Advances in the Diagnosis and Management of MASH: The Role of Targeted Therapies and Artificial Intelligence

Abstract

Advances in the Diagnosis and Management of Mash: The Role of Targeted Therapies and Artificial Intelligence Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) currently represents one of the leading causes of chronic liver disease worldwide, with an estimated prevalence of 25% to 30% in the general population, a figure that rises significantly among individuals with obesity, type 2 diabetes or metabolic syndrome. The pathological spectrum ranges from simple hepatic steatosis to more severe forms such as Metabolic Dysfunction-Associated Steatohepatitis (MASH), advanced fibrosis, cirrhosis, and even hepatocellular carcinoma. Given its asymptomatic progression in early stages, early diagnosis and comprehensive management are essential to avoid serious complications. Currently, there is no approved drug treatment specifically for NASH. However, several therapeutic strategies are under development and investigation. These include drugs that target altered metabolic pathways such as lipogenesis, insulin resistance, inflammation, and fibrosis. FXR (Farnesoid X Receptor) agonists, PPAR (Peroxisome Proliferator-Activated Receptors), GLP-1 (Glucagon-Like Peptide-1), and ACC (Acetyl-CoA Carboxylase) inhibitors are among the most promising agents. Artificial intelligence (AI) has begun to play a pivotal role in this context, facilitating early disease detection, risk stratification, and progression prediction through advanced analysis of images, biomarkers, and clinical data. Integrating personalized predictive models into clinical practice can revolutionize both diagnosis and therapeutic strategies for MASH, bringing us closer to truly effective precision medicine.