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Predicting Immunotherapy Response and Survival of Liver Cancer Patients Using Artificial Intelligence and Radiomics (Radiology-AI-Liver)

Predicting Immunotherapy Response and Survival of Liver Cancer Patients Using Artificial Intelligence and Radiomics (Radiology-AI-Liver)

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07059936
Enrollment
350
Registered
2025-07-11
Start date
2025-07-31
Completion date
2026-09-30
Last updated
2025-07-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hepatocellular Carcinoma (HCC)

Brief summary

CT imaging data and MR imaging data from liver cancer (hepatocellular carcinoma) patients prior to the initiation of immunotherapy (and possibly also after treatment) will be collected. The processing pipeline includes automatic tumor segmentation, radiomics feature extraction, feature selection, and construction of a classification model.

Interventions

None listed

Sponsors

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

1. Patients were treated for hepatocellular carcinoma in Wuhan Union Hospital from July 2025 to July 2026; 2. Aged \> 18 years old; 3. At least one CT scan or MR scan before treatment; 4. Tissue biopsy pathological examination confirmed the diagnosis of the above tumors.

Exclusion criteria

1. Poor image quality; 2. Incomplete clinical data or loss of follow-up; 3. Presence of another primary malignancy other than liver cancer; 4. Unclear pathological diagnosis.

Design outcomes

Primary

MeasureTime frame
disease-free survival1 year
Progression-free survival1 year
overall survival1 year

Countries

China

Contacts

Primary ContactLian Yang
yanglian@hust.edu.cn18986273791

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026