Challenge
Multiple sclerosis (MS) is the most widespread disabling neurological condition of young adults around the world. One can develop MS at any age, but most people are diagnosed between the ages of 20 and 40 with prevalence among caucasian women. The Multiple Sclerosis Foundation estimates that more than 400,000 people in the United States and about 2.5 million people around the world have MS.
Magnetic resonance imaging (MRI) of the brain is useful in the diagnosis and treatment of MS. Multiple Sclerosis is defined as an inflammatory, demyelinating condition of the central nervous system (CNS) that is generally considered to be autoimmune in nature. MRI provides reliable detection and quantitative estimation of focal white matter lesions in vivo. Diagnosis of MS is based on the disease dissemination in space and time but also on excluding other disorders that can mimic the symptoms of MS.
Neurological impairment of MS patients is poorly associated with the lesion load observed on conventional MRI scans, partly due to the low sensitivity of conventional MRI in detection of grey-matter and white-matter damage.
In order to overcome these limitations new MRI techniques have been developed such as Diffusion Weighted Imaging (DWI) and Resting State - functional MRI.
Solution
In this project, we developed a unique solution for quantification of track damage in patients in MS. This is state of the art data analysis, based on our proprietary algorithms for track reconstruction in MS and quantification of track damage using DWI in combination with conventional MRI modalities.
