Elsevier

NeuroImage

Volume 41, Issue 3, 1 July 2008, Pages 657-667
NeuroImage

Voxel-based analysis derived from fractional anisotropy images of white matter volume changes with aging

https://doi.org/10.1016/j.neuroimage.2008.03.021Get rights and content

Abstract

Although age-related effects on brain volume have been extensively investigated post mortem and in vivo using magnetic resonance imaging (MRI), regional and temporal patterns of white matter (WM) volume changes with aging are not defined yet. The aim of this study was to assess the topographical distribution of age-related WM volume changes using a recently developed voxel-based method to obtain estimates of WM fiber bundle volumes using diffusion tensor (DT) MRI. Brain conventional and DT MRI were obtained from 84 healthy subjects (mean age = 44 years, range = 13–70). Linear and non-linear relationships between age and WM fiber bundle volume changes were tested. A negative linear correlation was found between age and WM volume decline in the corona radiata, anterior cingulum, body and crus of the fornix and left superior cerebellar peduncle. A positive linear correlation was found between age and volume increase of the right deep temporal association fibers. The non-linear regression analysis also showed age-related changes of the genu of the corpus callosum and fitted better the volume changes of the right deep temporal association fibers. WM volume decline with age is unevenly distributed across brain regions. Our approach holds promise to gain additional information on the pathological changes associated to neurological disorders of the elderly.

Introduction

Age-related effects on the volume of the human brain tissues have been extensively studied both at post mortem (Rees, 1976, Meier-Ruge et al., 1992, Kemper, 1994, Aboitiz et al., 1996, Pakkenberg and Gundersen, 1997, Tang et al., 1997, Marner et al., 2003) and in vivo using magnetic resonance imaging (MRI) (Sowell et al., 2004, Raz and Rodrigue, 2006). The most shared hypothesis is that grey matter (GM) volume declines linearly with age (Sowell et al., 2004, Raz and Rodrigue, 2006), while white matter (WM) volume essentially remains steady or increases slowly through adulthood, peaking at the 40–50 year range (Courchesne et al., 2000, Bartzokis et al., 2001, Bartzokis et al., 2004, Jernigan et al., 2001, Ge et al., 2002, Allen et al., 2005, Fotenos et al., 2005, Walhovd et al., 2005), followed by a precipitous decline starting around 60 years of age (Guttmann et al., 1998, Salat et al., 1999, Courchesne et al., 2000, Bartzokis et al., 2001, Bartzokis et al., 2004, Jernigan et al., 2001, Ge et al., 2002, Liu et al., 2003, Allen et al., 2005, Fotenos et al., 2005, Walhovd et al., 2005).

The topographic patterns of age-related GM decline have been investigated using both global and regional MR-based approaches (Sowell et al., 2004, Raz and Rodrigue, 2006), whereas the actual topographic distribution of WM changes with aging is still controversial (Raz and Rodrigue, 2006). The remarkable heterogeneity between studies regarding WM volume changes with aging might be due to at least three reasons. First, these studies differ in the sample size and age ranges studied. In this context, the inclusion of adolescents should serve to clarify the impact of ongoing progressive volume changes that can be thought of as continuous with brain maturational effects (Sowell et al., 1999, 2002, 2004). This is particularly important for those WM fiber bundles that post mortem (Yakovlev and Lecours, 1967, Benes et al., 1994, Kemper, 1994) and in vivo MRI (Jernigan et al., 1991, Pfefferbaum et al., 1994, Reiss et al., 1996, Giedd et al., 1999, Courchesne et al., 2000, Bartzokis et al., 2001, Bartzokis et al., 2004, Sowell et al., 2002) studies have shown to progressively increase in size throughout childhood and into young adulthood. Second, the lack of a correlation between subjects’ age and whole WM volume might relate to an uneven distribution of WM loss across different brain regions (Salat et al., 1999, Bartzokis et al., 2001, Bartzokis et al., 2004, Jernigan et al., 2001, Allen et al., 2005, Lemaitre et al., 2005, Walhovd et al., 2005, Abe et al., 2008, Brickman et al., 2007, Smith et al., 2007). As a consequence, these regional changes might go undetected when using a global approach (Good et al., 2001, Sullivan et al., 2004, Abe et al., 2008, Agosta et al., 2007, Smith et al., 2007). Third, in spite of the optimization of methods to map GM density (Good et al., 2001), a careful standardization of MRI methods to assess WM morphometry is still lacking. To date, the majority of the studies evaluating age-related WM volume regional changes (Salat et al., 1999, Bartzokis et al., 2001, Jernigan et al., 2001, Good et al., 2001, Sato et al., 2003, Taki et al., 2004, Tisserand et al., 2004, Allen et al., 2005, Lemaitre et al., 2005, Walhovd et al., 2005, Abe et al., 2008, Brickman et al., 2007, Smith et al., 2007) were based on sequences and post-processing algorithms used for GM volumetry assessment, which may not represent the best approach to image the well-known pathological heterogeneity of the WM (Sullivan and Pfefferbaum 2006).

