Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis.

PURPOSE: To compare the diffusion tensor imaging (DTI) measures of multiple sclerosis (MS) patients and healthy subjects in every brain voxel and to correlate them with Paced Auditory Serial Addition Test (PASAT) scores. MATERIALS AND METHODS: Fractional anisotropy (FA), and mean, longitudinal, and transverse diffusivity are compared between control subjects and MS patients, which were subdivided as mildly and moderately impaired. In addition, PASAT scores are correlated for both MS groups with the diffusion measures. An optimized voxel based analysis (VBA) method, in terms of coregistration, atlas construction, and image smoothing, was thereby used. RESULTS: Diffusion differences between the control subjects and the patients with MS were found in the corpus callosum, inferior longitudinal fasciculus, cortico spinal tracts, forceps major, superior longitudinal fasciculus, and cingulum. In addition, we observed significant correlations of the FA and PASAT scores in the left inferior longitudinal fasciculus, the forceps minor, the capsula interna and externa, the genu of the corpus callosum, the left cingulum, the superior longitudinal fasciculus, and the corona radiata. CONCLUSION: Diffusion differences were observed between the mildly impaired MS patients and control subjects. In addition, different diffusion measures correlated with PASAT scores for cognitive decline in parietal, frontal, as well as temporal white matter (WM) regions.

On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain.

Voxel based morphometry (VBM) has been increasingly applied to detect diffusion tensor (DT) image abnormalities in patients for different pathologies. An important requisite for a robust VBM analysis is the availability of a high-dimensional non-rigid coregistration technique that is able to align both the spatial and the orientational DT information. Consequently, there is a need for an inter-subject DTI atlas as a group specific reference frame that also contains this orientational DT information. In this work, a population based DTI atlas has been developed that incorporates such orientational DT information with high accuracy and precision. The proposed methodology for constructing such an atlas is compared with a subject based DTI atlas, in which a single subject is selected as the reference image. Our results demonstrate that the population based atlas framework is more accurate with respect to the underlying diffusion information.

A tracking-based diffusion tensor imaging segmentation method for the detection of diffusion-related changes of the cervical spinal cord with aging.

PURPOSE: To compare region of interest (ROI)-based and diffusion tensor tractography (DTT)-based methods for evaluating diffusion properties of the spinal cord as a function of age. MATERIALS AND METHODS: Commonly, an ROI segmentation is used to delineate the spinal cord. In this work, new segmentation methods are developed based on DTT. In a first, DTT-based, segmentation approach, the diffusion properties are calculated on the tracts. In a second method, the diffusion properties are analyzed in the spinal cord voxels that contain a certain number of tracts. We studied the changes in diffusion properties of the human spinal cord in subjects of different ages. Diffusion tensor imaging (DTI) measurements of the cervical spinal cord were acquired on 42 healthy volunteers (age range = 19-87 years). The fractional anisotropy (FA), the mean diffusivity (MD), and eigenvalues (lambda(1), lambda(2), and lambda(3)) were compared for the ROI- and DTT-based segmentation methods. RESULTS: Our automatic techniques are shown to be highly reproducible and sensitive for detecting DTI changes. FA decreased (r = -0.38; P < 0.05), whereas MD and eigenvalues increased (r = +/- 0.45; P < 0.05) with age. These trends were not statistically significant for the ROI-based segmentation (P > 0.05). CONCLUSION: DTT is a robust and reproducible technique to segment the voxels of interest in the spinal cord.

Nonrigid coregistration of diffusion tensor images using a viscous fluid model and mutual information.

In this paper, a nonrigid coregistration algorithm based on a viscous fluid model is proposed that has been optimized for diffusion tensor images (DTI), in which image correspondence is measured by the mutual information criterion. Several coregistration strategies are introduced and evaluated both on simulated data and on brain intersubject DTI data. Two tensor reorientation methods have been incorporated and quantitatively evaluated. Simulation as well as experimental results show that the proposed viscous fluid model can provide a high coregistration accuracy, although the tensor reorientation was observed to be highly sensitive to the local deformation field. Nevertheless, this coregistration method has demonstrated to significantly improve spatial alignment compared to affine image matching.