ave S, Birmingham, AL, 35249, USA
| | - Kristin K Porter
- Department of Radiology, University of Alabama at Birmingham, 619 19th Street S, JT N374, Birmingham, AL, 35249, USA.
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41
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Magnetic resonance imaging of the prostate after focal therapy with high-intensity focused ultrasound. Abdom Radiol (NY) 2020; 45:3882-3895. [PMID: 32447414 DOI: 10.1007/s00261-020-02577-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
For clinically significant, locally confined prostate cancer, whole-gland radical prostatectomy and radiotherapy are established effective treatment strategies that, however, come at a cost of significant morbidity related to urinary and sexual side effects. The concept of risk stratification paired with a better understanding of prognostic factors has led to the development of alternative management options including active surveillance and focal therapy for appropriately selected patients with localized disease. High-intensity focused ultrasound (HIFU) is one such minimally invasive, image-guided treatment option for prostate cancer. Due to the relative novelty of HIFU and the increased use of magnetic resonance imaging in prostate cancer, many radiologists are not yet familiar with imaging findings related to HIFU, their temporal evolution as well as imaging appearance of recurrent disease after this type of focal therapy. HIFU induces sharply demarcated, localized coagulative necrosis of a tumor through thermal energy delivered via an endorectal or transurethral ultrasound transducer. In this pictorial review, we aim at providing relevant background information that will guide the reader through the general principles of HIFU in the prostate, as well as demonstrate the imaging appearance of expected post-HIFU changes versus recurrent tumor.
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42
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Zhu J, Liang Z, Song Y, Yang Y, Xu Y, Lu Y, Hu R, Ou N, Zhang W, Liu X. Can the combination of biparametric magnetic resonance imaging and PSA-related indicators predict the prostate biopsy outcome? Andrologia 2020; 52:e13734. [PMID: 32609397 DOI: 10.1111/and.13734] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 04/18/2020] [Accepted: 05/31/2020] [Indexed: 11/30/2022] Open
Abstract
To assess the value of biparametric magnetic resonance imaging (bpMRI) for detecting and ruling out prostate cancer in patients with elevated prostate-specific antigen (PSA). The basic information and bpMRI images of enrolled patients who took transperineal template saturate biopsy were retrospectively collected for analysis. Based on our results, we found that free/total PSA, and PI-RADS score were independent risk factors of PCa (p < .05), the PSA density, PI-RADS score were the independent risk factors of csPCa (p < .05). PI-RADS score threshold of 3 could achieve the highest Yonder index for predicting PCa, and PI-RADS score threshold of 4 could achieve the highest Yonder index for predicting csPCa. Therefore, we draw a conclusion that PI-RADSv2 score-based bpMRI could diminish the unnecessary prostate biopsies in patients with elevated PSA when combined with other PSA-related indicators.
