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Abstract #0311

Diagnostic Performance of Multiparametric Models Using Fat Fraction, Liver Stiffness, and T1 for Detection of Nonalcoholic Steatohepatitis 

Xin Lu1, Jiahui Li1, Zheng Zhu1, Alina Allen2, Taofic Mounajjed3, Kevin J Glaser1, Jinhang Gao 4, Jingbiao Chen1, Jie Chen1, Safa Hoodeshenas1, Armando Manduca1, Richard L Ehman1, and Meng Yin1
1Department of Radiology, Mayo Clinic, Rochester, MN, United States, 2Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, United States, 3Anatomic Pathology, Mayo Clinic, Rochester, MN, United States, 4Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, United States

NASH is traditionally diagnosed by liver biopsy, limited by subjective scoring and sampling error. This motivates identifying imaging-based biomarkers that might quantitatively characterize the pathophysiologic features of NASH. This prospective study established a streamlined imaging protocol for acquiring three candidate biomarkers ( fat fraction, liver stiffness, and T1 ) in a cohort of 66 patients with suspected NASH who underwent biopsy. The results indicate that a two-parameter model using fat fraction and liver stiffness has superior accuracy in diagnosing NASH, including ones that include the T1 relaxation time, which was found to have high collinearity with the fat fraction.

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