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. Author manuscript; available in PMC: 2023 Jan 1.
Published in final edited form as: Magn Reson Imaging. 2021 Oct 19;85:87–92. doi: 10.1016/j.mri.2021.10.019

Cerebral aggregate g-ratio mapping using magnetic resonance relaxometry and diffusion tensor imaging to investigate sex and age-related differences in white matter microstructure

Luis E Cortina 1,†, Richard W Kim 1,†, Matthew Kiely 1, Curtis Triebswetter 1, Zhaoyuan Gong 1, Maryam H Alsameen 1, Mustapha Bouhrara 1,*
PMCID: PMC8629921  NIHMSID: NIHMS1750687  PMID: 34678436

Abstract

Axonal demyelination is a cardinal feature of aging and age-related diseases. The g-ratio, mathematically defined as the inner-to-outer diameter of a myelinated axon, is used as a structural index of optimal axonal myelination and has been shown to represent a sensitive imaging biomarker of microstructural integrity. Several magnetic resonance imaging (MRI) methods for whole-brain mapping of aggregate g-ratio have been introduced. Computation of the aggerate g-ratio requires estimates of the myelin volume fraction (MVF) and the axonal volume fraction (AVF). While accurate determinations of MVF and AVF can be obtained through multicomponent relaxometry or diffusion analyses, respectively, these methods require lengthy acquisition times making their implementation challenging in a clinical context. Therefore, any attempt to overcome this drawback is needed. Expanding on our previous work, we introduced a new MRI method for whole-brain mapping of aggregate g-ratio. This new approach is based on the use of a single-shell diffusion for AVF determination, reducing the acquisition time by approximately ~10 min from our recently introduced approach, while offering the possibility to investigate g-ratio differences in previous studies with existing data for MVF mapping and single-shell diffusion data for AVF mapping. Our comparison analysis indicates that our newly derived aggregate g-ratio values were similar to those derived from our previous method, which requires a longer acquisition time. Further, in agreement with our previous observations, we found quadratic U-shaped relationships between aggregate g-ratio and age in this much larger study cohort. However, our results show that sexual dimorphism in g-ratio was not significant in any brain region investigated.

Keywords: Aging, DTI, MRI, g-ratio

1. INTRODUCTION

Brain tissue microstructural properties change across the adult lifespan. Specifically, axonal loss and demyelination have been associated with the neurofunctional decline seen in aging as well as neurodegeneration (1–7). Thus, identifying biomarkers to characterize normative aging effects will therefore provide critical insights into normal neurophysiology and distinguish it from neuropathology. The g-ratio, an index of axonal myelination and integrity, has been shown to be a sensitive imaging biomarker for microstructural changes with neurodevelopment and neurological disorders (8–12). However, the current gold standard for g-ratio calculation is electron microscopy. This limits studies to ex-vivo measurements and renders real-time g-ratio correlational investigations with cognitive performance and interventions challenging.

To address this limitation, Stikov and colleagues introduced the magnetic resonance imaging (MRI)-based approach of whole-brain in-vivo mapping of g-ratio (13); this method provides measures of “aggregate g-ratio” as it operates under the assumption of uniform g-ratio for all axonal fibers within a voxel (14). Stikov and colleagues’ method requires the calculation of axonal and myelin volume fractions; recognized as axonal volume fraction (AVF) and myelin volume fraction (MVF), respectively. More recently, various groups have introduced novel MRI methods to measure the aggregate g-ratio, incorporating a variety of approaches for MVF (9, 15–17) and AVF (9, 10, 14–16) determinations.

In our previous work, using multicomponent relaxometry for MVF estimation, through use of the Bayesian Monte Carlo analysis of multicomponent driven equilibrium single pulse observation of T1 and T2 (BMC-mcDESPOT) (18–20), and neurite orientation dispersion and density imaging (NODDI) (21), a multi-shell diffusion technique, for AVF estimation, we investigated sex and age-related differences in aggregate g-ratio in a cohort of 52 cognitively intact subjects (22). Our results indicated a quadratic, U-shaped association between aggregate g-ratio and age in various white matter regions examined (22), suggesting continuous myelination until middle age followed by a decline in myelin content at older ages. These findings were consistent with postmortem observations as well as in-vivo MRI investigations (23–33). While our previous findings identified widespread brain microstructural changes, it more importantly, demonstrated the utility of using aggregate g-ratio as a reliable imaging marker of microstructural integrity in normal aging. However, our AVF estimation using the NODDI approach as well as that of other studies (9, 10, 14–16) require lengthy acquisition times which make the integration of these aggregate g-ratio mapping methods challenging in clinical contexts.

