A method for the analysis of the geometrical relationship between white matter pathology and the vascular architecture of the brain.
A novel method for the visual and quantitative analysis of the geometrical relationship between the vascular architecture of the brain and white matter pathology is presented. The cerebro vascular system is implicated in the pathogenesis of many diseases of the cerebral white matter, for example, stroke, microcerebrovascular disease, and multiple sclerosis (MS). In our work, white matter lesions and vessels are depicted using magnetic resonance imaging (MRI) and extracted using image analysis techniques. We focus on measuring distance relationships between white matter lesions and vessels, and distribution of lesions with respect to vessel caliber. Vascular distance maps are generated by computing for each voxel the Euclidean distance to the closest vessel. Analogously, radius maps assign the radius of the closest vessel to each voxel in the image volume. The distance and radius maps are used to analyze the distribution of lesions with respect to the vessels' locations and their calibers. The method was applied to three MS patients to demonstrate its functionality and feasibility. Preliminary findings indicate that larger MS lesions tend to be farther from detected vessels and that the caliber of the vessels nearest to larger lesions tends to be smaller, suggesting a possible role of relative hypoperfusion or hypoxia in lesion formation.
Center for Neurological Imaging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Dorota
D
Kozinska
Christopher M
CM
Holland
Karl
K
Krissian
Carl-Fredrik
CF
Westin
Charles R G
CR
Guttmann
D001921:Brain / Q000473:pathology; D002545:Brain Ischemia / Q000175:diagnosis / Q000473:pathology*; D002536:Cerebral Arteries / Q000473:pathology; D002550:Cerebral Veins / Q000473:pathology; D002561:Cerebrovascular Disorders / Q000175:diagnosis / Q000473:pathology*; D006801:Humans; D002534:Hypoxia, Brain / Q000175:diagnosis / Q000473:pathology*; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D018810:Magnetic Resonance Angiography; D008279:Magnetic Resonance Imaging; D008432:Mathematical Computing; D009103:Multiple Sclerosis / Q000175:diagnosis / Q000473:pathology*; D012016:Reference Values