Optimising preoperative risk stratification tools for prostate cancer using mpMRI.

Purpose: To improve preoperative risk stratification for prostate cancer (PCa) by incorporating multiparametric MRI (mpMRI) features into risk stratification tools for PCa, CAPRA and D'Amico.

Methods: 807 consecutive patients operated on by robot-assisted radical prostatectomy at our institution during the period 2010-2015 were followed to identify biochemical recurrence (BCR). 591 patients were eligible for final analysis. We employed stepwise backward likelihood methodology and penalised Cox cross-validation to identify the most significant predictors of BCR including mpMRI features. mpMRI features were then integrated into image-adjusted (IA) risk prediction models and the two risk prediction tools were then evaluated both with and without image adjustment using receiver operating characteristics, survival and decision curve analyses.

Results: 37 patients suffered BCR. Apparent diffusion coefficient (ADC) and radiological extraprostatic extension (rEPE) from mpMRI were both significant predictors of BCR. Both IA prediction models reallocated more than 20% of intermediate-risk patients to the low-risk group, reducing their estimated cumulative BCR risk from approximately 5% to 1.1%. Both IA models showed improved prognostic performance with a better separation of the survival curves.

Conclusion: Integrating ADC and rEPE from mpMRI of the prostate into risk stratification tools improves preoperative risk estimation for BCR.

Key Points: • MRI-derived features, ADC and EPE, improve risk stratification of biochemical recurrence. • Using mpMRI to stratify prostate cancer patients improves the differentiation between risk groups. • Using preoperative mpMRI will help urologists in selecting the most appropriate treatment.