In this present work, expanding on our previous investigation (21), we showed that aggregate g-ratio estimates can be obtained from single-shell diffusion images. Aside from reducing the total acquisition time by ~10 min (approx. ~27% reduction), this approach opens the possibility to previous studies with existing data for MVF mapping and single-shell diffusion data for AVF mapping to examine differences in aggregate g-ratio. We applied this novel technique to investigate age and sex-related aggregate g-ratio differences on a cohort of 133 cognitively intact participants across a wider age range of 21 to 94 years. Our results provide further confirmation for a nonlinear association between age and aggregate g-ratio in most white matter regions studied in this much larger sample of adults. Finally, in contrast to our previous finding, sexual-dimorphism in aggregate g-ratio was not significant.

2. MATERIAL & METHODS

2.1. Study cohort

Participants were drawn from the Baltimore Longitudinal Study of Aging (BLSA) (34, 35), and the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT); two ongoing studies to evaluate multiple biomarkers related to aging. The inclusion and exclusion criteria for these two studies are essentially identical. Participants underwent a myriad of cognitive tests and were excluded if they had metallic implants, neurologic, or medical disorders (36). The final study cohort consisted of 133 volunteers ranging in age from 21 to 94 years (mean ± standard deviation 53.6 ± 21.5 years), of which 74 were men (55.3 ± 22.5 years) and 59 were women (51.5 ± 19.9 years), after the removal of three imaging datasets with technically limited scans caused by excessive motion. The difference in mean age between men and women did not reach statistical significance. Figure 1 provides a detailed distribution of the number of participants per age decade and for each sex. Experimental procedures were performed in compliance with our local Institutional Review Board, and participants provided written informed consent.

Figure 1.

Figure 1.

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Number of participants per age decade and sex within the study cohorts.

2.2. MRI acquisition

MRI scans were performed using a 3T Philips MRI system (Achieva, Best, The Netherlands). All 133 participants underwent our BMC-mcDESPOT imaging protocol for MWF mapping (18–20), and single-shell DTI for intra-cellular volume fraction (ICVF) mapping (37). BMC-mcDESPOT comprises 3D spoiled gradient recalled echo (SPGR) images acquired with flip angles (FAs) of [2 4 6 8 10 12 14 16 18 20]°, echo time (TE) of 1.37 ms, repetition time (TR) of 5 ms and voxel size of 1.6 mm × 1.6 mm × 1.6 mm, 3D balanced steady state free precession (bSSFP) images acquired with radiofrequency (RF) excitation pulse phase increments of 0 or π in order to account for off-resonance effects (38) at FAs of [2 4 7 11 16 24 32 40 50 60]°, TE of 2.8 ms, TR of 5.8 ms and voxel size of 1.6 mm × 1.6 mm × 1.6 mm, and two fast spin-echo images acquired with FAs of 45° and 90°, TE of 102 ms, TR of 3000 ms and acquisition voxel size of 2.6 mm × 2.6 mm × 4 mm to correct for excitation RF inhomogeneity using the double-angle method (DAM) (39). The acquisition time for this BMC-mcDESPOT imaging protocol was ~21 min. The DTI protocol consisted of diffusion-weighted images (DWI) acquired with single-shot EPI, TR of 7 s, TE of 70 ms, two b-values of 0 and 700 s/mm2, with the latter encoded in 32 directions, acquisition voxel size of 2 mm × 2 mm × 2 mm, and acquisition time of ~6 min. All images were obtained with field of view of 240 mm × 208 mm × 150 mm and reconstructed to a voxel size of 2 mm × 2 mm × 2 mm.

