Elsevier

NeuroImage

Volume 125, 15 January 2016, Pages 267-279
NeuroImage

Trajectories of cortical thickness maturation in normal brain development — The importance of quality control procedures

https://doi.org/10.1016/j.neuroimage.2015.10.010Get rights and content

Highlights

  • Cortical thickness follows mostly a monotonic linear decline after 5 years of age.

  • Areas with cubic developmental trajectories have peaks of cortical thickness prior to age 8.

  • The only sex difference in maturation is faster occipital thinning in males.

  • Mean cortical thickness follows a monotonic linear decline of 0.027 mm per year.

  • Quality control processes have a significant impact on identified trajectories.

  • A post-processing quality control should be applied in all cortical thickness studies.

Abstract

Several reports have described cortical thickness (CTh) developmental trajectories, with conflicting results. Some studies have reported inverted-U shape curves with peaks of CTh in late childhood to adolescence, while others suggested predominant monotonic decline after age 6. In this study, we reviewed CTh developmental trajectories in the NIH MRI Study of Normal Brain Development, and in a second step, evaluated the impact of post-processing quality control (QC) procedures on identified trajectories. The quality-controlled sample included 384 individual subjects with repeated scanning (1–3 per subject, total scans n = 753) from 4.9 to 22.3 years of age. The best-fit model (cubic, quadratic, or first-order linear) was identified at each vertex using mixed-effects models. The majority of brain regions showed linear monotonic decline of CTh. There were few areas of cubic trajectories, mostly in bilateral temporo-parietal areas and the right prefrontal cortex, in which CTh peaks were at, or prior to, age 8. When controlling for total brain volume, CTh trajectories were even more uniformly linear. The only sex difference was faster thinning of occipital areas in boys compared to girls. The best-fit model for whole brain mean thickness was a monotonic decline of 0.027 mm per year. QC procedures had a significant impact on identified trajectories, with a clear shift toward more complex trajectories (i.e., quadratic or cubic) when including all scans without QC (n = 954). Trajectories were almost exclusively linear when using only scans that passed the most stringent QC (n = 598). The impact of QC probably relates to decreasing the inclusion of scans with CTh underestimation secondary to movement artifacts, which are more common in younger subjects. In summary, our results suggest that CTh follows a simple linear decline in most cortical areas by age 5, and all areas by age 8. This study further supports the crucial importance of implementing post-processing QC in CTh studies of development, aging, and neuropsychiatric disorders.

Introduction

The human brain undergoes rapid development in utero and during the first few years of life (http://www.bic.mni.mcgill.ca/~vfonov/obj2/obj2model2.mpg) (Clouchoux et al., 2012). Although this process slows down after 4 years of age, significant remodeling of the cortex continues up to the late twenties/early thirties (Giedd and Rapoport, 2010, Shaw et al., 2008). The advent of longitudinal magnetic resonance imaging (MRI) scanning of the developing brain has allowed for a better understanding of typical cortical development. Understanding cortical developmental trajectories of healthy children and adolescents is of crucial importance given the demonstrated impact of cortical maturation on intellectual capacities, behavior, and pediatric neuropsychiatric disorders (Giedd and Rapoport, 2010, Giedd et al., 2009, Shaw et al., 2006, Shaw et al., 2011, Ducharme et al., 2012, Ducharme et al., 2014, Lenroot et al., 2007, Kharitonova et al., 2013, Thormodsen et al., 2013).

Initial MRI studies of brain development used cortical volume as the main morphometric measure. In a landmark study, Giedd et al. (1999) found that cortical volume follows an ‘inverted U’ shape development (Giedd et al., 1999). Gray matter was found to increase in volume in childhood, but started to decline after peaks in adolescence that varied across the different brain areas (age 12 in fronto-parietal, 16 in temporal, 20 in occipital). In addition, average peaks occurred earlier in females (Lenroot et al., 2007, Giedd et al., 1999). A subsequent detailed study of 13 subjects with repeated scanning over 8 to 10 years revealed that higher-order association areas mature after lower-order somatosensory areas, and that phylogenetically newer areas mature later than older ones (Gogtay et al., 2004).

