A review of diffusion MRI of typical white matter development from early childhood to young adulthood

Abstract

Understanding typical, healthy brain development provides a baseline from which to detect and characterize brain anomalies associated with various neurological or psychiatric disorders and diseases. Diffusion MRI is well suited to study white matter development, as it can virtually extract individual tracts and yield parameters that may reflect alterations in the underlying neural micro-structure (e.g. myelination, axon density, fiber coherence), though it is limited by its lack of specificity and other methodological concerns. This review summarizes the last decade of diffusion imaging studies of healthy white matter development spanning childhood to early adulthood (4-35 years). Conclusions about anatomical location, rates, and timing of white matter development with age are discussed, as well as the influence of image acquisition, analysis, age range/sample size, and statistical model. Despite methodological variability between studies, some consistent findings have emerged from the literature. Specifically, diffusion studies of neurodevelopment overwhelmingly demonstrate regionally varying increases of fractional anisotropy and decreases of mean diffusivity during childhood and adolescence, some of which continue into adulthood. While most studies use linear fits to model age-related changes, studies with sufficient sample sizes and age range provide clear evidence that white matter development (as indicated by diffusion) is non-linear. Several studies further suggest that maturation in association tracts with frontal-temporal connections continues later than commissural and projection tracts. The emerging contributions of more advanced diffusion methods are also discussed, as they may reveal new aspects of white matter development. Although non-specific, diffusion changes may reflect increases of myelination, axonal packing, and/or coherence with age that may be associated with changes in cognition.

A multiparametric analysis of white matter maturation during late childhood and adolescence

“…While most regions and measures showed linear trends, quadratic models outperformed linear models for MD in the splenium, and NDI in all regions except the right IFOF, right CST, and splenium, however, quadratic age effects did not survive multiple comparisons. When viewed across the full developmental period, white matter maturation is nonlinear (Lebel, Treit, & Beaulieu, ), but can appear linear when considering restricted age ranges. NDI has previously been shown to be more sensitive to age‐related change than diffusion measures (Genc, Malpas, et al, ), thus NDI may be sensitive enough to developmental processes to appropriately describe nonlinear white matter development occurring during adolescence.…”

“…In all cases, FA was higher for males than females. Previous investigations of gender differences have been mixed, and many studies have identified no significant FA or MD differences between males and females (Bonekamp et al, ; Eluvathingal, Hasan, Kramer, Fletcher, & Ewing‐Cobbs, ; Giorgio et al, ; Uda et al, ), while other studies report significant gender differences in some brain regions, with inconsistent location and direction of differences (for review, see [Geeraert, Reynolds, & Lebel, in press; Lebel et al, ]). We also found an age‐by‐gender interaction for MD in the left uncinate such that MD decreased with age in boys but no relationship was observed in girls, as shown in Figure .…”

Advances in computational and statistical diffusion MRI

“…Statistical analyses of neuroimaging data enable the quantitative study of the human brain in health and disease . The mathematical characteristics of non‐scalar entities derived from dMRI data, such as the diffusion tensor (DT) or orientation distribution function (ODF), have led to exciting theoretical and computational developments.…”

Preserved white matter microstructure in adolescent patients with atypical anorexia nervosa

“…In adults, a reduction in FA due to the impact of malnutrition, dehydration, and weight loss (King, Frank, Thompson, & Ehrlich, 2017) might thus be more likely to occur compared with an increase in FA. The adolescent brain, on the other hand, is at a stage of rapid development (Lebel, Treit, & Beaulieu, 2017). The adolescent brain, on the other hand, is at a stage of rapid development (Lebel, Treit, & Beaulieu, 2017).…”

“…The adolescent brain, on the other hand, is at a stage of rapid development (Lebel, Treit, & Beaulieu, 2017). As a result, white matter undergoes complex structural and architectural changes during adolescence (Lebel et al, 2017), and increases and decreases in FA can be observed at different stages and in different structures. As a result, white matter undergoes complex structural and architectural changes during adolescence (Lebel et al, 2017), and increases and decreases in FA can be observed at different stages and in different structures.…”