14 Background: Our practice utilizes a biopsy-based 17 gene test that is clinically validated as a predictor of favorable pathology and used to guide use of active surveillance for men with very low, low, and intermediate risk prostate cancer. The purpose of this study was to evaluate the imaging characteristics and PIRADS score of prostate cancer patients with a Genomic Prostate Score (GPS) indicating favorable pathology. Methods: 300 consecutive 3T Multiparametric Prostate MRI (MP-MRI) were identified from March 26, 2012, to June 29, 2015. Thirty patients (age 44-84 years) with GPS scores indicating favorable pathology were included in the study. Prostate Imaging Reporting and Data System (PIRADS) scores were assigned to each MP-MRI. MRI index lesions were defined as discrete hypointense T2 signal with at least one anatomically corresponding abnormal functional MRI parameter (diffusion weighted and dynamic contrast-enhanced images). The MRI examinations were evaluated for number and laterality of MRI index lesions and in relation to biopsy pathology findings after the MP-MRI was performed. Results: Out of 30 MP-MRI, 7 (23.3%) PIRADS 5, 10 (33.3%) PIRADS 4, 10 (33.3%) PIRADS 3, 1 (3.3%) PIRADS 2, and 2 (6.7%) PIRADS 1. Thirteen (43%) had bilateral MRI index lesions. Twenty-six (87%) MP-MRI had 1-3 MRI index lesions, 2 (7%) had 4-6 MRI index lesions and 2 (7%) had no index lesions. Six (20%) patients underwent curative treatment. Four (13.3%) patients underwent a transrectal ultrasound guided targeted biopsy and one underwent a prostatectomy after the MP-MRI. One harbored Gleason 7 with a PIRADS 1, 2 harbored Gleason 7 with PIRADS 5, and two were benign with PIRADS scores of 3 and 4. Conclusions: Patients with prostate cancer with a GPS score indicating favorable pathology had PIRADS scores ranging from 5 to 1, with the majority indicating either high or very high likelihood of harboring clinically significant cancer. This may imply that MP-MRI should continue to play an important role in stratifying patients with prostate cancer, even in those with favorable pathology. A study with a larger sample size and biopsy results after the initial MP-MRI to look for tumor upgrading is needed.
An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study