With the improvement of automated cortical surface measurement, subsequent studies have been able to distinguish cortical thickness (CTh) and cortical surface area (CSA) as two components underlying cortical volume (CV). Major studies in large cohorts have mostly characterized the developmental changes in CTh over time. In a study of 375 typically developing subjects between the ages of 3.5 and 33, Shaw et al. (2008) suggested that CTh of brain regions follow variable trajectories of developmental trajectories based on the complexity of the underlying laminar architecture (Shaw et al., 2008). The best fitting model was cubic for most of the brain (initial increase, decline in teenage years, then stabilization phase), with some areas (e.g., insular cortex, anterior cingulate cortex) following a quadratic trajectory (initial increase followed by a decline in teenage years), and some areas showing first-order linear decline (e.g., orbito-frontal cortex, subgenual anterior cingulate cortex, medial temporal cortex). Peaks of CTh were attained in primary sensory-motor areas first, followed by secondary association areas, and finally in polymodal association areas. Peaks of CTh occurred earlier than what was reported in older studies (e.g., 10.5 years of age in dorsolateral prefrontal cortex and cingulate cortex). In a later study on 647 typically developing children and young adults (ages 3–30), Raznahan et al. (2011) reported a curvilinear (‘inverted U’) growth pattern of mean CTh (Raznahan et al., 2011). Contrary to previous reports, CTh peaks were not sexually dimorphic (8.6 males, 8.4 females) (Raznahan et al., 2011). Although CSA trajectories have been less extensively investigated, Raznahan et al. (2011) showed a similar curvilinear growth pattern, with later peaks than for CTh (9.7 males, 8.1 females).

In contrast, some studies have not identified ‘inverted U’ shape or cubic developmental trajectories of gray matter, and casted doubts on the precise age of CTh peaks. A longitudinal study of 45 subjects between the ages of 5 and 11 showed primarily cortical thinning during this age period, except in small parts of the inferior frontal and perisylvian areas (Sowell et al., 2004). Another study of preadolescents (n = 126) showed only thinning between 6 and 10 years of age, with minimal differences between males and females (Muftuler et al., 2011). In 68 healthy participants from 8 to 30 years of age, Tamnes et al. (2010) reported no increase in CTh after age 8, and regions following quadratic trajectories showed an accelerating decline in adolescence as opposed to a U shaped curve (Tamnes et al., 2010). Another sample from the Netherlands also showed almost exclusively linear decline in thickness and gray matter volume between 8 and 30 years of age, with no gender differences in CTh trajectories (Koolschijn and Crone, 2013). A study of cortical thickness in twins has reported only thinning between the ages of 9 and 12, in addition to demonstrating a strong increasing genetic influence on mean and local thickness (65% at age 9, 82% at age 12) (van Soelen et al., 2012). Finally, in 137 healthy subjects between 6.3 and 29.7 years of age (total 209 scans), Mutlu et al. (2013) did not find evidence of cubic trajectories using a Bayesian information criterion (Mutlu et al., 2013). There were quadratic trajectories in the frontal and parietal association areas, the temporo-parietal junction, medial frontal areas, and the posterior cingulate/precuneus. However, the large majority of areas showed a first-order linear decline. In summary, although the general assumption is that CTh follows a curvilinear or cubic trajectory, there are inconsistencies across samples, and the age at which CTh peaks remains uncertain.

The NIH MRI Study of Normal Brain Development is a scientific initiative aiming to provide better understanding of normal brain development and brain–behavior relationships (Evans and Brain Development Cooperative Group, 2006). In this study, 431 subjects between 4.6 and 18 years of age were recruited throughout 6 sites in the USA after a careful assessment to select only typically developing children. A major strength of this study was the population-based sampling method of recruitment with continuous monitoring to ensure socio-demographic representation of the American population (Waber et al., 2007). In an initial cross-sectional report (only the first visit for each subject), total and lobar gray matter volume linearly declined over time (1.11% decline per year), while white matter increased over time (1.54% per year) (Brain Development Cooperative Group, 2012). The only significant sex difference was the previously reported 10% greater total brain volume (TBV) in males compared to females.

