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Related Concept Videos

Structural Protein Function01:56

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Related Experiment Video

Updated: Feb 14, 2026

An Investigation of the Effects of Sports-related Concussion in Youth Using Functional Magnetic Resonance Imaging and the Head Impact Telemetry System
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Research Imaging of Brain Structure and Function After Concussion.

Catherine D Chong1, Todd J Schwedt1

  • 1Department of Neurology, Mayo Clinic, AZ, USA.

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|February 25, 2018
PubMed
Summary
This summary is machine-generated.

Advanced brain imaging techniques like diffusion tensor imaging can detect subtle neuropathology from concussions, which are often invisible on standard scans. These methods show promise for diagnosing concussions and distinguishing affected individuals from healthy controls.

Keywords:
arterial spin labelingconcussiondiffusion tensor imagingfunctional magnetic resonance imagingmagnetic resonance imagingmigrainemild traumatic brain injurypost-traumatic headacheresting-statesingle-photon emission tomography

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Sports Medicine

Background:

  • Concussions often result in lasting physical and cognitive issues.
  • Standard brain imaging fails to detect concussion-related neuropathology.
  • Advanced imaging may reveal subtle brain changes.

Purpose of the Study:

  • To review research on structural and functional brain imaging in concussion.
  • To discuss the utility of advanced imaging for concussion detection.
  • To evaluate machine learning classification models for concussion identification.

Main Methods:

  • Review of diffusion tensor imaging (DTI) studies.
  • Review of resting-state functional magnetic resonance imaging (rs-fMRI) studies.
  • Review of brain perfusion imaging studies.
  • Analysis of machine learning classification models.

Main Results:

  • Advanced imaging techniques (DTI, rs-fMRI, perfusion imaging) show potential in identifying concussion neuropathology.
  • These methods offer insights into brain changes post-concussion.
  • Machine learning models demonstrate accuracy in classifying concussed patients.

Conclusions:

  • Advanced neuroimaging techniques are valuable tools for understanding concussion.
  • These imaging modalities can aid in differentiating concussed individuals from healthy controls.
  • Machine learning algorithms enhance the diagnostic accuracy of imaging data for concussion.