Advancements in Artificial Intelligence Applications for Liver Ultrasound Imaging

Abstract Liver diseases consistently plague people’s daily lives as a result of their high morbidity and mortality rates. Ultrasound (US), favored by its flexibility, free of radiation, cost-effectiveness and real-time capabilities, has been commonly employed as one of the first-line imaging tool for hepatic conditions. Artificial intelligence (AI) algorithms are increasingly applied to automatically identify intricate patterns and perform quantitative analyses in US imaging, potentially reducing radiologists’ workload and improving diagnostic efficiency. AI-based US has been of substantial assistance in the detecting, diagnosing, screening as well as monitoring of various liver diseases, and has attracted extensive attention among the medical community. In this review, we present a general introduction to AI in medical imaging; we next review its rapidly evolving applications in liver US, covering evaluation of hepatic steatosis severity, assessment of liver fibrosis, identification of focal hepatic lesions, preoperative prediction of high-risk pathological characteristics, assessment of postoperative prognosis, and the analysis of the model of integrated application of multi-omics data; finally, we present an outlook on the clinical applications of AI-based US in the liver diseases.