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.
Recruiting now
Conditions studied: Hepatocellular Carcinoma (HCC), Intrahepatic Cholangiocarcinoma (ICC), Primary Liver Cancer
In brief
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.
Key facts
- Study ID
- NCT07101237
- Run by
- Peking Union Medical College Hospital
- People needed
- 308
- Starts
- 2024-08-01
- Expected to finish
- 2030-12-31
- Last updated by the study team
- 2025-08-03
Who can join
Age: 18 and older, up to 70. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- Age >18 and ≤70 years;
- Both sexes eligible;
- Diagnosed with primary HCC or ICC;
- Scheduled for surgical resection or conversion therapy;
- Pathologically confirmed HCC/ICC via surgery or biopsy;
- Posterior margin of the lesion ≤ 8 cm from the skin surface.
You may not qualify if…
- Pregnancy, lactation, or planned pregnancy during the study period;
- History of other malignancies;
- Cardiac, pulmonary, cerebral, or renal insufficiency;
- Lesion depth >8 cm from the skin surface on ultrasound;
- Massive ascites;
- Poor compliance (e.g., inability to hold breath during examination);
- Allergy to ultrasound contrast agents.
Where it is running
- Peking Union Medical College Hospital — Beijing, China (enrolling)
Full record on ClinicalTrials.gov
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