The eyes are not only the windows to the soul, but also the window to detect traumatic brain injuries. Researchers at the University of Birmingham have developed a non-invasive, handheld device that shines a safe laser into the eye to detect biomarkers of damage to brain tissue after a concussion or other traumatic brain injury. The device can be used on-site at the time of injury, ensuring early diagnosis, which is crucial to improving treatment outcomes.
Traumatic brain injury (TBI) can occur after a strong impact, blow, or jolt to the head or body, causing damage that can range from mild to severe. A concussion is a type of traumatic brain injury that is common in contact sports. Although traumatic brain injuries can develop immediately after the initial trauma, many people have few clinical symptoms in the early stages, making it difficult to diagnose at the time of injury. Diagnostic tools such as MRIs and CT scans are expensive and slow to work.
Pola Goldberg Oppenheimer, corresponding author of the study, said: "Early diagnosis of traumatic brain injury is crucial because critical decisions about treatment must be made within the first 'golden hour' after injury. However, current diagnostic procedures rely on observations by ambulance personnel, and MRI or CT scans in hospitals, which may be distant."
Believing there is an urgent need to develop new technologies to ensure early diagnosis of traumatic brain injuries, researchers have developed a non-invasive handheld device that uses an eye-safe laser to rapidly detect known brain injury biomarkers.
At the back of the eye are the retina and optic nerve. The optic nerve is a projection of brain tissue and a clear optical window for observing the biochemical processes of the brain. The device developed by the researchers uses a Raman spectroscopy-based eye-protection laser (EyeD) to target specific protein and lipid biomarkers produced by localized brain tissue damage.
Raman spectroscopy is a highly specific analytical technique that can accurately identify changes in disease-specific diagnostic biomarkers by measuring the subtle responses of molecules to scattered light, thereby providing real-time, quantitative diagnostic information. Previous research has shown that the technology can accurately detect changes in brain and eye tissue in animals with varying degrees of brain damage and capture the most subtle changes.
EyeD uses a smartphone camera, and the researchers tested it on a "prosthetic eye." A "prosthetic eye" that approximates a real eye is often used in the development and evaluation of retinal imaging to ensure its ability to align and focus the back of the eyeball. They then tested it on pig eyes, and the device was able to clearly differentiate between traumatic brain injuries and healthy controls. Integrating the self-optimizing Kohonen Index Network (SKiNET) neural network algorithm into EyeD can automatically interpret data without expert support, thus greatly improving the speed and cost of diagnosis.
Researchers say using smartphone cameras will improve the device's usability. The smartphone camera-based system is easy to use, coupled with AI diagnostic support, produces an output when it gets enough signal. The experience of using smartphones to capture images is ubiquitous, so user acceptance is high.
Further research will determine the extent to which paramedics and clinicians rely on the device to drive their decision-making, but the researchers envision EyeD being incorporated into current practice.
"EyeD readings will form part of a protocolized decision tree, for example: normal EyeD + no 'red flag' symptoms or signs would classify the head injury as a mild TBI and would not require hospital evaluation; abnormal EyeD would require additional evaluation in the emergency department," the researchers said.
The proof-of-concept device is ready for further evaluation, including clinical feasibility and efficacy studies.
The research was published in the journal Science Advances.