Elsevier

NeuroImage

Volume 46, Issue 2, June 2009, Pages 530-541
NeuroImage

Assessing the effects of age on long white matter tracts using diffusion tensor tractography

https://doi.org/10.1016/j.neuroimage.2009.01.068Get rights and content

Abstract

Aging is associated with significant white matter deterioration and this deterioration is assumed to be at least partly a consequence of myelin degeneration. The present study investigated specific predictions of the myelodegeneration hypothesis using diffusion tensor tractography. This technique has several advantages over other methods of assessing white matter architecture, including the possibility of isolating individual white matter tracts and measuring effects along the whole extent of each tract. The study yielded three main findings. First, age-related white matter deficits increased gradually from posterior to anterior segments within specific fiber tracts traversing frontal and parietal, but not temporal cortex. This pattern inverts the sequence of myelination during childhood and early development observed in previous studies and lends support to a “last-in-first-out” theory of the white matter health across the lifespan. Second, both the effects of aging on white matter and their impact on cognitive performance were stronger for radial diffusivity (RD) than for axial diffusivity (AD). Given that RD has previously been shown to be more sensitive to myelin integrity than AD, this second finding is also consistent with the myelodegeneration hypothesis. Finally, the effects of aging on select white matter tracts were associated with age difference in specific cognitive functions. Specifically, FA in anterior tracts was shown to be primarily associated with executive tasks and FA in posterior tracts mainly associated with visual memory tasks. Furthermore, these correlations were mirrored in RD, but not AD, suggesting that RD is more sensitive to age-related changes in cognition. Taken together, the results help to clarify how age-related white matter decline impairs cognitive performance.

Introduction

Post-mortem and in vivo studies of the structural composition of the human brain converge on the idea that aging is associated with significant changes in white matter architecture (Meier-Ruge et al., 1992; for review, see Raz, 2005, Resnick et al., 2003, Scahill et al., 2003, Tang and Nyengaard, 1997). Evidence from humans (Yakovlev and Lecours, 1967) and non-human primates (Peters et al., 2000) suggests that this deterioration is partly due to the degeneration of myelin in old age, which is a process likely to impair the conduction of neural signals across the brain. The main goal of the current study was to investigate the possible predictions of this myelodegeneration hypothesis using diffusion tensor imaging (DTI) tractography.

DTI tractography is a non-invasive imaging technique for investigating changes in white matter integrity. Whereas early neuroimaging studies of white matter and aging typically used qualitative measures of white-matter hyperintensities or quantitative analyses of white matter volume (for review, see Sullivan and Pfefferbaum, 2006, Wozniak and Lim, 2006), more recent studies have used DTI. This technique assesses the diffusion of water molecules, which is more constrained for intact than degraded white matter fibers (Concha et al., 2006, Thomalla et al., 2004). Most DTI studies of aging have focused on regions-of-interest (ROI) or clusters of voxels showing significant differences (e.g., Grieve et al., 2007, Madden et al., 2004). These methods afford a number of benefits: manual ROI volumetry is the gold standard of neuroanatomical assessment and affords a high degree of spatial precision when compared to other voxelwise methods (Kennedy et al., 2008); voxel-based morphometry (VBM; Ashburner and Friston, 2000) approaches, on the other hand, benefit from a finer spatial localizability. The contributions of both ROI- and voxel-based analyses have been critical in identifying the finding that age-related differences in white matter integrity are largely localized to the frontal cortex. However, these approaches are limited in their assessment of white matter anatomy in that a single ROI or voxel cluster (1) includes several different white matter tracts connecting any number of different cortical areas, and (2) covers only a fraction of a particular long white matter tract. Both of these limitations are addressed in diffusion tensor tractography because the tracts identified with this method can be more specific to an individual white matter tract (e.g., the uncinate fasciculus), and can assess the whole extent of a longitudinal tract. DTI tractography therefore offers not only the opportunity to map fiber tracts representative of the underlying anatomy (Burgel et al., 2006), but also allows for the ability to test specific hypotheses about age-related changes in white matter morphology along the length of specific fiber tracts. In the present study, we used a seed-based diffusion tensor tractography approach (Corouge et al., 2006, Mori and van Zijl, 2002) to investigate two predictions motivated by the myelodegeneration hypothesis.

