Diffusion tensor and magnetization transfer MRI measurements of periventricular white matter hyperintensities in old age
Introduction
Understanding the biological bases of age-related deterioration in brain function and structure, and ameliorating their deleterious effects, is one of the most important challenges facing medical research (National Research Council, 2000). With age, the brain shrinks within the skull and this has been largely attributed to a reduction in grey matter volume (Benedetti et al., 2006, Hedden and Gabrielli, 2004). However, there is increasing evidence that the brain's white matter also changes with age. For example, a common finding on T2-weighted MRI scans of older subjects is diffuse regions of white matter signal hyperintensity located under the cortex (subcortical) and adjacent to the ventricles (periventricular), so-called ‘leukoaraiosis’ (Fazekas et al., 1987, Hachinski et al., 1987). The aetiology of these white matter hyperintensities (WMH), which are characterised by neuronal loss, demyelination and gliosis on neuropathological examination (Fazekas et al., 1993), is yet to be fully understood, but may be consequent upon small vessel disease (Basile et al., 2006, Schmidt et al., 2004). How the presence and severity of these WMH affect brain function is still a matter of active research (Deary et al., 2003, de Groot et al., 2000, Gunning-Dixon and Raz, 2000, van den Heuvel et al., 2006), but it is thought that these lesions may affect the integrity of white matter tracts connecting cortical and subcortical regions leading to a ‘disconnection syndrome’ (O'Sullivan et al., 2001, O'Sullivan et al., 2004, Shenkin et al., 2005). This and other hypotheses can be investigated using MRI methods which give quantitative information on the state of the brain's white matter, e.g. diffusion tensor MRI (DT-MRI) and magnetization transfer MRI (MT-MRI).
DT-MRI, which measures the mobility of water molecules in vivo, provides two scalar metrics of white matter integrity, namely the mean diffusivity (<D>), which measures the magnitude of water diffusion, and fractional anisotropy (FA), which indicates the directional coherence of diffusion (Basser and Pierpaoli, 1996). In regions of the brain with highly organised myelinated structures, such as the corpus callosum, water diffusion will be highly restricted and dependent on fibre direction, and so <D> will be low and FA high. Alterations in axonal microstructure will change the magnitude and directional coherence of water molecule diffusion, which will be reflected in the measured <D> and FA values. A number of studies have shown that generally <D> increases and FA decreases with normal ageing, indicating a gradual microstructural deterioration in white matter coherence (Abe et al., 2002, Nusbaum et al., 2001, Pfefferbaum et al., 2000, Pfefferbaum and Sullivan, 2003, Rovaris et al., 2003, Salat et al., 2005, Wozniak and Lim, 2006).
MT-MRI, which has proved useful in examining brain structural changes in diseases such as multiple sclerosis (MS) (Rovaris et al., 2000), dementia (van der Flier et al., 2002) and schizophrenia (Foong et al., 2001), provides an additional indicator of white matter integrity, namely the magnetization transfer ratio (MTR). This parameter measures the efficiency of the magnetization exchange between the relatively free water protons inside tissue and those bound to protein macromolecules in cellular membranes. Any pathological change in brain tissue structure that involves change in cell membrane macromolecules, such as inflammation, myelin pallor or demyelination, will cause a reduction in MTR. Thus, MT-MRI has been suggested as a complementary means of assessing white matter integrity in normal ageing (Armstrong et al., 2004, Fazekas et al., 2005, Silver et al., 1997).
In a previous study of forty healthy surviving participants of the Scottish Mental Survey of 1932 (SMS 1932), we investigated whether white matter integrity, as measured by DT- and MT-MRI, was significantly associated with cognitive ability in youth (11 years) and old age (83 years) (Deary et al., 2006). This was achieved by measuring <D>, FA and MTR in macroscopically normal-appearing white matter (NAWM) in several different brain regions and correlating these imaging parameters with tests of cognitive ability and information processing speed. Yet, although these subjects were healthy, a significant number had regions of diffuse confluent periventricular WMH (PVWMH) on T2-weighted MRI, which were avoided in the region-of-interest (RoI) analysis. However, since PVWMH are a common feature of the ageing brain, in the present analysis we measured DT- and MT-MRI parameters specifically in PVWMH in this same cohort to investigate further the biological bases of brain ageing. If DT- and MT-MRI parameters do provide complementary measures of white matter integrity, then we hypothesize that there would be significant differences between <D>, FA and MTR measured in NAWM and PVWMH, and there would be correlations between MTR and the water diffusion parameters, <D> and FA, in both NAWM and PVWMH. In other words, we expect low <D> and high FA to be associated with high MTR in healthy white matter, and high <D> and low FA to be associated with low MTR in PVWMH.
Additionally, several studies in other pathologies have investigated whether the eigenvalues (λ1, λ2 and λ3) of the apparent water diffusion tensor (D) obtained from DT-MRI can be used to differentiate dysmyelination from axonal injury (Harsan et al., 2006, Song et al., 2002, Tyszka et al., 2006). Song et al. (2002), for example, found that shiverer mice, which are characterized by incomplete myelin formation in the CNS, had increased radial diffusivity (λrad = {λ2 + λ3}/2) but similar axial diffusivity (λax = λ1) to age-matched controls. Since the axial and radial diffusivities represent water diffusion parallel and perpendicular to the axonal fibres, their results of increased cross-fibre diffusion in the presence of dysmyelination suggest that λrad may be an indicator of myelin loss and thus could have some relation to MTR. We therefore investigated whether λax and λrad are different in NAWM and PVWMH in this cohort, and if so whether PVWMH are characterized by axonal and/or myelin injury. We also determined whether there was evidence for correlations between λax and λrad and MTR in the two tissue types.
Section snippets
Subjects
Subjects were surviving participants of the SMS 1932 (Deary et al., 2006), who were involved in follow-up cognitive testing during 2004 at a mean age of 83 years. There were no selection criteria; subjects were invited to undergo brain MRI as they appeared for follow-up. All were born in 1921 and were living independently in the community. None had a history of dementia or other neurological disorders, and had no contraindications to MRI. The mini-mental state examination (MMSE) was used
Results
Seventy-one subjects were invited to participate in the study. Of these volunteers, 16 did not wish to have an MRI scan, five agreed but then later cancelled appointments, three had claustrophobia, one had a pacemaker, one had dizziness when lying flat, one was unable to lie in a supine position due to kyphosis of the upper spine, one did not complete the full examination, and one was found to have a meningioma on structural MRI. This resulted in DT- and MT-MRI data for 42 subjects (22 males
Discussion
The DT- and MT-MRI results presented above provide support for the stated hypotheses that NAWM water diffusion parameters and MTR are significantly different from those measured in PVWMH, and that these indices of white matter integrity are correlated in the ageing brain, albeit only in PVWMH and not surrounding normal white matter. In addition to being the first study to report such a correlation, this is also the first to measure axial and radial diffusivities in these two tissue types. If
Disclosure statement
All authors certify that they do not have any actual or potential conflicts of interest, including any financial, personal or other relationships with other people or organizations within 3 years of beginning this work, that could inappropriately influence (bias) this work.
Acknowledgements
Ian Deary is the recipient of a Royal Society-Wolfson Research Merit Award, which also funded the collection of phenotypic data for this study. All MRI data were collected at the SFC Brain Imaging Research Centre, University of Edinburgh (http://www.dcn.ed.ac.uk/bic). Thanks are also due to two anonymous referees who made insightful suggestions during the review process.
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