Voxel-based morphometry of unilateral temporal lobe epilepsy reveals abnormalities in cerebral white matter

www.elsevier.com/locate/ynimg NeuroImage 23 (2004) 167 – 174

Voxel-based morphometry of unilateral temporal lobe epilepsy reveals abnormalities in cerebral white matter Alan B. McMillan, a,* Bruce P. Hermann, b Sterling C. Johnson, c Russ R. Hansen, b Michael Seidenberg, d and Mary E. Meyerand e a

Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53706, USA Department of Neurology, University of Wisconsin-Madison, Madison, WI 53706, USA c VA Medical Center and Department of Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA d Department of Psychology, Chicago Medical School, North Chicago, IL 60064, USA e Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53706, USA b

Received 16 January 2004; revised 22 April 2004; accepted 5 May 2004

Voxel-based morphometric (VBM) investigations of temporal lobe epilepsy have focused on the presence and distribution of gray matter abnormalities. VBM studies to date have identified the expected abnormalities in hippocampus and extrahippocampal temporal lobe, as well as more diffuse abnormalities in the thalamus, cerebellum, and extratemporal neocortical areas. To date, there has not been a comprehensive VBM investigation of cerebral white matter in nonlesional temporal lobe epilepsy. This study examined 25 lateralized temporal lobe epilepsy patients (13 left, 12 right) and 62 healthy controls in regard to both temporal and extratemporal lobe gray and white matter. Consistent with prior reports, gray matter abnormalities were evident in ipsilateral hippocampus and ipsilateral thalamus. Temporal and extratemporal white matter was affected ipsilateral to the side of seizure onset, in both left and right temporal lobe epilepsy groups. These findings indicate that chronic temporal lobe epilepsy is associated not only with abnormalities in gray matter, but also with concomitant abnormalities in cerebral white matter regions that may affect connectivity both within and between the cerebral hemispheres. D 2004 Elsevier Inc. All rights reserved. Keywords: Voxel-based morphometry; Temporal lobe epilepsy; White matter; Gray matter

Introduction The majority of traditional region-of-interest-based quantitative volumetric magnetic resonance (MR) imaging studies in temporal lobe epilepsy have focused on neural regions involved in the genesis and propagation of seizures. Volumetric abnormalities (atrophy) are evident in hippocampus (Jack et al., 1992; Quigg et al., 1997; Tasch et al., 1999; Woermann et al., 1998), associated

* Corresponding author. Department of Medical Physics, University of Wisconsin-Madison, 1530 Medical Sciences Center, 1300 University Avenue, Madison, WI 53706. Fax: +1-608-265-9840. E-mail address: [email protected] (A.B. McMillan). Available online on ScienceDirect (www.sciencedirect.com.) 1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2004.05.002

mesial temporal lobe structures including amygdala (Kalviainen et al., 1997; Martin et al., 1999), fornix (Kuzniecky et al., 1999; Martin et al., 1999), and entorhinal cortex (Bernasconi et al., 1999); as well as thalamus and basal ganglia (DeCarli et al., 1998). In addition, atrophy has been reported in extrahippocampal temporal lobe regions (Moran et al., 2001) and extratemporal areas such as the cerebellum (Bohnen et al., 1998; Lawson et al., 2000a,b; Sandok et al., 2000). Considerably fewer quantitative MR studies of temporal lobe epilepsy have examined whole brain volumes or volumes of extratemporal gray or white matter, but the findings to date suggest that abnormalities in brain structure extend well outside the neuronal networks responsible for seizure generation and propagation. Sisodiya et al. (1997) described widespread occult structural abnormalities occurring in visually normal appearing MRIs in 27 patients with hippocampal sclerosis. Marsh et al. (1997) reported significant bilateral volumetric reductions in frontoparietal regions in 14 males with temporal lobe epilepsy. Lee et al. (1998) reported reduced whole brain volume in 27 patients with temporal lobe epilepsy, and Theodore et al. (2003) recently described reduced whole brain volume in patients with temporal lobe epilepsy with a history of complex febrile convulsions. Comparing patients with temporal lobe epilepsy (n = 58) to healthy controls (n = 62), we recently reported that significant volumetric reductions were particularly evident in cerebral white matter, both ipsilateral and contralateral to the side of temporal lobe seizure onset (Hermann et al., 2003a). Closer examination of the corpus callosum in patients with chronic temporal lobe epilepsy revealed significant volumetric reduction of this major white matter tract (Hermann et al., 2003b), as well as lower diffusion anisotropy and higher diffusivity in directions perpendicular to the axons on DTI (Arfanakis et al., 2002). However, much remains to be clarified regarding the nature and distribution of abnormalities suggested by region-of-interest-based approaches. For instance, the distribution of white matter abnormality within and between lobar regions of interest remains unclear. In addition, many specific and important gray matter structures (such as the thalamus) are not routinely quantified in standard lobar-based segmentation pro-

