O-26 : MR-Based Non-Alcoholic Steato Hepatitis (MASH) Score in Patients with Non-Alcoholic Fatty Liver Disease

2020 
Aims: As prevalence of NAFLD accounts for up to 30% of the general population worldwide, non-invasive evaluation of disease severity of NAFLD and non-invasive diagnosis of NASH are important issues. The objective of this prospective cross-sectional study was to develop a diagnostic scoring system that could improve the accuracy of NASH diagnosis by combining multiparametric MR and clinical indicators. Methods: This study included 130 patients who were diagnosed NAFLD by liver biopsy from October 2016 to July 2019. All patients were examined for medical history, laboratory tests, and multiparametric MR consisting of MRI proton density fat fraction, MR spectroscopy, T1 mapping, and MR elastography (MRE). Scoring model was developed using logistic regression. Internal validation was performed using bootstrapping. Results: NASH patients were older (59 years vs. 46 years, P<0.001) and had lower BMI (28.23 kg/㎡ vs. 31.19 kg/㎡, P=0.032) than nonalcoholic fatty liver (NAFL) patients. NASH group showed higher prevalence of diabetes/impaired fasting glucose, hypertension, and dyslipidemia. Four categorical variables and 19 continuous variables were evaluated for NASH diagnostic model. Diabetes/IFG and hypertension among categorical variables and age, BMI, hemoglobin, platelet count, T1 mapping, and MRE among continuous variables met the criterion of P-value ≤ 0.1. Variable interactions were identified between BMI and hemoglobin, between platelet count and diabetes/IFG, and between platelet count and MRE. Finally, equation for MR-based NASH (MASH) score was obtained using four demographic factors, two laboratory variables, and two MRI parameters (Figure 1). MASH score showed satisfactory accuracy for NASH diagnosis (C-statistics: 0.892; 95% CI: 0.834-0.950; P<0.001). When MASH score of 0.73 was set as a cut-off for NASH diagnosis, its sensitivity was 0.67 and its specificity was 0.90 (PPV = 0.89, 47/53). When MASH score of 0.37 was set as a cut-off for NASH exclusion, its sensitivity was 0.90 and its specificity was 0.78 (NPV = 0.87, 47/54). Only 17% (22/130) of patients were located in the gray zone (Table 1). Internal validation using 1000 bootstrapping also showed satisfactory accuracy for NASH diagnosis (C-statistics: 0.909; 95% CI: 0.855-0.964; P<0.001). Conclusions: MASH score is a novel non-invasive biomarker for the diagnosis of NASH in patients with NAFLD. Further external validation is required for its clinical application.
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