AI-Assisted Staging and Treatment Decision-Making for Hepatocellular Carcinoma

The precise treatment of primary hepatocellular carcinoma (HCC) highly depends on accurate disease staging (CNLC, TNM, BCLC) and scientific treatment decision-making, which necessitate the integration of both imaging and clinical baseline data. This study prospectively recruits HCC patients and clinical physicians across different hospital tiers to evaluate the clinical value of a self-developed artificial intelligence (AI) model in assisting multi-dimensional comprehensive assessment and treatment decision-making. Utilizing a Multi-Rater Multi-Case (MRMC) crossover balanced design, the study compares the accuracy of clinical evaluations performed by physicians under "unassisted (without AI)" versus "AI-assisted" conditions. A key focus is to explore whether AI can significantly enhance the comprehensive assessment capabilities of physicians in primary/secondary care hospitals, thereby prospectively reducing diagnostic and therapeutic heterogeneity across different institutional levels.

NCT Number	NCT07538882
Lead Sponsor	Beijing Tsinghua Chang Gung Hospital Collaborators: Affiliated Hospital of Hebei University, Meng Chao Hepatobiliary Hospital of Fujian Medical University, Zhongnan Hospital, Xingtai People's Hospital, Second Affiliated Hospital of Xi'an Jiaotong University, Xinan hospital of Army Medical University
Conditions	Hepatocellular Carcinoma (HCC)
Enrollment	108 participants
Start Date	2026-04-13
Primary Completion	2026-05-13 (estimated)
Study Completion	2026-05-20 (estimated)
Updated on ClinicalTrials.gov	2026-04-20