The integration of artificial intelligence (AI) and radiomics in managing urological cancers such as bladder, kidney, and prostate cancers represents a significant advancement in personalized cancer care. This review discusses how AI’s rapid data processing and the detailed image analysis provided by radiomics are enhancing diagnosis and treatment strategies, thereby moving toward more tailored and patient-specific medical interventions. The technologies are notably improving diagnostic accuracy and the staging of diseases such as bladder cancer through enhanced imaging techniques like multiparametric MRI and CT scans.

Furthermore, in kidney and prostate cancers, AI and radiomics assist in distinguishing between different cancer subtypes and grades, enhancing the understanding of disease biology through the integration of radiogenomics, which combines imaging features with genetic data, leading to more personalized therapeutic approaches. The review also addresses significant challenges in the clinical integration of these technologies, including the need for standardization, ensuring high data quality, and overcoming the opaque nature of AI processes. It advocates for continuous research and multicenter collaborations to improve the applicability and accuracy of these technologies in diverse clinical settings.

Reference: Feretzakis G, Juliebø-Jones P, Tsaturyan A, et al. Emerging Trends in AI and Radiomics for Bladder, Kidney, and Prostate Cancer: A Critical Review. Cancers (Basel). 2024;16(4):810. doi: 10.3390/cancers16040810