These technologies show promise in predicting dementia years before clinical symptoms develop; diagnosing concussion and other brain injuries; and more.
Researchers at Technion-Israel Institute of Technology  have developed an eyelid motion meter (EMM) for non-invasive early diagnosis and follow-up of ophthalmic, neurological, and autoimmune diseases. The device uses standard refraction glasses and two small magnets stuck to the upper eyelids. It monitors and interprets eyelid movement by using a computer algorithm that processes electrical signals sent by the magnets.
Clinical trials are being conducted at Haemek Medical Center in Afula, Israel. Findings from preliminary research in patients with blepharospasm dystonia suggest a significant correlation between blink pattern and disease, demonstrating that the device could be used for diagnosis. Studies are also being conducted in patients with dementia and Parkinson Disease. The EMM has won several international awards, and was ranked in the top 20 in the Texas Instruments Innovation Challenge (TIIC) – Europe Design Contest.
A dozen hospitals in the US have developed high tech mobile stroke units aimed at decreasing time to treatment in stroke. The units include state-of-the-art ambulances with a CT scanner, imaging tech, paramedic, nurse, neurologist or telemedicine technology connecting to one, and tPA for treating clots. When a 9-1-1 call is placed for stroke, the mobile unit drives within a 7 to 8 mile radius while paramedics in a regular ambulance evaluate the patient. If the patient is having an ischemic stroke, the mobile stroke unit continues to the patient’s location or meets them halfway during transport in the regular ambulance. So far, about 30% of stroke patients treated with mobile stroke units receive care within the first hour after a stroke, compared to just 1% in the ER. A large randomized trial in Houston, Memphis, and Denver is currently looking at outcomes and cost effectiveness of these units.
In October 2017, the FDA cleared the Siemens High-Field 7 Tesla MRI Scanner, MAGNETOM Terra, which until now has been available only in research settings. The more powerful scanner can produce more detailed images of the brain, potentially allowing for visualization of structures not seen before. It can distinguish between white and gray matter, which may aid in treatment decisions for epilepsy or identify lesions in multiple sclerosis. The device uses the same software as Siemens Healthineers, which enables users to work the same way as they would with 1.5T and 3T technology.
Researchers at the University of Washington have developed PupilScreen, a smartphone app for assessing the pupillary light reflex and diagnosing concussion. The app is designed to be as easy to use as the pen light test: when the patient looks at the phone, the app produces a flash and records the person’s response. Algorithms process the video and measure the increase in pupil size after the flash. The app currently uses a head mount like a virtual reality display to block surrounding light, but researchers are developing a version that can work with surrounding ambient lighting. Preliminary research suggests that app can diagnose significant traumatic brain injury, but larger studies are needed.
Researchers at McGill University[4,5] have developed software for analyzing images of amyloid PET scans and estimating the risk of developing dementia. Findings suggest that the software can predict dementia up to two years before clinical symptoms develop. An initial study using data from the Alzheimer Disease Neuroimaging Initiative (ADNI) showed that the algorithm achieved 84% accuracy in predicting the development of dementia. Researchers are continuing to evaluate other biomarkers to incorporate into the algorithm to improve its accuracy. The software is already available to scientists, but will not be ready for clinical use until larger trials have been conducted and regulatory authorities have weighed in.