AUTHOR=Samadani Uzma , Spinner Robert J. , Dynkowski Gerard , Kirelik Susan , Schaaf Tory , Wall Stephen P. , Huang Paul TITLE=Eye tracking for classification of concussion in adults and pediatrics JOURNAL=Frontiers in Neurology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.1039955 DOI=10.3389/fneur.2022.1039955 ISSN=1664-2295 ABSTRACT=Introduction

In order to obtain FDA Marketing Authorization for aid in the diagnosis of concussion, an eye tracking study in an intended use population was conducted.

Methods

Potentially concussed subjects recruited in emergency department and concussion clinic settings prospectively underwent eye tracking and a subset of the Sport Concussion Assessment Tool 3 at 6 sites. The results of an eye tracking-based classifier model were then validated against a pre-specified algorithm with a cutoff for concussed vs. non-concussed. The sensitivity and specificity of eye tracking were calculated after plotting of the receiver operating characteristic curve and calculation of the AUC (area under curve).

Results

When concussion is defined by SCAT3 subsets, the sensitivity and specificity of an eye tracking algorithm was 80.4 and 66.1%, The AUC was 0.718. The misclassification rate (n = 282) was 31.6%.

Conclusion

A pre-specified algorithm and cutoff for diagnosis of concussion vs. non-concussion has a sensitivity and specificity that is useful as a baseline-free aid in diagnosis of concussion. Eye tracking has potential to serve as an objective “gold-standard” for detection of neurophysiologic disruption due to brain injury.