NCT07101237 An Exploratory Study on Developing an Integrated Approach Combining Multimodal Imaging and Multi-omics Characterization of Tumor Heterogeneity for Precision Diagnosis and Treatment Optimization in Liver Cancer.

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What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 308 participants in total. It began in 2024-08-01 with a primary completion date of 2029-12-31.

Brief Summary

Primary liver cancer, mainly including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), represents the third leading cause of cancer-related mortality. Enhancing the precision of liver cancer diagnosis and providing early therapeutic efficacy and prognostic evaluation during clinical decision-making hold significant clinical importance. Ultrasound is the preferred imaging modality for liver cancer screening. Contrast-enhanced ultrasound (CEUS) can dynamically visualize the microvascular perfusion of liver cancer lesions. Liver elastography has become a commonly used clinical assessment tool for cirrhosis. Photoacoustic imaging (PAI), an emerging non-invasive functional imaging technique, enables visualization of specific molecules through their spectroscopic characteristics at designated wavelengths. The objectives of this study include: (1) Conducting an observational investigation combining CEUS, elastography, and superb microvascular imaging (SMI) to collect imaging data; (2) Preserving tumor specimens from participants to investigate heterogeneous protein characteristics of primary liver cancer organoids using PAI; (3) Analyzing peripheral venous blood samples to study transcriptomic profiles. Artificial intelligence (AI) technology will be employed to establish models integrating ultrasound radiomics with tumor multi-omics characteristics, aiming to provide novel strategies for precision diagnosis and treatment of liver cancer. Key questions：(1) How to develop a multimodal imaging model combining CEUS, elastography, and SMI for predicting differentiation of liver cancer, microvascular invasion (MVI) and prognosis; (2) Whether PAI can identify heterogeneous proteins in liver cancer organoids through specific spectral recognition; (3) Whether AI can integrate multi-dimensional data to establish models based on ultrasound radiomics and multi-omics features.

Eligibility Criteria

Inclusion Criteria: 1. Age \>18 and ≤70 years; 2. Both sexes eligible; 3. Diagnosed with primary HCC or ICC; 4. Scheduled for surgical resection or conversion therapy; 5. Pathologically confirmed HCC/ICC via surgery or biopsy; 6. Posterior margin of the lesion ≤ 8 cm from the skin surface. Exclusion Criteria: 1. Pregnancy, lactation, or planned pregnancy during the study period; 2. History of other malignancies; 3. Cardiac, pulmonary, cerebral, or renal insufficiency; 4. Lesion depth \>8 cm from the skin surface on ultrasound; 5. Massive ascites; 6. Poor compliance (e.g., inability to hold breath during examination); 7. Allergy to ultrasound contrast agents.

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