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Affiliation(s)
- Jun Zhu
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhen Liang
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuxuan Song
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Yongjiao Yang
- Urology Department, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yawei Xu
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Yi Lu
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Rui Hu
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Ningjing Ou
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Zhang
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaoqiang Liu
- Urology Department, Tianjin Medical University General Hospital, Tianjin, China
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Liang Z, Hu R, Yang Y, An N, Duo X, Liu Z, Shi S, Liu X. Is dynamic contrast enhancement still necessary in multiparametric magnetic resonance for diagnosis of prostate cancer: a systematic review and meta-analysis. Transl Androl Urol 2020; 9:553-573. [PMID: 32420161 PMCID: PMC7215029 DOI: 10.21037/tau.2020.02.03] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Background The purpose of this study is to systematically review the literatures assessing the value of dynamic contrast enhancement (DCE) in the multiparametric magnetic resonance imaging (mpMRI) for the diagnosis of prostate cancer (PCa). Methods We searched Embase, PubMed and Web of science until January 2019 to extract articles exploring the possibilities whether the pre-biopsy biparametric magnetic resonance imaging (bpMRI) can replace the position of mpMRI in the diagnosis of PCa. The sensitivity and specificity of bpMRI were all included. The study quality was assessed by QUADAS-2. Bivariate random effects meta-analyses and a hierarchical summary receiver operating characteristic plot were performed for further study through Revman 5 and Stata12. Results After searching, we acquired 752 articles among which 45 studies with 5,217 participants were eligible for inclusion. The positive likelihood ratio for the detection of PCa was 2.40 (95% CI: 1.50–3.80) and the negative likelihood ratio was 0.31 (95% CI: 0.18–0.53). The sensitivity and specificity were 0.77 (95% CI: 0.73–0.81) and 0.81 (95% CI: 0.76–0.85) respectively. Based on our result, pooled specificity demonstrated little difference between bpMRI and mpMRI [bpMRI, 0.81 (95% CI, 0.76–0.85); mpMRI, 0.82 (95% CI, 0.72–0.88); P=0.169]. The sensitivity, however, indicated a significant difference between these two groups [bpMRI, 0.77 (95% CI, 0.73–0.81); mpMRI, 0.84 (95% CI, 0.78–0.89); P=0.001]. Conclusions bpMRI with high b-value is a sensitive tool for diagnosing PCa. Consistent results were found in multiple subgroup analysis.
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Affiliation(s)
- Zhen Liang
- Department of Urology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Rui Hu
- Department of Urology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Yongjiao Yang
- Department of Urology, Tianjin Medical University Second Hospital, Tianjin 300000, China
| | - Neng An
- Department of Urology, Tianjin Medical University Second Hospital, Tianjin 300000, China
| | - Xiaoxin Duo
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China
| | - Zheng Liu
- Department of Rheumatology and Immunology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Shangheng Shi
- Department of Transplantation, Affiliated Hospital of Medical College Qingdao University, Qingdao 266000, China
| | - Xiaoqiang Liu
- Department of Urology, Tianjin Medical University General Hospital, Tianjin 300000, China
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Onwuharine EN, Clark AJ. Comparison of double inversion recovery magnetic resonance imaging (DIR-MRI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in detection of prostate cancer: A pilot study. Radiography (Lond) 2020; 26:234-239. [PMID: 32052752 DOI: 10.1016/j.radi.2019.12.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 12/12/2019] [Accepted: 12/16/2019] [Indexed: 01/09/2023]
Abstract
INTRODUCTION DCE-MRI is established for detecting prostate cancer (PCa). However, it requires a gadolinium contrast agent, with potential risks for patients. The application of DIR-MRI is simple and may allow cancer detection without the use of an intravenous contrast agent by differentially nullifying signal from normal and abnormal prostate tissue, creating contrast between the cancer and background normal prostate. In this pilot study we gathered data from DIR-MRI and DCE-MRI of the prostate for an equivalence trial. We also looked at how the DIR-MRI appearance varies with the aggressiveness of PCa. METHOD DIR-MRI and DCE-MRI were acquired. The images were assessed by an experienced Consultant Radiologist and a novice reporter (Radiographer). The potential PCa lesions were quantified using a lesion to normal ratio (LNR). Radiological pathological correlation was made to identify the MRI lesions that represented significant PCa. A Wilcoxon sign rank was used to compare DCE-LNR and DIR-LNR for PCa containing lesions. Pearson's correlation was used to look at the relationship between DIR-LNR and PCa grade group (aggressiveness). RESULTS DCE-LNR and DIR-LNR were found to be significantly different (Z = -5.910, p < 0.001). However, a significant correlation was found between PCa grade group and DIR-LNR. CONCLUSION DIR and DCE sequences are not equivalent and significant cancer is more conspicuous on the DCE sequence. However, DIR-LNR does correlate with PCa aggressiveness. IMPLICATIONS FOR PRACTICE With the correlation of PCa grade group with DIR-LNR this may be a useful sequence in evaluation of the prostate; stratifying the risk of there being clinically significant PCa before biopsy is performed. Furthermore, given that DIR-LNR appears to predict PCa aggressiveness DIR might be used as part of a multiparametric MRI protocol designed to avoid biopsy.
