Age-Related Effects and Sex Differences in Gray Matter Density, Volume, Mass, and Cortical Thickness from Childhood to Young Adulthood - PubMed (original) (raw)

Efstathios D Gennatas et al. J Neurosci. 2017.

Abstract

Developmental structural neuroimaging studies in humans have long described decreases in gray matter volume (GMV) and cortical thickness (CT) during adolescence. Gray matter density (GMD), a measure often assumed to be highly related to volume, has not been systematically investigated in development. We used T1 imaging data collected on the Philadelphia Neurodevelopmental Cohort to study age-related effects and sex differences in four regional gray matter measures in 1189 youths ranging in age from 8 to 23 years. Custom T1 segmentation and a novel high-resolution gray matter parcellation were used to extract GMD, GMV, gray matter mass (GMM; defined as GMD × GMV), and CT from 1625 brain regions. Nonlinear models revealed that each modality exhibits unique age-related effects and sex differences. While GMV and CT generally decrease with age, GMD increases and shows the strongest age-related effects, while GMM shows a slight decline overall. Females have lower GMV but higher GMD than males throughout the brain. Our findings suggest that GMD is a prime phenotype for the assessment of brain development and likely cognition and that periadolescent gray matter loss may be less pronounced than previously thought. This work highlights the need for combined quantitative histological MRI studies.SIGNIFICANCE STATEMENT This study demonstrates that different MRI-derived gray matter measures show distinct age and sex effects and should not be considered equivalent but complementary. It is shown for the first time that gray matter density increases from childhood to young adulthood, in contrast with gray matter volume and cortical thickness, and that females, who are known to have lower gray matter volume than males, have higher density throughout the brain. A custom preprocessing pipeline and a novel high-resolution parcellation were created to analyze brain scans of 1189 youths collected as part of the Philadelphia Neurodevelopmental Cohort. A clear understanding of normal structural brain development is essential for the examination of brain-behavior relationships, the study of brain disease, and, ultimately, clinical applications of neuroimaging.

Keywords: MRI; T1-weighted imaging; brain structure; cortical thickness; gray matter density; gray matter volume.

Copyright © 2017 the authors 0270-6474/17/375065-09$15.00/0.

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Figures

Figure 1.

Figure 1.

T1 preprocessing and high-resolution gray matter parcellation. A, Raw T1 MPRAGE volumes were first corrected for field inhomogeneity and then skull stripped by transforming the MNI brain mask to native space. Gray matter segmentation was performed without the use of tissue priors to produce unbiased estimates of GMD. B, The GMD maps of an age- and sex-balanced subsample of 240 subjects were averaged and smoothed; 1 − the gradient of the resulting image was calculated and passed to a 3D watershed algorithm, resulting in 1625 regions covering the whole-brain gray matter.

Figure 2.

Figure 2.

Density increases in adolescence while other measures largely decrease. Females have higher density and lower volume. Plots show fitted values of whole-brain gray matter measures against age for the two sexes. GMD and CT were averaged across the brain (weighted by N voxels in each parcel), and GMV and GMM were summed. To make results comparable across measures, they are plotted as percentages: 100% is defined as the fitted value for males at 8 years of age. Shaded bands correspond to ±2 × SE of the fit (∼95% confidence interval).

Figure 3.

Figure 3.

Percentage net change and variance explained by sex and modality. A, For each parcel, the percentage net change was calculated as follows: (fitted value at 23 − fitted value at 8)/(fitted value at 8) × 100%. GMD increased virtually throughout the brain, while the other modalities show mostly decreases. Females showed a greater increase in density than males throughout the brain. B, Percentage variance of each measure explained by age. GMD showed the highest _R_2 values, followed by CT. High bilateral symmetry on all maps suggests biological plausibility. Interactive movies including all axial slices in this figure are available on-line at

https://egenn.github.io/gmdvdev

.

Figure 4.

Figure 4.

Sex differences by modality by MNI label against age. The difference of male and female fitted values for each modality for each MNI label was calculated at each year from 8 to 23 years of age. This plot highlights qualitatively how sex differences vary with age, in most cases in a nonlinear fashion (a constant sex difference in any measure would appear as a horizontal line). Note that only in CT the direction of the difference changes in frontal and occipital lobes as well as the bilateral insula from a male to a female advantage.

Figure 5.

Figure 5.

Intermodal correlations averaged by MNI label. Pairwise spearman correlations (rho) were estimated between the fitted values of model 3 (top row) of all gray matter measures to summarize the similarity of age-related effects among modalities and between their residuals (bottom row). Brain slices with these results are available on-line at

https://egenn.github.io/gmdvdev/imcor.html

. D, Gray matter density; V, gray matter volume; M, gray matter mass; T, cortical thickness.

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