Study integrates pathological and imaging systems in prostate cancer for improved risk stratification, suggesting enhanced treatment decisions.
In the clinical management of prostate cancer, continuously refined scoring systems form the cornerstone of precise risk stratification. Pathological assessment systems, represented by the Gleason score and the International Society of Urological Pathology (ISUP) grade groups, have long been the cornerstone of prostate cancer risk stratification; however, they are subject to inherent limitations such as sampling bias and spatial heterogeneity. With advances in imaging technology, the PI-RADS scoring system based on multiparametric magnetic resonance imaging (mpMRI) has been widely adopted for the detection and localization of prostate cancer; however, inter-observer variability remains a significant issue in clinical practice. Concurrently, emerging functional imaging scoring systems based on PSMA-PET, such as PSMA-RADS and miTNM staging, have provided new tools for the precise staging of prostate cancer and restaging following biochemical recurrence. Currently, an increasing number of studies are attempting to integrate pathological and multimodal imaging information to construct comprehensive predictive models, thereby addressing the shortcomings of single-modality assessment methods, achieving more personalized and precise risk stratification, and ultimately optimizing treatment decisions and improving patient prognosis.
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Zhang et al. (2026) studied this question.
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