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Affiliation(s)
- E N Onwuharine
- Radiology Department, University Hospitals of North Midlands (UHNM) NHS Trust, UK.
| | - A J Clark
- Radiology Department, University Hospitals of North Midlands (UHNM) NHS Trust, UK.
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Hectors SJ, Said D, Gnerre J, Tewari A, Taouli B. Luminal Water Imaging: Comparison With Diffusion-Weighted Imaging (DWI) and PI-RADS for Characterization of Prostate Cancer Aggressiveness. J Magn Reson Imaging 2020; 52:271-279. [PMID: 31961049 DOI: 10.1002/jmri.27050] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 12/14/2019] [Accepted: 12/16/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Luminal water imaging (LWI), a multicomponent T2 mapping technique, has shown promise for prostate cancer (PCa) detection and characterization. PURPOSE To 1) quantify LWI parameters and apparent diffusion coefficient (ADC) in PCa and benign peripheral zone (PZ) tissues; and 2) evaluate the diagnostic performance of LWI, ADC, and PI-RADS parameters for differentiation between low- and high-grade PCa lesions. STUDY TYPE Prospective. SUBJECTS Twenty-six PCa patients undergoing prostatectomy (mean age 59 years, range 46-72 years). FIELD STRENGTH/SEQUENCE Multiparametric MRI at 3.0T, including diffusion-weighted imaging (DWI) and LWI T2 mapping. ASSESSMENT LWI parameters and ADC were quantified in index PCa lesions and benign PZ. STATISTICAL TESTS Differences in MRI parameters between PCa and benign PZ were assessed using Wilcoxon signed tests. Spearman correlation of pathological grade group (GG) with LWI parameters, ADC, and PI-RADS was evaluated. The utility of each of the parameters for differentiation between low-grade (GG ≤2) and high-grade (GG ≥3) PCa was determined by Mann-Whitney U tests and ROC analyses. RESULTS Twenty-six index lesions were analyzed (mean size 1.7 ± 0.8 cm, GG: 1 [n = 1; 4%], 2 [n = 14, 54%], 3 [n = 8, 31%], 5 [n = 3, 12%]). LWI parameters and ADC both showed high diagnostic performance for differentiation between benign PZ and PCa (highest area under the curve [AUC] for LWI parameter T2,short [AUC = 0.98, P < 0.001]). The LWI parameters luminal water fraction (LWF) and amplitude of long T2 component Along significantly correlated with GG (r = -0.441, P = 0.024 and r = -0.414, P = 0.036, respectively), while PI-RADS, ADC, and the other LWI parameters did not (P = 0.132-0.869). LWF and Along also showed significant differences between low-grade and high-grade PCa (AUC = 0.776, P = 0.008 and AUC = 0.758, P = 0.027, respectively). Maximum diagnostic performance for discrimination of high-grade PCa was found with combined LWI parameters (AUC 0.891, P = 0.001). DATA CONCLUSION LWI parameters, in particular in combination, showed superior diagnostic performance for differentiation between low-grade and high-grade PCa compared to ADC and PI-RADS assessment. J. Magn. Reson. Imaging 2020;52:271-279.
