AI-Based Multimodal Integration for Tumor Microenvironment Analysis and Response Prediction in HCC Treated With TACE Plus Immunotherapy and Targeted Therapy (CHANCE2601)
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial Intelligence.
- Who it may be relevant to
- Registry conditions: Hepatocellular Carcinoma. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Artificial Intelligence-Based Multimodal Data Integration for Tumor Microenvironment Analysis and Response Prediction in Hepatocellular Carcinoma Patients Undergoing TACE Combined With Immunotherapy and Targeted Therapy
Overview
This study aims to prospectively validate a retrospective cohort-derived AI-based multimodal model and explore tumor heterogeneity and the immune microenvironment to guide TACE combined with immunotherapy and targeted therapy in HCC.
Detailed description
This study will integrate a retrospective cohort with a prospective observational cohort. Multimodal data will be collected in the prospective cohort to validate the AI-based imaging model developed from the retrospective cohort. In addition, advanced multi-omics technologies will be incorporated to characterize tumor heterogeneity and the immune microenvironment, thereby supporting early and precise guidance for TACE combined with immunotherapy and targeted therapy in HCC.
Interventions
- Other Artificial Intelligence
Investigators utilize a AI-based supportive system to predict clinical outcomes for patients with hepatocellular carcinoma who received TACE combined with immunotherapy and targeted therapy
Primary outcome measures
- Prediction Performance of the AI Model [Time frame: From enrollment to approximately 2 years]
Secondary outcome measures (4)
- Objective response rate(ORR) [Time frame: up to approximately 2 years]
- Overall Survival(OS) [Time frame: up to approximately 2 years]
- Progression free survival(PFS) [Time frame: up to approximately 2 years]
- Other prediction performance of the model [Time frame: From enrollment to approximately 2 years]
Eligibility criteria
- Retrospective Study Cohort 1.1 Inclusion Criteria Age ≥18 years; Patients with hepatocellular carcinoma confirmed by histopathology or clinical diagnosis; At least one intrahepatic lesion that is repeatedly measurable according to RECIST v1.1.
1.2 Exclusion Criteria Known sarcomatoid hepatocellular carcinoma or fibrolamellar hepatocellular carcinoma; Presence of other active malignancies within the past 5 years or concurrent active malignancies other than hepatocellular carcinoma; Missing preoperative imaging examinations, including CT or MRI, or poor image quality; Missing key baseline clinical data; Loss to follow-up after treatment.
- Prospective Study Cohort 2.1 Inclusion Criteria Age ≥18 years; Patients with hepatocellular carcinoma confirmed by histopathology or clinical diagnosis; Scheduled to receive first-line TACE combined with immunotherapy and targeted therapy; At least one intrahepatic lesion that is repeatedly measurable according to RECIST v1.1; Expected survival of more than 3 months. 2.2 Exclusion Criteria Known sarcomatoid hepatocellular carcinoma or fibrolamellar hepatocellular carcinoma; Presence of other active malignancies within the past 5 years or concurrent active malignancies other than hepatocellular carcinoma; Other factors that, in the investigator's judgment, make the patient unsuitable for participation in this study; Severe allergy to iodinated contrast agents that preclude imaging examinations or TACE treatment.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Center list to be confirmed — check the primary protocol.
Publications
- Zhong BY, Fan W, Guan JJ, Peng Z, Jia Z, Jin H, Jin ZC, Chen JJ, Zhu HD, Teng GJ. Combination locoregional and systemic therapies in hepatocellular carcinoma. Lancet Gastroenterol Hepatol. 2025 Apr;10(4):369-386. doi: 10.1016/S2468-1253(24)00247-4. Epub 2025 Feb 21. PMID 39993404
- Jin ZC, Wei J, Xiao YD, Si A, Chen JJ, Zhu XL, Li JZ, Nie F, Ding R, Zhou HF, Ding W, Zhong BY, Xie Y, Hu HT, Yin GW, Ji JS, Zhang WH, Shi HB, Wu JB, Xu GH, Yuan CW, Yang WZ, Liu RB, Wu YM, Zheng CS, Xu AB, Huang MS, Li JP, Chen L, Wen SW, Wang YQ, Gu SZ, Li D, Wang D, Zhou GH, Wang WD, Peng Z, Wang X, Zhu HD, Tian J, Teng GJ. Decoding tumor heterogeneity with imaging biomarkers predicts response PMID 41213031
- Vithayathil M, Koku D, Campani C, Nault JC, Sutter O, Ganne-Carrie N, Aboagye EO, Sharma R. Machine learning based radiomic models outperform clinical biomarkers in predicting outcomes after immunotherapy for hepatocellular carcinoma. J Hepatol. 2025 Oct;83(4):959-970. doi: 10.1016/j.jhep.2025.04.017. Epub 2025 Apr 17. PMID 40246150
Identifiers
NCT: NCT07584317 · CHANCE2601