Comprehensive Summary
Grobholz et al. discusses how artificial intelligence is being used in modern prostate cancer diagnosis, more specifically in imaging and pathology. For instance, AI tools in prostate MRI have shown high levels of accuracy, similar to those of human experts, while reducing reading time and variability between readers. Reader-assisted AI can also spot suspicious lesions, support PI-RADS scoring, and help standardize reporting. In pathology, AI and pathologists have concluded similar results when it came to cancer detection and Gleason grading. However, both AI and human experts continue to struggle with certain features, especially Gleason pattern 4, which remains a major source of diagnostic variability. Some of these tools are now being tested in clinical trials and have begun to appear in guidelines, depicting integration of AI into real clinical settings.
Outcomes and Implications
This review shows that AI is moving from experimental research into real world clinical use in prostate cancer diagnostics. Instead of using AI as a replacement of human experts, it can be used as a support tool to improve consistency and access to high-quality diagnosis in both imaging and pathology. A major focus in the future is multimodal AI, as it brings various types of data together to improve patient treatment. Nonetheless, external validation and careful supervision are vital in order to integrate AI models into the majority of healthcare systems. AI’s role in prostate cancer should be an assistive technology that supports clinicians, rather than replacing them.