Diffusion tensor (DT) MRI is a non-invasive method which is sensitive to features of tissue microstructure, such as axonal density and axonal fiber orientational coherence. Diffusion is anisotropic in WM, and DT-derived maps allow to visualize anisotropic structures that are consistent with the anatomy of the major WM fiber bundles (Pierpaoli et al., 1996). Recently, we developed a voxel-based (VB) method to obtain estimates of WM fiber bundles volumetry using DT MRI (Pagani et al., 2007). Such an approach, which provides an index of atrophy derived from the transformation between a fractional anisotropy (FA) atlas (resuming average morphometry of a reference population) and individual subjects FA maps, has been shown to be sensitive to fiber bundles volume changes related to disease (Pagani et al., 2007).

Against this background, the aim of this study was to investigate the age-related changes of WM fiber bundles volumes at a VB resolution, using DT MRI obtained from a large sample of healthy subjects, spanning six decades of life. Since there is recent evidence that WM changes with aging may not be linear (Courchesne et al., 2000, Bartzokis et al., 2001, Bartzokis et al., 2004, Jernigan et al., 2001, Ge et al., 2002, Allen et al., 2005, Walhovd et al., 2005), we also tested for non-linear effects in the age-functions observed.

Section snippets

Subjects

We studied 84 healthy volunteers (36 women and 48 men, mean age = 44 years, range = 13–70 years), with no previous history of neurological dysfunction and a normal neurological exam. Eighty-one subjects (96.4%) were right-handers and three subjects (3.6%) were left-handers, according to the Edinburgh Handedness Questionnaire (Oldfield, 1971). All subjects had normal Mini-Mental State Examination scores (Folstein et al., 1975), after correction for age and education. All subjects were assessed

Results

One or more WMHs were seen on the T2-weighted MRI scans from 31 subjects (37%). Mean WMH loads per each age year decade are reported in Table 1. The characteristics of the brain lesions were always consistent with those of non-specific changes in the WM. No other major abnormalities such as infarct, vascular malformation, or tumor were found.

Table 2 reports parameter estimates of regressor equations, cluster sizes (i.e., the number of contiguous voxels passing the height threshold), F values,

Discussion

Previous reports on the relationship between age and brain WM volume changes have provided conflicting results, since some studies have reported a decrease in WM volume with aging (Guttmann et al., 1998, Salat et al., 1999, Courchesne et al., 2000, Bartzokis et al., 2001, Bartzokis et al., 2004, Jernigan et al., 2001, Ge et al., 2002, Liu et al., 2003, Allen et al., 2005, Fotenos et al., 2005, Lemaitre et al., 2005, Walhovd et al., 2005, Abe et al., 2008, Benedetti et al., 2006, Brickman et

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