2.3. Aggregate g-ratio mapping

The aggregate g-ratio is defined as the inner-to-outer diameter of myelinated axons in a given voxel; its calculation requires the estimation of MVF and AVF (9, 15, 16), and is calculated as follows: gratio=1/(1+MVF/AVF). For each subject, corresponding MVF map was derived using BMC-mcDESPOT as described in detailed in our previous work (22). The corresponding AVF map was calculated from the MVF and the ICVF maps as follows: AVF = (1 − MVF) × ICVF (9, 15, 16); the ICVF map was derived from NODDI-DTI (37), a single-shell diffusion approximation of NODDI, using an in house MATLAB script. NODDI-DTI requires calculation of eigenvalues from the DTI dataset (37); this calculation was conducted using the DTIfit tool implemented in FSL.

2.4. Regions-of-interest (ROIs) determination

For each participant, nonparenchymal regions within the images were eliminated using the FSL software (40). This was followed by registering the averaged SPGR image over FAs for each participant using nonlinear registration to the Montreal Neurological Institute (MNI) atlas. The derived transformation matrix was then applied to the aggregate g-ratio map for that corresponding participant. Sixteen white matter (WM) regions of interest (ROIs) were defined from MNI. These ROIs correspond to whole brain (WB), frontal lobes (FL), parietal lobe (PL), occipital lobe (OL), temporal lobe (TL), cerebellum (CRB), splenium of corpus callosum (SCC), body of corpus callosum (BCC), genu of corpus callosum (GCC), internal capsule (IC), anterior thalamic radiation (ATR), inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), forceps major (FM), forceps minor (Fm), and corticospinal tract (CST). Each ROI was eroded to decrease partial volume effects and to account for imperfect image registration. Finally, for each ROI and each participant, mean aggregate g-ratio values were calculated.

2.5. Analyses

For each ROI, we first investigated the correlation between mean aggregate g-ratio values derived from our new approach presented here, NODDI-DTI, and our previously introduced method which is based on multi-shell diffusion NODDI acquisition, NODDI. Briefly, the previous NODDI cohort, a subset of the NODDI-DTI cohort, consisted of 52 volunteers ranging in age from 21 to 84 years (44.6 ± 18.1 years), of which 24 were men (43.1 ± 17.5 years) and 28 were women (46.3 ± 18.6 years). The NODDI protocol consisted of DWI images acquired with a single shot EPI with TR of 10 s, TE of 67 ms, and three b-values of 0, 700, and 2000 s/mm2, with the latter two encoded in 32 directions, and acquisition voxel size of 2 mm × 2 mm × 3 mm. Two images at b = 0 s/mm2 were acquired. The acquisition time was ~16 min. Please note that the acquisition time was mistakenly reported as equal to ~12 min in our original paper (22). For each participant, the corresponding aggerate g-ratio map was derived from NODDI and the BMC-mcDESPOT imaging protocols described above.

Furthermore, in each ROI, the effects of age and sex on aggregate g-ratio were investigated using a multiple linear regression model with the mean aggregate g-ratio within the ROI as the dependent variable and sex, age, and age2 as independent variables, after mean age centering. The initial model incorporated interactions between sex and age as well as sex and age2, but interaction terms were removed if found to be non-significant. The resulting parsimonious model was then constructed without the nonsignificant interactions.

In all analyses, the threshold for statistical significance was p < .05 after correction for multiple ROI comparisons using the false discovery rate (FDR) method (41).

3. RESULTS

Figure 2 shows the aggregate g-ratio maps derived from both the current and the previously introduced method for representative participants within three distinct age groups: young, middle-aged, and elderly. Two representative axial slices are displayed. Visual inspection indicates decrease in aggregate g-ratio values from early adulthood until middle age, that is, 40–49 years, followed by increases in aggregate g-ratio in later ages for both methods, with expected regional variation. Moreover, although both methods exhibited overall similar regional aggregate g-ratio values, some brain regions demonstrated more pronounce absolute differences in computed g-ratio values, especially in regions adjacent to gray matter structures. However, in agreement with Figure 2, a correlation analysis of derived aggregate g-ratio values from both methods showed strong correlations in most ROIs investigated (Fig. 3), with, overall, slightly underestimated values using NODDI-DTI.

Figure 2.

Figure 2.

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Aggregate g-ratio maps derived using the two g-ratio approaches (NODDI-DTI- or NODDI-based approach), and corresponding absolute difference maps, from the brains of three participants of different age groups: young, middle-aged, and elderly. For each participant, results are shown for two representative slices covering the main cerebral structures studied. 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 3.

