Longitudinal, regional and deformation-specific corpus callosum shape analysis for multiple sclerosis.
The corpus callosum (CC) is an anatomical structure which connects the two brain hemispheres. Neurological diseases can cause atrophy of the CC resulting in a change in its size and shape. The measurement and analysis of this change is one of the goals of clinical research. We perform statistical analysis of the shape of the CC extracted from MR brain scans of a group of multiple sclerosis patients undergoing a longitudinal (serial) study. In contrast to the classical boundary-based, global shape variability measures, e.g. principal component analysis (PCA) of CC boundary vertices, we perform a deformation-specific PCA for analyzing the global and regional shape of the CC. This deformation-specific PCA is based on a medial-based shape representation. The adopted shape representation describes shape variability in terms of intuitive deformations (e.g. bending, stretching and thickness). We present qualitative and quantitative results for 412 MR images of the CC. We show that our method is successful in identifying and quantifying the effect of each type of deformation on the shape variability of the CC. In addition to analyzing the spatial shape variability in the CC, we explore shape changes as the disease progresses. Our method allows the exploration of the shape variability quantitatively (e.g. the amount of variance explained by a particular principal mode of shape variation) as well as in a qualitative visual manner (e.g. by visualizing, say, the 2nd principal mode of shape variation due to bending at the 4th sub-region of the CC) which is useful for developing an intuitive understanding of the effects of MS on the CC shape.
Ishaq
Omer
O
Medical Image Analysis Lab, School of Computing Science, Simon Fraser University, Burnaby, Canada.
Hamarneh
Ghassan
G
Tam
Roger
R
Traboulsee
Anthony
A
D001921:Brain / Q000033:anatomy & histology* / Q000473:pathology; D001931:Brain Mapping; D003337:Corpus Callosum / Q000033:anatomy & histology* / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D008279:Magnetic Resonance Imaging; D008953:Models, Anatomic; D015233:Models, Statistical; D008962:Models, Theoretical; D009103:Multiple Sclerosis / Q000175:diagnosis* / Q000473:pathology*; D025341:Principal Component Analysis; D013997:Time Factors