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Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH
Published on: April 20, 2021
The Future Is Beyond Bright: The Evolving Role of Quantitative US for Fatty Liver Disease
Arinc Ozturk1, Viksit Kumar1, Theodore T Pierce1
1From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.).
Abstract:
Nonalcoholic fatty liver disease (NAFLD) is a common cause of morbidity and mortality. Nonfocal liver biopsy is the historical reference standard for evaluating NAFLD, but it is limited by invasiveness, high cost, and sampling error. Imaging methods are ideally situated to provide quantifiable results and rule out other anatomic diseases of the liver. MRI and US have shown great promise for the noninvasive evaluation of NAFLD. US is particularly well suited to address the population-level problem of NAFLD because it is lower-cost, more available, and more tolerable to a broader range of patients than MRI. Noninvasive US methods to evaluate liver fibrosis are widely available, and US-based tools to evaluate steatosis and inflammation are gaining traction. US techniques including shear-wave elastography, Doppler spectral imaging, attenuation coefficient, hepatorenal index, speed of sound, and backscatter-based estimation have regulatory clearance and are in clinical use. New methods based on channel and radiofrequency data analysis approaches have shown promise but are mostly experimental. This review discusses the advantages and limitations of clinically available and experimental approaches to sonographic liver tissue characterization for NAFLD diagnosis as well as future applications and strategies to overcome current limitations.
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