TY - JOUR
T1 - Assessment of hepatic steatosis in nonalcoholic fatty liver disease by using quantitative US
AU - Han, Aiguo
AU - Zhang, Yingzhen N.
AU - Boehringer, Andrew S.
AU - Montes, Vivian
AU - Andre, Michael P.
AU - Erdman, John W.
AU - Loomba, Rohit
AU - Valasek, Mark A.
AU - Sirlin, Claude B.
AU - O’Brien, William D.
N1 - Funding Information:
Disclosures of Conflicts of Interest: A.H. disclosed no relevant relationships. Y.N.Z. Activities related to the present article: disclosed money to author’s institution for a postdoctoral fellowship education grant from GE Healthcare. Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. A.S.B. disclosed no relevant relationships. V.M. disclosed no relevant relationships. M.P.A. disclosed no relevant relationships. J.W.E. disclosed no relevant relationships. R.L. disclosed no relevant relationships. M.A.V. disclosed no relevant relationships. C.B.S. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed money to author’s institution for board memberships from AMRA, Guerbet, Bristol Meyers Squibb; consultancies from GE Healthcare, Bayer, AMRA, Fulcrum Therapeutics, IBM/Watson Health; grants/grants pending from Gilead, GE Healthcare, Siemens, GE MRI, Bayer, GE Digital, GE US, ACR Innovation, Philips, Celgene, Enanta, ICON Medical Imaging, Gilead, Shire, Virtu-alscopics, Intercept, Synageva, Takeda, Genzyme, Janssen, NuSirt, Celgene-Parexel, and Organovo; payment for lectures including service on speakers bureaus from GE Healthcare and Bayer; royalties from Wolters Kluwer Health; payment for the development of educational presentations from Medscape, Resoundant; and consulting fees from Epigenomics. Other relationships: disclosed no relevant relationships. W.D.O. Activities related to the present article: disclosed money to author’s institution for a grant from National Institutes of Health. Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships.
Funding Information:
Our prospective, cross-sectional study was Health Insurance Portability and Accountability Act–compliant and institutional review board approved. Written informed consent was obtained. Our study was supported in part by Siemens Healthineers (Mu- nich, Germany) through a research grant and US scanner loan. The authors had control of the data and information submitted for publication. Some study participants were previously reported in work by Han et al (20–22), which assessed the repeatability and reproducibility of AC and BSC measurements.
Funding Information:
Study supported by National Institute of Environmental Health Sciences (5P42ES010337), National Center for Advancing Translational Sciences (5UL1TR001442), National Institute of Diabetes and Digestive and Kidney Diseases (R01DK106419, P30DK120515), and Siemens Healthineers. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The use of the Siemens scanner was loaned to University of California, San Diego, under a research agreement with Siemens Healthineers.
Publisher Copyright:
© RSNA, 2020.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
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U2 - 10.1148/radiol.2020191152
DO - 10.1148/radiol.2020191152
M3 - Article
C2 - 32013792
AN - SCOPUS:85082148062
SN - 0033-8419
VL - 295
SP - 106
EP - 113
JO - Radiology
JF - Radiology
IS - 1
ER -