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Whole-brain voxel-based morphometry of white matter in medial temporal lobe epilepsy
European Journal of Radiology 65 (2008) 86–90
Whole-brain voxel-based morphometry of white matter in medial temporal lobe epilepsy Aihong Yu a , Kuncheng Li a,∗ , Lin Li b , Baoci Shan b , Yuping Wang c , Sufang Xue c a
Department of Radiology, Xuanwu Hospital, Capital University of Medical Sciences, Beijing 100053, China b Institute of High Energy Physics, Chinese Academy of Sciences, China c Department of Neurology, Xuanwu Hospital, Capital University of Medical Sciences, China Received 27 July 2006; received in revised form 27 January 2007; accepted 10 April 2007
Abstract Purpose: The purpose of this study was to analyze whole-brain white matter changes in medial temporal lobe epilepsy (MTLE). Materials and methods: We studied 23 patients with MTLE and 13 age- and sex-matched healthy control subjects using voxel-based morphometry (VBM) on T1-weighted 3D datasets. The seizure focus was right sided in 11 patients and left sided in 12. The data were collected on a 1.5 T MR system and analyzed by SPM 99 to generate white matter density maps. Results: Voxel-based morphometry revealed diffusively reduced white matter in MTLE prominently including bilateral frontal lobes, bilateral temporal lobes and corpus callosum. White matter reduction was also found in the bilateral cerebellar hemispheres in the left MTLE group. Conclusion: VBM is a simple and automated approach that is able to identify diffuse whole-brain white matter reduction in MTLE. © 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Epilepsy; White matter; Magnetic resonance imaging; Voxel-based morphometry
1. Introduction To date, most MRI morphometric studies have been based on manual delineation of single brain structures, namely ROIbased morphometry. This procedure, which is rater-dependent, suffers from difficulties related to defining reliable anatomical boundaries, and to obtaining results with low reproducibility and objectivity. Voxel-based morphometry (VBM) is a fully automated technique allowing identification of regional differences in gray matter or white matter with no a priori region of interest, enabling an objective analysis of the whole brain [1,2]. This technique has showed promise in revealing pathological changes of gray matter in various neurological conditions including Alzheimer’s disease, schizophrenia and medial temporal lobe epilepsy (MTLE) [2–5]. However, few studies using VBM investigate white matter abnormalities [2,6]. Much remains to be clarified regarding the nature and distribution of white matter
∗
Corresponding author. Tel.: +86 10 83198376; fax: +86 10 83198376. E-mail address: [email protected] (K. Li).
0720-048X/$ – see front matter © 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejrad.2007.04.011
abnormalities. The purpose of this study was to investigate white matter changes in MTLE using VBM.
2. Materials and methods 2.1. Clinical material Subjects were 23 patients with MTLE (10 men and 13 women, mean age 24.1 years ± 9.6, range 11–43 years). Selection criteria for MTLE patients included the following: The diagnosis of unilateral MTLE was based on the combined review of clinical history, EEG findings (including video-EEG) and high-resolution MR images, with absence of MRI abnormalities other than hippocampal sclerosis and atrophy. All patients had been treated by internal medicine for more than 2 years, but seizures could not be controlled. No other neurological disorder was known to be present. The control group included 13 sexand age-matched healthy volunteers (mean age 25.2 years ± 8.9, range 14–42 years). Informed consent was obtained from all subjects.
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
Lateralization of the seizure focus was determined by a comprehensive evaluation including detailed clinical history, neurological examination, review of medical records, and neuropsychological testing, but interictal EEG and prolonged
87
video-EEG monitoring were the principle methods. Based on these criteria, 11 right-sided seizure foci and 12 left-sided seizure foci were determined. The epileptogenic site was concordant with the site of hippocampal sclerosis or atrophy in all patients.
Fig. 1. Brain regions of decreased white matter volume in the right MTLE were shown on sagittal view.
88
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
2.2. MRI technique MR imaging was performed with a 1.5-T MR scanner (Sonata Siemens, Germany). For each subject, a T1-weighted, three-
dimensional image using a MPRAGE (magnetization prepared rapid acquisition gradient echo) sequence was acquired with the following parameters: TR/TE/TI = 2200 ms/3.9 ms/1100 ms, flip angle = 15◦ , slice plane: sagittal, slice thickness = 1.70 mm,
Fig. 2. Brain regions of decreased white matter volume in the left MTLE were shown on sagittal view.
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
FOV = 250 mm × 218 mm, slices.
