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Life sciences · Journal article
Artificial Intelligence Surgery · September 22, 2026
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With increasing detection and longer survival in localized prostate cancer (PCa), treatment goals increasingly emphasize preserving urinary continence and sexual function without compromising oncological control. This review synthesizes evidence on function-preserving strategies, focusing on minimally invasive radical prostatectomy, focal ablation, and artificial intelligence (AI)-assisted surgery. Laparoscopic and robot-assisted radical prostatectomy remain the principal radical approaches; multiport robot-assisted surgery has the most mature evidence for balancing cancer control and functional recovery. Relevant refinements include nerve-sparing, fluorescence imaging, three-dimensional reconstruction, and AI-assisted risk stratification, planning, navigation, and outcome prediction. In carefully selected patients with low- or intermediate-risk disease, focal therapies may reduce treatment burden and preserve function. Focal therapy is not yet a standard option for localized prostate cancer, but it may be discussed during shared decision-making with carefully selected, fully informed patients. Some focal modalities are already used in selected clinical settings, including outside formal trials where locally permitted, although implementation varies across health-care systems. Counseling should address limitations in long-term evidence, the need for structured surveillance, and possible repeat or salvage treatment. Heterogeneous selection, endpoints, and follow-up, together with a lack of high-quality head-to-head comparisons, preclude reliable ranking of focal modalities; sexual recovery and long-term oncological durability also vary. Direct evidence that AI improves nerve preservation, continence, erectile function, or margin control remains insufficient for routine adoption. Optimal function preservation requires risk-adapted selection, technical expertise, multidisciplinary decision-making, and rigorous follow-up. Future studies should prospectively validate AI tools and standardize imaging, outcomes, and clinically meaningful endpoints.