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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