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Abstract Details
US Backscatter for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative
Radiology. 2022 Dec;305(3):526-537. doi: 10.1148/radiol.220606.Epub 2022 Oct 18.
1From the Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Ave, WO62, Room 2114, Silver Spring, MD 20993 (K.A.W.); Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Ill (A.H.); Department of Radiology, University of Michigan, Ann Arbor, Mich (J.M.R.); Ultrasound Research and Education, Rocky Vista University, Ivins, Utah (J.G.); Department of Engineering, Pontificia Universidad Católica del Perú, Lima, Peru (R.L.); Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montreal, Canada (G.C.); Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Division of Radiotherapy and Imaging, Joint Department of Physics, London, UK (J.B.); and Pfizer, Cambridge, Mass (T.T.).
Abstract
Nonalcoholic fatty liver disease (NAFLD) is believed to affect one-third of American adults. Noninvasive methods that enable detection and monitoring of NAFLD have the potential for great public health benefits. Because of its low cost, portability, and noninvasiveness, US is an attractive alternative to both biopsy and MRI in the assessment of liver steatosis. NAFLD is qualitatively associated with enhanced B-mode US echogenicity, but visual measures of B-mode echogenicity are negatively affected by interobserver variability. Alternatively, quantitative backscatter parameters, including the hepatorenal index and backscatter coefficient, are being investigated with the goal of improving US-based characterization of NAFLD. The American Institute of Ultrasound in Medicine and Radiological Society of North America Quantitative Imaging Biomarkers Alliance are working to standardize US acquisition protocols and data analysis methods to improve the diagnostic performance of the backscatter coefficient in liver fat assessment. This review article explains the science and clinical evidence underlying backscatter for liver fat assessment. Recommendations for data collection are discussed, with the aim of minimizing potential confounding effects associated with technical and biologic variables.