Assessment of hepatic steatosis in nonalcoholic fatty liver disease by using quantitative US

Aiguo Han, Yingzhen N. Zhang, Andrew S. Boehringer, Vivian Montes, Michael P. Andre, John W. Erdman, Rohit Loomba, Mark A. Valasek, Claude B. Sirlin, William D. O’Brien

Research output: Contribution to journalArticlepeer-review


Background: Advanced confounder-corrected chemical shift–encoded MRI-derived proton density fat fraction (PDFF) is a leading parameter for fat fraction quantification in nonalcoholic fatty liver disease (NAFLD). Because of the limited availability of this MRI technique, there is a need to develop and validate alternative parameters to assess liver fat. Purpose: To assess relationship of quantitative US parameters to MRI PDFF and to develop multivariable quantitative US models to detect hepatic steatosis and quantify hepatic fat. Materials and Methods: Adults with known NAFLD or who were suspected of having NAFLD were prospectively recruited between August 2015 and February 2019. Participants underwent quantitative US and chemical shift–encoded MRI liver examinations. Liver biopsies were performed if clinically indicated. The correlation between seven quantitative US parameters and MRI PDFF was evaluated. By using leave-one-out cross validation, two quantitative US multivariable models were evaluated: a classifier to differentiate participants with NAFLD versus participants without NAFLD and a fat fraction estimator. Classifier performance was summarized by area under the receiver operating characteristic curve and area under the precision-recall curve. Fat fraction estimator performance was evaluated by correlation, linearity, and bias. Results: Included were 102 participants (mean age, 52 years 6 13 [standard deviation]; 53 women), 78 with NAFLD (MRI PDFF ≥ 5%). A two-variable classifier yielded a cross-validated area under the receiver operating characteristic curve of 0.89 (95% confidence interval: 0.82, 0.96) and an area under the precision-recall curve of 0.96 (95% confidence interval: 0.93, 0.99). The cross-validated fat fraction predicted by a two-variable fat fraction estimator was correlated with MRI PDFF (Spearman r = 0.82 [P , .001]; Pearson r = 0.76 [P , .001]). The mean bias was 0.02% (P = .97), and 95% limits of agreement were 612.0%. The predicted fat fraction was linear with MRI PDFF (R2 = 0.63; slope, 0.69; intercept, 4.3%) for MRI PDFF of 34% or less. Conclusion: A multivariable quantitative US approach yielded excellent correlation with MRI proton density fat fraction for hepatic steatosis assessment in nonalcoholic fatty liver disease.

Original languageEnglish (US)
Pages (from-to)106-113
Number of pages8
Issue number1
StatePublished - 2020

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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