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Affiliation(s)
- Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Daniela Said
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Universidad de los Andes, Santiago, Chile
| | - Jeffrey Gnerre
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ashutosh Tewari
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Lu Y, Peng W, Song J, Chen T, Wang X, Hou Z, Yan Z, Koh TS. On the potential use of dynamic contrast-enhanced (DCE) MRI parameters as radiomic features of cervical cancer. Med Phys 2019; 46:5098-5109. [PMID: 31523829 DOI: 10.1002/mp.13821] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 07/30/2019] [Accepted: 09/05/2019] [Indexed: 12/26/2022] Open
Abstract
PURPOSE To evaluate whether the analysis of high-temporal resolution DCE-MRI by various tracer kinetic models could yield useful radiomic features in discriminating cervix carcinoma and normal cervix tissue. METHODS Forty-three patients (median age 51 yr; range 26-78 yr) diagnosed with cervical cancer based on postoperative pathology were enrolled in this study with informed consent. DCE-MRI data with temporal resolution of 2 s were acquired and analyzed using the Tofts (TOFTS), extended Tofts (EXTOFTS), conventional two-compartment (CC), adiabatic tissue homogeneity (ATH), and distributed parameter (DP) models. Ability of all kinetic parameters in distinguishing tumor from normal tissue was assessed using Mann-Whitney U test and receiver operating characteristic (ROC) curves. Repeatability of parameter estimates due to sampling of arterial input functions (AIFs) was also studied using intraclass correlation (ICC) analysis. RESULTS Fractional extravascular, extracellular volume (Ve) of all models were significantly smaller in cervix carcinoma than normal cervix tissue, and were associated with large values of area under ROC curve (AUC 0.884-0.961). Capillary permeability PS derived from the ATH, CC, and DP models also yielded large AUC values (0.730, 0.860, and 0.797). Transfer constant Ktrans derived from TOFTS and EXTOFTS models yielded smaller AUC (0.587 and 0.701). Repeatability of parameters derived from all models was robust to AIF sampling, with ICC coefficients typically larger than 0.80. CONCLUSIONS With the use of high-temporal resolution DCE-MRI, all tracer kinetic models could reflect pathophysiological differences between cervix carcinoma and normal tissue (with significant differences in Ve and PS) and potentially yield radiomic features with diagnostic value.
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Affiliation(s)
- Yi Lu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Wenwen Peng
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Jiao Song
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Tao Chen
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Xue Wang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Zujun Hou
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China
| | - Tong San Koh
- Department of Oncologic Imaging, National Cancer Centre, 247969, Singapore, Singapore
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Peled S, Vangel M, Kikinis R, Tempany CM, Fennessy FM, Fedorov A. Selection of Fitting Model and Arterial Input Function for Repeatability in Dynamic Contrast-Enhanced Prostate MRI. Acad Radiol 2019; 26:e241-e251. [PMID: 30467073 DOI: 10.1016/j.acra.2018.10.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 10/19/2018] [Accepted: 10/21/2018] [Indexed: 12/18/2022]
Abstract
RATIONALE AND OBJECTIVES Analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging is notable for the variability of calculated parameters. The purpose of this study was to evaluate the level of measurement variability and error/variability due to modeling in DCE magnetic resonance imaging parameters. MATERIALS AND METHODS Two prostate DCE scans were performed on 11 treatment-naïve patients with suspected or confirmed prostate peripheral zone cancer within an interval of less than two weeks. Tumor-suspicious and normal-appearing regions of interest (ROI) in the prostate peripheral zone were segmented. Different Tofts-Kety based models and different arterial input functions, with and without bolus arrival time (BAT) correction, were used to extract pharmacokinetic parameters. The percent repeatability coefficient (%RC) of fitted model parameters Ktrans, ve, and kep was calculated. Paired t-tests comparing parameters in tumor-suspicious ROIs and in normal-appearing tissue evaluated each parameter's sensitivity to pathology. RESULTS Although goodness-of-fit criteria favored the four-parameter extended Tofts-Kety model with the BAT correction included, the simplest two-parameter Tofts-Kety model overall yielded the best repeatability scores. The best %RC in the tumor-suspicious ROI was 63% for kep, 28% for ve, and 83% for Ktrans . The best p values for discrimination between tissues were p <10-5 for kep and Ktrans, and p = 0.11 for ve. Addition of the BAT correction to the models did not improve repeatability. CONCLUSION The parameter kep, using an arterial input functions directly measured from blood signals, was more repeatable than Ktrans. Both Ktrans and kep values were highly discriminatory between healthy and diseased tissues in all cases. The parameter ve had high repeatability but could not distinguish the two tissue types.