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grams, and potential differences in the patterns of white or gray matter abnormality remain to be determined. Voxel-based morphometry (VBM) is a technique used to examine regional morphological differences in gray or white matter between groups. Methods of VBM have been described that include an automated approach to the distribution and localization of whole-brain morphometric abnormalities that are less restricted to the limitations associated with traditional region of interest approaches (Good et al., 2001). To date, VBM studies of temporal lobe epilepsy have focused on gray matter abnormalities (Keller et al., 2002a,b; Woermann et al., 1999), and no investigation has examined the presence or distribution of abnormalities in white matter using VBM. The purpose of this investigation is to comprehensively characterize the distribution of abnormalities in gray and white matter in patients with unilateral temporal lobe epilepsy. As will be demonstrated, abnormalities in cerebral white matter in unilateral temporal lobe epilepsy were significant, affected temporal and extratemporal regions ipsilateral to the side of seizure onset, and were equal in magnitude to abnormalities detected in gray matter.

Table 1 Demographic and clinical information of study groups

Age (years) Years of education IQ Onset age (years) Duration (years)

Group

Mean

SD

Control Epilepsy Control Epilepsy Control Epilepsy Epilepsy Epilepsy

32.42 32.23 13.68 12.96 107.67 96.42 11.95 19.09

12.181 11.198 2.418 2.289 13.812 15.256 9.072 12.341

Image acquisition Images were obtained on a 1.5-T GE Signa MR scanner. For each subject, a T1-weighted, three-dimensional SPGR image was acquired with the following parameters: TE = 5, TR = 24, NEX = 2, flip angle = 40j, slice plane = coronal, matrix size = 256  192, FOV = 26 cm, slice thickness = 1.5 mm. Voxel-based morphometry

Methods Subjects Subjects were patients with temporal lobe epilepsy (n = 25, 13 unilateral left TLE, 12 unilateral right TLE) and healthy controls (n = 62). Selection criteria for epilepsy patients included the following: (a) chronological age from 14 to 60 years, (b) complex partial seizures of unilateral temporal lobe origin demonstrated by ictal EEG monitoring of spontaneous seizures, (c) absence of MRI abnormalities other than atrophy on clinical reading, and (d) no other neurological disorder. The majority of these patients were candidates for anterior temporal lobectomy and as such underwent a series of procedures including FDG-PET, Wada Test, neuropsychological assessment, and extensive EEG monitoring of spontaneous seizures with scalp or more invasive (e.g., subdural strip or grid electrodes, depending on the details of the case as decided by a multidisciplinary team). Patients with bilateral independent left and right temporal lobe seizure onset were excluded from the study. The subjects investigated here demonstrated consistent unilateral temporal lobe onset of their typical complex partial seizures. Selection criteria for healthy controls included the following: (a) chronological age from 14 to 60, (b) either a friend or family member of the patient, (c) no current substance abuse, medical, or acute psychiatric condition that could affect cognitive functioning, and (d) no history of loss of consciousness >5 min or developmental learning disorder. Table 1 provides sociodemographic and clinical features of the subjects. As can be seen, the groups were equivalent in age and education, while the epilepsy patients had significantly lower Full Scale IQ. The epilepsy patients suffered from chronic epilepsy (mean duration = 19.1 years) of childhood onset (mean onset age = 11.9 years). The left and right temporal lobe groups were not significantly different in chronological age, duration of epilepsy, or Full Scale IQ. The left temporal lobe group had significantly (P = 0.02) less formal education than the right temporal lobe group (11.9 versus 14.2 years).

