Unmet Need
A recent study by the National Multiple Sclerosis Society found that nearly one million people are living with multiple sclerosis (MS) in the United States, making it the most common immune-mediated inflammatory demyelinating disease of the nervous system. Due to few disease-specific characteristic symptoms and the varied pace of disease progression from patient to patient, the disease surveillance strategy for patients can vary across medical teams. Optical coherence tomography (OCT) to measure the thickness of the retinal nerve fiber layer, has been proposed as a high resolution, noninvasive way to image the retina and detect progressive optic tract demyelination, which can occur after clinically apparent and subclinical optic neuritis (ON), a condition thought to be common in MS due to the primary neurodegenerative pathology. Currently, there is no suitable method for monitoring the disease progression of MS via the retinal thickness. This is an important biomarker which can assist clinicians in treatment and disease management.
Technology Overview
Researchers at Johns Hopkins University have developed an iterative registration and deep learning based method for the longitudinal segmentation of optical coherence tomography (OCT) images of the retina. This method will allow for consistent monitoring of MS disease progression through comparisons of OCT scans taken at different times.
Stage of Development
Currently, the algorithm has been developed and tested, and is undergoing further improvements and refinement.
