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A Prospective Blinded Study of Endoscopic Ultrasound Elastography in Liver Disease: Towards a Virtual Biopsy

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2018

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Korean Society of Gastrointestinal Endoscopy
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Schulman, Allison R., Ming V. Lin, Anna Rutherford, Walter W. Chan, and Marvin Ryou. 2018. “A Prospective Blinded Study of Endoscopic Ultrasound Elastography in Liver Disease: Towards a Virtual Biopsy.” Clinical Endoscopy 51 (2): 181-185. doi:10.5946/ce.2017.095. http://dx.doi.org/10.5946/ce.2017.095.

Abstract

Background/Aims Liver biopsy has traditionally been used for determining the degree of fibrosis, however there are several limitations. Endoscopic ultrasound (EUS) real-time elastography (RTE) is a novel technology that uses image enhancement to display differences in tissue compressibility. We sought to assess whether liver fibrosis index (LFI) can distinguish normal, fatty, and cirrhotic liver tissue. Methods: A total of 50 patients undergoing EUS were prospectively enrolled. RTE of the liver was performed to synthesize the LFI in each patient. Univariate and multivariable analyses were performed. Chi-square and t-tests were performed for categorical and continuous variables, respectively. A p-value of <0.05 was considered significant. Results: Abdominal imaging prior to endoscopic evaluation suggested normal tissue, fatty liver, and cirrhosis in 26, 16, and 8 patients, respectively. Patients with cirrhosis had significantly increased mean LFI compared to the fatty liver (3.2 vs. 1.7, p<0.001) and normal (3.2 vs. 0.8, p<0.001) groups. The fatty liver group showed significantly increased LFI compared to the normal group (3.8 vs. 1.4, p<0.001). Multivariable regression analysis suggested that LFI was an independent predictor of group features (p<0.001). Conclusions: LFI computed from RTE images significantly correlates with abdominal imaging and can distinguish normal, fatty, and cirrhotic-appearing livers; therefore, LFI may play an important role in patients with chronic liver disease.

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Endosonography, Endoscopic ultrasound, Elasticity imaging techniques, Chronic liver disease, Advanced imaging

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