Analysis was performed on a workstation running MATLAB 6.5 (The Mathworks, Inc., Natick, MA) and the statistical parametric mapping software SPM2 (Wellcome Department of Cognitive Neurology, London, UK). The methodology used closely parallels that of Good et al. (2001). Before the creation of a study-specific template and morphometric analysis, each image was visually inspected to ensure that its orientation was compatible with SPM2, its origin centered on the anterior commissure, and free of image artifacts. This was accomplished using the MRIcro software package (Rorden and Brett, 2000). Template creation To allow for group comparison, voxel-based morphometry registers each MR image to a standard template (spatial normalization) before the image is automatically segmented into gray and white matter components (Ashburner and Friston, 2000). While it has been noted that the use of templates derived from the study population has been shown to have insignificant consequences on the quality of spatial normalization (Salmond et al., 2002) when compared to the templates included with the SPM software, VBM studies have used templates created from the study population or a subset thereof to improve the quality of the segmentation step (e.g., Good et al., 2001; Karas et al., 2003; Ru¨sch et al., 2003). Thus, study-specific templates for whole brain volumes, gray matter, and white matter were created. To accomplish this, images were first segmented and spatial normalization parameters were calculated to best match the segmented gray matter image to the SPM gray matter template image. The whole brain image was then spatially normalized using these calculated parameters and automatically segmented into gray matter, white matter, and CSF. Note that the templates were spatially normalized only to the default gray matter template so that the resultant template images are complementary between gray matter, white matter, and CSF compartments. Normalizing each image to the respective gray and white matter template image is performed in subsequent processing of the images, but at this stage would have likely resulted in non-overlapping spatial normalization between respective gray and white matter images. The respective template images were formed from the average voxel

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intensity for each segmented image for all subjects in the study and smoothed with an 8-mm full width at half maximum (FWHM) Gaussian kernel.

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Table 2 Locations of local maximum of volume decreases in gray matter VBM analysis significant at P < 0.05, corrected for multiple comparisons Location

Image preprocessing Similar to the template creation step, the images were spatially normalized to the same coordinate system before group comparison. Each image was first segmented and spatial normalization parameters were calculated for the segmented gray matter image from the created gray matter template. Because accurate spatial normalization is crucial for VBM, spatial normalization parameters for the segmented white matter image were calculated from the created white matter template. Each whole brain image was then spatially normalized for each set of normalization parameters obtained from the previous step and automatically segmented into gray and white matter components, where the respective images normalized to the specific template were used in analysis (i.e., gray-matter-template-normalized images were used for gray matter analysis and white-matter-template-normalized images were used for white matter analysis). To account for the different spatial normalization parameters applied to each image, as individual voxels were either shrunk or stretched, the voxel intensities were multiplied by the Jacobian determinates from the spatial normalization parameters (Ashburner and Friston, 2000). In previous VBM methods, this process has been named modulation (Good et al., 2001). The resulting gray and white matter images were smoothed with a 12-mm FWHM Gaussian kernel. Statistical analysis To eliminate voxels outside of the volume of interest (i.e., gray or white matter), the images were masked before analysis so that voxels of noninterest (e.g., regions corresponding to white matter and CSF in a gray matter mask) were not included in statistical calculations. Masks were created from the study template images. A gray matter mask was created where voxels in the complementary image compartments (white matter and CSF) were removed from the mask. Nonzero voxels from the white matter and CSF template images with intensity greater than or equal to the mean intensity plus one standard deviation from the respective white matter and CSF templates were then removed from the gray matter template image. Upon smoothing with a small diameter Gaussian kernel, the statistical comparisons were confined to an area more inclusive of the gray matter volume. A white matter mask was created and applied in a similar manner. The mask images are shown in Fig. 1. To compare groups, analysis of covariance (ANCOVA) was performed using the total volume of each segmented image after modulation, with age and gender as confounding covariates for the

