Purpose To evaluate MRI features associated with pathologically defined extraprostatic extension (EPE) of prostate cancer and to propose an MRI grading system for pathologic EPE. Materials and Methods In this prospective study, consecutive male study participants underwent preoperative 3. 0-T MRI from June 2007 to March 2017 followed by robotic-assisted laparoscopic radical prostatectomy. An MRI-based EPE grading system was defined as follows: curvilinear contact length of 1.5 cm or capsular bulge and irregularity were grade 1, both features were grade 2, and frank capsular breach were grade 3. Multivariable logistic regression and decision curve analyses were performed to compare the MRI grade model and clinical parameters (prostate-specific antigen, Gleason score) for pathologic EPE prediction by using the area under the receiver operating characteristic curve (AUC) value. Results Among 553 study participants, the mean age was 60 years ± 8 (standard deviation); the median prostate-specific antigen value was 6.3 ng/mL. A total of 125 of 553 (22%) participants had pathologic EPE at radical prostatectomy. Detection of pathologic EPE, defined as number of pathologic EPEs divided by number of participants with individual MRI features, was as follows: curvilinear contact length, 88 of 208 (42%); capsular bulge and irregularity, 78 of 175 (45%); and EPE visible at MRI, 37 of 56 (66%). For MRI, grades 1, 2, and 3 for detection of pathologic EPE were 18 of 74 (24%), 39 of 102 (38%), and 37 of 56 (66%), respectively. Clinical features plus the MRI-based EPE grading system (prostate-specific antigen, International Society of Urological Pathology stage, MRI grade) predicted pathologic EPE better than did MRI grade alone (AUC, 0.81 vs 0.77, respectively; P < .001). Conclusion Higher MRI-based extraprostatic extension (EPE) grading categories were associated with a greater risk of pathologic EPE. Clinical features plus MRI grading had the highest diagnostic performance for prediction of pathologic EPE. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Eberhardt in this issue.
Radiology. 2019 Jan 22 [Epub]
Sherif Mehralivand, Joanna H Shih, Stephanie Harmon, Clayton Smith, Jonathan Bloom, Marcin Czarniecki, Samuel Gold, Graham Hale, Kareem Rayn, Maria J Merino, Bradford J Wood, Peter A Pinto, Peter L Choyke, Baris Turkbey
From the Department of Urology and Pediatric Urology, University Medical Center, Mainz, Germany (S.M.); Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Md (S.M., J.B., S.G., G.H., K.R., P.A.P.); Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182, Building 10, Room B3B85, Bethesda, MD 20892-1088 (S.M., C.S., M.C., P.L.C., B.T.); Division of Cancer Treatment and Diagnosis: Biometric Research Program, National Cancer Institute, National Institutes of Health, Rockville, Md (J.H.S.); Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, NCI Campus at Frederick, Frederick, Md (S.H.); Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, Md (M.J.M.); and Center for Interventional Oncology, National Cancer Institute and Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Md (B.J.W.).