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

Journal of Imaging 2026 Open access

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Authors: Baltasar Ramos, Cristián Garrido, Paulette Narváez, Santiago Gelerstein-Claro, Haotian Li, R. Salvador, Constanza Vásquez-Venegas, Iván Gallegos, Víctor Castañeda, Cristian Acevedo, Gonzalo Cárdenas, Claudio Sotomayor
DOI: 10.3390/jimaging12010053
Cited by: 2
References: 45

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.

Fields of Study & Subjects

Prostate Cancer Diagnosis and Treatment MRI in cancer diagnosis Advanced Neuroimaging Techniques and Applications

Publication details

Journal / source
Journal of Imaging
Publisher
MDPI AG
Volume
12
Issue
1
Pages
53–53
Publication date
22 January 2026
Language
EN