Left TLE GM < controls

Right TLE GM < controls

33 12 22 27 28 29 22 41 3 5 43 11 28 11 11 57 10 57 55 4 10 8

3 35 32 50 52 55 27 2 24 37 25 6 35 2 8 18 7 14 12 38 42 4

34 9 20 3 1 2 21 30 35 9 11 12 13 14 10 10 8 12 14 31 55 8

Size (voxels)

t

P (FDR corrected)

12,140 1260 105 339 76 1 1 16,181 262 475 171 14 141 2 2 2 5 3 1 1 1 1

5.7 4.82 3.8 3.75 3.65 3.4 3.39 5.47 4.06 3.83 3.73 3.67 3.65 3.64 3.5 3.45 3.42 3.41 3.34 3.32 3.31 3.31

0.003 0.004 0.019 0.022 0.027 0.047 0.048 0.001 0.008 0.014 0.019 0.021 0.022 0.023 0.032 0.036 0.039 0.039 0.046 0.048 0.049 0.049

respective gray and white matter analyses. Total volume of each segmented and modulated image before smoothing was used to investigate regional volume changes beyond global gray or white matter changes. Both left and right temporal lobe epilepsy groups were incorporated as separate groups into the same statistical model because it was expected that differences in temporal lobe epilepsy laterality added more information to the statistical model. Using SPM2, t-statistic maps were created for each voxel in the standard atlas space to reflect differences in gray and white matter for the lateralized (left and right) groups. Resultant t-statistic maps were thresholded at a P-value of <0.05 corrected for multiple comparisons using the False Discovery Rate approach (Genovese et al., 2002).

Results Gray Matter Table 2 details the regions of gray matter volume decrease that were apparent at P < 0.05, corrected for multiple comparisons

Fig. 1. Example of template image used to mask input images. The gray matter mask is shown in green and the white matter mask is shown in red. Note that overlap exists between gray and white matter masks, as the purpose is to restrict the respective analysis to regions more representative of gray or white matter.

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across the entire search volume. Cluster size is included for reader convenience, but all inferences are drawn from voxelwise tests. Additionally, results will be discussed in relation to their voxelwise correspondence with anatomical structures. While presented in tables for completeness, results indicating volume differences of only a few voxels are difficult to interpret and will not be discussed in detail. Fig. 2 depicts areas of decreased gray and white matter volume in the left and right temporal lobe groups. As can be seen in Fig. 3, left temporal lobe epilepsy patients exhibited significant abnormalities relative to controls in the thalamus (both ipsilateral and contralateral to side of seizure onset) and ipsilateral hippocampus. The left temporal lobe epilepsy group did not exhibit significant regions of increased gray matter volume with respect to the controls. The right temporal lobe epilepsy group exhibited decreased gray matter volume in the ipsilateral thalamus and abnormalities near the ipsilateral hippocampus. The right temporal lobe epilepsy group also did not exhibit significant regions of increased gray matter volume in comparison to the controls. White matter Table 3 details the white matter volume decreases for left and right TLE groups apparent at P < 0.05, corrected for multiple comparisons across the entire search volume. In addition to Fig. 2, Fig. 4 provides a detailed depiction of decreased white matter volume in the left and right TLE groups. As can be seen, temporal lobe epilepsy patients exhibited a marked white matter volume

decrease predominantly focused in ipsilateral temporal pole white matter. This volume loss extends extratemporally to bilateral prefrontal white matter in the left temporal lobe epilepsy group, affecting voxels in the corpus callosum of both left and right TLE groups, and the fornix of the right TLE group. The left temporal lobe epilepsy group did not exhibit areas of increased white matter volume compared to the controls. A significant amount of white matter increase was found in the right TLE group in the right hemisphere near the parietal – occipital fissure. However, the voxels in this region are predominantly gray matter, likely due to misregistration of tissue during the automated segmentation, and therefore discounted from further inference.