First, we investigated the prediction that age-related white matter deficits should increase gradually from posterior to anterior brain regions. Developmental studies have shown that frontal and temporal association regions are the last ones to myelinate (Kinney et al., 1988, Sakuma et al., 1991). Given the assumption that the brain regions that mature last during development tend to decline first during aging–“last in, first out” (Raz, 2000)–one would expect that age-related white matter should be more pronounced in anterior compared to posterior brain regions. DTI studies using ROI and VBM approaches have generally reported greater age effects in frontal compared to primary posterior cortices, though age-related decline in white matter volume and integrity occurs throughout the brain (Head et al., 2004, Madden et al., 2006, Madden et al., 2007, O'Sullivan et al., 2001, Raz et al., 2005, Salat et al., 1999, Sullivan et al., 2006). While many of these previous studies have reported a general “anterior–posterior gradient” describing the pattern of age-related changes (Head et al., 2004, Madden et al., 2009, Pfefferbaum et al., 2005), this model has not been directly investigated in either voxelwise or ROI methods. We test one specific prediction of this model, in that the gradient hypothesis is specific to certain fiber systems within cerebral regions where the anterior–posterior gradient has been previously observed, namely within frontal and parietal white matter. Tractography is well-suited to isolate these fiber systems and provides a means of directly testing the question of whether the age-related differences found in these frontal regions reflects a general anterior–posterior gradient within specific tracts connecting anterior and posterior regions, or instead reflects the selective vulnerability of frontal white matter. Given the debate about whether age-related cognitive decline is primarily due to frontal dysfunction (Moscovitch and Winocur, 1992, West, 1996) or to more widespread changes in the brain (Greenwood, 2000), this is an issue with important theoretical implications. If the anterior–posterior gradient is in fact demonstrable in specific white matter tracts, age effects should increase gradually from posterior to anterior sections of each fiber tract traversing the frontal lobe association regions. In contrast, if age-related decline is specific to frontal regions, age effects should increase abruptly at the point in which the fiber tract enters the frontal lobes.

Second, we investigated the prediction that the effects of aging on white matter and their impact on cognitive performance should be stronger for radial diffusivity (RD) than for axial diffusivity (AD) measures. Evidence from post-mortem studies in primates suggests that the protracted age-related degeneration of white matter is at least partially related to changes in myelination, including increases in the number of dense inclusions, the formation of myelin balloons, or the formation of redundant myelin (Feldman and Peters, 1998, Peters and Sethares, 2002). While these morphological changes may underlie the observed age-related differences in white matter volume or integrity, in vivo evidence for myelodegeneration in humans is limited. Although most DTI studies have focused on fractional anisotropy (FA) as a summary measure of white matter integrity, there is evidence that two components of the diffusion signal, namely AD and RD, have different relations to cellular mechanisms of white matter deterioration. AD describes the principal eigenvector (λ1) and is assumed to contribute information regarding the integrity of axons (Glenn et al., 2003) or changes in extra-axonal/extracellular space (Beaulieu and Allen, 1994). In contrast, RD describes an average of the eigenvectors perpendicular to the principal direction ([λ2 + λ3] / 2) and is assumed to characterize changes associated with myelination or glial cell morphology (Song et al., 2002, Song et al., 2003, 2005). This relationship has recently been extended to humans in a study by Schmierer et al. (2004), in which a combined diffusion imaging and histological assessment of unfixed brain tissue collected post mortem from multiple sclerosis (MS) patients showed that both FA and RD, but not AD, were significant predictors of myelin content. While this direct relationship between RD and myelin has yet to be extended to healthy adults, DTI studies in healthy older adult populations have generally found greater age-related declines in the medium and minor eigenvectors, indicating a decline in radial diffusivity (Bhagat and Beaulieu, 2004, Madden et al., 2009, Sullivan et al., 2006, Sullivan et al., 2008, Vernooij et al., 2008). Furthermore, given that studies have shown that developmental maturation of white matter may primarily be driven by decreases in RD (Giorgio et al., 2008, Snook et al., 2005), it is reasonable to hypothesize that changes to white matter anatomy later in life are also a consequence of myelination, and maybe evidenced by increases in RD in fiber systems that are the latest to myelinate (Lebel et al., 2008). Thus, the myelodegeneration hypothesis predicts that age effects should be larger for RD and AD, and that these effects should be observed in all late-myelinating regions, including both frontal and temporal association cortices. Moreover, this hypothesis predicts that correlations between white matter integrity and cognitive performance in older adults should be stronger for RD than for AD measures.

