Segmentation of Grey and White Matter Hyperintensity in Typically Developing Children and Children With Intellectual...

This study evaluated childhood brain volumes using voxel-based morphometry and examined their relationships with grey matter, white matter and total brain volume in children diagnosed with intellectual disability (ID) and healthy controls.

Sixty children (age range 6-12 years) diagnosed with mild to moderate ID according to DSM-5 and 60 age- and sex-matched healthy controls (age range 6-12 years) were included in the study. Total brain volume (TBV), white matter volume (WMV) and grey matter volume (GMV) were automatically calculated from magnetic resonance images of all participants. Normality was assessed using the Shapiro-Wilk test, group differences were assessed using Welch t-tests and associations were assessed using multiple regression and logistic regression analyses.

The Shapiro-Wilk test results indicated that many variables were not normally distributed (TBV: p < 0.001; GMV: p < 0.001). In group comparisons, no significant effect of gender on TBV, WMV and GMV was found (t-values ranged from -0.757 to -0.276, all p > 0.45). Age was a strong predictor of TBV (β = 7.25, 95% CI [3.07, 11.43], p < 0.001), and the regression model had high explanatory power (R² = 0.977). Logistic regression analyses showed that WMV (OR = 0.82, 95% CI [0.73, 0.92], p = 0.001) and GMV (OR = 1.16, 95% CI [1.06, 1.26], p = 0.0012) significantly predicted diagnostic status. However, the very high odds ratios calculated for the WMVM variable (OR > 10⁶³, p < 0.001) indicate a multicollinearity problem.

The findings indicate that white and grey matter volumes may differ in children with MR compared to healthy controls, and these structures have potential as diagnostic biomarkers. The study demonstrates the developmental heterogeneity of the brain during childhood. However, the limited sample size, the presence of outliers and multicollinearity should be considered as limitations.