Applications of Artificial Intelligence in Prostate Cancer Radiotherapy: A Narrative Review

Abstract

Introduction: Radiotherapy (RT) plays a crucial role in the management of prostate cancer (PC). Artificial intelligence (AI) is reshaping cancer care by providing innovative tools for diagnosis, treatment optimization, and outcome prediction. This review provides an end-to-end synthesis of AI applications across the prostate RT workflow, critically evaluating their clinical maturity, level of evidence, and current barriers to real-world implementation. Methods: A literature review of PubMed/MEDLINE and Embase was conducted to investigate the impact of AI on prostate RT. Only original articles published up to 1 August 2025 were included. The 27 selected studies were categorized into the following clusters: adaptive radiotherapy, autocontouring, autoplanning, prediction, synthetic computed tomography (CT), quality assurance (QA), and tracking. Results: Autocontouring was the most represented cluster, followed by prediction, autoplanning, and adaptive RT. Fewer studies addressed tracking, QA, and synthetic CT. Conclusions: AI shows significant potential across multiple phases of the prostate RT workflow; however, most evidence is based on retrospective or technical validation studies. Further research is required to establish clinical benefit and support integration into personalized treatment strategies.

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