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

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology350 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

350

Conditions

Hepatocellular Carcinoma (HCC)

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

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.

Locations (1)

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

Wuhan, Hubei, China

Outcomes

Primary Outcomes

disease-free survival

Time frame: 1 year

Progression-free survival

Time frame: 1 year

overall survival

Time frame: 1 year

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

Overview

Conditions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Central Contacts