Prediction of Postsurgical Progression of Prostate Cancer Using MRI Cancer Risk Maps

Motivation: Biochemical recurrence (BCR) remains a significant concern for patients after radical prostatectomy. Goal(s): This study’s objective was to determine whether automated mpMRI cancer risk maps could predict postsurgical prostate cancer (PCa) progression (Biochemical Recurrence (BCR). Approach: Derived lesion volumes and mpMRI parameters from the cancer risk maps were used to analyze factors for BCR. Results: A decision tree model for BCR was generated with sensitivity = 0.81, specificity = 0.82, and ROC AUC = 0.85. The prediction results indicate the potential of mpMRI and PCa risk maps to improve prediction of BCR after prostatectomy. Impact: In this study we used preprostatectomy multiparametric MRI (mpMRI) cancer risk maps to analyze potential predictors of postsurgical prostate cancer (PCa) progression (Biochemical Recurrence (BCR) or treatment failure). A decision tree model was generated with ROC AUC 0.85.