In addition to testing the foregoing two predictions derived from the myelodegeneration hypothesis, the third goal of the study was to investigate the specificity of associations between the effects of aging on different white matter tracts and different cognitive measures. Given that (a) each cognitive function depends on a certain set of brain regions and corresponding white matter connections and (b) that the effects of aging across the brain show substantial individual differences (Glisky et al., 1995, Glisky et al., 2001), it is reasonable to expect that correlations between the effects of aging on white matter tracts and cognitive tasks should be specific rather than global. Examining this idea requires assessment of several different tracts and several different cognitive measures, but most previous DTI studies of aging have focused on a few white matter ROIs and a few cognitive measures (Bucur et al., 2007, Madden et al., 2004, Persson et al., 2006, Sullivan et al., 2001, Sullivan et al., 2006). Two studies investigated DTI-behavior correlations using larger set of cognitive tests (Grieve et al., 2007, O'Sullivan et al., 2001), but their conclusions regarding specificity are limited because they found significant age effects only in executive functions tests. To address this issue, we investigated cognitive performance using a standardized neuropsychological battery (Owen et al., 1996, Robbins et al., 1998) likely to yield reliable age effects on several different tasks, including tests of memory as well as executive functioning. We then correlated DTI measures and cognitive performance measures to identify tracts that were significant predictors of age-related differences in cognitive performance in older adults.

Section snippets

Participants

The participants were 20 older adults (12 female; M = 68.89 years, SD = 5.3 years,) and 20 younger adults (9 female; M = 20.04 years, SD = 2.5 years) with normal or corrected-to-normal vision, and no history of neurological or psychiatric disease. Written informed consent was obtained from each participant, and the study was approved by the Duke University Institutional Review Board. Younger adults were recruited from the Duke University community; older adults were community-dwelling individuals who

Anterior–posterior trend analysis

Fig. 2 shows age-related differences in FA (younger–older) along the length of five tracts: the genu and the splenium of the corpus callosum, the cingulum bundle (CB), the inferior longitudinal fasciculus (ILF), and the uncinate fasciculus (UF). Qualitative inspection of this figure suggests that the greatest age-related differences in FA (i.e., warmer colors in Fig. 2) occurred mainly in anterior segments of longitudinal tracts traversing the frontal lobe. To investigate the prediction that

Discussion

Our results revealed three main findings. First, age-related white matter deficits within tracts traversing frontal and parietal cortices increased gradually, not abruptly, from posterior to anterior brain regions. Second, the effects of aging on white matter structure and their impact on cognitive performance were stronger for RD than for AD measures. Finally, results revealed that the effects of aging on particular white matter tracts had an impact on specific cognitive functions; in

Conclusions

In summary, the DTI tractography findings presented here make three significant contributions to the literature characterizing age-related changes in white matter integrity. First, DTI tractography results support an anterior–posterior gradient in age-related white matter degradation within specific long-range white matter tracts traversing frontal and parietal cortex. This finding demonstrates a gradual age-related decline in white matter integrity along the anteroposterior extent of a tract,

Acknowledgments

This work was supported by a NIH grants AG19731 to RC and AG011622 to DJM. NAD was supported by NIA grant T32 AG000029. The authors would like to thank Amber Baptiste-Tarter for the assistance in participant recruitment, Jared Stokes, Vanessa A. Thomas, Matthew Emery and Jamaur Bronner for their assistance with the data collection, and Josh Bizzell and James Kragel for their analysis support.

References (102)

  • HayakawaK. et al.

    Normal brain maturation in MRI

    Eur. J. Radiol.

    (1991)
  • HusainJ. et al.

    Oligodendroglial precursor cell susceptibility to hypoxia is related to poor ability to cope with reactive oxygen species

    Brain Res.

    (1995)
  • LebelC. et al.

    Microstructural maturation of the human brain from childhood to adulthood

    Neuroimage

    (2008)
  • MaddenD.J. et al.

    Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time

    Neuroimage

    (2004)
  • MarkowitschH.J.

    Which brain regions are critically involved in the retrieval of old episodic memory?

    Brain Res. Brain Res. Rev.

    (1995)
  • PfefferbaumA. et al.

    frontal circuitry degradation marks healthy adult aging: evidence from diffusion tensor imaging

    Neuroimage

    (2005)
  • PriceG. et al.

    White matter tracts in first-episode psychosis: a DTI tractography study of the uncinate fasciculus

    Neuroimage

    (2008)
  • SmithS.M. et al.

    Accurate, robust, and automated longitudinal and cross-sectional brain change analysis

    Neuroimage

    (2002)
  • SmithS.M. et al.

