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Age-dependence of g-ratio values for subcortical white matter structures in the human brain
Richard Wonjoong Kim1, Nikkita Khattar1, Wenshu Qian1, Joseph Alisch1, Richard G. Spencer1, and Mustapha Bouhrara1
1NIA, NIH, Baltimore, MD, United States

Synopsis

Emerging evidence indicates that myelination and axonal abnormalities could lead to alterations of brain connectivity, contributing to a myriad of neurological disorders. Measurement of myelin to axonal volume, as defined by the g-ratio, has been shown to represent a sensitive and specific metric of neurodevelopment and neurodegeneration. However, only a single study to date has sought to evaluate age-related differences in g-ratio in the adult human brain. Here, we introduce and compare two novel approaches to g-ratio mapping. Both methods revealed a quadratic relationship between g-ratio and age in a large cohort of cognitively unimpaired participants.

PURPOSE

The g-ratio is defined as the inner-to-outer diameter of a myelinated axon; its calculation requires estimation of myelin volume fraction (MVF) and axonal volume fraction (AVF). A recent report found that g-ratio increases linearly with age (1), interpreted as reduction in myelin throughout adulthood and decreased axonal density at older ages. However, this is inconsistent with several reports of increased myelination throughout adulthood followed by decrease at older ages (2, 3). This discrepancy is likely due to use of magnetization transfer saturation for estimation of MVF which, while sensitive to myelin content, is not specific. Here, we introduce two novel approaches for g-ratio mapping, the first based on NODDI (4), a multi-shell diffusion technique, for AVF estimation, and the second based on NODDI-DTI (5), a single-shell diffusion approximation of NODDI. MVF was determined using BMC-mcDESPOT, a direct method for myelin mapping (2, 6-9). These new g-ratio approaches were compared on a large age-range cohort of cognitively unimpaired participants and used to establish the g-ratio differences across the lifespan.

METHODS

Subjects and MRI
The study cohort for the NODDI-DTI-based approach to g-ratio estimation consisted of 133 subjects (49.2±21.5years); 59 women (47.7±19.9years) and 74 men (50.5±22.5years), spanning an age-range between 21 and 94 years. The NODDI-based method was applied to a subset of 53 participants (41.5±18.6years); 25 women (43.7±19.4years) and 28 men (39.7±17.5years), spanning an age-range between 21 and 83 years. Age was not statistically different between men and women in either group. The imaging protocol was:

· NODDI-DTI: diffusion-weighted images (DWI) were acquired with single-shot EPI, repetition time (TR) 10000ms, echo time (TE) 70ms, b-values 0 and 700s/mm2 in 32 directions, and voxel size 2mm×2mm×2mm.

· NODDI: DWI were acquired using single-shot EPI with TR of 10000ms, TE of 67ms, three b-values of 0, 700, and 2000s/mm2 (encoded in 32 directions), and voxel size 3mm×3mm×3mm.

· BMC-mcDESPOT: ten 3D spoiled-gradient-recalled-echo (SPGR) images were acquired with flip angles (FAs) [2 4 6 8 10 12 14 16 18 20]°, TE 1.37ms, TR 5ms, and ten 3D balanced steady-state free-precession images were acquired with FAs [2 7 11 16 24 32 40 60]°, TE 2.8ms, TR 5.8ms, and radiofrequency excitation pulse phase increments of 0o or 180o to account for off-resonance effects (10). Images were acquired with voxel size 1.6mm×1.6mm×1.6mm. We used the dual angle method (DAM) to correct for B1 inhomogeneity (11), based on two fast spin-echo images acquired with FAs 45° and 90°, TE 102ms, TR 3000ms, and acquisition voxel size 2.6mm×2.6mm×4mm. All images were obtained with field-of-view 240mm×208mm×150mm and reconstructed to a voxel size 2mm×2mm×2mm.

