Automated Analysis of Multiparametric Magnetic Resonance Imaging/Magnetic Resonance Elastography Exams for Prediction of Nonalcoholic Steatohepatitis

Abstract

Nonalcoholic fatty liver disease (NAFLD) affects 25% of the global population. The standard of diagnosis, biopsy, is invasive and affected by sampling error and inter‐reader variability. We hypothesized that widely available rapid MRI techniques could be used to predict nonalcoholic steatohepatitis (NASH) noninvasively by measuring liver stiffness, with magnetic resonance elastography (MRE), and liver fat, with chemical shift‐encoded (CSE) MRI. Besides, we validate an automated image analysis technique to maximize the utility of these methods.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 15, 2021
Source ID
10.1002/jmri.27549

Entities

People

  • Alina M Allen
  • Bogdan Dzyubak
  • Jiahui Li
  • Jie Chen
  • Kristin C. Mara
  • Meng Yin
  • Richard Ehman
  • Sudhakar Kundapur Venkatesh
  • Terry M. Therneau

Organizations

  • Mayo Clinic
  • National Institutes of Health Clinical Center
  • United States Department of Defense

Tags

Fields of Study

  • Medicine
  • Physics

Readers

  • Medical Imaging.
  • Molecular and Cellular Biology