    Advances in functional and structural MR image analysis and implementation as FSL

    Neuroimage

    (2004)
  • SmithS.M. et al.

    Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data

    Neuroimage

    (2006)
  • SnookL. et al.

    Diffusion tensor imaging of neurodevelopment in children and young adults

    Neuroimage

    (2005)
  • SongS.K. et al.

    Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water

    Neuroimage

    (2002)
  • SongS.K. et al.

    Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia

    Neuroimage

    (2003)
  • SongS.K. et al.

    Demyelination increases radial diffusivity in corpus callosum of mouse brain

    Neuroimage

    (2005)
  • SullivanE.V. et al.

    Diffusion tensor imaging and aging

    Neurosci. Biobehav. Rev.

    (2006)
  • SunS.W. et al.

    Selective vulnerability of cerebral white matter in a murine model of multiple sclerosis detected using diffusion tensor imaging

    Neurobiol. Dis.

    (2007)
  • TangY. et al.

    A stereological method for estimating the total length and size of myelin fibers in human brain white matter

    J. Neurosci. Methods

    (1997)
  • ThomallaG. et al.

    Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke

    Neuroimage

    (2004)
  • TripS.A. et al.

    Optic nerve diffusion tensor imaging in optic neuritis

    Neuroimage

    (2006)
  • VernooijM.W. et al.

    White matter atrophy and lesion formation explain the loss of structural integrity of white matter in aging

    Neuroimage

    (2008)
  • WakanaS. et al.

    Reproducibility of quantitative tractography methods applied to cerebral white matter

    Neuroimage

    (2007)
  • WozniakJ.R. et al.

    Advances in white matter imaging: a review of in vivo magnetic resonance methodologies and their applicability to the study of development and aging

    Neurosci. Biobehav. Rev.

    (2006)
  • XuD. et al.

    A framework for callosal fiber distribution analysis

    Neuroimage

    (2002)
  • BasserP.J. et al.

    In vivo fiber tractography using DT-MRI data

    Magn. Reson. Med.

    (2000)
  • BassettD.L.

    A Stereoscopic Atlas of Human Anatomy

    (1952)
  • BeaulieuC. et al.

    Determinants of anisotropic water diffusion in nerves

    Magn. Reson. Med.

    (1994)
  • BhagatY.A. et al.

    Diffusion anisotropy in subcortical white matter and cortical gray matter: changes with aging and the role of CSF-suppression

    J. Magn. Reson. Imaging

    (2004)
  • BucurB. et al.

    Age-related slowing of memory retrieval: contributions of perceptual speed and cerebral white matter integrity

    Neurobiol. Aging

    (2007)
  • CabezaR.

    Hemispheric asymmetry reduction in older adults: the HAROLD model

    Psychol. Aging

    (2002)
  • CurranE.J.

    A new association fiber tract in the cerebrum. With remarks on the fiber tract dissection of studying the brain

    J. Comp. Neurol.

    (1909)
  • DaselaarS.M. et al.

    Functional neuroimaging of cognitive aging

  • DaselaarS.M. et al.

    Age-related changes in hemispheric organization

  • DuboisJ. et al.

    Asynchrony of the early maturation of white matter bundles in healthy infants: quantitative landmarks revealed noninvasively by diffusion tensor imaging

    Hum. Brain. Mapp.

    (2008)
  • DuvernoyH.

    The Human Brain, Surface, Blood Supply, and Three-Dimensional Sectional Anatomy

    (1999)
  • EbelingU. et al.

    Topography of the uncinate fascicle and adjacent temporal fiber tracts

    Acta. Neurochir.

    (1992)
  • EluvathingalT.J. et al.

    Quantitative diffusion tensor tractography of association and projection fibers in normally developing children and adolescents

    Cereb. Cortex

    (2007)
  • FeldmanM.L. et al.

    Ballooning of myelin sheaths in normally aged macaques

    J. Neurocytol.

    (1998)
  • FlechsigP.

    Developmental (myelogenetic) localisation of the cerebral cortex in the human subject

    Lancet

    (1901)
  • GeulaC. et al.

    Aging renders the brain vulnerable to amyloid beta-protein neurotoxicity

    Nat. Med.

    (1998)
  • GieddJ.N. et al.

    Brain development during childhood and adolescence: a longitudinal MRI study

    Nat. Neurosci.

    (1999)
  • Cited by (371)

    View all citing articles on Scopus
    View full text