Discussion This report confirms and extends previous findings concerning structural brain abnormalities observed in patients with unilateral temporal lobe epilepsy. In addition, an extensive degree of temporal lobe white matter abnormality is demonstrated. These findings, their implications, potential significance, and the limitations of this investigation are reviewed in the material to follow. Gray matter abnormalities Overall, the VBM gray matter findings observed in this study complement previously reported abnormalities in patients with

Fig. 2. VBM results at P < 0.05, corrected for multiple comparisons. Top left, regions of gray matter volume reduction for left TLE group; top right, regions of gray matter volume reduction for right TLE group; bottom left, regions of white matter volume reduction for left TLE group; bottom right, regions of white matter volume reduction for right TLE group.

A.B. McMillan et al. / NeuroImage 23 (2004) 167–174 Table 3 Locations of local maximum of volume decreases in white matter VBM analysis significant at P < 0.05, corrected for multiple comparisons Location Left TLE WM < controls

Right TLE WM < controls

9 9 3 46 11 54 32 33 24 25 26 32

25 14 24 48 25 8 20 17 19 16 18 23

9 5 17 61 10 16 13 16 8 8 8 10

Size (voxels)

t

P (FDR corrected)

8739 724 2 1 7957 41 8 10 1 1 1 1

5.27 3.94 3.7 3.61 5.63 3.75 3.72 3.69 3.69 3.67 3.67 3.66

0.01 0.027 0.041 0.048 0.003 0.039 0.042 0.044 0.044 0.047 0.047 0.048

chronic temporal lobe epilepsy using either region-of-interestbased quantitative MRI or VBM. Prior VBM investigations of gray matter in temporal lobe epilepsy have shown slightly different results, possibly due to variations in methodology used, mainly in that other VBM methods in TLE have not included a modulation step (Keller et al., 2002a,b; Woermann et al., 1999). In methods including a modulation step, the statistical output represents a region of significant volume change. Analysis of unmodulated data yields regions of significant concentration differences (Ashburner and Friston, 2000). In a group comparison of 10 patients with left TLE and evident hippocampal sclerosis versus controls, Woermann et al. (1999) detected an increase in temporal lobe gray matter concentration hypothetically implicated by disorganized gray matter and underlying white matter changes. Additionally, no significant differences were detected in a comparison of a group of 10 patients with left TLE and normal appearing MRI. Keller et al. (2002a) detected gray matter concentration decreases in the ipsilateral hippocampus of patients with measured left and right hippocampal atrophy with dispersed effects throughout the cortex, most notably in the prefrontal cortex. Regions of gray matter concentration increase were reported in the cingulate gyrus, ipsilateral hippocampal regions, and cerebellum; again, these increases were hypothesized to be resultant of decreased distinction between gray and white matter and more representative of white matter abnormalities. Further studies demonstrated decreases in gray matter concentration in ipsilateral hippocampus, thalamus, and cerebellum, with dispersed neocortical effects across frontal, parietal, and occipital lobes in relation to left or right temporal lobe seizure origin (Keller et al., 2002b). These VBM reports of gray matter concentration decrease complement previous region-of-interest-based quantitative volumetric MRI studies in which abnormalities have been reported in the hippocampus (Jack et al., 1992; Quigg et al., 1997; Tasch et al., 1999; Woermann et al., 1998), amygdala (Kalviainen et al., 1997; Martin et al., 1999), fornix (Kuzniecky et al., 1999; Martin et al., 1999), entorhinal cortex (Bernasconi et al., 1999), thalamus (DeCarli et al., 1998; Natsume et al., 2003), basal ganglia (Dreifuss et al., 2001), extrahippocampal temporal lobe regions (Moran et al., 2001), and extratemporal areas such as the cerebellum (Bohnen et al., 1998; Ney et al., 1994; Sandok et al., 2000; Specht et al., 1997). Additionally, these VBM reports acknowledge a possible white matter effect in

