BLOG: Eye-tracking technology may help clinicians identify TBI
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Early detection is critical for traumatic brain injury patients to have the best chance of a successful recovery.
One of the biggest challenges, however, is diagnosing the condition. The symptoms are varied, impairment can be difficult to see with the naked eye, and most types of brain injuries are mild. The scientific community has been trying to find ways to assist clinicians via technology.
The three “legs” of the diagnostic tool for TBI are balance, vision and cognition. Although many traditional diagnostic methods tend to be subjective, eye movements can provide an objective window into the neural dysfunction associated with head injuries (Bedell et al; Johnson et al). Different types of eye movements are triggered by different parts of the brain. For example, vertical smooth pursuits (VSPs) are a marker of brain function (Contreras et al), meaning injuries like TBI can impair smooth pursuit performance (Leigh et al).
Although evaluating eye movements like VSPs can be difficult to identify with the naked eye, eye-tracking technology can detect several different types of eye movements several times per second (Barnes). As an objective test, eye-tracking technology can be used to uncover VSP deficits (Hunfalvay et al). As such, it can detect damage to neural circuitry caused by TBI, supplying sensitive quantifiable data that can be added to other methods (Maruta et al). As the widespread cortico-cerebellar circuits involved in smooth pursuits are easily compromised after TBI, it is important to measure smooth pursuit deficits.
Previous research has shown that patients with mild TBI who tracked an object in a circular path had decreased target prediction and increased eye position error and variability compared with controls. These impairments correlated with cognitive deficits (Suh, Kolster, et al; Suh, Basu et al). Other studies have found increased error and variability in gaze position with reduced smooth pursuit velocity in acute mild TBI patients on a circular visual tracking task (Maruta et al).
A study was conducted to compare VSPs in healthy participants with patients with different levels of TBI. The investigators divided the 92 participants into four groups: mild TBI, moderate TBI, severe TBI and healthy controls.
Each group had their VSP eye movements evaluated using the RightEye Vision Tracker2. The results showed the VSP eye tracking test was able to distinguish between severe TBI, mild TBI and healthy controls. No significant differences were found between mild TBI and healthy controls on these variables. Follow-up logistic regressions resulted in smooth pursuit percentage and smooth pursuit variance differentiating between all TBI groups and healthy controls. Sensitivity was reported as a moderate 0.68, and specificity was higher at 0.73. Area under the curve was a high 0.772, indicating a good level of accuracy.
These results indicate that VSP testing can be one important additive test to give clinicians a more specific understanding of the level of TBI and location of possible injury. When combined with other eye tracking tests such as saccades and fixations, brain mapping is more comprehensive.
Eye tracking is a highly quantitative and specific tool to assess vision and give clinicians data that relate to ocular motor behavior as it pertains to differentiating individuals with moderate and severe levels of TBI. The practicality lies in its speed and ease of use, and it has great potential to fill a void in current TBI testing.
The objective data not only measure eye movement deficits at the time of injury but can be used to track recovery by retesting to determine if symptoms have subsided. VSP, although representing just one of several metrics that can be measured using eye tracking, by itself offers valuable information about the patient's condition and recovery.
References:
- Barnes GR. Brain Cogn. 2008;doi:10.1016/j.bandc.2008.08.020.
- Bedell HE, Stevenson SB. Vision Res. 2013;doi:10.1016/j.visres.2013.02.001.
- Contreras R, et al. Brain Res. 2011;doi:10.1016/j.brainres.2011.05.004.
- Hunfalvay M, et al. Concussion. 2020;doi:10.2217/cnc-2019-0013.
- Johnson B, et al. Brain Imaging Behav. 2015;doi:10.1007/s11682-014-9316-x.
- Leigh RJ, Zee DS. The Neurology of Eye Movements. New York: Oxford University Press; 2015.
- Maruta J, et al. Ann NY Acad Sci. 2010;doi:10.1111/j.1749-6632.2010.05695.x.
- Maruta J, et al. Mil Med. 2014;doi:10.7205/MILMED-D-13-00420.
- Suh M, Kolster R, et al. Neurosci Lett. 2006;doi:10.1016/j.neulet.2006.02.074.
- Suh M, Basu S, et al. Neurosci Lett. 2006;doi:10.1016/j.neulet.2006.10.001.
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Melissa Hunfalvay, PhD, is the cofounder and chief science officer of RightEye.
Disclaimer: The views and opinions expressed in this blog are those of the authors and do not necessarily reflect the official policy or position of the Neuro-Optometric Rehabilitation Association unless otherwise noted. This blog is for informational purposes only and is not a substitute for the professional medical advice of a physician. NORA does not recommend or endorse any specific tests, physicians, products or procedures. For more on our website and online content, click here.
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