Continuous Transpalpebral Pupillometer for Early Detection of Brain Swelling and Visual Loss in the ICU and Operating Room Through Closed Eyelids

About This Grant

Project Summary ICU care contributes to as much as 30% of total hospital costs and surgical complications occur in as many as 20% of operations, with a combined estimated annual cost to the U.S. of almost one trillion dollars. Devices that can reduce complications and lower these expenses are desperately needed. The pupillary light reflex is a cornerstone of both the neurological and ophthalmological examinations. This simple test provides the clinician with an enormous amount of objective information about the health of the brain and visual system, particularly in unconscious or sedated patients in the ICU after head trauma or cardiac arrest, who are at risk of sudden deterioration from brain swelling. Likewise, patients undergoing routine operations on the brain, heart, spine, and nasal sinuses are at risk of accidental loss of vision and there is no reliable method for assessing visual function in the operating room. The current standard of care in the ICU is to have the nurse manually open the eye and estimate the pupil’s response with a flashlight, which is subjective and unreliable, or use a quantitative, monocular, hand- held pupillometer once every few hours. Both methods are labor intensive, risk corneal injury, and only performed intermittently, which means that acute and dangerously high increases in brain pressure are often not identified in time. There is no reliable method for monitoring vision in the operating room, which can be accidentally lost during routine surgeries on the brain, spine, heart, nasal sinuses, and carotid arteries. Illumination Diagnostics is developing a continuous transpalpebral pupillometer to measure pupil responses through closed eyelids to solve these unmet needs. In this Phase 1 proposal, we plan to validate and optimize an adhesive eye patch design that uses infra-red light to continuously perform quantitative pupillometry, simultaneously through both closed eyelids with the following aims: 1) Use of computer modelling to design the device for maximal performance and safety, 2) Build a prototype transpalpebral pupillometer and develop image analysis software, and 3) Build an eye phantom to test and further optimize the prototype and train a machine learning algorithm. A successful device will enable clinicians to identify imminent brain or eye damage in their unconscious ICU or surgical patients and intervene earlier to preserve brain and eye function and save lives.