Artificial Intelligence-based Tumor Microenvironment Analysis for Prognosis Prediction in Gallbladder Cancer

Samsung Medical Center266 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

266

Conditions

Gallbladder Cancer

Eligibility

Sex: ALL

Medical Language ↔ Plain English

Inclusion Criteria: * Patients who underwent curative surgery for gallbladder cancer. Exclusion Criteria: * Patients who did not achieve R0 resection. * Patients with metastatic disease.

Locations (1)

Samsung Medical Center

Seoul, South Korea

Outcomes

Primary Outcomes

Overall survival

Time frame: From date of surgery (or diagnosis) to the date of death from any cause or the last follow-up, assessed up to 165 months

Secondary Outcomes

Disease-free survival

Time frame: From date of surgery to the date of disease recurrence, assessed up to 165 months

Data from ClinicalTrials.gov

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