The overall goal of this project is to develop software which can quantitatively analyze MRI data from patients with multiple sclerosis (MS). The outcome of this project will be commercialized as: an MS image-processing service for clinical trials; a GE-specific extension of our AutoAlign MR alignment software; and finally as medical device software providing MS specific functionality (MS CAD, computer aided diagnosis) for patient care use. The proposed software, with its utilization of advanced registration, segmentation and quantification techniques, is intended to solve persistent problems in this field. MS is an incurable, neurodegenerative disease that affects approximately 1 in 1000 persons. It is the prototypical inflammatory autoimmune disorder of the central nervous system and may be the most common cause of neurological disability in young adults. To maintain functioning and alleviate symptoms, patients must undergo lifelong treatment, frequently including expensive interferon drug therapy. The appearance of new symptoms, remissions, and exacerbations over periods of years is characteristic of the clinical course of MS. Because of this variability, clinicians have sought paraclinical tests to guide treatment decisions when patients experience progressing MS attacks. MRI is recommended during the initial diagnosis by the International Panel on MS Diagnosis and is extensively utilized to monitor disease progression after a positive MS diagnosis has been determined. In the typical clinical setting, MRI evaluations of MS patients are limited to visual inspections by radiologists, and no quantification of this information is performed. Furthermore, while multicenter MS clinical trials typically utilize serial MRI scans, this information is confounded by MR registration problems because of fundamental, acquisition-level variability between scans and scanners. The technology in this project addresses all of these challenges, and should lead to greater clinical utility of MR evaluations in MS. ? Based on the 4 specific aims detailed below, during phase I of this project a software prototype which will be created to demonstrate the feasibility of this quantified MR approach to facilitate more accurate MS disease monitoring. Our first specific aim is to implement methods to provide a mask of the cerebral white matter, to aid in the detection, quantification and differentiation of MS lesions in various MR modalities. Our second specific aim is to develop algorithms to correct for patient motion between consecutive multimodal MRI scans, which is a prerequisite for multispectral MS lesion analysis. Our third specific aim is to develop prototype techniques for automatically identifying, quantifying and differentiating white matter abnormalities (i.e., putative MS lesions) on standard MR modalities. Our fourth specific aim is to validate this prototype against """"""""gold standard"""""""" methods. ? ?
