Elsevier

NeuroImage

Volume 60, Issue 1, March 2012, Pages 340-352
NeuroImage

Diffusion tensor imaging of white matter tract evolution over the lifespan

https://doi.org/10.1016/j.neuroimage.2011.11.094Get rights and content

Abstract

Diffusion tensor imaging (DTI) has been used widely to show structural brain changes during both development and aging. Lifespan studies are valuable because they connect these two processes, yet few DTI studies have been conducted that include both children and elderly subjects. This study used DTI tractography to investigate 12 major white matter connections in 403 healthy subjects aged 5–83 years. Poisson fits were used to model changes of fractional anisotropy (FA) and mean diffusivity (MD) across the age span, and were highly significant for all tracts. FA increased during childhood and adolescence, reached a peak between 20 and 42 years of age, and then decreased. MD showed an opposite trend, decreasing first, reaching a minimum at 18–41 years, and then increasing later in life. These trajectories demonstrate rates and timing of development and degradation that vary regionally in the brain. The corpus callosum and fornix showed early reversals of development trends, while frontal–temporal connections (cingulum, uncinate, superior longitudinal) showed more prolonged maturation and delayed declines. FA changes were driven by perpendicular diffusivity, suggesting changes of myelination and/or axonal density. Tract volume changed significantly with age for most tracts, but did not greatly influence the FA and MD trajectories. This study demonstrates clear age-related microstructural changes throughout the brain white matter, and provides normative data that will be useful for studying white matter development in a variety of diseases and abnormal conditions.

Highlights

► We model diffusion changes across the lifespan (5–83 years) using tractography. ► Fractional anisotropy (FA) and mean diffusivity (MD) show non-linear trajectories. ► FA peaks occurred between 20–42 years and MD minima occurred between 18–43 years. ► The fornix and callosal tracts had the earliest trend reversals. ► The frontal–temporal connections had the most prolonged development.

Introduction

Lifespan studies of the normal human brain provide the necessary link between the developmental processes of childhood and the degenerative processes of old age. Postmortem lifespan studies of the human brain demonstrate a variety of structural changes, including overall brain weight (Dekaban, 1978), myelination (Benes et al., 1994, Yakovlev and Lecours, 1967), and synaptic density (Huttenlocher, 1979, Huttenlocher and de Courten, 1987). Imaging studies also show changes in brain tissue volumes (Courchesne et al., 2000, Good et al., 2001, Walhovd et al., 2011) and cortical thickness (Sowell et al., 2003, Westlye et al., 2010) across wide age ranges. In general, these studies show rapid development during childhood, slower maturation during adolescence and young adulthood, and a plateau and/or reversal of developmental processes during adulthood.

Diffusion tensor imaging (DTI) shows robust increases of fractional anisotropy (FA) and decreases of mean diffusivity (MD) during healthy childhood and adolescence in most brain white matter regions (Barnea-Goraly et al., 2005, Eluvathingal et al., 2007, Lebel et al., 2008b, Schmithorst et al., 2002). DTI studies of healthy aging demonstrate opposite trends, with FA decreasing and MD increasing during old age (Abe et al., 2002, Hsu et al., 2010, Ota et al., 2006, Pfefferbaum et al., 2000). Although studies connecting childhood development with aging are essential to accurately assess which regions mature “early” and “late”, only a handful of DTI studies assess microstructural white matter changes across the lifespan. Three groups recently used DTI to study multiple brain white matter regions across wide age ranges beginning in childhood: one looked at 119 subjects aged 7–68 years using tractography (Hasan et al., 2010); another examined 430 subjects aged 8–85 years using tract-based spatial statistics (TBSS) (Westlye et al., 2009), and a third group analyzed subjects (n = 1031, 831) aged 11–90 years also using TBSS and a region-of-interest approach for examining specific white matter tracts (Kochunov et al., 2010, Kochunov et al., 2011). These studies demonstrate nonlinear (quadratic) FA changes across most of the brain white matter, with timing of FA peak varying from early twenties to mid-forties, depending on the tract. In general, these studies observed early FA peaks in the corpus callosum and inferior longitudinal fasciculus, while they saw relatively late peaks in the cingulum. Other association and projection fibers had mixed results across studies. Two studies reported radial (perpendicular) diffusivity curves demonstrating trajectories opposite to those of FA—decreasing diffusivity initially, followed by increases at older ages (Hasan et al., 2010, Westlye et al., 2009). Additional studies have focused on the corpus callosum (Hasan et al., 2008a, Hasan et al., 2008b, Hasan et al., 2009b, Lebel et al., 2010, McLaughlin et al., 2007) or the uncinate fasciculus (Hasan et al., 2009a), demonstrating similar U-shaped trajectories for diffusion parameters.