Image processing and statistical analysis
Whole-brain myelin water fraction maps were generated using BMC-mcDESPOT (7-9), and converted to MVF using the geometrical analysis suggested by Jung (12). AVF was calculated from the intracellular volume fraction derived from NODDI (4, 12) or NODDI-DTI (5). MVF and AVF were then used to calculate corresponding g-ratio maps (1, 12-14). The averaged SPGR image over FAs was nonlinearly registered to the MNI space, with the transformation matrix then applied to the corresponding g-ratio map using FSL (15). Ten regions of interest (ROIs) were derived from the MNI structural atlas encompassing the main white matter (WM) regions (Figure 1) (15). For each ROI, the effects of age and sex on g-ratio were investigated using linear regression with mean g-ratio within the ROI as the dependent variable and sex, age, and age2 as independent variables. Additionally, the correlation between mean g-ratio values derived from the two g-ratio approaches was calculated within each ROI.

RESULTS & DISCUSSION

Figure 2 shows g-ratio maps derived from the two g-ratio methods for representative participants of three different ages. The two approaches provide very similar g-ratio maps. Visual inspection and quantitative ROI analyses (Figs. 2-3) indicate decreasing g-ratio from early adulthood through middle age, followed by increase with age in most ROIs (Table 1). While the derived g-ratio values agree with previous literature, the quadratic, U-shaped, trends are not consistent with the previous observation of a linear relationship between g-ratio and age (1). As indicated above, this discrepancy is likely due to methodological differences in MVF determination. The quadratic association observed here suggests progressive myelination through middle age, followed by reduction through late adulthood (2, 3).

The effect of sex on g-ratio was significant in several brain regions (Table 1), with females exhibiting overall lower values; this agrees with recent studies indicating greater myelination in females (2, 3). These results disagree with Cercignani (1), who reported no sexual dimorphism (1). However, our findings are consistent with previous demonstrations that proliferation of oligodendrocytes and myelin proteins are modulated by sex steroids and hence regulated differently in males and females (16-19).

Finally, in agreement with Fig. 1, correlation analysis of g-ratio values derived from the two approaches showed strong correlations in most ROIs (Fig 4). Small discrepancies are likely due to the fact that NODDI is more sensitive to intracellular water diffusion due to the use of high diffusion b-values.

CONCLUSIONS

We propose two new approaches for g-ratio mapping. Both showed a U-shaped association between g-ratio and age across multiple white matter regions.

Acknowledgements

This work was supported by the Intramural Research Program of the National Institute on Aging of the National Institutes of Health.

References

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Figures

Figure 1: Visualization of the white matter ROIs. 1) Frontal lobes, 2) Parietal lobes, 3) Occipital lobes, 4) Cerebellum, 5) Splenium of corpus callosum, 6) Body of corpus callosum, 7) Genu of corpus callosum, 8) Internal capsule, 9) Temporal lobes.

Figure 2: g-ratio maps derived using the two g-ratio approaches (NODDI- or NODDI-DTI-based) from the brains of three participants of different ages. For each participant, results are shown for three representative slices. Results indicate that the g-ratio decreases until middle age and then increases through older adulthood. Further, derived maps from the two g-ratio approaches are similar, as quantified in Figure 4.

Figure 3: (A) Plots of g-ratio values, calculated using the NODDI-DTI-based g-ratio approach, as a function of age (N = 133). (B) Plots of g-ratio values, calculated using the NODDI-based g-ratio approach, as a function of age (N = 53). Results are shown for the 10 main white matter cerebral structures evaluated. For each region, the significance of the regression model, p, and corresponding coefficient of determination, R2, are reported. Most regions investigated show a quadratic, U-shaped, association of g-ratio with age.

Figure 4: Correlation plots of voxel-by-voxel g-ratio values within the ROIs indicated, derived from the NOODI- or NODDI-DTI-based approach (N = 53). Results are shown for the 10 WM brain structures evaluated. For each ROI, the coefficient of determination, R2, is reported. All regions show a high correlation between the two g-ratio calculation methods.

Table 1: Statistical significance as indicated by p-value for each coefficient incorporated into the regression analysis of g-ratio, derived using the NODDI- or NODDI-DTI-based approach, as a function of sex, age, and age2. The quadratic effect of age, age2, is significant in most brain structures. Similarly, the effect of sex is significant in several brain structures.

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)
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