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

NCT07538882 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 108

Last updated 2026-04-20

No results posted yet for this study

Summary

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.

Conditions

  • Hepatocellular Carcinoma (HCC)

Interventions

DIAGNOSTIC_TEST

Unassisted Independent Evaluation

Physicians independently evaluate the HCC cases and provide staging and treatment decisions using only complete clinical baseline data and imaging data, without any assistance from the AI model.

DIAGNOSTIC_TEST

AI-Assisted Evaluation

Physicians evaluate the HCC cases and provide final staging and treatment decisions after reviewing the initial predictions and related evidence generated by the self-developed artificial intelligence (AI) model, alongside the clinical baseline and imaging data.

Sponsors & Collaborators

  • Affiliated Hospital of Hebei University

    collaborator OTHER

  • Meng Chao Hepatobiliary Hospital of Fujian Medical University

    collaborator OTHER

  • Zhongnan Hospital

    collaborator OTHER

  • Xingtai People's Hospital

    collaborator OTHER

  • Second Affiliated Hospital of Xi'an Jiaotong University

    collaborator OTHER

  • Xinan hospital of Army Medical University

    collaborator UNKNOWN

  • Beijing Tsinghua Chang Gung Hospital

    lead OTHER

Principal Investigators

  • Jiahong Dong · Beijing Tsinghua Changgeng Hospital

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-04-13
Primary Completion
2026-05-13
Completion
2026-05-20

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07538882 on ClinicalTrials.gov