Clinical trial · Observational
Radiomics Analysis of Focal Liver Lesions Based on Contrast-Enhanced Ultrasound Imaging
Research on Key Techniques for Intelligent Diagnosis and Ablation Decision-making of Liver Cancer and Evolution by Contrast-enhanced Ultrasound
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Contrast-enhanced ultrasound (CEUS) substantially improves the potential of ultrasound (US) for the identification and characterization of focal liver lesions (FLLs). Compared to contrasted-enhanced MRI and CT, it has some unique advantages, such as the absence of ionizing radiation, and easy operability and repeatability. However, the efficacy of CEUS in diagnosing liver lesions is challenged by several factors including being highly dependent on doctor's experience, low signal-to-noise ratio, and low interobserver agreement. Therefore, it is a beneficial attempt to construct an intelligent CEUS diagnosis system using digital information technology. This study aims to collect standard data of CEUS cines recordings and develop deep learning model for accurate segmentation, detection and classification of liver lesions.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Contrast-enhanced Ultrasound | — | UNRESOLVED | — |
| Focal Liver Lesions | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| diagnosis | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (3)
- measure
- AUC value
- timeFrame
- through study completion, an average of 7 year
- description
- Area under the receiver operating characteristic (ROC) curve (AUC）
- measure
- specificity
- timeFrame
- through study completion, an average of 7 year
- description
- diagnosis specificity of intelligent CEUS analysis
- measure
- sensitivity
- timeFrame
- through study completion, an average of 3 year
- description
- diagnosis sensitivity of intelligent ultrasound analysis
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: 1. patients with a solid liver tumor visible during routine ultrasound and received CEUS. 2. disease history and standard of reference of the lesions can be acquired Exclusion Criteria: 1. hypersensitivity for ultrasound contrast media 2. pregnant or lactating patients 3. previously treated lesions or local relapse from previously treated lesions 4. diffuse tumors
References
Publications (3)
- DERIVEDDing W, Li B, Zhao L, Zheng L, Li X, Liu S, Yu J, Liang P. Improving Detection of Intrahepatic Cholangiocarcinoma with a Contrast-enhanced US-based Deep Learning Model. Radiol Imaging Cancer. 2025 Nov;7(6):e250078. doi: 10.1148/rycan.250078. PMID 41236388
- DERIVEDWu J, Liu S, Zhang Y, Ding W, Zhao Q, Wang Y, Xiao F, Yu X, Xie X, Liu S, Zhao J, Liao J, Yu J, Liang P. Prediction of Macrotrabecular-Massive Hepatocellular Carcinoma and Associated Prognosis Using Contrast-enhanced US and Clinical Features. Radiol Imaging Cancer. 2025 Jul;7(4):e240419. doi: 10.1148/rycan.240419. PMID 40607931
- DERIVEDDing W, Meng Y, Ma J, Pang C, Wu J, Tian J, Yu J, Liang P, Wang K. Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions. J Hepatol. 2025 Aug;83(2):426-439. doi: 10.1016/j.jhep.2025.01.011. Epub 2025 Jan 21. PMID 39848548