Standard-space atlas of the viscoelastic properties of the human brain

Abstract

Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast-based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18-35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM-152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons.

Keywords: MRI templates; brain atlases; magnetic resonance elastography; magnetic resonance imaging; mechanical properties; viscoelasticity.

FIGURE 1

Overview of the MRE imaging and analysis procedure. In the first step, shear waves at 50 Hz are introduced to the brain via a pneumatic actuation system (Resoundant; Rochester, MN). The resulting tissue deformation is captured using motion‐encoding gradients embedded within the MRE spiral sequence, and displacement data is captured along three separate axes (anterior–posterior, right–left, and superior–inferior). The displacement data along with a binary brain mask is supplied to the nonlinear algorithm which models tissue as a heterogenous, viscoelastic material. A subzone optimization procedure is used to iteratively update the property description in a finite element computational model to minimize the difference between the model displacements and the measured displacement data. Finally, maps of the complex shear modulus are converted to shear stiffness, μ = 2|G*|2/(G' + |G*|), and damping ratio, ξ = G″/2G′. The subject specific T1‐weighted MPRAGE and MRE T2 magnitude images are provided to illustrate the images required for the spatial normalization procedure

FIGURE 2

(a) Representative axial images and sagittal view (last column) from the MNI152 T1‐weighted template; (b) mean shear stiffness, μ _mean, and (c) mean damping ratio, ξ_mean, templates created by averaging the spatially normalized images from all 134 participants

FIGURE 3

Panels (a–d) illustrate the binary masks used to quantify MRE measurements for (a) the entire brain excluding the ventricles, (b) white matter, (c) subcortical gray matter, and (d) the cerebral cortex. Note that panel (a) illustrates the excluded regions, whereas Panels (b–d) show the binary masks themselves. Variable density boxplots are provided for MRE measures of (e) shear stiffness, μ, and (f) damping ratio, ξ, for each global region of interest (ROI) to show data dispersion. The length of the box plots illustrates the 25th and 75th percentiles (i.e., interquartile range), with the central black line showing the median. Extended lines indicate the maximum and minimum values. Individual data points have been adjusted for study and sex by removing the relevant estimated coefficients from the mixed model. Inset shows Bonferroni corrected pairwise comparisons of each global ROI pair, * indicating p < .05

FIGURE 4

Variable density boxplots, significance charts, and sex x region interaction plots for subcortical gray matter (a) shear stiffness, μ, and (b) damping ratio, ξ. The length of the box plots illustrates the 25th and 75th percentiles (i.e., interquartile range), with the central black line showing the median. Individual data points have been adjusted for study and sex by removing the relevant estimated coefficients from the mixed model. Significant differences between structures were determined through post‐hoc linear correlations which were adjusted for multiple comparisons with Bonferroni correction. A significant interaction was found between sex and SGM, μ, with amygdala (AM; p = .024), pallidum (PA; p = .028), putamen (p = .031), and thalamus (TH; p = .018) being significantly stiffer in males. Hippocampus was the only SGM region stiffer in females (HC; p = .054). No significant sex differences were observed for ξ (p > .05)

FIGURE 5

Variable density boxplots, pairwise significant charts, and sex x region interaction plots for white matter tract (a) shear stiffness, μ, and (b) damping ratio, ξ. The length of the box plots illustrates the 25th and 75th percentiles (i.e., interquartile range), with the central black line showing the median. Extended lines indicate the maximum and minimum values. Individual data points have been adjusted for study and sex by removing the relevant estimated coefficients from the mixed model. Significant differences between structures were determined through post‐hoc linear correlations which were adjusted for multiple comparisons with Bonferroni correction. A significant interaction was found between sex and WMT μ, with corticospinal tract (CST; p = .007) being stiffer in males. In contrast, the major forceps (FMa; p = .041) were significantly stiffer in females. For ξ, females had greater ξ in both the corticospinal tract (CST; p = .005), and inferior longitudinal fasciculus (ILF; p = .020). No other pairwise comparison was significant for either measure (p > .05)

FIGURE 6

Variable density boxplots, pairwise significant charts, and sex x region interaction plots for cortical gray matter (a) shear stiffness, μ, and (b) damping ratio, ξ. The length of the box plots illustrates the 25th and 75th percentiles (i.e., interquartile range), with the central black line showing the median. Extended lines indicate the maximum and minimum values. Individual data points have been adjusted for study and sex by removing the relevant estimated coefficients from the mixed model. Significant differences between structures were determined through post‐hoc linear correlations which were adjusted for multiple comparisons with Bonferroni correction. A significant interaction was found between sex and CGM μ, with the postcentral cortex (POST; p < .001), precuneus (PCN; p < .001), and superior parietal cortex (SPC; p < .001) being stiffer in males. A significant interaction was also found for ξ; females had greater ξ for cuneus (CN; p = .046), fusiform (FSM; p = .007), lingual occipital (LiO; p = .010), precentral (PRE; p = .014), postcentral (POST; p = .025), and superior temporal (STC; p = .005) cortices