Figure 3:

Figure 3:

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Correlation plots of mean aggregate g-ratio values within the ROIs derived from the NOODI- or NODDI-DTI-based approach (N = 53). Results are shown for the 16 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.

Figure 4 illustrates the representative plots of derived aggregate g-ratio values, calculated using the NODDI-DTI-based approach, from all subjects as a function of age for each ROI. Significant associations with age were observed for most brain WM regions examined except for the whole brain, occipital lobes, temporal lobes, GCC, FM, and IFL (Table 1). The quadratic effect of age, that is, age2, on aggregate g-ratio was significant in several brain regions except in the GCC, IC, SCC, FM, and IFOF (Table 1). Furthermore, most of the brain structures evaluated exhibited minimum aggregate g-ratio values within the 5th decade, that is, between 40 and 49 years. Interestingly, in agreement with our previous findings, anterior brain structures such as the frontal lobes, parietal lobes, and body of the corpus callosum exhibited slightly earlier ages of minimum aggregate g-ratio as compared to more posterior structures such as the occipital lobes, temporal lobes, and splenium of the corpus callosum (Table 1). Lastly, the effect of sex did not reach statistical significance in any of the ROIs studied (Table 1).

Figure 4:

Figure 4:

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Plots of aggregate g-ratio values, calculated using the NODDI-DTI-based g-ratio approach, as a function of age (N = 133). Results are shown for the 16 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.

Table 1.

Aggregate g-ratio results. Significance of regression terms in the multiple linear regression analysis, and year of apparent minimum aggregate g-ratio value for each brain structure investigated. NA indicates that the linear model was the best fit to the data, with the age minimum therefore occurring at the youngest or oldest age decade. Bold indicates significance; all p-values presented are obtained after FDR correction.

Age Sex Age2 Year of Minimum g-ratio
p F p F p F
WB 0.21 2.0 0.37 1.1 0.01 8.3 52.2
FL 5×10 −4 15.1 0.31 1.9 0.01 9.0 45.1
OL 0.3 1.2 0.57 0.3 0.01 9.2 53.3
PL 5×10 −4 15.6 0.31 3.1 0.01 12.4 46.6
TL 0.14 2.8 0.32 1.5 0.04 5.4 50.1
CRB 3×10 −4 18.8 0.1 7.7 0.01 9.2 43.9
IC 0.01 9.4 0.31 2.0 0.63 0.2 NA
BCC 2×10 −3 11.6 0.14 5.0 0.04 5.2 43.3
GCC 0.96 0.0 0.32 1.4 0.15 2.2 NA
SCC 0.03 3.7 0.14 5.8 0.08 3.5 47.4
ATR 3×10 −4 17.8 0.39 0.8 0.04 5.9 41.4
CST 2×10 −8 47.3 0.39 0.9 0.01 12.2 39.3
FM 0.28 1.4 0.31 2.1 0.04 5.3 52.0
Fm 0.04 5.3 0.31 2.4 0.09 3.1 45.0
IFOF 0.04 5.5 0.31 2.1 0.09 3.2 45.0
ILF 0.11 3.3 0.31 1.7 0.04 5.2 49.5
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4. DISCUSSION

In this current study, expanding on our previous work (21), we introduced a new MRI approach for aggregate g-ratio mapping to investigate differences in cerebral microstructure with age and sex. This new approach uses BMC-mcDESPOT for MWF mapping and NODDI-DTI for AVF mapping (18–20, 37, 42), allowing whole-brain mapping of aggregate g-ratio within ~27 min; this represents a ~10 min reduction in acquisition time from our recently introduced approach (22). We note that this high-spatial resolution protocol, especially for MVF imaging, provides a faster approach as compared to available protocols proposed in the literature (Table 2). However, it must be emphasized that a direct comparison between these protocols is challenging given differences in the methods used for AVF or MVF determination as well as in the spatial resolution of the acquired images. Derived aggregate g-ratio from both approaches were markedly similar in most cerebral white matter regions investigated. We note that our DTI images used in NODDI-DTI were acquired with a higher spatial resolution, that is, with a voxel volume of 8 mm2 which is 1.5 times lower than that of the NODDI images. Therefore, aside from providing a rapid protocol, our new approach provides aggerate g-ratio maps that are less prone to partial volume bias. Moreover, faster protocols based on magnetization transfer imaging could be used for MVF determination allowing for a drastic reduction in the acquisition time (9, 16, 17). Furthermore, aside from the improved spatial and temporal resolutions, this new approach permits analyzing existing imaging data of MWF mapping and DTI to investigate differences in aggregate g-ratio with aging or neuropathology. Finally, while both methods showed great sensitivity to aggregate g-ratio differences with age providing overall similar values, they exhibited discrepancies in derived values in different regions, especially in the CC, which represents a structure with more complex fiber bundle geometries. These discrepancies are likely due to the greater sensitivity of NODDI to intracellular water diffusion due to the use of high diffusion b-values. However, it must be emphasized that these differences could be exacerbated by differences in the spatial resolution of the acquired images between the NODDI-DTI and NODDI modalities and the propagated noise (43).