It is important to note that none of these previous studies, nor our current one presented here, analyze infants or very young children, and therefore miss a period of very rapid brain development. Nonetheless, these studies provide valuable information about the regional variation of age-related brain changes across a wide age range. DTI tractography provides robust estimates of diffusion parameters across the entire tract, does not rely on spatial normalization, and is more reliable than region-of-interest analysis (Kanaan et al., 2006). Yet, only one of the previous studies used tractography to measure the parameter changes (Hasan et al., 2010), and, with only 119 subjects, had high uncertainty in the fits (errors of 9–29 years for peak age estimates). All of the previous studies used a quadratic model for age-related changes (Hasan et al., 2010, Kochunov et al., 2010, Westlye et al., 2009); Westlye et al. also used a smoothing function to demonstrate nonlinear changes in tract-specific sections of the white matter skeleton. Quadratic models tend to provide reasonable fits, but are not ideal because they restrict the slopes on either side of the peak or minimum in the curve to be the same and tend to underestimate peak ages (Fjell et al., 2010). Less restrictive fits, such as a Poisson curve, are beneficial because they allow differential slopes on either side of the peak/minimum while still maintaining a small number of estimation parameters.

The goal of this study was to use DTI tractography to provide a comprehensive analysis of age-related microstructural changes of brain white matter in a large number of healthy subjects (n = 403) across a very wide age range (5–83 years).

Section snippets

Subjects

In total, 403 healthy volunteers (195 males/208 females) aged 5 to 83 years (mean age ± standard deviation: 31.3 ± 21.5, 374 right-handed/26 left-handed/3 no preference) participated in this study; Table 1 shows the number of subjects by 5-year age group. Subjects had no self-reported history of neurological or psychiatric disease or brain injury. All volunteers gave informed consent; both child assent and parent/guardian consent was obtained for volunteers under 18 years.

Image acquisition

All data was acquired on the

Brain volumes

Age-related changes of gray matter, white matter, and CSF volume were nonlinear (Fig. 1). Poisson fits were highly significant (p < 0.001) and gave robust parameter estimates for native and normalized volume changes. Males had significantly higher white matter, gray matter, CSF and total brain volumes than females, although the development curves were not significantly different (linear and exponential parameters). The normalized volumes were not significantly different between genders. Gray

Discussion

This comprehensive DTI analysis of major white matter tracts within the human brain demonstrates regionally varying, non-linear changes across a wide age range. This study used tractography to build upon previous works using voxel-based methods (Kochunov et al., 2010, Kochunov et al., 2011, Westlye et al., 2009), and a smaller tractography study (Hasan et al., 2010) to provide relative timing measures of maturation for twelve major white matter fiber bundles in a large group of 403 healthy

Acknowledgments

The authors acknowledge the Canadian Institutes of Health Research and Networks of Centres of Excellence—Canadian Language and Literacy Research Network (CLLRNet) for operating grants, and Alberta Innovates—Health Solutions (CB, CL) for salary support. MRI infrastructure was provided by the Canada Foundation for Innovation, Alberta Science and Research Authority, Alberta Heritage Foundation for Medical Research, and the University Hospital Foundation.

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