MP43-20 PREDICTING CANCER DETECTION RATES FROM MULTIPARAMETRIC PROSTATE MRI: REFINING BEYOND THE PI-RADS CLASSIFICATION SYSTEM

Abstract

You have accessJournal of UrologyProstate Cancer: Detection & Screening IV (MP43)1 Sep 2021MP43-20 PREDICTING CANCER DETECTION RATES FROM MULTIPARAMETRIC PROSTATE MRI: REFINING BEYOND THE PI-RADS CLASSIFICATION SYSTEM Francisco Ramos, Aaron Fleishman, Sumedh Kaul, Ruslan Korets, Michael Johnson, Aria Olumi, Leo Tsai, and Boris Gershman Francisco RamosFrancisco Ramos More articles by this author , Aaron FleishmanAaron Fleishman More articles by this author , Sumedh KaulSumedh Kaul More articles by this author , Ruslan KoretsRuslan Korets More articles by this author , Michael JohnsonMichael Johnson More articles by this author , Aria OlumiAria Olumi More articles by this author , Leo TsaiLeo Tsai More articles by this author , and Boris GershmanBoris Gershman More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002064.20AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The PI-RADS categorization represents the standardized method for assessing risk of prostate cancer using prostate MRI. However, there exists a discrepancy in widely accepted cancer detection rates (CDRs) as reported in seminal prospective studies (e.g., PROMIS, PRECISION) and CDRs observed in real-world practice. We hypothesized that CDRs vary according to patient and MRI features beyond what is captured in the PI-RADS categorization system. Herein, we examine the associations of clinical and radiographic features with CDRs and develop a predictive model to improve clinical management. METHODS: We identified men aged 18-89 with elevated PSA or Gleason 6 prostate cancer on active surveillance and ≥1 PI-RADS 3-5 lesion on prostate MRI who underwent MRI-U/S fusion biopsy or in-bore MRI-targeted biopsy. The associations of features with the per-lesion cancer-detection rate (CDR; Gleason 6-10) and clinically-significant cancer detection rate (csCDR; Gleason 7-10) were examined using logistic regression. To operationalize results, a predictive model was developed using lasso regression to minimize overfitting. Patients with Gleason 6 prostate cancer on active surveillance were included only in csCDR analyses. RESULTS: Targeted biopsy was performed for 347 lesions in 281 patients, including MRI-U/S fusion biopsy in 129 lesions and in-bore MRI-targeted biopsy in 218 lesions. Median pre-biopsy PSA was 7.1 ng/mL (IQR 5.1-10.0). 37.7% of patients had no prior prostate biopsy, while 24.2% were on active surveillance for Gleason 6 prostate cancer. PI-RADS category was 3 in 13.8%, 4 in 62.2%, and 5 in 23.9% of lesions. Lesions were located in the anterior/transition zone in 36.7% of cases, and median lesion diameter was 12 mm (IQR 8-16 mm). Overall, the CDR was 49.0% and the csCDR was 28.0%. Multivariable associations of features with CDR and csCDR are presented in Table 1. A predictive model developed with lasso regression demonstrated optimism adjusted c-statistics of 0.77 and 0.75 for CDR and csCDR, respectively. CONCLUSIONS: Several clinical and radiographic features were independently associated with risk of cancer in men undergoing MRI-targeted biopsy. These findings were operationalized into a predictive model to provide personalized risk-stratification beyond the PI-RADS categorization. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e790-e791 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Francisco Ramos More articles by this author Aaron Fleishman More articles by this author Sumedh Kaul More articles by this author Ruslan Korets More articles by this author Michael Johnson More articles by this author Aria Olumi More articles by this author Leo Tsai More articles by this author Boris Gershman More articles by this author Expand All Advertisement Loading ...