Quantitative Pupillometry Combined with Blood Biomarkers for the Diagnosis and Prognosis of Mild Traumatic Brain Injury

Objectives and Rationale: The evaluation of patients who sustain a mild-traumatic brain injury (mTBI), otherwise known as a concussion, has long relied on self-reported symptoms to make a diagnosis. Additionally, there has been no way to predict how long the symptoms will last and when athletes can return to play or Soldiers can return to duty. This leads to diagnostic uncertainty. There is evidence that the symptoms produced after the blow to the head can be linked to the dysfunction of certain brain areas and circuitry throughout the brain. This dysfunction can be measured by many different means, including the response of the pupil to light. The forces required to cause a mTBI or concussive event can also damage brain structures. This damage releases certain molecules into the blood that can be quantified in peripheral blood. This device used to quantify those molecular injury markers in blood, combined with a small device that rapidly (

Study Design: The objective of this work will be to create a diagnostic and predictive model for mTBI based on measuring the pupil's response to light and blood-based markers of brain cell injury. This will be accomplished by prospectively enrolling cadets at West Point. We will compare the changes in their pupillary data to the blood-based biomarkers. Data from commonly used markers of symptom severity, reaction time, and concentration will also be collected prior to any injury, within 48 hours of their injury, when they are allowed to start exercising again, and when they are released for full activity. Collecting this data will provide the ability to link pupil changes and blood-based marker elevations with symptom severity, as well as a much better ability to diagnose and predict outcomes.

Impact: The impact of this research will be substantial, as it will produce a simple, easy-to-use device and an algorithm that could be used in a far-forward military operations or on the sideline of a sporting event. 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 repeat concussions which are known risk factors for worsening long-term symptoms. 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 a concussion, determine who is at risk for continued post-injury symptoms, and allow their treatments to start earlier. 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 whether and when they are able to return to play. Therefore, the patients to be helped will be all athletes at risk for concussion and military members both in training and on deployments. Ideally, decreasing evacuations and increasing combat power. The timeline to achieving patient related outcomes is 6 years. This proposal designs and tests the algorithm in a population of cadets an defines the algorithm's ability to diagnose the concussion. A follow-on study testing the algorithm and blood markers in a different group of athletes and military members would make the algorithm more generalizable and more applicable throughout the military population. The second clinical trial in a more robust patient population would also collect data for a new FDA licensure to use the tool as a diagnostic aide in concussions. This second study is projected to last 3 years. It will substantially impact Veterans and Service members, as we can start therapies earlier if they are at high risk of long-term symptoms and will likely lead to improved outcomes with shorter lengths of symptoms.