Longitudinal mapping of cortical thickness and brain growth in normal children

Abstract

Recent advances in magnetic resonance imaging (MRI) technology now allow the tracing of developmental changes in the brains of children. We applied computer-matching algorithms and new techniques for measuring cortical thickness (in millimeters) to the structural MRI images of 45 children scanned twice (2 yr apart) between the ages 5 and 11. Changes in brain size were also assessed, showing local brain growth progressing at a rate of approximately 0.4-1.5 mm per year, most prominently in frontal and occipital regions. Estimated cortical thickness ranged from 1.5 mm in occipital regions to 5.5 mm in dorsomedial frontal cortex. Gray matter thinning coupled with cortical expansion was highly significant in right frontal and bilateral parieto-occipital regions. Significant thickening was restricted to left inferior frontal (Broca's area) and bilateral posterior perisylvian (Wernicke's area on the left) regions. In the left hemisphere, gray matter thickness was correlated with changing cognitive abilities. For the first time, developmental changes in gray matter thickness, brain size, and structure-function relationships have been traced within the same individuals studied longitudinally during a time of rapid cognitive development.

Figure 1.

A-C, Cortical thickness maps: original T1-weighted image for one representative subject (A), tissue segmented image (B), gray matter thickness image where thickness is progressively coded in millimeters from inner to outer layers of cortex using the 3D Eikonal Fire equation (C). Note that the images were resampled to a voxel size of 0.33 mm cubed, so the thickness measures are at a submillimeter level of precision according to the color bar on the right (in millimeters). A-C are sliced at the same level in all three image volumes from the same subject. D is an in vivo average cortical thickness map created from our 45 subjects at their first scan. The brain surface is color coded according to the color bar where thickness is shown in millimeters. E, Our average thickness map can be compared with an adapted version of the 1929 cortical thickness map of Von Economo (1929). Color coding has been applied over Von Economo's original stippling pattern, respecting the boundaries of the original work, to highlight the similarities between the two maps.

Figure 2.

Error estimation maps. A, In the top row, a map of the average absolute value of the cortical thickness difference between short-interval scans for the five subjects is shown. The average error estimate for these subjects ranges from 0 to 1.4 mm. B, To estimate the error for each individual in the larger group of 45 subjects, we divided the average error maps by the square root of 45 minus 1. Thus, the estimated error for each of the 45 subjects ranges from 0 to ∼0.15 mm, which is considerably less than the maturational difference observed in these 45 children over a 2 year interval (C), which ranges regionally from -0.6 to 0.3 mm.

Figure 3.

Regions of interest used in the permutation analyses. Lateral regions are color coded as follows: ventral frontal, yellow; dorsal frontal, pink; temporal, dark blue; occipital, green; parietal, light blue; perisylvian, brick red [created from a statistical map published previously (Sowell et al., 2003)]. Medial regions are color coded as follows: dorsal frontal, purple; ventral frontal, olive green; parietal, dark blue; occipital, red; callosal brainstem area (not tested in permutations), white.

Figure 4.

Average cortical thickness. Shown here are left and right, medial and lateral, and top views of average cortical thickness maps for all 45 subjects at time 1. Cortical thickness is shown in color representing millimeters according to the color bar.

Figure 5.

Annualized rate of change in cortical thickness. Shown in this figure is the average rate of change in cortical thickness in millimeters according to the color bar on the right. Maximum gray matter loss is shown in shades of red, and maximum gray matter gain is shown in shades of blue.

Figure 6.

One-sample t test map for gray matter thickness. These brain maps show the statistical significance of annualized change in cortical thickness measures. Color coding represents t values at each cortical surface point according to the left color bar (ranging from t = -3.0 to t = 3.0), and significant values are overlaid in shades of red [significant thickness decreases (TD)] and white [significant thickness increases (TI)] according to the color bar on the right. Arrows point to the three regions of significant gray matter thickness increases, representative of the only three regions to withstand permutation correction for multiple comparisons for thickness increase shown in Table 1.

Figure 7.

Annualized rate of change in DFC (lateral surface) and DFC-H (medial surface). Brain maps showing the annualized rate of change in DFC in millimeters according to the color bar. Corpus callosum and brainstem regions have been masked out of the midline views. Note the most prominent growth shown in red where brain size increases on average 0.5-1.0 mm per year.

Figure 8.

One-sample t test map for radial expansion (or shrinkage). These brain maps show the statistical significance of annualized brain growth measures. Note that the color coding is inverse of that shown in Figure 6. As in both figures, we wanted to highlight the most prominent changes in red (gray matter loss for thickness but brain growth for DFC-H). Color coding represents t values at each cortical surface point according to the left color bar (ranging from t = -3.0 to t = 3.0), and significant values overlaid in shades of red [significant brain growth (BG)] and white [significant brain shrinkage (BS); according to the color bar on the right].

Figure 9.

Brain-behavior maps for vocabulary and cortical thickness. These maps show the p value for negative correlations between change in cortical thickness (time 2 minus time 1) and change in vocabulary raw scores (time 2 minus time 1). Negative p values (i.e., regions where greater thinning was associated with greater vocabulary improvement) are represented in color according to the color bar, and regions in white were not significant. Positive correlations were not significant in the permutation analyses for any of the ROIs and are not shown here.