TBM is a non-linear image registration tool that measures brain changes using serial MRI scans. The Jacobian determinants of the deformation map are used to provide 3D visualization of local tissue growth or atrophy with improved spatial resolution compared to traditional volumetry-based morphometry (VBM). We demonstrate this advantage in the individual study (). Visual inspection suggests a localized white matter growth in the orbito-frontal area. The overall increase in frontal white matter volume is 1%, as calculated by integrating the Jacobian determinants over the region-of-interest. This result is comparable to the large scale longitudinal MRI study [Giedd et al., 1999
]. Thus, TBM offers equivalent information to VBM with superior spatial details, making it a favorable method for studying age and disease-related changes in brain morphometry.
Our results from the permutation tests confirm previous developmental MRI studies that have provided evidence for age-related increases in total white matter volume and decreases in total gray matter volume [Caviness et al., 1996
; Giedd et al., 1996
; Jernigan et al., 1991
; Pfefferbaum et al., 1994
; Reiss et al., 1996
; Sowell et al., 1999a
]. Moreover, we provide detailed spatial mapping of the developing brain by utilizing the Jacobian matrix field to encode local volume changes. We have attained high resolution 3D mapping of white matter growth and growth dynamics. The frontiers of the tissue growth correspond well with the anatomical boundaries of brain structures such as cerebral white matter, indicating the sensitivity and specificity of our mapping approach. Global enlargement of white matter is observed across all lobes indicating an overall growth of white matter tract system in the subjects. Every brain was edited carefully by trained raters to include only brain tissues. Nevertheless, there could still be a small amount of registration errors at the edge of the brain due to imperfect segmentation and/or registration. As a result, the brain masks (ROI) used in this study do not include boundary voxels. Therefore, the results of permutation tests provide accurate estimate of the overall significance levels within each region-of-interest.
Postmortem studies have revealed an extended myelination process that continues into the third decade of life, especially for frontal and parietal regions [Yakovlev and Lecours, 1967
]. Several recent findings also suggest an accelerated maturation of gray and white matter in frontal lobe during adolescence [Giedd et al., 1999
; Sowell et al., 1999b
]. In this study, we demonstrate a wide-spread growth in white matter, with the most prominent expansion in the frontal lobe. Inference on white matter growth using TBM, however, is based on changes in tissue boundaries or gray/white contrast, which are related to the underlying tissue microstructure. Nevertheless, it does not offer a direct measurement of the true changes to white matter integrity or myelination. MR spectroscopy [Lopez-Villegas et al., 1996
] and quantitative MR relaxometry [House et al., 2006
] might provide a better answer to address these questions.
The individual growth map shown in demonstrates cortical gray matter tissue growth over the primary sensorimotor areas. The same growth pattern is revealed again in the group average map (). However, other studies has shown gray matter loss in dorsal parietal and primary sensorimotor regions at this age range [Gogtay et al., 2004
; Sowell et al., 2003
]. This seemingly discrepant result might be explained by the partial volume effect. At the resolution of FFT 64, the size of each computational voxel is about 30 mm3
(199 mm/64 = 3.1 mm). This is a relatively large size that might contain both gray and white matter within the same voxel, especially for the areas where the gray matter is thin. As illustrated in , if the voxel holds a large proportion of growing white matter with a small proportion of shrinking gray matter, the overall signal from that voxel will be dominated by the white matter growth.
Figure 8 Partial volume effect. A relatively large computational voxel (outlined by the dotted lines) could contain both gray matter (GM) and white matter (WM). The illustrated voxel holds a large proportion of growing white matter (red) with a small proportion (more ...)
Our study is based on 13 developing children with two consecutive brain scans taken as they matured in age. The data set is relatively small compared to the few medium-to-large scale neuro-imaging studies published to date [Giedd et al., 1999
; Paus et al., 1999
; Sowell et al., 2004
]. The warp diagram () is implemented to compensate for this relatively low degree of freedom and large variance among individual brains. The step of inter-subject registration is computationally intensive but it matches the local shape properties among the subjects. This enables regional comparisons and voxel-wise statistical analyses of the growth maps. A larger sample size would further improve the power, and it is necessary to track the gender specific patterns in brain development.
In this study, we map the patterns of normal brain development using TBM. TBM is a highly automated image analysis technique that delineates local tissue gain or loss at a greater spatial resolution than the traditionally used volumetry-based method. In addition to brain development, TBM has a wide spectrum of applications in longitudinal brain analysis, such as understanding how brain is affected by certain psychiatric disorders (e.g. autism, schizophrenia, depression, etc), tracking degenerative disease progression, and monitoring drug treatment effect. In future work, we look to apply TBM to a study with relatively large sample size and expand the statistical models to answer interesting questions like brain asymmetry, correlations with IQ, cognitive measures, as well as genome types.