Non-Invasive Detection of Prostate Cancer with Novel Time-Dependent Diffusion MRI and AI-Enhanced Quantitative Radiological Interpretation: PROS-TD-AI
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.
Authors
- Gonzalo Cárdenas (ORCID: https://orcid.org/0000-0002-5531-2533)
- Claudio Sotomayor
- Baltasar Ramos (ORCID: https://orcid.org/0009-0001-6750-1518)
- Constanza Vásquez-Venegas (ORCID: https://orcid.org/0000-0003-0052-7649)
- Cristián Garrido
- Haotian Li
- Santiago Gelerstein Claro
- Iván Gallegos
- Víctor Castañeda
- Cristian Acevedo
- Paulette Narváez
Institutions
- Universidad de Santiago de Chile (CL)
- San Sebastián University (CL)
- Colegio Médico de Chile (CL)
- Hospital Clínic de Barcelona (ES)
- Hospital Clínico de la Universidad de Chile (CL)
- Clínica Dávila (CL)
- Millennium Institute for Integrative Biology (CL)
- University of Chile (CL)
- Universitat de Barcelona (ES)
- Zhejiang University (CN)
Publication Details
- Journal
- Journal of Imaging
- Published
- 2026-01-22
- DOI
- https://doi.org/10.3390/jimaging12010053
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00