The role of multiparametric POCUS with AI support and visceral morphometry in the diagnosis of metabolic dysfunction-associated steatotic liver disease (MASLD) in family medicine practice

Background. Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a major global health concern. Early detection, particularly in primary care, is essential to prevent progression to cirrhosis and hepatocellular carcinoma (HCC). Methodology. This study included 4751 high-risk patients assessed through standardized multiparametric liver ultrasound (MLUS) and visceral morphometry supported by AI. Liver measurements were compared to axial lengths of the spleen and kidneys. Findings were confirmed using FibroScan and APRI/FIB-4 scores. Results. We identified 2592 patients with hepatic steatosis, 971 with MASH, 22 with cirrhosis, and six with HCC. Diagnostic accuracy reached 94%, with 96.31% sensitivity and 87.85% specificity. Agreement between general practitioners and specialists was very high (kappa = 0.875). Conclusions. AI-supported multiparametric ultrasound in primary care enables early, noninvasive, and cost-effective detection of MASLD and can bridge the diagnostic gap in underserved populations.