ReviewA review of diffusion tensor imaging studies in schizophrenia
Introduction
While a great deal of progress has been made in delineating gray matter abnormalities in schizophrenia using magnetic resonance imaging (MRI) (for a review see Shenton et al., 2001), far less progress has been made in evaluating white matter abnormalities, or in evaluating white matter fiber tracts interconnecting brain regions, particularly those that connect the frontal and temporal lobes, tracts that have long been thought to be abnormal in schizophrenia (e.g., Wernicke, 1906, Kraepelin, 1919/1971).
Of particular note, unlike studies of gray matter, MR structural studies of white matter have not been as informative. More specifically, only a small number of MRI studies have evaluated white matter volume differences between patients with schizophrenia and controls, and these findings have been largely negative (e.g., Suddath et al., 1990, Wible et al., 1995). Moreover, in one of the few studies reporting white matter volume reduction in schizophrenia, Breier and coworkers (Breier et al., 1992) noted a correlation between prefrontal white matter reduction and amygdala–hippocampal complex volume reduction, thus highlighting the potential importance of frontal–temporal interactions in schizophrenia. More recently, two studies using voxel-based analyses have shown white matter abnormalities in both temporal and frontal lobe regions (Sigmudsson et al., 2001), and bilaterally in the frontal lobe (Paillere-Martinot et al., 2001).
There are also only a few post-mortem studies of white matter in schizophrenia, and these findings, similar to the MRI findings, are inconclusive. Specifically, two recent studies report decreased fiber number and density in the anterior commissure and the corpus callosum in women but not in men with schizophrenia (Highley et al., 1999a, Highley et al., 1999b), and no differences in the number and density of fibers in the uncinate fasciculus (Highley et al., 2002). There is also growing evidence to suggest that glial cells, particularly oligodendrocytes, which form myelin sheaths around axons, are abnormal in schizophrenia (Hakak et al., 2001, Uranova et al., 2001, Uranova et al., 2004). For example, Hakak et al. study reported abnormal expression of myelin related genes in schizophrenia, which suggests a disruption in oligodendrocyte function. Furthermore, Uranova et al. (2001) study, using electron microscopy, showed both qualitative and quantitative abnormalities in post-mortem brains of schizophrenics in the oligodentroglia in the prefrontal cortex and caudate nucleus, including a marked increase in the density of concentric lamellar bodies (indicating damage to myelinated fibers) in the caudate nucleus in post-mortem brains of patients diagnosed with schizophrenia, as well as decreased density of the oligodendrocytes in layer IV of the prefrontal cortex in schizophrenia (Uranova et al., 2004). In another study, Hof et al. (2003) found decreased oligodendrocyte number and density in layer III of Brodmann area 9 and in gyral prefrontal white matter in schizophrenia.
In addition, Benes’ (1993) work suggests delayed myelination in the prefrontal cortex in patients with schizophrenia. Importantly, if glial dysfunction is confirmed in schizophrenia, this alone could explain abnormal neuronal cytoarchitecture and functional deficits including functional fronto-temporal disconnections observed in schizophrenia (see also the recent review of white matter in schizophrenia by Davis et al. (2003). Finally, Akbarian et al. (1996) reported a maldistribution of the interstitial neurons in both prefrontal and temporal white matter in schizophrenia brains. The observed altered neuronal distributions in both prefrontal and temporal lobe regions suggested to these investigators that neurodevelopmental abnormalities were present in at least a subgroup of patients, and that such abnormalities could alter the connectivity of these brain regions.
Taken together, these studies serve to underscore the importance of evaluating white matter fiber tract abnormalities in schizophrenia.
Below, we provide a brief review of the principles of DTI, including some of the different measures employed, followed by a review of the findings to date in schizophrenia. For the selection of published DTI studies in schizophrenia, we used PubMed and Medline, where we used the key words diffusion tensor imaging and schizophrenia. We end with a review of future applications of DTI techniques to schizophrenia, which will likely further our understanding of the neuropathology of schizophrenia.
Section snippets
The theory behind diffusion tensor imaging
One of the main reasons for inconsistent findings regarding white matter abnormalities in schizophrenia is the difficulty in evaluating this brain compartment using conventional MRI. This is primarily because white matter appears homogeneous in conventional MRI, as this methodology is not sensitive to discerning fiber tract direction and/or organization. In contrast, recently, diffusion tensor MRI techniques have been developed which have proven to be useful in the evaluation of different white
Acquisition of diffusion tensor images in the brain
In order to detect water diffusion along different directions, Stejskal and Tanner (1965) method is used. This method uses two strong gradient pulses, symmetrically positioned around a refocusing pulse, allowing for diffusion weighting. To eliminate the dependence of spin density, T1 and T2, at least two measurements of diffusion-weighting must be obtained, that are differently sensitized to diffusion but remain identical in all other respects.
As noted previously, in order to correctly assess
Quantitative representation of diffusion tensor
Data from diffusion tensor imaging can be analyzed in several ways. The most general approach is to characterize the overall displacement of the molecules (average ellipsoid size) by calculating the mean diffusivity. To do so, the trace (Tr) (Basser, 1995) of the diffusion tensor, which is calculated as the sum of the eigenvalues of the tensor, has been introduced. The mean diffusivity is then given by Tr(D)/3.
To describe the anisotropy of diffusion, several scalar indices have been introduced.
Applications of DTI to schizophrenia research
As noted previously, based on geometry and the degree of anisotropy loss, white matter tract alterations, such as dislocation, disruption or disorganization can be documented. The cross-sectional size of these pathways, as well as diffusion anisotropy measured within the bundle, yield a quantitative measure of connectivity between different brain regions. In fact, the tissue properties of white matter fiber tracts, including the density of the fibers, the fiber diameter, the thickness of the
DTI schizophrenia findings
In order to compare diffusion anisotropy between control subjects and schizophrenics, most studies reported in the literature have used fractional anisotropy (FA). Only one study has used relative anisotropy (RA), (Buchsbaum et al., 1998) and only one study has used inter-voxel coherence as an index of diffusion (Kalus et al., 2004). In comparison with FA, RA maps show lower visual contrast between white and gray matter areas of the brain, since RA tends to be less sensitive to anisotropy
Implications, conclusions and future directions
Preliminary DTI results, data from other MR techniques, such as magnetization transfer techniques and MR relaxation measurements (both sensitive to the myelin abnormalities), as well as MR spectroscopy (measuring neuronal markers), in combination with pathomorphological data, all suggest that white matter pathways play an important role in the neuropathology of schizophrenia, and are likely related to the myriad of clinical symptoms observed in this disorder. DTI findings to date are
Acknowledgments
The authors thank Marie Fairbanks for her administrative assistance. They also gratefully acknowledge the support of the National Alliance for Research on Schizophrenia and Depression (MK), the National Institute of Health (R03 MH068464-01 to MK, K02 MH 01110 and R01 MH 50747 to MES, R01 NS 39335 to SEM and R01 MH 40799 to RWM), the Post-doctoral Fellowship Program of Korea Science and Engineering Foundation (KOSEF) (HJP), the Department of Veterans Affairs Merit Awards (MES, RWM), and the
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