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Voxel-based analyses (VBA) are increasingly being used to detect white matter abnormalities with diffusion tensor imaging (DTI) in different types of pathologies. However, the validity, specificity, and sensitivity of statistical inferences of group differences to a large extent depend on the quality of the spatial normalization of the DTI images. Using high-dimensional nonrigid coregistration techniques that are able to align both the spatial and orientational diffusion information and incorporate appropriate templates that contain this complete DT information may improve this quality. Alternatively, a hybrid technique such as tract-based spatial statistics (TBSS) may improve the reliability of the statistical results by generating voxel-wise statistics without the need for perfect image alignment and spatial smoothing. In this study, we have used (1) a coregistration algorithm that was optimized for coregistration of DTI data and (2) a population-based DTI atlas to reanalyze our previously published VBA, which compared the fractional anisotropy and mean diffusivity maps of patients with amyotrophic lateral sclerosis (ALS) with those of healthy controls. Additionally, we performed a complementary TBSS analysis to improve our understanding and interpretation of the VBA results. We demonstrate that, as the overall variance of the diffusion properties is lowered after normalizing the DTI data with such recently developed techniques (VBA using our own optimized high-dimensional nonrigid coregistration and TBSS), more reliable voxel-wise statistical results can be obtained than had previously been possible, with our VBA and TBSS yielding very similar results. This study provides support for the view of ALS as a multisystem disease, in which the entire frontotemporal lobe is implicated.

Motoneuron disease is a term encompassing three phenotypes defined largely by the balance of upper versus lower motoneuron involvement, namely amyotrophic lateral sclerosis, primary lateral sclerosis and progressive muscular atrophy. However, neuroradiological and pathological findings in these phenotypes suggest that degeneration may exceed the neuronal system upon which clinical diagnosis is based. To further delineate the phenotypes within the motoneuron disease spectrum, this controlled study assessed the upper- and extra-motoneuron white matter involvement in cohorts of patients with motoneuron disease phenotypes shortly after diagnosis by comparing diffusion tensor imaging data of the different cohorts to those of healthy controls and directly between the motoneuron disease phenotypes (n = 12 for each cohort). Furthermore, we acquired follow-up data 6 months later to evaluate fractional anisotropy changes over time. Combined use of diffusion tensor tractography of the corticospinal tract and whole-brain voxel-based analysis allowed for comparison of the sensitivity of these techniques to detect white matter involvement in motoneuron disease. The voxel-based analysis demonstrated varying extents of white matter involvement in different phenotypes of motoneuron disease, albeit in quite similar anatomical locations. In general, fractional anisotropy reductions were modest in progressive muscular atrophy and most extensive in primary lateral sclerosis. The most extensive patterns of fractional anisotropy reduction were observed over time in the voxel-based analysis, indicating progressive extra-motor white matter degeneration in limb- and bulbar onset amyotrophic lateral sclerosis and in progressive muscular atrophy. The observation of both upper motor and extra-motoneuron involvement in all phenotypes of motoneuron disease shortly after diagnosis suggests that these are all part of a single spectrum of multisystem neurodegenerative disease. Voxel-based analysis was more sensitive to detect longitudinal changes than diffusion tensor tractography of the corticospinal tract. Voxel-based analyses may be particularly valuable in the evaluation of motor and extra-motor white matter involvement in the early symptomatic stages of motoneuron disease, and for monitoring the spread of pathology over time.

Reconstruction of white matter (WM) fiber tracts based on diffusion tensor imaging (DTI) is increasingly being used in clinical and research settings to study normal and pathological WM tissue as well as the maturation of this WM tissue. Such fiber tracking (FT) methodology, however, is highly dependent on the manual delineation of anatomical landmarks and the algorithm settings, often rendering the reproducibility and reliability questionable. Predefining these regions of interest on a fractional anisotropy (FA) atlas in standard space has already been shown to improve the reliability of FT results. In this paper, we constructed a new DTI atlas, which contains the complete diffusion tensor information in ICBM152 coordinates. From this high-dimensional DTI atlas, and using robust FT protocols, we reconstructed a large number of WM tracts. Subsequently, we created tract masks from these fiber tract bundles and evaluated the atlas framework by comparing the reproducibility of the results obtained from our standardized tract masks with regions-of-interest labels from the conventional FA-based WM atlas. Finally, we assessed laterality and age-related WM changes in 42 normal subjects aged 0 to 18 years using these tractography-derived tract segmentations. In agreement with previous literature, we observed an FA increase with age, which was mainly due to the decrease of perpendicular diffusivity. In addition, major functional pathways in the language, motor, and limbic system, showed a significant asymmetry in terms of the observed diffusion metrics.

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