Table 2.

Summary of the total acquisition time of our proposed and available approaches. We note that other approaches exist in the literature but were not reported given the missing corresponding information regarding the total acquisition time. We recommend the following review articles for an exhaustive description of the available aggregate g-ratio protocols (16, 17).

Total acquisition time
Our proposed method ~27 min
Dean et al., 2016 ( 10 ) ~33 min
Bouhrara et al. 2021 ( 22 ) ~37 min
Mohammadi et al., 2015 ( 49 ) ~49 min
Ellerbrock and Mohammadi, 2018 ( 50 ) ~62 min
Yu et al., 2019 ( 51 ) ~66 min
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In agreement with our previous findings (22), our results confirm the quadratic, U-shaped, association between aggregate g-ratio and age in cerebral white matter in this much larger cohort with improved age distribution and wider age range. In line with postmortem observations and quantitative MRI studies (23–31), these results provide further evidence of brain maturation, including myelination, until middle age, followed by rapid decline in senescence. Furthermore, our results provide additional support for the retrogenesis paradigm of aging. This hypothesis postulates that later maturing brain regions such as the anterior cerebral structures are more prone to neurodegeneration than the earlier maturing structures such as the posterior cerebral regions (44–47). Indeed, our results indicate a delay in nadir aggregate g-ratio development in the occipital lobes as compared to other regions. We note, however, that these findings are based on cross-sectional analyses and therefore require further validation through longitudinal investigations. Further, although sex-differences in aggregate g-ratio was not statistically significant, women exhibited lower cerebral g-ratio values as compared to men in most ROIs investigated. We conjecture that this observation is likely to correspond to the higher myelin content seen in women’s brain (29, 30). It is unclear whether our non-significant sex-differences reflect the power of the present study or rather mirror the true biological myelination time course between men and women. Further work utilizing larger cohorts is necessary to establish these aggregate g-ratio sex differences.

This work comes with limitations. While our cohort spanned a wider age range, it does not include participants younger than 20 years. Inclusion of younger participants may influence the shape of the age-related aggregate g-ratio trends (29). Further, these results require additional validation through longitudinal studies; this work is underway. Moreover, all methods of aggregate g-ratio mapping assume a constant g-ratio for all axons within a given voxel. However, it has been shown that the aggregate g-ratio measure is more sensitive to larger diameter axons (48). Finally, we note that all quantitative MRI methods for MVF or AVF, including those used in our investigations, are based on models’ simplifications and assumptions. Indeed, the effects of magnetization transfer between macromolecules and free water protons, iron content, exchange between water pools, J-coupling, off-resonance, spin locking, water diffusion within different compartments, and internal gradients are not incorporated. The importance of these effects in an experimental design will depend both on the specifics of the sample or subject under investigation and on the details of the pulse sequence.

5. CONCLUSIONS

Based on multicomponent relaxometry and diffusion tensor imaging, we propose a new approach to map aggregate g-ratio in the human brain. Derived aggregate g-ratio values were consistent with those derived from our previously introduced method which is much more time consuming. In agreement with our previous results, we showed that aggregate g-ratio values follow a U-shaped trend with normal aging in the human brain in a much larger cohort of cognitively unimpaired men and woman. Finally, although not statistically significant, women exhibited trends toward lower cerebral aggregate g-ratio values as compared to men.

6. ACKNOWLEDGEMENT

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

Footnotes

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Declarations of interest: None

The datasets generated for this study are available on request to the corresponding author.

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