Quantitative Pupillometry for the Diagnosis and Prognosis of Mild Traumatic Brain Injury

Background: The evaluation of patients who sustain a mild traumatic brain injury, otherwise known as a concussion, has long relied on self-reporting symptoms instead of objective measures. This leads to diagnostic uncertainty and the lack of an ability to predict when Service Members or players in sporting events can go back to duty or return to play, respectively. The symptoms produced after the blow to the head can be linked to dysfunction of certain brain areas and circuitry. This dysfunction can be measured by many different means. One of the simplest and most easily measured is how the pupil of the eye reacts to a light stimulus. The normal pupil response involves the complex interaction of multiple different pathways; all of which can be affected after a head injury. A small device that is already used clinically in intensive care units to measure pupil responses on patients who are in comas can be used to evaluate the degree of change in the pupil's response after a brain injury. This data can then be combined in a way to produce an algorithm that can diagnosis a mild traumatic brain injury. This directly addresses the Focus Area: solutions for the assessment of mild traumatic brain injury, to include portable devices, as it proposes to evaluate the use of a small hand-held device to evaluate pupillary changes after concussion. Additionally, given its light weight and ease of use, it also meets the area of encouragement for technologies that can be used for the objective assessment, diagnosis, and prognosis of mild traumatic brain injury in far-forward environments. The device only involves pointing it at a subject's eye and then pushing a button. It will produce a result in less than 30 seconds per eye. This ease of use and minimal training and fast response is exactly what is needed in a far-forward environment.

Study Design: The objective of this work will be to prospectively enroll cadets at West Point so that we can obtain baseline pupillary data and post-injury data. We will then modify the existing algorithm to produce an algorithm that can diagnose a concussion based on pupillary changes. Finally, we seek to test out this algorithm prospectively in a new group of cadets and determine how likely it is to correctly diagnose a concussion. We will accomplish these objectives by seeking to enroll high-risk athletes and incoming freshman at West Point. Cadets will be evaluated at the beginning of the academic year with baseline pupillary responses along with past medical histories and symptom profiles on standardized metrics. This same data will then be collected within 48 hours of a concussive event, when they are allowed to start exercising lightly, and when they are able to return to full exercise. The pupillary data and symptoms will then be compared to baseline data. This will allow the formation of a specific algorithm for the diagnosis of mild traumatic brain injury (concussion) based on the changes in the pupil's response to light. Collecting symptom data after the event will allow us to link the changes in the pupil response to severity of symptoms.

Impact: The impact of this research would be substantial as it will produce a simple and easy-to-use device that can be deployed in far-forward operational environments. This would allow medics to screen Service Members after a concussive event or head injury and identify those who are at the greatest risk of long-term symptoms. These Service Members can then be evacuated to prevent secondary injury or repeat concussions. Additionally, Service Members can be identified who would benefit from earlier initiation of therapies that could potentially decrease post-injury symptom severity. This will directly improve medical readiness by helping to diagnose and concussion and diagnose patients at risk for post-injury symptoms early. By identifying those with minimal injuries who will be able to return to duty sooner, combat power and assets can therefore be left farther forward and not have to be evacuated. These same tools could be used in training environments to evaluate suspected head injuries and remove those with severe injuries from training, thus preventing secondary injuries. Finally, this device could be used on the sideline to evaluate players after a potentially concussive event and determine if and when they are able to return to play. By providing far-forward medics with a device that can objectively assess casualties after a potentially concussive event, we will be able to evacuate the most severely injured and start therapy earlier. Ideally, decreasing evacuations and increasing combat power.