Integrative Multimodal Imaging and Multi-omics Profiling of HCC Heterogeneity: a Translational Exploratory Study Leveraging CEUS, Elastography, SMI, PAI, Multi-omics Analysis, and AI-driven Modeling to Advance Precision Diagnosis and Therapeutic Optimization
Trial ID: NCT07101237
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-08-01
Completion date: 2030-12-31
Sponsor: Peking Union Medical College Hospital
Conditions: Hepatocellular Carcinoma (HCC); Intrahepatic Cholangiocarcinoma (ICC); Primary Liver Cancer
Interventions: Multi-modal ultrasonic imaging system for liver cancer
Locations: Peking Union Medical College Hospital
Countries: China
Enrollment: 308
Age range: 18 Years - 70 Years
Sex: ALL

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.

Outcomes:
tumor progression or follow-up failure.