This retrospective study aims to investigate the prognostic significance of artificial intelligence (AI)-powered analysis of tumor-infiltrating lymphocytes (TILs) and the tumor microenvironment (TME) in patients with resected gallbladder cancer. Using hematoxylin and eosin (H&E)-stained slides, the study quantifies spatial TME features, including TIL density, tertiary lymphoid structures, and fibroblast density, to identify potential TME-related risk factors associated with survival.

Inclusion Criteria:

• Patients who underwent curative surgery for gallbladder cancer.

Exclusion Criteria:

• Patients who did not achieve R0 resection.
• Patients with metastatic disease.

Patients with gallbladder cancer who underwent curative-intent surgery with R0 resection at Samsung Medical Center between 2010 and 2020 formed the main study cohort. An external validation cohort included patients with gallbladder cancer at Asan Medical Center between 2017 and 2022 with available archived hematoxylin and eosin-stained slides for AI-powered tumor microenvironment analysis. Patients with inadequate tissue samples were excluded.

There is no current plan to publicly share individual participant data (IPD). However, de-identified data may be shared upon reasonable request, subject to approval by the institutional review board and compliance with data protection regulations.