Noninvasive Assessment to Identify Patients With At-Risk Metabolic Dysfunction-Associated Steatohepatitis

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease, is a major global health issue and a leading cause of chronic liver disease. The prevalence of MASLD is increasing globally, with the disease in some patients progressing to metabolic dysfunction-associated steatohepatitis (MASH), which significantly raises the risk of fibrosis, cirrhosis, and adverse outcomes. Accurate identification of patients with at-risk MASH, defined as MASH with a fibrosis stage of 2 or higher, is critical for timely intervention and management. Although liver biopsy remains the gold standard for diagnosing MASH, its invasive nature, potential complications, and variability in interpretation necessitate the implementation of noninvasive tests (NITs). NITs hold the potential for reducing reliance on liver biopsies, enhancing early diagnosis, and improving patient management of chronic liver disease. Continued research and validation are essential to optimize these tools for clinical application. This article explores current NITs, including imaging biomarkers, combined imaging and serum biomarkers, advanced biomarkers and composite scores, as well as artificial intelligence-based approaches, which also show promise in improving the accuracy of noninvasive at-risk MASH detection.