In this study, we explored the maturational trajectory of local CTh across the whole brain in the NIH MRI Study of Normal Brain Development. Given the preliminary cross-sectional finding of monotonic linear decrease of gray matter volume in this database (Brain Development Cooperative Group, 2012) and assuming some degree of association between volume and thickness, we expected that if higher order trajectories were present, CTh peaks occur prior to the lower age limit of the studied sample (ages 5–6), which is earlier age than peaks reported in past studies that identified inverted-U shape trajectories (ages 8.4–10.5) (Shaw et al., 2008, Raznahan et al., 2011). The impact of factoring TBV as a control variable was also analyzed in order to differentiate absolute morphological changes from relative remodeling in the cortical mantle. We decided to focus on CTh (as opposed to CSA or CV) because variations in this measure have been most frequently associated with cognitive and behavioral phenotypes in children. However, data on trajectories for CSA and CV are provided in an associated Data in Brief article (Ducharme et al., submitted for publication).

In a second step, we explored the impact of implementing various levels of quality control (QC) on the estimation of CTh trajectories. Given the sensitivity of CTh estimations to very small movement artifacts (some present but hard to notice on native MRI volumes), our group always systematically implements a visual quality control of extracted white and gray matter surfaces to eliminate subjects with probable erroneous measurements. We hypothesize that differences in results of cortical trajectories between research groups could be explained in part by different QC methods. Indeed, Reuter et al (2014) recently demonstrated that movement artifacts can lead to underestimation of CTh (Reuter et al., 2014). By excluding any post-processing MRI with inadequate tissue identification, we ensure that only reliable data are included in statistical analyses. Although QC can decrease sample size and power, this is counterbalanced by a reduction in variance by minimizing the artificially inflated component of the variance due to movement artifacts. This issue is especially important for younger subjects who tend to move more during MRI data acquisition.

Section snippets

Sampling and recruitment

Subjects were recruited at 6 pediatric study centers across the USA with a population-based sampling method seeking to minimize selection biases (Waber et al., 2007). There were extensive exclusion criteria including the presence of a current or past Axis I diagnosis established with the Diagnostic Interview for Children and Adolescents (with the exception of simple phobia, social phobia, adjustment disorder, oppositional defiant disorder, enuresis, encopresis, and nicotine dependence), any

Cortical thickness

As seen in Fig. 3, absolute CTh (i.e., results of analyses without including TBV) predominantly followed a first-order linear thinning trajectory. There were few areas showing cubic trajectories, such as the bilateral superior and inferior parietal cortex, left angular gyrus, left postero-lateral temporal cortex, left precentral gyrus, right dorsolateral prefrontal cortex (DLPFC) (superior frontal and rostral middle frontal areas), and left medial paracentral/superior frontal cortex. There were

Discussion

This study revisited developmental trajectories of CTh in the longitudinal sample of the NIH MRI Study of Normal Brain Development, which is socio-demographically representative of the American population. A few key findings emerged. First, we found that CTh predominantly follows a monotonic first-order linear decline over time between the age of 4.9 and 22.3, in line with multiple other studies (Sowell et al., 2004, Muftuler et al., 2011, Tamnes et al., 2010, Koolschijn and Crone, 2013). There

Conclusions

In summary, CTh follows a negative first-order linear trajectory in most of the brain between the ages of 4.9 and 22, with a mean decline of 0.027 mm per year. In areas of cubic trajectories, peaks of CTh occurred no later than at 8 years of age. The only sexually dimorphic finding was faster thinning in parts of the occipital lobe of boys compared to girls. Crucially, the application of a visual QC to ensure the reliability of data shifts identified trajectories from more complex models to a

Acknowledgments

Authors do not report conflicts of interest related to this work. This project has been funded in whole or in part with Federal funds from the National Institute of Child Health and Human Development, the National Institute on Drug Abuse, the National Institute of Mental Health, and the National Institute of Neurological Disorders and Stroke (Contract #s N01-HD02-3343, N01-MH9-0002, and N01-NS-9-2314, -2315, -2316, -2317, -2319 and -2320). SD receives funding from the Montreal General Hospital

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