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Shi Z, Han J, Qin J, Zhang Y. Clinical application of diffusion-weighted imaging and dynamic contrast-enhanced MRI in assessing the clinical curative effect of early ankylosing spondylitis. Medicine (Baltimore) 2019; 98:e15227. [PMID: 31096431 PMCID: PMC6531155 DOI: 10.1097/md.0000000000015227] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
The study aimed to demonstrate the clinical application value of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing a clinical curative effect of early ankylosing spondylitis (AS).Forty-eight patients with early AS who were already treated combinations by traditional Chinese and Western medicine were involved in this study. All subjects underwent the conventional MRI, DWI, and DCE-MRI scanning of bilateral sacroiliac joints before and after treatment. The relevant data, such as the mean apparent diffusion coefficient (ADC) value, time-intensity curve of subarticular surface bone marrow, and the relationship between ADC value and enhancement factor (Fenh), enhancement slope (Senh), and time to peak (TTP), were obtained.1. The mean ADC value of the subarticular surface bone marrow of patients and after clinical treatment was (5.05 ± 1.10) × 10 and (4.34 ± 0.55) × 10 mm/s in ilium and (4.63 ± 0.79) × 10 and (3.96 ± 0.23) × 10 mm/s in sacrum, respectively. 2. In the DCE-MRI follow-up treatment imaging of 48 patients with AS (192 parts), the TIC curve type recorded was as follows: 43.75% (84/192) of type II, 56.25% (108/192) of type III, and type I curve was not seen. The number of type II curve was significantly reduced for pre treatment group (84 cases) compared with that post treatment group (124 cases). The Fenh, Senh, and TTP values were respective (113.38 ± 44.71)%, (60.94 ± 38.56)% min, (129.52 ± 42.66) s in ilium and (83.03 ± 20.39)%, (44.91 ± 15.19)% min, (123.44 ± 28.50) s in sacrum before clinical treatment. After the treatment, the Fenh, Senh, and TTP values were respective (75.90 ± 17.97)%, (33.96 ± 11.36)% min, (138.67 ± 26.60) s in ilium and (73.28 ± 15.67)%, (31.92 ± 8.15)% min, (140.19 ± 19.88) s in sacrum. The Fenh, Senh, and TTP values of semiquantitative indexes before and after clinical treatment were significantly different.DWI and DCE-MRI sequences can help evaluate the degree of active changes in AS inflammation and treatment effect in patients with early AS, and provide reliable imaging evidence.
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Affiliation(s)
- Zhaojuan Shi
- Department of Nuclear Medicine, Qilu Hospital, Shandong University, Jinan
- Department of Diagnostic Radiology, Affiliated Hospital of Taishan Medical University, Taian, Shandong, China
| | - Jiankui Han
- Department of Nuclear Medicine, Qilu Hospital, Shandong University, Jinan
| | - Jian Qin
- Department of Diagnostic Radiology, Affiliated Hospital of Taishan Medical University, Taian, Shandong, China
| | - Yue Zhang
- Department of Diagnostic Radiology, Affiliated Hospital of Taishan Medical University, Taian, Shandong, China
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Magnetic Resonance Angiography Shows Increased Arterial Blood Supply Associated with Murine Mammary Cancer. Int J Biomed Imaging 2019; 2019:5987425. [PMID: 30792738 PMCID: PMC6354161 DOI: 10.1155/2019/5987425] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 01/06/2019] [Indexed: 12/20/2022] Open
Abstract
Breast cancer is a major cause of morbidity and mortality in Western women. Tumor neoangiogenesis, the formation of new blood vessels from pre-existing ones, may be used as a prognostic marker for cancer progression. Clinical practice uses dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to detect cancers based on increased blood flow and capillary permeability. However, DCE-MRI requires repeated injections of contrast media. Therefore we explored the use of noninvasive time-of-flight (TOF) MR angiography for serial studies of mouse mammary glands to measure the number and size of arteries feeding mammary glands with and without cancer. Virgin female C3(1) SV40 TAg mice (n=9), aged 18-20 weeks, were imaged on a 9.4 Tesla small animal scanner. Multislice T2-weighted (T2W) images and TOF-MRI angiograms were acquired over inguinal mouse mammary glands. The