A technology that tracks patients’ eye movements as they watch music videos may be a possible biomarker for concussion, according to researchers.
A study published recently in the journal Concussion examines this technology, which was developed by Uzma Samadani, MD, PhD, and researchers at the Steven and Alexandra Cohen Veterans Center at NYU Langone Medical Center, according to a news release from Hennepin County Medical Center, where Samadani recently joined the faculty.
The release explains that the technology works by having patients watch a music video for 220 seconds while eye movements are measured using a tracking camera. Multiple measures of each eye’s movement, followed by comparisons of their positions over time, are used to distinguish between normal subjects and those with concussion.
During the study, Samadani, and colleagues Charles Marmar, MD, and Eugene Laska PhD, built a classifier based on 34 emergency department patients with brain injury and 34 uninjured healthy control subjects of similar age. A classifier is a mathematical model that converts a patient’s eye movement measures into a prediction of the concussive status of the individual.
They then tested the models on a dataset of 255 subjects, of whom eight had concussions, and found that the eye tracking test had an optimal sensitivity of 88% and a specificity of 87%, the release continues.
Typically, a classifier produces a score, and a subject is classified as having a concussion if the score exceeds a predefined threshold value. The accuracy of a biomarker is measured by plotting the probability of a true versus false positivity at each possible threshold value and the Area Under the Curve (AUC) is computed.
A perfect biomarker has an AUC of 1.00, while a worthless marker—no better than the chance toss of a coin—has an AUC of 0.50. Most tests used clinically have AUCs greater than 0.80. For example, serum troponin, the most commonly performed blood test for heart attacks, has an AUC ranging in various studies from 0.76 to 0.96. In this study, the eye tracking-based classifier had an AUC of 0.88 and a cross-validated AUC of 0.85, the release explains.
According to Samadani, the major challenge for any technology proposed as a biomarker for concussion is first defining concussion.
“Potentially, eye tracking may be more accurate than it appears, because of its objective appraisal of a complicated process of coordination that may be impaired,” she adds in the release.
In an accompanying editorial that also appears with the study, Samadani proposes that eye tracking will help diagnose and classify brain injury and concussion, particularly in patients with elevated pressure inside their skulls and disruption of pathways in the brain that control eye movements, per the release.
[Source(s): Hennepin County Medical Center, PR Newswire]