Automation of Quantifying Axonal Loss in Patients with Peripheral Neuropathies through Deep Learning Derived Muscle Fat Fraction.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: May 1, 2021

Abstract

BACKGROUND: Axonal loss denervates muscle, leading to an increase of fat accumulation in the muscle. Therefore, fat fraction (FF) in whole limb muscle using MRI has emerged as a monitoring biomarker for axonal loss in patients with peripheral neuropathies. In this study, we are testing whether deep learning-based model can automate quantification of the FF in individual muscles. While individual muscle is smaller with irregular shape, manually segmented muscle MRI images have been accumulated in this lab; and make the deep learning feasible.

Authors

  • Yongsheng Chen
    The MRI Institute for Biomedical Research, Bingham Farms, MI, United States; Department of Radiology, Wayne State University, Detroit, MI, United States.
  • Daniel Moiseev
    Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan.
  • Wan Yee Kong
    Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA.
  • Alexandar Bezanovski
    Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA.
  • Jun Li
    Department of Emergency, Zhuhai Integrated Traditional Chinese and Western Medicine Hospital, Zhuhai, 519020, Guangdong Province, China. quanshabai43@163.com.

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