data were analyzed to determine tumor burden in each mammary gland and the volume of arteries feeding each mammary gland. After in vivo MRI, inguinal mammary glands were excised and fixed in formalin for histology. TOF angiography detected arteries with a diameter as small as 0.1 mm feeding the mammary glands. A significant correlation (r=0.79; p< 0.0001) was found between tumor volume and the arterial blood volume measured in mammary glands. Mammary arterial blood volumes ranging from 0.08 mm3 to 3.81 mm3 were measured. Tumors and blood vessels found on in vivo T2W and TOF images, respectively, were confirmed with ex vivo histological images. These results demonstrate increased recruitment of arteries to mammary glands with cancer, likely associated with neoangiogenesis. Neoangiogenesis may be detected by TOF angiography without injection of contrast agents. This would be very useful in mouse models where repeat placement of I.V. lines is challenging. In addition, analogous methods could be tested in humans to evaluate the vasculature of suspicious lesions without using contrast agents.
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Dappa E, Elger T, Hasenburg A, Düber C, Battista MJ, Hötker AM. The value of advanced MRI techniques in the assessment of cervical cancer: a review. Insights Imaging 2017; 8:471-481. [PMID: 28828723 PMCID: PMC5621992 DOI: 10.1007/s13244-017-0567-0] [Citation(s) in RCA: 81] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Revised: 07/18/2017] [Accepted: 07/18/2017] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVES To assess the value of new magnetic resonance imaging (MRI) techniques in cervical cancer. METHODS We searched PubMed and MEDLINE and reviewed articles published from 1990 to 2016 to identify studies that used MRI techniques, such as diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and dynamic contrast enhancement (DCE) MRI, to assess parametric invasion, to detect lymph node metastases, tumour subtype and grading, and to detect and predict tumour recurrence. RESULTS Seventy-nine studies were included. The additional use of DWI improved the accuracy and sensitivity of the evaluation of parametrial extension. Most studies reported improved detection of nodal metastases. Functional MRI techniques have the potential to assess tumour subtypes and tumour grade differentiation, and they showed additional value in detecting and predicting treatment response. Limitations included a lack of technical standardisation, which limits reproducibility. CONCLUSIONS New advanced MRI techniques allow improved analysis of tumour biology and the tumour microenvironment. They can improve TNM staging and show promise for tumour classification and for assessing the risk of tumour recurrence. They may be helpful for developing optimised and personalised therapy for patients with cervical cancer. TEACHING POINTS • Conventional MRI plays a key role in the evaluation of cervical cancer. • DWI improves tumour delineation and detection of nodal metastases in cervical cancer. • Advanced MRI techniques show promise regarding histological grading and subtype differentiation. • Tumour ADC is a potential biomarker for response to treatment.
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Affiliation(s)
- Evelyn Dappa
- Department of Diagnostic and Interventional Radiology, Johannes Gutenberg-University Medical Centre, Langenbeckstr. 1, 55131, Mainz, Germany.
| | - Tania Elger
- Department of Gynaecology and Obstetrics, Johannes Gutenberg-University Medical Centre, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Annette Hasenburg
- Department of Gynaecology and Obstetrics, Johannes Gutenberg-University Medical Centre, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Christoph Düber
- Department of Diagnostic and Interventional Radiology, Johannes Gutenberg-University Medical Centre, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Marco J Battista
- Department of Gynaecology and Obstetrics, Johannes Gutenberg-University Medical Centre, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Andreas M Hötker
- Department of Diagnostic and Interventional Radiology, Johannes Gutenberg-University Medical Centre, Langenbeckstr. 1, 55131, Mainz, Germany
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