Examining the Boundary Sharpness Coefficient as an Index of Cortical Microstructure in Autism Spectrum Disorder

Abstract

Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multicenter structural magnetic resonance imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male), and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. Increases were observed in different brain regions in males and females, with larger effect sizes in females. BSC correlated with ADOS-2 Calibrated Severity Score in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared with cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.

Keywords: autism spectrum disorder; cerebral cortex; microstructure; myelin; tissue contrast.

Figure 1

Intensity sampling and sigmoid fit method used to calculate BSC for each vertex. At each vertex, the T1w image intensity was measured at 10 cortical surfaces surrounding the gray/white boundary, including the mid-surface, gray/white boundary surface, and a total of eight newly generated gray and white surfaces equally spaced apart (A, B). A sigmoid curve (Equation 1) was fit to the 10 sample points (C) and parameter BSC, reflecting the sigmoid growth rate (D), was log-transformed to create the measure that is the BSC at that vertex. Higher BSC values reflect a quicker transition between gray and white matter and a less blurred cortical boundary, whereas lower BSC values reflect a slower transition between gray and white matter and a more blurred cortical boundary (D). The tissue contrast ratio was calculated by dividing the intensity sampled at the gray 25% surface by the intensity sampled at the white 25% surface.

Figure 2

Diagnostic group comparisons of BSC. (A) Average BSC map versus average T1/T2 ratio myelin map from Glasser et al. (2011). Olafson et al. BSC map depicts the average BSC values across control subjects aged 22–35 for a single site (Sick Kids) for correspondence with the HCP dataset used by Glasser et al. (2011) to derive T1/T2 ratio maps. The top row displays lateral views (left hemisphere on the left, right hemisphere on the right), and the bottom row displays medial views (with midline vertices masked out), for each map. (B) Individuals with ASD had significantly higher BSC measures (<5% FDR, peak Cohen’s d = 0.38) in the bilateral superior temporal gyrus, inferior temporal gyrus, and left inferior frontal gyrus. (C) Forest plot displaying site-specific effect sizes at a peak vertex in the left frontal gyrus represented by an asterisk in (B).

Figure 3

Age-stratified and age-centered analyses. Individuals under 18 with ASD had significantly higher BSC measures in the bilateral superior temporal gyrus as well as the left precentral gyrus (<5% FDR, peak Cohen’s d = 0.41) (A). Individuals over 18 with ASD showed significantly increased BSC in the bilateral precuneus and superior temporal gyrus (<5% FDR, peak Cohen’s d = 0.62). (B) For the age-centered analysis, group differences in BSC were greatest between the ages of 12 and 20 in the right superior temporal gyrus and left inferior temporal gyrus. (C) Zoom of the left superior temporal lobe (top) and right inferior temporal lobe (bottom) displaying qvalues between 1% and 5% FDR (same colormap as in B). (D) Plot of BSC across age in a single site (Toronto) at vertex highlighted with a white asterisk in A.

Figure 4

Relationship between BSC and ADOS-CSS. Across all subjects with ASD with severity scores, ADOS-CSS was positively correlated with BSC, shown for a peak vertex in the right medial temporal gyrus (A). Correlations between ADOS-CSS and BSC were also observed in the female-only group in the left parietal lobe (B).

Figure 5

Cohen’s d effect size maps of BSC (A) and cortical thickness (B, used with permission from Bedford et al. 2020). Spatial correspondence assessed by the Pearson correlation coefficient in a permutation-based “spin-test” analysis between BSC and cortical thickness is demarcated in red (C) was significant (P = 0.00; P < 0.001 as per the software output) with 1000 null spatial permutations. FDR-thresholded q-value maps of significant increases in BSC and increases in cortical thickness in individuals with ASD (D).