Outsmarting Metastatic Prostate Cancer: Integration of Imaging, Liquid Biopsies and Biomarkers With Artificial Intelligence
Management of metastatic prostate cancer (mPCa) poses significant challenges due to inherent tumor heterogeneity and therapeutic resistance. Advances in molecular imaging, liquid biopsies, and biomarkers are enabling precision oncology, while artificial intelligence (AI), including machine learning (ML) and deep learning (DL), integrates complex datasets to improve diagnostic accuracy, risk stratification, and treatment guidance. This review highlights AI's applications in mPCa, focusing on imaging, cell-free nucleic acids, circulating tumor cells, and genomic classifiers. We emphasize AI's role in enhancing diagnostics and personalizing treatments, with implications for improving clinical outcomes through better decision-making. Finally, we discuss opportunities and challenges in deploying AI systems, stressing multimodal integration and validation for real-world clinical impact.
Authors
- Jingyi He (ORCID: https://orcid.org/0000-0002-2407-7446)
- Tanziela Tanziela (ORCID: https://orcid.org/0000-0002-7991-9620)
- Jonghoon Chang
- Wensi Tao (ORCID: https://orcid.org/0000-0003-2396-9829)
- Nai-Kei Wong (ORCID: https://orcid.org/0000-0003-1303-3170)
- Shuhong Chen (ORCID: https://orcid.org/0000-0001-6648-6486)
- Wesley Burrow
- Luyuan Li
- Rong-Jun Chen
- R. Daniel Bonfil
- Chang Liu
- Jia-Le Zhuang
Institutions
- Nova Southeastern University (US)
- Shantou University (CN)
- Guangzhou University (CN)
- Shantou University Medical College (CN)
- University of South Alabama Medical Center (US)
Publication Details
- Journal
- Technology in Cancer Research & Treatment
- Published
- 2026-04-01
- DOI
- https://doi.org/10.1177/15330338261440434
- Primary Topic
- Prostate Cancer Treatment and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shantou University
- National Natural Science Foundation of China
- Shantou University Medical College