Retinal eye-tracking as a prognostic tool for traumatic brain injury and concussion

NIH RePORTER · NIH · R44 · $1,454,697 · view on reporter.nih.gov ↗

Abstract

Abstract The goal of our project is to further develop the tracking scanning laser ophthalmoscope (TSLO), the Retitrack device, to enable widespread use of the technology for high-resolution eye- tracking for head injuries, such as mild traumatic brain injury (mTBI)/concussions. Phase I of this grant enabled the collection of data from 50 patients who had recently been diagnosed with a concussion both during their acute recovery period and upon clearance. Accounting for age and time since injury, fixational eye motion metrics were able to predict individuals with prolonged recovery (AUC=0.81; 95% CI: 0.68-0.93; p<0.001). The Retitrack brings an unprecedented level of accuracy of eye tracking to the clinic by using an image-based retinal approach resulting in motion measurements with a sensitivity of 0.25 arcmin (~1 micron). Currently, this system is the most accurate, fast and functional eye-tracking system used in a standard ophthalmic instrument. Research has suggested that pupil eye-tracking technologies have validated the idea of using eye movements as a biomarker of concussion, but the current eye-trackers available lack the capacity, repeatability, and sensitivity to predict recovery in mTBI. The Retitrack device can accurately measure fixational eye movements (FEMs), quantify retinal saccades at an unprecedented level, and can become an emerging biomarker of mTBI prognosis. Furthermore, it can serve as an indicator of severity in the symptomatology of multiple other neurological disorders. The Retitrack device as a concussive prognostic tool would be the perfect fit for Sport Medicine Clinics and the locker room for post-concussion recovery monitoring ensuring a safe return to activity and mitigating long-term consequences of concussion by guiding the most effective therapies. Further optimization of fixational tasks and the construction of innovative software that uses Artificial Intelligence algorithms to automatically quantify retinal microsaccades which will lead to the improvement of predicting the recovery and/or worsening of concussion.

Key facts

NIH application ID
10547738
Project number
2R44NS095090-02A1
Recipient
C. LIGHT TECHNOLOGIES, INC.
Principal Investigator
Christy Kathleen Sheehy
Activity code
R44
Funding institute
NIH
Fiscal year
2022
Award amount
$1,454,697
Award type
2
Project period
2016-07-16 → 2024-08-31