AI-based CT assessment of sarcopenia in borderline resectable pancreatic Cancer: A narrative review of clinical and technical perspectives.

Fiche publication

Date publication

juin 2025

Journal

Computers in biology and medicine

Auteurs

Membres identifiés du Cancéropôle Est :
Dr LAMBERT Aurélien

Tous les auteurs :
Gehin W, Lambert A, Bibault JE

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/40570765

Résumé

Sarcopenia, defined as the progressive loss of skeletal muscle mass and function, has been associated with poor prognosis in patients with pancreatic cancer, particularly those with borderline resectable pancreatic cancer (BRPC). Although body composition can be extracted from routine CT imaging, sarcopenia assessment remains underused in clinical practice. Recent advances in artificial intelligence (AI) offer the potential to automate and standardize this process, but their clinical translation remains limited. This narrative review aims to critically evaluate (1) the clinical impact of CT-defined sarcopenia in BRPC, and (2) the performance and maturity of AI-based methods for automated muscle and fat segmentation on CT images.