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temporal lobe epilepsy, which will be discussed further in the following section. As demonstrated here, volume decreases in the hippocampus are more defined for the left TLE group; however, voxels in brain regions near the hippocampus of the right TLE group do indicate a volume decrease. An analysis of the effect at an uncorrected threshold (P < 0.001) indicated a larger underlying effect throughout the spatial extent of the hippocampus similar to the findings in the left TLE group. Furthermore, a large hippocampal effect was not necessarily expected because the epilepsy subjects were selected on the basis of EEG criteria (i.e., consistent unilateral temporal lobe onset of seizures), not neuropathological criteria (i.e., hippocampal volume loss or sclerosis). Recent VBM publications have also hypothesized that large degrees of smoothing with respect to smaller structures like the hippocampus may cause expected structural differences to remain undetected by VBM (White et al., 2003). In addition, volume increases in gray matter were not expected. The subjects chosen for this study exhibited no lesions or MRI abnormalities resultant from cortical dysplasias. Finally, especially striking was the significant impact on the thalamus in both the left and right TLE groups. As noted, decreased thalamic volume has been reported previously in region-of-interest-based quantitative MRI investigations (DeCarli et al., 1998; Natsume et al., 2003). The robustness of the effect across imaging techniques and the relative magnitude of the abnormality in the thalamus in this investigation certainly suggests that further attention should be devoted to the etiology and clinical consequences of comorbid thalamic abnormality. White matter abnormalities An important finding of this investigation is the presence, degree, and distribution of white matter abnormalities in unilateral temporal lobe epilepsy (see Table 3; Figs. 2 and 4). White matter abnormalities were marked in both the left and right temporal lobe epilepsy groups. The distribution of these abnormalities included not only the ipsilateral temporal lobe, but also bilaterally in the frontal and parietal lobes in the left TLE group. Further, discrete white matter tracks such as the corpus callosum were affected and additionally the fornix in the right TLE group. These patterns of white matter abnormality were seen in both the right and left temporal lobe epilepsy groups. Using traditional region-of-interest-based quantitative MRI, our group has reported significant reductions in cerebral white matter in TLE (Hermann et al., 2003a). Among patients with unilateral temporal lobe onset, reductions in white matter volumes are detected in temporal as well as extratemporal regions (frontal and parietal) and are also evident contralaterally in the same regions (temporal, frontal, and parietal), but the volume loss is significantly greater ipsilateral to the side of seizure onset. In the future, we plan to directly compare and contrast the abnormalities identified in the same cohort of TLE patients using both VBM and traditional regionof-interest quantitative MRI volumetrics. Additionally, our group has applied diffusion tensor imaging (DTI) to the corpus callosum in TLE. Increased diffusion perpendicular to the axons was apparent indicating compromised axonal structure in the anterior corpus callosum, posterior corpus callosum, and the external capsule (Arfanakis et al., 2002). Other studies using DTI in temporal lobe epilepsy have indicated an abnormality in temporal lobe white matter. For example, Rugg-

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Fig. 3. VBM results at P < 0.05, corrected for multiple comparisons indicating gray matter volume decrease. (a) Left thalamus in left TLE group, (b) coronal slice showing bilateral thalamic volume reduction and ipsilateral hippocampus in left TLE group, (c) hippocampus in left TLE group, (d), and (e) right thalamus in right TLE group.

Gunn et al. (2001) reported decreased diffusion anisotropy in the left temporal lobes of patients with left TLE. Similar results were recently reported by Assaf et al. (2003), 12 TLE patients exhibited decreased diffusion anisotropy in the hippocampal region ipsilateral to side of seizure onset compared to the contralateral side. The findings reported here represent the first depiction of these ipsilateral and contralateral abnormalities in gray and white matter using modulated VBM and contrast the magnitude of white matter abnormality to a similar degree of gray matter abnormality. Further demonstrated in unilateral left and right temporal lobe epilepsy

groups is a distribution of white matter temporal and extratemporal lobe abnormality observed ipsilateral to the side of seizure onset. Of considerable interest is the degree to which significant changes in both gray and white matter are evident among patients with demonstrated localization-related temporal lobe epilepsy. Limitations The subjects investigated here were seeking care at a tertiary university-based center and as such are not representative of the broader population of patients with temporal lobe epilepsy. How-

Fig. 4. VBM results at P < 0.05, corrected for multiple comparisons indicating white matter volume decrease. (a) Left temporal pole white matter in left TLE group, (b) corpus callosum in left TLE group, (c) prefrontal white matter in left TLE group, (d) right temporal pole white matter in right TLE group, and (e) fornix in right TLE group.

