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Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH
Published on: April 20, 2021
Multiparametric US for Identifying Patients with High-Risk NASH: A Derivation and Validation Study
Katsutoshi Sugimoto1, Dong Ho Lee1, Jae Young Lee1
1From the Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan (K. Sugimoto, H. Takahashi, T.K., Y.T., M.A., Y.Y., H. Takeuchi, T.I.); Departments of Radiology (D.H.L., J.Y.L.) and Internal Medicine, Division of Gastroenterology and Hepatology (S.J.Y.), Seoul National University, Seoul, Korea; Department of Gastroenterology and Hepatology, International University of Health and Welfare, Sanno Hospital, Tokyo, Japan (F.M.); Center for Data Science, Yokohama City University, Kanagawa, Japan (K. Sakamaki); Department of Pathology, Jichi Medical University, Tochigi, Japan (H.O.); Department of Radiology, Chung-Ang University Hospital, Seoul, Korea (B.I.C.).
Abstract:
Background Nonalcoholic fatty liver disease (NAFLD) is common in the general population but identifying patients with high-risk nonalcoholic steatohepatitis (NASH) who are candidates for pharmacologic therapy remains a challenge. Purpose To develop a score to identify patients with high-risk NASH, defined as NASH with an NAFLD activity score (NAS) of 4 or greater and clinically significant fibrosis (stage 2 [F2] or higher). Materials and Methods This was a cross-sectional secondary analysis of data prospectively collected between April 2017 and March 2019 for a group of patients with NAFLD in Japan (Japan NAFLD, the derivation data set) with contemporaneous two-dimensional shear-wave elastography and biopsy-proven NAFLD (age range, 20-89 years). Three US markers (liver stiffness [LS, measured in kilopascals], attenuation coefficient [AC, measured in decibels per centimeter per megahertz], and dispersion slope [DS, measured in meters per second per kilohertz]) were determined, together with aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels and the AST-to-ALT ratio. The best-fit multivariate logistic regression model for identifying patients with high-risk NASH was determined. Diagnostic performance was assessed by using the area under the receiver operating characteristic curve (AUC). The findings were validated in an independent data set (Korea NAFLD; age range, 20-78 years). Results The Japan NAFLD data set included 111 patients (mean age, 53 years ± 18 [standard deviation]; 57 men), 84 (76%) with NASH. The Korea NAFLD data set included 102 patients (mean age, 48 years ± 18; 43 men), 55 (36%) with NASH. The most predictive model (LAD NASH score) combined LS, AC, and DS. Performance was satisfactory in both the derivation sample (AUC, 0.86; 95% CI: 0.79, 0.93) and the validation sample (AUC, 0.88; 95% CI: 0.80, 0.95). The LAD NASH score showed a positive predictive value of 86.5% and a negative predictive value of 87.5% for high-risk NASH in the derivation sample. Conclusion A score combining three US markers may be useful for noninvasive identification of patients with high-risk nonalcoholic steatohepatitis for inclusion in clinical trials and pharmacologic therapy. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Lockhart in this issue.
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