Artificial intelligence in contrast enhanced ultrasound: A new era for liver lesion assessment
Year: 2025
Type: article
Abstract: Artificial intelligence (AI)-augmented contrast-enhanced ultrasonography (CEUS) is emerging as a powerful tool in liver imaging, particularly in enhancing the accuracy of Liver Imaging Reporting and Data System (known as LI-RADS) classification. This review synthesized published data on the integration of machine learning and deep learning techniques into CEUS, revealing that AI algorithms can improve the detection and quantification of contrast enhancement patterns. Such improvements led to more consistent LI-RADS categorization, reduced interoperator variability, and enabled real-time analysis that streamlined workflow. The enhanced sensitivity of AI tools facilitated better differentiation between benign and malignant lesions, ultimately optimizing patient management. These advances suggest that AI-augmented CEUS could transform liver imaging by providing rapid, reliable, and objective assessments. However, the review also highlighted the need for further large-scale, multicenter studies to fully validate these findings and ensure the safe integration of AI into routine clinical practice.
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4416156249