Sonia Gaur1, Stephanie Harmon2, Lauren Rosenblum1, Matthew D Greer1, Sherif Mehralivand3, Mehmet Coskun4, Maria J Merino1, Bradford J Wood5, Joanna H Shih6, Peter A Pinto3, Peter L Choyke1, Baris Turkbey1. 1. 1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, Rm B3B85, Bethesda, MD 20814. 2. 2 Clinical Research Directorate, Clinical Monitoring Research Program, Leidos Biomedical Research, National Cancer Institute, Frederick, MD. 3. 3 Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD. 4. 4 İzmir Katip Çelebi University, Atatürk Training and Research Hospital, Izmir, Turkey. 5. 5 Center for Interventional Oncology, Clinical Center, National Institutes of Health, Bethesda, MD. 6. 6 Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD.
Abstract
OBJECTIVE: The purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines. MATERIALS AND METHODS: In this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each reader's PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone. RESULTS: ADC metrics negatively correlated with ISUP category in the whole prostate (ADC, τ = -0.21, p = 0.0002; normalized ADC, τ = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, τ = -0.34; normalized ADC, τ = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader. CONCLUSION: ADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.
OBJECTIVE: The purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines. MATERIALS AND METHODS: In this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each reader's PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone. RESULTS:ADC metrics negatively correlated with ISUP category in the whole prostate (ADC, τ = -0.21, p = 0.0002; normalized ADC, τ = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, τ = -0.34; normalized ADC, τ = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader. CONCLUSION:ADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.
Entities:
Keywords:
International Society of Urological Pathology; PI-RADS; apparent diffusion coefficient; multiparametric MRI; prostate
Authors: Edward M Lawrence; Ferdia A Gallagher; Tristan Barrett; Anne Y Warren; Andrew N Priest; Debra A Goldman; Deborah Goldman; Evis Sala; Vincent J Gnanapragasam Journal: AJR Am J Roentgenol Date: 2014-09 Impact factor: 3.959
Authors: Andrew B Rosenkrantz; Luke A Ginocchio; Daniel Cornfeld; Adam T Froemming; Rajan T Gupta; Baris Turkbey; Antonio C Westphalen; James S Babb; Daniel J Margolis Journal: Radiology Date: 2016-04-01 Impact factor: 11.105
Authors: M Minhaj Siddiqui; Soroush Rais-Bahrami; Baris Turkbey; Arvin K George; Jason Rothwax; Nabeel Shakir; Chinonyerem Okoro; Dima Raskolnikov; Howard L Parnes; W Marston Linehan; Maria J Merino; Richard M Simon; Peter L Choyke; Bradford J Wood; Peter A Pinto Journal: JAMA Date: 2015-01-27 Impact factor: 56.272
Authors: Baris Turkbey; Vijay P Shah; Yuxi Pang; Marcelino Bernardo; Sheng Xu; Jochen Kruecker; Julia Locklin; Angelo A Baccala; Ardeshir R Rastinehad; Maria J Merino; Joanna H Shih; Bradford J Wood; Peter A Pinto; Peter L Choyke Journal: Radiology Date: 2010-12-21 Impact factor: 11.105
Authors: Kirema Garcia-Reyes; Niccolò M Passoni; Mark L Palmeri; Christopher R Kauffman; Kingshuk Roy Choudhury; Thomas J Polascik; Rajan T Gupta Journal: Abdom Imaging Date: 2015-01
Authors: Antonio C Westphalen; Farhad Fazel; Hao Nguyen; Miguel Cabarrus; Katryana Hanley-Knutson; Katsuto Shinohara; Peter R Carroll Journal: Int Braz J Urol Date: 2019 Jul-Aug Impact factor: 1.541
Authors: Gehad Ahmad Saleh; Ahmed Abdel Khalek Abdel Razek; Lamiaa Galal El-Serougy; Walaa Shabana; Rihame Abd El-Wahab Journal: Pol J Radiol Date: 2022-01-17
Authors: Riccardo Laudicella; Jan H Rüschoff; Niels J Rupp; Irene A Burger; Daniela A Ferraro; Muriel D Brada; Daniel Hausmann; Iliana Mebert; Alexander Maurer; Thomas Hermanns; Daniel Eberli Journal: Eur J Nucl Med Mol Imaging Date: 2022-04-18 Impact factor: 10.057