AI-based body composition mapping from CT scans to predict outcomes after TACE for liver cancer

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This single-center observational project uses deep learning to automatically analyze pre-treatment CT scans from adult HCC patients who underwent transarterial chemoembolization (TACE) between January 1, 2018 and May 31, 2024. The algorithm will quantify multidimensional body composition features such as organ sizes and muscle/fat condition across the abdomen and link these imaging features with clinical records. Patients with poor image quality, other active malignancies, loss to follow-up, or incomplete records will be excluded. The resulting model aims to predict survival and treatment outcomes after TACE to support more personalized treatment decisions.

Why it matters

Who can join: the full rules

Inclusion Criteria:

1. Patients diagnosed with "Hepatocellular Carcinoma" from January 1, 2018 to May 31, 2024;
2. Age \> 18 years old.

Exclusion Criteria:

1. Poor image quality;
2. Loss of follow-up;
3. Presence of another type of malignant tumor other than liver cancer;
4. Incomplete medical records.

Where it's running

• Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
  Wuhan, Hubei, China Recruiting

Study contacts

• Study coordinator: Yuanyuan Chu
• Email: whunionlunli@126.com
• Phone: +8602785726375

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.