Frontiers in Neuroscience (Dec 2020)

Evaluation of White Matter Integrity Utilizing the DELPHI (TMS-EEG) System

  • Ofri Levy-Lamdan,
  • Noa Zifman,
  • Efrat Sasson,
  • Shai Efrati,
  • Shai Efrati,
  • Dallas C. Hack,
  • David Tanne,
  • David Tanne,
  • Iftach Dolev,
  • Hilla Fogel

DOI
https://doi.org/10.3389/fnins.2020.589107
Journal volume & issue
Vol. 14

Abstract

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ObjectiveThe aim of this study was to evaluate brain white matter (WM) fibers connectivity damage in stroke and traumatic brain injury (TBI) subjects by direct electrophysiological imaging (DELPHI) that analyzes transcranial magnetic stimulation (TMS)-evoked potentials (TEPs).MethodsThe study included 123 participants, out of which 53 subjects with WM-related pathologies (39 stroke, 14 TBI) and 70 healthy age-related controls. All subjects underwent DELPHI brain network evaluations of TMS-electroencephalogram (EEG)-evoked potentials and diffusion tensor imaging (DTI) scans for quantification of WM microstructure fractional anisotropy (FA).ResultsDELPHI output measures show a significant difference between the healthy and stroke/TBI groups. A multidimensional approach was able to classify healthy from unhealthy with a balanced accuracy of 0.81 ± 0.02 and area under the curve (AUC) of 0.88 ± 0.01. Moreover, a multivariant regression model of DELPHI output measures achieved prediction of WM microstructure changes measured by FA with the highest correlations observed for fibers proximal to the stimulation area, such as frontal corpus callosum (r = 0.7 ± 0.02), anterior internal capsule (r = 0.7 ± 0.02), and fronto-occipital fasciculus (r = 0.65 ± 0.03).ConclusionThese results indicate that features of TMS-evoked response are correlated to WM microstructure changes observed in pathological conditions, such as stroke and TBI, and that a multidimensional approach combining these features in supervised learning methods serves as a strong indicator for abnormalities and changes in WM integrity.

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