1*,2,5Research Scholar, Department of Radiological Imaging Techniques, College of Paramedical Sciences, Teerthanker Mahaveer University, Moradabad, U.P. India.
3Assistant Professor, Department of Radiological Imaging Techniques, College of Paramedical Sciences, Teerthanker Mahaveer University, Moradabad, U.P. India.
4Assistant Professor, Department of Radiology, School of Allied Health Science, Galgotias University, Greater Noida, U.P., India.
Background: The most common chronic liver illness in the world is non-alcoholic fatty liver disease (NAFLD), which was recently renamed metabolic dysfunction–associated steatotic liver disease (MASLD). Early detection and risk assessment are crucial since progressive illness can result in cirrhosis, severe fibrosis, and hepatocellular cancer. Non-invasive imaging methods have taken centre stage in the assessment of diseases due to the limitations of liver biopsy.
Objective: To comprehensively review current and emerging imaging modalities in NAFLD/MASLD, highlighting quantitative magnetic resonance techniques and artificial intelligence–based advancements.
Methodology: Ultrasonography remains the primary screening modality due to its accessibility and cost-effectiveness, though it is limited by qualitative assessment and reduced sensitivity for mild steatosis. Computed tomography provides objective attenuation measurements but is constrained by radiation exposure and limited early-stage sensitivity. Ultrasound-based elastography enhances non-invasive fibrosis assessment; however, technical variability persists, particularly in obese individuals. Magnetic resonance imaging techniques, including proton density fat fraction (PDFF) and magnetic resonance elastography (MRE), offer highly accurate, reproducible, and quantitative biomarkers for steatosis and fibrosis evaluation. Multiparametric MRI enables comprehensive whole-liver phenotyping and is increasingly incorporated into clinical trials. Emerging artificial intelligence and radiomics applications demonstrate promise for automated quantification and risk stratification, although further multicenter validation is required.
Conclusion: Imaging has evolved from a supportive diagnostic tool to a cornerstone of non-invasive NAFLD/MASLD evaluation. Advances in quantitative MRI and AI-driven analytics are poised to enhance precision-based disease assessment and may substantially reduce reliance on invasive liver biopsy.
Keywords: Non-alcoholic fatty liver disease (NAFLD); Metabolic dysfunction–associated steatotic liver disease (MASLD); Magnetic resonance imaging; Proton density fat fraction (PDFF); Magnetic resonance elastography (MRE); Liver fibrosis; Elastography; Artificial intelligence; Radiomics; Quantitative imaging biomarkers.
How to cite this article: Gaur P, Aswal S, Bisht A, Upadhyay N, Singh A, Imaging in Non-Alcoholic Fatty Liver Disease (NAFLD): Current Advances, Quantitative Biomarkers, and Future Directions.Int J Drug Deliv Technol. 2026;16(12s): 517-529. DOI: 10.25258/ijddt.16.12s.63
Source of support: Nil
Conflict of interest: None