Magnetoencephalography in the Detection and Characterization of Brain Abnormalities Associated with Traumatic Brain Injury: A Comprehensive Review.

Geoffrey W Peitz,Ramesh Grandhi,Elisabeth A Wilde

doi:10.3390/medsci9010007

Abstract

Magnetoencephalography (MEG) is a functional brain imaging technique with high temporal resolution compared with techniques that rely on metabolic coupling. MEG has an important role in traumatic brain injury (TBI) research, especially in mild TBI, which may not have detectable features in conventional, anatomical imaging techniques. This review addresses the original research articles to date that have reported on the use of MEG in TBI. Specifically, the included studies have demonstrated the utility of MEG in the detection of TBI, characterization of brain connectivity abnormalities associated with TBI, correlation of brain signals with post-concussive symptoms, differentiation of TBI from post-traumatic stress disorder, and monitoring the response to TBI treatments. Although presently the utility of MEG is mostly limited to research in TBI, a clinical role for MEG in TBI may become evident with further investigation.

Highlights

Traumatic brain injury (TBI) occurs an estimated 27 million to 69 million times per year throughout the world [1,2]
Dunkley (2015) theorized that the two disorders could be distinguished based on MEG and that increased high-frequency phase synchronization seen in post-traumatic stress disorder (PTSD) could be the result of a psychological state, whereas increased low-frequency amplitude coupling in mild TBI could be the result of neurostructural alteration [50]
MEG is a functional brain imaging technique with high temporal resolution and reasonable spatial resolution when co-registered with anatomical magnetic resonance imaging (MRI)

Summary

Introduction

Traumatic brain injury (TBI) occurs an estimated 27 million to 69 million times per year throughout the world [1,2]. Byrnes et al have comprehensively reviewed the use of FDG-PET in TBI [12] These techniques, especially fMRI, provide good spatial resolution, there is a delay between neuronal activation and the associated increase in blood flow and energy supply. The articles described the use of MEG for detecting TBI, differentiating TBI from conditions with similar features, characterizing changes in brain rhythm or connectivity from TBI, correlating imaging findings with clinical features, and monitoring the response to treatments. These applications are described in detail . Tensor subspace analysis Iterative bootstrap Rank-feature k-NN, ENS, ELM k-NN, SVM k-NN

Detection of TBI

Differentiating Mild TBI from Post-traumatic Stress Disorder

Monitoring Response to Treatments

Limitations of MEG

Findings

Conclusions