Human-Mouse Convergence in Metabolic Dysfunction-Associated Steatotic Liver Disease: Mouse Model Selection and Non-Invasive Diagnostic Strategies

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Abstract
Background Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a global health priority affecting approximately 30% of the population. It represents the hepatic manifestation of metabolic syndrome, potentially progressing from simple ste-atosis to Metabolic Dysfunction-Associated Steatohepatitis (MASH), cirrhosis, and hepa-tocellular carcinoma. This review aims to compare current knowledge of MASLD in mouse models and humans, focusing on pathophysiology, histological phenotypes, and the role of preclinical imaging as a non-invasive translational screening tool. Methods The study synthesizes recent evidence (last five years) regarding the multi-factorial aetiology of MASLD, focusing on some of the key aspects in selecting the ap-propriate animal model and on the recent non-invasive techniques applicable to both humans and mice. Results MASLD arises from complex interactions between genetics, sedentary lifestyles, and imbalanced diets. While mouse models have been refined to capture the multifac-torial interplay driving disease progression and are still essential for drug development, no single model fully mirrors the human condition. This process must take into account key variables, including diet composition, mouse strain, the use of genetically modified mice (GEMs), and housing temperature. Histological assessment remains the gold standard for MASLD staging, particularly in mouse models; however, preclinical im-aging is increasingly emerging as a complementary, non-invasive technique for in vivo investigation. Conclusions Rational, fit-for-purpose mouse models are essential to address specific mechanistic and therapeutic questions. Given the multifactorial and heterogeneous na-ture of MASLD, understanding the limitations and strengths of specific mouse models is therefore crucial for translational research. Integrating phenotype-driven approaches in both humans and mice, combining traditional histology, quantitative imaging and metabolic profiling, as well as longitudinal, combinatorial and humanized preclinical models, will enhance translational alignment and accelerate the development of therapies for MASLD.

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