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ever, a recent population-based study of a heterogeneous group of epilepsy patients also found substantial presence of both focal and generalized neocortical atrophy among chronic epilepsy patients (Liu et al., 2003). While the automated approach of voxel-based morphometry has distinct advantages over traditional region-of-interest-based methods, it is not without limitations due to imperfect spatial normalization, segmentation, and smoothing of the source images (Good et al., 2001). Systematic misclassification of structures can cause volume changes to appear in regions where none truly exists, such as gray matter changes in brain regions that should be white matter. This problem is potentially worsened in regions without distinct gray – white matter boundaries (Ashburner and Friston, 2000; Keller et al., 2002b) and poor boundaries due to pathological reasons as previously described. Here, the search volume for the VBM results was confined to an area more inclusive of the respective gray or white matter. By eliminating voxels outside of the tissue type of interest, the results are confined to areas with greater probabilities of being correctly classified. Even with a modest sample size, we present gray and white matter results with findings that are well complemented between the left and right TLE groups and previous volumetric findings. It is likely that inclusion of larger numbers of patients would provide increased statistical power resulting in the identification of additional areas of abnormality. Implications The identified changes in gray and especially white matter affected multiple brain regions and could be expected to adversely affect cognitive status. Indeed, neuropsychological investigations of patients with chronic temporal lobe epilepsy have demonstrated diffuse cognitive dysfunction, the etiology of which has been difficult to determine (Hermann et al., 1997). The clinical significance of identified extratemporal gray matter VBM abnormalities has recently been demonstrated by Keller et al. (2003). They reported that frontal lobe gray matter abnormalities were evident in patients with temporal lobe epilepsy, and importantly that these frontal lobe VBM abnormalities were associated with poorer performance on measures of frontally dependent executive functions. We have recently reported that whole brain white matter brain volume abnormalities are also significantly associated with neuropsychological dysfunction in TLE (Hermann et al., 2003a). Thus, the presence of extratemporal lobe abnormalities in TLE may contribute to the cumulative cognitive burden of the disorder. Future research examining the relationship between VBM identified abnormalities in cerebral white matter and abnormalities in specific mental functions and emotional – behavioral status could provide further clarification of the etiologies underlying important comorbidities of TLE. The identified anomalies in cerebral white matter raise the possibility of compromised connectivity within the temporal lobe as well as within and between the left and right cerebral hemispheres. The presence of significant disruption in cortical connectivity secondary to abnormalities in cerebral white matter in a disease traditionally considered a disorder of gray matter represents a new conceptualization of the etiology underlying some of the cognitive pathology in epilepsy. Sophisticated functional imaging research has led to the widely appreciated view that many cognitive tasks dependent on the coordinated activity of distributed neuronal network for efficient and successful perfor-

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mance. Disruptions in cerebral connectivity could be expected to adversely affect tasks dependent on such distributed neuronal systems. Finally, the pathophysiology and etiology of the identified abnormalities in cerebral white matter remains to be determined. Possible causes include the neurodevelopmental impact of epilepsy and its treatment on white matter development and/or the potential adverse effects of chronic epilepsy and its treatment with antiepilepsy medications on brain structure. Resolution of this issue has considerable theoretical and treatment implications. Ultimately, longitudinal studies employing multimodal neuroimaging techniques will be necessary to provide data relevant to this issue.

Acknowledgments This study was supported by NIH NS 2RO1-37738 and NIH RO1 RR16591-02.

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