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All Journal Sriwijaya Journal of Radiology and Imaging Research
Armalia, Sarah
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Dentistry Health Professions Medicine & Pharmacology Neuroscience Physics

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Evaluation of MRI-PDFF (Magnetic Resonance Imaging-Proton Density Fat Fraction) as a Non-invasive Biomarker for Liver Steatosis in a Medan Population: A Cross-Sectional Study Armalia, Sarah; Agus Supriyatno
Sriwijaya Journal of Radiology and Imaging Research Vol. 2 No. 1 (2024): Sriwijaya Journal of Radiology and Imaging Research
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjrir.v1i2.73

Abstract

Introduction: Liver steatosis is a growing global health concern, often linked to metabolic syndrome. Accurate non-invasive assessment is vital for early diagnosis and management. MRI-PDFF has emerged as a promising quantitative technique for measuring liver fat. This study aimed to evaluate the utility of MRI-PDFF in quantifying liver steatosis in a Medan population and its correlation with clinical and metabolic parameters. Methods: A cross-sectional study was conducted on individuals residing in Medan, Indonesia. Participants underwent clinical assessments, laboratory tests, and MRI examinations, including PDFF measurements. Liver steatosis was categorized based on PDFF thresholds. Statistical analyses assessed correlations between MRI-PDFF and clinical parameters, including age, gender, BMI, liver function tests, and metabolic markers. Results: 200 participants were enrolled. MRI-PDFF demonstrated a strong correlation with liver steatosis grades (r = 0.85, p < 0.001). PDFF values were significantly higher in individuals with obesity, metabolic syndrome, and elevated liver enzymes. ROC curve analysis revealed high sensitivity (88%) and specificity (85%) of MRI-PDFF in diagnosing liver steatosis at an optimal cutoff of 8.5% PDFF. Conclusion: MRI-PDFF is a reliable and non-invasive biomarker for quantifying liver steatosis in the Medan population. Its strong correlation with clinical and metabolic parameters underscores its potential for risk stratification and monitoring treatment response in individuals with fatty liver disease.
Co-Authors Agus Supriyatno