Diffusion-weighted MRI provides a powerful tool for probing tissue microstructure on the micrometer scale and is, therefore, a potential candidate for developing a noninvasive neuroimaging measure of tissue complexity. Although DTI and its associated indices of FA and MD are the most common diffusion measures used to date, it is well known that diffusion-weighted imaging is capable, in principle, of yielding considerably more information than that contained in DTI. However, because DTI is incapable of measuring non-Gaussian diffusion, DKI is potentially a more sensitive and specific indicator of the diffusional heterogeneity and, hence, tissue microstructure.
The data presented herein support significant age-associated micro-structural changes within the prefrontal cortex and reveal, for the first time, age-related changes in MK. During the period of adolescence the FA tended to increase rapidly, possibly reflecting the ongoing process of myelination and white matter organization still present during this age range, which is in agreement with postmortem studies (22
). Additionally, our data showed a significant age-related FA decrease and MD increase with aging. For the elderly adult group, the FA histogram () clearly showed an increase of the fraction of voxels for the FA range of 0–0.2, reflective of increased cerebrospinal fluid consequent to increased brain atrophy. Moreover, the mean FA for the range of 0.2 and above showed a shift to lower FA in the elderly group and an associated increase in MD, which likely reflects the white matter degeneration demonstrated by postmortem studies (23
) of subjects in this age group. Our FA and MD results are in general agreement with several previous DTI studies (7
). However, a direct comparison to the present study would be difficult due to methodological differences regarding population sample, brain regions of interest and the analytical approach used that varied from voxel-based analysis, region of interest-based or histogram analysis.
The non-Gaussian diffusion patterns of brain tissue microstructure in the prefrontal brain region, as measured by DKI, showed several interesting features that are consistent with what is known from previous histopathological studies (1
). First, MK increased during the transition from adolescence to adulthood, consistent with continuing myelination and an overall increase of the microstructural complexity in this brain region. Second, MK decreased with aging, which is probably associated with the degenerative changes and neuronal shrinkage. Furthermore, the analysis of the peak position for both MK grey and white matter tissue types () illustrated patterns consistent with known histological patterns of brain maturation (6
). The grey matter MK peak position showed a shift to higher values with increasing age, which is consistent with the known increase of the cortical cell-packing density (6
). The MK white matter peak location showed a rapid shift to higher values up until age 18, likely reflecting the intense and continuous myelination and fiber organization that occurs at this time, with a shift to lower values with aging, probably related to the decrease of myelin density and myelinated fibers (23
). Visual differences in grey-to-white matter voxel fraction ratio were also evident in the MK histograms. The adolescent group had the highest ratio followed by the younger adult group followed by the elderly adult group. This order is in agreement with postmortem studies (1
Although structural MRI studies have shown age-related volume changes in grey matter, only few reports have shown age-related MD grey matter patterns, with these reporting mostly global changes or changes in subcortical grey matter (24
) and some reporting no significant changes with aging (26
). However, to our knowledge, no diffusion patterns representing age-related changes in the prefrontal cortical grey matter structural integrity have been previously reported. The non-Gaussian diffusion patterns of brain tissue microstructure in the prefrontal brain reported in this study demonstrate specific changes in cortical grey matter consistent with known age-related morphological changes for specific age ranges. Because age-related changes in prefrontal cortex are associated with cognitive changes (4
) and changes in patterns of brain activation (27
), our ability to characterize and measure age-related grey matter diffusion changes is potentially of clinical interest.
Since age-related DTI changes have been reported to be more pronounced in the frontal lobe, particularly in the prefrontal region, we decided to initially focus on this region. We chose to use an ROI encompassing a large amount of the frontal lobe instead of smaller, more regionally specific ROIs to demonstrate that MK can segment, measure, and assess both grey and white matter from a large ROI containing both tissue types without the need to draw individual tissue-type (grey and white matter) specific ROIs, which highlights a particular strength of this technique. Another advantage of this technique is that unlike other diffusion parameters (e.g., FA and MD), MK is relatively insensitive to partial volume effects (28
). A direct advantage of this is that the measurement is less sensitive to the subjectivity (size and location) of the definition of the ROI. Hence, with MK it is possible to obtain the same sensitivity to diffusional changes in the brain using large ROIs.
There are some limitations to this study, mainly the modest number of subjects studied and the lack of full brain coverage. However, even though the number of subjects was small, it still allowed the demonstration of statistically significant age-related diffusion changes. Additionally, in future longitudinal studies with whole brain coverage, we will seek to investigate additional brain regions. Nevertheless, we believe it is important to report these preliminary results because this is the first study demonstrating the application of diffusional kurtosis measurements in assessing age-related changes and highlighting one advantage using this technique, namely the quantification of microstructural complexity in both grey and white matter.
The current study demonstrates distinct MK patterns for different age ranges, with significant age-related correlation for MK and MK peak position, indicating that diffusion kurtosis is able to characterize and measure age-related diffusion changes for both grey and white matter, in the developing and aging brain. In summary, our results suggest that microstructural complexity in the prefrontal cortex, as measured by MK, increases sharply during adolescence, continues to increase throughout adulthood, albeit more slowly, while eventually decreasing with aging.