AI-driven precision in prostate brachytherapy: A systematic review of 70 studies
Artificial intelligence (AI) has transformed prostate brachytherapy by enhancing precision, efficiency, and personalization. This systematic review evaluates 70 peer-reviewed studies from PubMed, Embase, and Web of Science, focusing on the applications of AI in imaging, treatment planning, applicator reconstruction, and outcome prediction. Machine learning (ML) and deep learning (DL) techniques, including U-Net and deep reinforcement learning, demonstrate improvements in segmentation (84% sensitivity), dose optimization (20-30% time savings), and quality assurance (25% error reduction). Challenges include limited dataset diversity, generalizability, and clinical integration. This review highlights AI's potential to revolutionize prostate brachytherapy and identifies research gaps necessary for its clinical adoption.
Authors
- Vibhay Pareek
- Nikunj Patil
- Carlton Johnny (ORCID: https://orcid.org/0000-0003-0756-4493)
- Bashir M. Bashir
- Sheen Dube
- Florence Mutua (ORCID: https://orcid.org/0000-0002-8115-9376)
Institutions
- CancerCare Manitoba (CA)
- The University of Winnipeg (CA)
Publication Details
- Journal
- Journal of Cancer Research and Therapeutics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.4103/jcrt.jcrt_1996_25
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00