Asymmetry analysis of cingulum based on scale-invariant parameterization by diffusion tensor imaging.
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, People's Republic of China.
Current analysis of diffusion tensor imaging (DTI) is based mostly on a region of interest (ROI) in an image dataset, which is specified by users. This method is not always reliable, however, because of the uncertainty of manual specification. We introduce an improved fiber-based scheme rather than an ROI-based analysis to study in DTI datasets of 31 normal subjects the asymmetry of the cingulum, which is one of the most prominent white matter fiber tracts of the limbic system. The present method can automatically extract the quantitative anisotropy properties along the cingulum bundles from tractography. Moreover, statistical analysis was carried out after anatomic correspondence specific to the cingulum across subjects was established, rather than the traditional whole-brain registration. The main merit of our method compared to existing counterparts is that to find such anatomic correspondence in cingulum, a scale-invariant parameterization method by arc-angle was proposed. It can give a continuous and exact description on any segment of cingulum. More interestingly, a significant left-greater-than-right asymmetry pattern was obtained in most segments of cingulum bundle (-50-25 degrees), except in the most posterior portion of cingulum (25-50 degrees).
PMID: 15455461 [Click to show in PubMed]