AI-driven tumor heterogeneity quantification and survival prediction in pancreatic ductal adenocarcinoma.
Artificial intelligence system accurately predicts overall survival in pancreatic ductal adenocarcinoma patients.
AI-driven tumor heterogeneity quantification and survival prediction in pancreatic ductal adenocarcinoma.
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide, and accurate prognostic prediction remains highly challenging due to its marked biological heterogeneity and complex tumor microenvironment.
Characterization of tumor heterogeneity and accurate postoperative survival prediction are enabled, with potential value for personalized management in PDAC.
how well the artificial intelligence system predicted how long patients with pancreatic cancer would live
To address this challenge, a histopathomics-based survival prediction system (HPSurv) was developed using histopathological whole-slide images (WSIs) for individualized overall survival (OS) prediction.
Within this framework, pathological tissue classification, quantitative characterization of tumor spatial heterogeneity, and a survival Transformer were integrated to enable multi-level representation learning from histopathological data.
The system was developed and evaluated in 1020 patients across five independent cohorts.
Objective characterization of tumor heterogeneity and accurate postoperative survival prediction are enabled, with potential value for personalized management in PDAC.