title: Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat Using a New Quantitative Ultrasound Technique.
abstract: OBJECTIVE
  Liver biopsy analysis is the standard method used to diagnose nonalcoholic fatty liver disease (NAFLD). Advanced magnetic resonance imaging is a noninvasive procedure that can accurately diagnose and quantify steatosis, but is expensive. Conventional ultrasound is more accessible but identifies steatosis with low levels of sensitivity, specificity, and quantitative accuracy, and results vary among technicians. A new quantitative ultrasound (QUS) technique can identify steatosis in animal models. We assessed the accuracy of QUS in the diagnosis and quantification of hepatic steatosis, comparing findings with those from magnetic resonance imaging proton density fat fraction (MRI-PDFF) analysis as a reference.
  
  
  METHODS
  We performed a prospective, cross-sectional analysis of a cohort of adults (N = 204) with NAFLD (MRI-PDFF, ≥5%) and without NAFLD (controls). Subjects underwent MRI-PDFF and QUS analyses of the liver on the same day at the University of California, San Diego, from February 2012 through March 2014. QUS parameters and backscatter coefficient (BSC) values were calculated. Patients were assigned randomly to training (n = 102; mean age, 51 ± 17 y; mean body mass index, 31 ± 7 kg/m(2)) and validation (n = 102; mean age, 49 ± 17 y; body mass index, 30 ± 6 kg/m(2)) groups; 69% of patients in each group had NAFLD.
  
  
  RESULTS
  BSC (range, 0.00005-0.25 1/cm-sr) correlated with MRI-PDFF (Spearman ρ = 0.80; P < .0001). In the training group, the BSC analysis identified patients with NAFLD with an area under the curve value of 0.98 (95% confidence interval, 0.95-1.00; P < .0001). The optimal BSC cut-off value identified patients with NAFLD in the training and validation groups with 93% and 87% sensitivity, 97% and 91% specificity, 86% and 76% negative predictive values, and 99% and 95% positive predictive values, respectively.
  
  
  CONCLUSIONS
  QUS measurements of BSC can accurately diagnose and quantify hepatic steatosis, based on a cross-sectional analysis that used MRI-PDFF as the reference. With further validation, QUS could be an inexpensive, widely available method to screen the general or at-risk population for NAFLD.
authors.affiliation: NAFLD Translational Research Unit, Division of Gastroenterology, University of California at San Diego, La Jolla, California.
authors.forename: Steven C
authors.initials: SC
authors.lastname: Lin
authors.affiliation: Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, California.
authors.forename: Elhamy
authors.initials: E
authors.lastname: Heba
authors.affiliation: Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California at San Diego, La Jolla, California.
authors.forename: Tanya
authors.initials: T
authors.lastname: Wolfson
authors.affiliation: NAFLD Translational Research Unit, Division of Gastroenterology, University of California at San Diego, La Jolla, California.
authors.forename: Brandon
authors.initials: B
authors.lastname: Ang
authors.affiliation: Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California at San Diego, La Jolla, California.
authors.forename: Anthony
authors.initials: A
authors.lastname: Gamst
authors.affiliation: Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois.
authors.forename: Aiguo
authors.initials: A
authors.lastname: Han
authors.affiliation: Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, Illinois.
authors.forename: John W
authors.initials: JW
authors.lastname: Erdman
authors.affiliation: Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois.
authors.forename: William D
authors.initials: WD
authors.lastname: O'Brien
authors.affiliation: Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, California; San Diego Veterans Affairs Healthcare System, San Diego, California.
authors.forename: Michael P
authors.initials: MP
authors.lastname: Andre
authors.affiliation: Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, California.
authors.forename: Claude B
authors.initials: CB
authors.lastname: Sirlin
authors.affiliation: NAFLD Translational Research Unit, Division of Gastroenterology, University of California at San Diego, La Jolla, California; Division of Epidemiology, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, California. Electronic address: roloomba@ucsd.edu.
authors.forename: Rohit
authors.initials: R
authors.lastname: Loomba
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000818:Animals; D002140:California; D003430:Cross-Sectional Studies; D005234:Fatty Liver / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging* / Q000473:pathology*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D065626:Non-alcoholic Fatty Liver Disease / Q000175:diagnosis*; D011446:Prospective Studies; D014463:Ultrasonography
keywords: AUC; Biomarker; Chronic Liver Disease; Diagnostic; Hepatic Steatosis; Magnetic Resonance Imaging; Nonalcoholic Steatohepatitis