Deep Learning Convolutional Neural Networks for the Automatic Quantification of Muscle Fat Infiltration Following Whiplash Injury

Sci Rep. 2019 May 28;9(1):7973. doi: 10.1038/s41598-019-44416-8.


Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated state-of-the-art performance in segmentation tasks. Here, we train and test a CNN for muscle segmentation and automatic MFI calculation using high-resolution fat-water images from 39 participants (26 female, average = 31.7 ± 9.3 years) 3 months post whiplash injury. First, we demonstrate high test reliability and accuracy of the CNN compared to manual segmentation. Then we explore the relationships between CNN muscle volume, CNN MFI, and clinical measures of pain and neck-related disability. Across all participants, we demonstrate that CNN muscle volume was negatively correlated to pain (R = -0.415, p = 0.006) and disability (R = -0.286, p = 0.045), while CNN MFI tended to be positively correlated to disability (R = 0.214, p = 0.105). Additionally, CNN MFI was higher in participants with persisting pain and disability (p = 0.049). Overall, CNN's may improve the efficiency and objectivity of muscle measures allowing for the quantitative monitoring of muscle properties in disorders of and beyond the cervical spine.

Publication types

  • Clinical Trial
  • Observational Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adipose Tissue / diagnostic imaging*
  • Adipose Tissue / physiopathology
  • Adult
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Longitudinal Studies
  • Magnetic Resonance Imaging
  • Male
  • Muscle, Skeletal / diagnostic imaging*
  • Muscle, Skeletal / physiopathology
  • Neck / diagnostic imaging*
  • Neck / physiopathology
  • Neural Networks, Computer*
  • Pain / diagnostic imaging*
  • Pain / physiopathology
  • Reproducibility of Results
  • Spectrum Analysis / methods
  • Spectrum Analysis / statistics & numerical data
  • Spine / diagnostic imaging*
  • Spine / physiopathology
  • Water / chemistry
  • Whiplash Injuries / diagnostic imaging*
  • Whiplash Injuries / physiopathology


  • Water