Application and Advances of Non-in vasive Magnetic Resonance Proton Density Fat Fraction in Hepatic Steatosis

Metabolic dysfunction-associated steatotic liver disease (MASLD), affecting approximately 32% of the global adult population, represents a leading cause of chronic liver disease. Hepatic steatosis, characterized by abnormal lipid accumulation in hepatocytes, serves as a fundamental histological hallmark and a key driver of disease progression towards metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and hepatocellular carcinoma. Accurate, non-invasive quantification of liver fat content is therefore paramount for diagnosis, risk stratification, and therapeutic monitoring in MASLD. Magnetic Resonance Imaging-proton density fat fraction (MRI-PDFF), based on chemical shift-encoded water-fat separation, has emerged as a highly accurate, reproducible, and quantitative non-invasive biomarker for assessing hepatic steatosis. This review synthesizes current evidence demonstrating the superior diagnostic performance of MRI-PDFF in grading hepatic steatosis compared to traditional techniques like Controlled Attenuation Parameter (CAP) and transient elastography (TE), as evidenced by high area-under-the-receiver-operating-characteristic-curve (AUROC) values across multiple studies. Furthermore, MRI-PDFF plays a pivotal role in evaluating treatment efficacy in clinical trials, effectively detecting significant reductions in liver fat content in response to pharmacotherapy. While MRI-PDFF excels in fat quantification, its combination with other MRI-based techniques (e.g., Magnetic Resonance Elastography - MRE, corrected T1 - cT1) significantly enhances the non-invasive assessment of co-existing pathologies like MASH and fibrosis. Despite advantages such as whole-liver coverage and excellent reproducibility, limitations including high cost, technical standardization challenges, and restricted applicability in certain patient populations remain. In conclusion, MRI-PDFF stands as a cornerstone non-invasive tool for quantifying liver fat in MASLD, driving advancements in diagnosis, therapeutic monitoring, and clinical trial endpoints, with ongoing developments in multimodal approaches and standardization promising further optimization of MASLD management.