The relationship between diffusion tensor imaging and volumetry as measures of white matter properties

Abstract

There is still limited knowledge about the relationship between different structural brain parameters, despite huge progress in analysis of neuroimaging data. The aim of the present study was to test the relationship between fractional anisotropy (FA) from diffusion tensor imaging (DTI) and regional white matter (WM) volume. As WM volume has been shown to develop until middle age, the focus was on changes in WM properties in the age range of 40 to 60 years. 100 participants were scanned with magnetic resonance imaging (MRI). Each hemisphere was parcellated into 35 WM regions, and volume, FA, axial, and radial diffusion in each region were calculated. The relationships between age and the regional measures of FA and WM volume were tested, and then FA and WM volume were correlated, corrected for intracranial volume, age, and sex. WM volume was weakly related to age, while FA correlated negatively with age in 26 of 70 regions, caused by a mix of reduced axial and increased radial diffusion with age. 23 relationships between FA and WM volume were found, with seven being positive and sixteen negative. The positive correlations were mainly caused by increased radial diffusion. It is concluded that FA is more sensitive than volume to changes in WM integrity during middle age, and that FA-age correlations probably are related to reduced amount of myelin with increasing age. Further, FA and WM volume are moderately to weakly related and to a large extent sensitive to different characteristics of WM integrity.

Fig. 1

Parcellation of the cerebral cortex. The brain surface was parcellated into 33 different gyral based areas, as previously described (Desikan et al., 2006). These areas are shown in different colors on a semi-inflated template brain. The inflation procedure makes it possible to see areas buried inside sulci that would otherwise be hidden from view.

Fig. 2

Parcellation of the gyral white matter. Gyral white matter was labeled according to the cortical parcellation of the gyri. The image to the left shows the intensity normalized, motion corrected, and skull-stripped mprage scans of a representative participant (58 year old male). In the second image from the left, the gray/white boundaries (orig surface) and the brain/CSF boundaries (pial surface) are illustrated by the red and green line. Examples of the cortical and the WM parcellations are shown in the two right images (coronal and horizontal views, respectively).

Fig. 3

Registration of FA to anatomical volumes. The FA images were registered to the anatomical scans, and mean FA in each of the WM parcellations (see Fig. 2) was calculated. Each parcellation was eroded by one voxel, to avoid effects of partial voluming along the cortical/WM boundary. The upper left image shows the brain volume with the eroded WM mask displayed. The upper right image shows the segmented WM volume with the eroded mask overlaid. As can be seen, the eroded WM mask is embedded well within the WM volume, and the risk of partial voluming is minute. The lower left image is the vector volume registered to the anatomical brain volume, and the lower right image is the transparent vector volume displayed on the non-eroded WM volume. All images are from the same participant as those in Fig. 2

Fig. 4

3D renderings of the probabilistic tracts overlaid on a transparent template brain with the FreeSurfer WM parcellations and whole-brain segmentation. The 11 atlas-based probabilistic tracts from the Mori atlas is shown as 3D renderings, displayed on a semi-transparent template brain from FreeSurfer (fsaverage). The subcortical structures are results from FreeSurfer's whole brain segmentation procedure. The colors on the cortical surface are the cortical parcellations on which the WM parcellations are based (see Fig. 1 and Fig. 2). The figure was made by use of 3D slicer software (http://www.slicer.org/).

Fig. 5

Correlations between age, FA, WM volume, and cortical thickness. The significance of the correlations between age and FA (upper panel), age and WM volume (2nd panel), FA and WM volume (3rd panel), and FA and cortical thickness (bottom panel) in each parcellation is color coded, and projected onto a template of the brain's WM (three upper panels) or cortical (bottom panel) surface. The correlations involving WM volume and cortical thickness are corrected for the influence of sex and ICV. The blue color indicate a positive correlation, the pink color indicate a negative correlation.

Fig. 6

Scatterplots of superior frontal gyrus. The figure illustrates the relationship between FA/axial diffusion/radial diffusion and age and WM volume for one selected area (superior frontal gyrus). Note that the scatterplots represent the raw data, while statistics are done with different variables partialled our (age, sex, and/or ICV). In addition, outliers were excluded from all analyses based on a criterion of not exceeding ±2 studentized deleted residuals, but are included in the scatterplots.

Fig. 7

Overlap between FreeSurfer parcellations and major tracts from the Mori probabilistic atlas. The bar plots show the number of voxels in each left hemisphere FreeSurfer WM parcel that overlapped with each of the 11 major tracts in the probabilistic atlas used (Mori). Tract numbers refer to 1. ATR, 2. CCG, 3. CHG, 4. CST, 5. FMa, 6. FMi, 7. IFOF, 8. ILF, 9. SLF, 10. SLFTP, 11. UF (see also Fig. 4 and Table 4).