# Non-Invasive Detection of Prostate Cancer with Novel Time-Dependent Diffusion MRI and AI-Enhanced Quantitative Radiological Interpretation: PROS-TD-AI

## TL;DR

This study introduces a new AI-enhanced MRI method called PROS-TD-AI to improve the detection of significant prostate cancer beyond standard techniques.

## Contribution

The novel contribution is an AI workflow integrating time-dependent diffusion MRI metrics for zone-aware prostate cancer risk prediction.

## Key findings

- PROS-TD-AI will be evaluated for its diagnostic accuracy in detecting clinically significant prostate cancer.
- The method aims to outperform PI-RADS v2.1 in routine clinical MRI interpretation.
- Time-dependent diffusion MRI provides microstructural data to enhance cancer characterization.

## Abstract

Prostate cancer (PCa) is the most common malignancy in men worldwide. Multiparametric MRI (mpMRI) improves the detection of clinically significant PCa (csPCa); however, it remains limited by false-positive findings and inter-observer variability. Time-dependent diffusion (TDD) MRI provides microstructural information that may enhance csPCa characterization beyond standard mpMRI. This prospective observational diagnostic accuracy study protocol describes the evaluation of PROS-TD-AI, an in-house developed AI workflow integrating TDD-derived metrics for zone-aware csPCa risk prediction. PROS-TD-AI will be compared with PI-RADS v2.1 in routine clinical imaging using MRI-targeted prostate biopsy as the reference standard.