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Related Experiment Video

Updated: Aug 23, 2025

Automated Gait Analysis to Assess Functional Recovery in Rodents with Peripheral Nerve or Spinal Cord Contusion Injury
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Functional Gait Assessment Using Manual, Semi-Automated and Deep Learning Approaches Following Standardized Models of

Daniel Umansky1, Kathleen M Hagen2, Tak Ho Chu1

  • 1Department of Clinical Neurosciences, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, AB T2N 4N1, Canada.

Biomolecules
|October 27, 2022
PubMed
Summary

A novel stretch-crush sciatic nerve injury model in mice showed more severe initial damage than crush-only injuries. However, behavioral recovery outcomes were similar, highlighting the need for further validation of advanced gait analysis methods.

Keywords:
CNNDNNsNCVNICPNISFIVGLVisual Gait Labconvolutional neural networkcrush injurydeep learningdeep neural networksgait analysisnerve conduction velocityneuroma in continuityperipheral nerve injurysciatic functional indexsciatic nervesemi-automatedstretch–crush injuryvon Frey monofilament test

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Area of Science:

  • Neuroscience
  • Regenerative Medicine
  • Biomedical Engineering

Background:

  • Peripheral nerve injuries (PNIs) significantly impact patient mobility and quality of life.
  • Developing standardized and reproducible animal models is crucial for studying PNI mechanisms and testing therapeutics.
  • Existing crush injury models may not fully replicate the complexity of certain nerve injuries.

Purpose of the Study:

  • To establish a standardized stretch-crush sciatic nerve injury model in mice.
  • To compare the outcomes of stretch-crush versus crush-only injuries using behavioral and histological assessments.
  • To evaluate the efficacy of semi-automated and deep-learning gait analysis in assessing PNI recovery.

Main Methods:

  • Development of crush and stretch-crush sciatic nerve injury models in mice.
  • Weekly behavioral assessments including von Frey monofilament testing and DigiGait platform analysis (Visual Gait Lab deep learning and sciatic functional index).
  • Histological analysis, nerve conduction velocity measurements, and calf muscle weight ratio determination at study termination.

Main Results:

  • Stretch-crush injury induced more severe histomorphological damage one week post-injury compared to crush-only.
  • Both injury types showed significant paw withdrawal and gait impairment initially, with recovery to baseline by week five.
  • Calf muscle weight ratios were significantly lower in the stretch-crush group, indicating greater muscle atrophy, despite similar nerve conduction velocities.

Conclusions:

  • The stretch-crush model provides a more reproducible and severe injury compared to crush-only models.
  • While initial injury severity differs, behavioral recovery kinetics are comparable between the two models.
  • Deep learning and semi-automated gait analysis show promise for PNI assessment but require further validation in murine models.