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. 2020 Nov 12:14:581819.
doi: 10.3389/fnbeh.2020.581819. eCollection 2020.

Oculomotor Behavior as a Biomarker for Differentiating Pediatric Patients With Mild Traumatic Brain Injury and Age Matched Controls

Melissa Hunfalvay  1 , Nicholas P Murray  2 , Claire-Marie Roberts  3 , Ankur Tyagi  1 , Kyle William Barclay  4 , Frederick Robert Carrick  5   6   7
Affiliations

Oculomotor Behavior as a Biomarker for Differentiating Pediatric Patients With Mild Traumatic Brain Injury and Age Matched Controls

Melissa Hunfalvay et al. Front Behav Neurosci. .

Abstract

Importance: Children have the highest incidence of mild traumatic brain injury (mTBI) in the United States. However, mTBI, specifically pediatric patients with mTBI, are notoriously difficult to detect, and with a reliance on traditional, subjective measurements of eye movements, the subtle but key oculomotor deficits are often missed.

Objective: The purpose of this project is to determine if the combined measurement of saccades, smooth pursuit, fixations and reaction time represent a biomarker for differentiating pediatric patients with mild traumatic brain injury compared to age matched controls.

Design: This study used cross-sectional design. Each participant took part in a suite of tests collectively labeled the "Brain Health EyeQ" to measure saccades, smooth pursuit, fixations and reaction time.

Participants: The present study recruited 231 participants - 91 clinically diagnosed with a single incident mTBI in the last 2 days as assessed by both the Glasgow Coma Scale (GCS) and Graded Symptoms Checklist (GSC), and 140 age and gender-matched controls (n = 165 male, n = 66 female, M age = 14.20, SD = 2.78).

Results: One-way univariate analyses of variance examined the differences in performance on the tests between participants with mTBI and controls. ROC curve analysis examined the sensitivity and specificity of the tests. Results indicated that together, the "Brain Health EyeQ" tests were successfully able to identify participants with mTBI 75.3% of the time, providing further validation to a growing body of literature supporting the use of eye tracking technology for mTBI identification and diagnosis.

Keywords: concussion; eye-tracking; mTBI; oculomotor; pediateric case.

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Figures

FIGURE 1
FIGURE 1
Mean Differences (with standard error) comparing BHEQ score between mTB and Control.
FIGURE 2
FIGURE 2
Dot Graph and probability curve for Control group (blue) and TBI group (red).
FIGURE 3
FIGURE 3
Receiver Operator Characteristic analysis predicting mTBI Status for all significant variables.
See this image and copyright information in PMC

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