# Validation of the Barcelona Magnetic Resonance Imaging Predictive Model for Significant Prostate Cancer Detection in Men Undergoing Mapping per 0.5 Mm-Core Targeted Biopsies of Suspicious Lesions and Perilesional Areas

## TL;DR

A predictive model using MRI data accurately identifies significant prostate cancer, reducing unnecessary biopsies while maintaining high detection rates.

## Contribution

The study validates the BCN-MRI predictive model's accuracy and clinical utility in a new biopsy protocol setting.

## Key findings

- The BCN-MRI model achieved an AUC of 0.862 for detecting significant prostate cancer.
- The model reduced unnecessary biopsies by 24.9% while maintaining 95% detection sensitivity.
- Calibration showed strong alignment between predicted and observed cancer probabilities.

## Abstract

The validation of predictive models is essential for informing clinical decisions, particularly in new individual populations or as diagnostic methods advance. This study evaluates the performance of the Barcelona-MRI predictive model (BCN-MRI PM) for identifying significant prostate cancer (sPCa) within the context of an advanced prostate biopsy protocol. In a cohort of 457 men suspected of having PCa, the model demonstrated high accuracy and clinical applicability, reducing unnece-ssary biopsies by 24.9% while maintaining a 95% detection rate for sPCa. These results validate the efficacy of the BCN-MRI PM and support its readiness for clinical implementation in this diagnostic framework.

Background/Objectives: Validation of predictive models (PMs) is crucial to be implemented in new populations or when advances in diagnostic approaches occurred. The aim of this study is to validate the BCN-MRI PM for sPCa when a highly effective prostate biopsy protocol is used. Methods: A prospective cohort of 457 men suspected of having PCa, for whom MRI results were reported with the Prostate Imaging-Reporting and Data System (PI-RADS) v 2.1, underwent a per 0.5 mm-core mapping targeted biopsy of suspicious lesions and perilesional areas, followed by a 12-core-systematic biopsy. These procedures took place between 1 February 2022, and 29 February 2024, at a reference center for prostate biopsy. The individual likelihood of sPCa was assessed through the BCN-MRI risk calculator. Results: The overall sPCa detection rate was 58.3%. The calibration curve of the BCN-MRI PM showed an appropriate accuracy between expected and observed probabilities with a discrimination ability for sPCa yielding an area under the curve (AUC) of 0.862 (95% CI 0.828–0.896) comparable to the AUC of 0.858 (95% CI 0.833–0.883) observed in the development cohort. The application of the BCN-MRI PM provided a net benefit over performing biopsies on all men, avoiding 24.9% of prostate biopsies at 95% sensitivity for sPCa, compared to the 23.7% reduction observed in the development cohort. Conclusions: We conclude that the BCN-MRI PM is ready to be implemented when this biopsy protocol is employed.