matrix
size = 256 × 179,
128
2.3. Image processing The data were analyzed using SPM 99 (Wellcome Department of Cognitive Neurology, www.fil.ion.ucl.ac.uk) to generate white matter density maps. First, The 3D MR data sets of all patients and controls were preprocessed using the following main steps: (1) Segmentation: Classification of brain tissue into gray matter, white matter and cerebral spinal fluid was performed. (2) Normalization: Segmented white matter images were normalized to the Montreal Neurological Institute (MNI) template [7]. (3) Smoothing: The normalized white matter images were smoothed using a 1.5 mm × 1.5 mm × 5.1 mm fullwidth half-maximum (FWHM) Gaussian kernel for subsequent statistical analysis. Statistical maps of differences in white matter between patients and controls were obtained using a general linear model [8]. Comparisons were made between the white matter of patients with left and right MTLE, and that of the healthy controls. The voxel-wise statistical threshold was at a P-value of <0.05. The output for each comparison was a statistical parametric map that revealed the location of white matter abnormalities in the brain. These areas were superimposed on a T1-weighted template. Spatial locations of the abnormal brain regions were detailed by Talairach coordinates [7]. 3. Results 3.1. Brain regions of decreased white matter volume Figs. 1 and 2 depict areas of reduced white matter volume in the right and left MTLE, respectively. As can be seen, patients with right MTLE or left MTLE exhibited a significant white matter volume decrease predominantly focused in the bilateral frontal lobes, the temporal lobes and the corpus callosum. Additionally, bilateral, parietal and occipital lobes showed decreases in white matter volume. Further white matter reduction in the bilateral cerebellar hemispheres was found in the left MTLE group. 3.2. Brain regions of increased white matter volume The left MTLE patients did not exhibit areas of increased white matter volume compared to the controls. In the right MTLE group small regions of increased white matter were found in the areas of the pyramidal tract at the level of the internal capsule as far as the pons. 4. Discussion 4.1. Comparison of VBM and ROI-based morphometry in MTLE Histological abnormality in MTLE is characterized by hippocampal sclerosis or atrophy. Previously, most studies of
89
hippocampal volume abnormality were performed preoperationally through ROI-based MRI quantitative assessment. Using this method, extrahippocampal abnormalities have been revealed including those in the parahippocampal gyrus, the amygdala, the entorhinal cortex [8,10], the lateral temporal lobe and the cerebellum [11]. However, ROI-based morphometry has some disadvantages [1]: (1) Results are difficult to reproduce due to difficulty in defining accurate anatomical boundaries. (2) Manual delineation has wide inter- and intra-rater variability leading to low objectivity. (3) Quantitative assessment must be limited in some brain areas because of labor intensiveness. These factors make ROI-based morphometry difficult to be applied clinically. In contrast, the VBM technique is fully automated, which allows identification of regional differences in the volume of the gray matter or white matter with no a priori region of interest; thus performing an objective analysis of the whole brain. In this study, we investigated whole-brain white matter changes in MTLE using VBM and found diffuse abnormality of white matter. However, it should be mentioned that the VBM technique is not completely mature because the accuracy and sensitivity of VBM analysis depend on the quality of the underlying preprocessing steps [12], including spatial normalization tissue segmentation and smoothing. For example, the gray matter–white matter interface will be blurred in a patient with MTLE, which can result in reduction in gray matter–white matter contrast. Since the tissue classification algorithms that are commonly used are intensity driven, it is difficult to identify anatomical structure precisely [13]. Fortunately, there is a large body of literature on the MRI quantitative analysis of hippocampal and extrahippocampal brain areas in TLE. ROI- and voxel-based approaches showed a good general consistency in displaying abnormalities of brain anatomical structure in TLE [1,14–16], which implied that VBM is a technique with high validity. 4.2. Pathophysiological mechanism and clinical implications Volume decreases of hippocampal and extra-hippocampal brain gray matter in MTLE were found in some previous studies using VBM [2,3,10,15]. In this study, diffuse reduction of white matter was also shown including the bilateral frontal lobes, the bilateral temporal lobes, the corpus callosum and so on. This result was consistent with a previous close examination of the white matter in patients with chronic TLE [17]. Additionally, some previous studies using diffusion tensor imaging (DTI) also revealed abnormalities of the white matter in patients with TLE. Arfanakis et al. [18] detected lower fractional anisotropy in directions perpendicular to the axons in the corpus callosum in TLE, and Dumas de la Roque et al. found higher diffusivity of white matter around the epileptogenic focus [19]. At present, pathogenesis of the white matter abnormality in MTLE is unclear; however a number of possible presumptions are as follows: First, it is direct tissue damage resulting from recurrent epileptic discharges [20]. Martin et al. [21] reported that prolonged activation of epileptic spikes could result in degeneration
90
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
of brain tissue and cause a reduction of nervous tissue volume. Secondly, loss of synaptic input from the atrophic hippocampus may impede the normal development of associated structures. Thirdly, because the onset of most refractory epilepsy is in childhood, prolonged activation of epileptic spikes may damage the brain development including that of the white matter [22]. Additionally, antiepileptic drugs may be responsible for diffuse brain volume reductions [11]. Compared with other research studies of white matter in MTLE using VBM [6], there was more diffuse reduction of white matter in our patients, which may be explained by a younger age of onset and by taking more doses of antiepileptic drugs in our patients. Functional imaging, lesional, and behavioral studies have shown that performance on many higher cognitive tasks depends on the coordinated activity of distributed neuronal networks. These distributed networks are linked by projection, association, and commissural white matter fiber tracks that connect cortical–subcortical, cortical–cortical, and interhemisphere regions [17]. Disruption in brain connectivity due to abnormalities in cerebral white matter can be associated with poorer neuropsychological performance. Clinically, many cognitive disorders involving memory, execution and attention can be found in patients with MTLE [21]. Diffuse abnormalities in the white matter may be the underlying mechanism of these cognitive dysfunctions [23,24]. The increase in the concentration of white matter in the right MTLE in this study can be interpreted by the hypothesis that it is due to disorganized white matter secondary to damage of white matter fibers. Further research to support or reject this hypothesis should be done. 4.3. Limitations Some previous research studies as well as this present study showed the ability of VBM technique to display abnormalities in whole-brain neuroanatomical structures for MTLE [2,6,9,10]. As was mentioned above, however, different studies have inconsistent results. These discrepancies between studies probably reflect the great variations in subjects’ age at seizure onset, interictal spike occurrence, duration of epilepsy and presence of febrile convulsions. Therefore, it is necessary to restrict the experiment conditions and increase the number of samples in order to obtain reliable results. In addition, finding reasonable explanations for experiment results is an important problem. 5. Conclusion VBM can be used objectively to assess abnormalities in whole-brain neuroanatomical structures of white matter in vivo. It is able to detect diffuse reductions of white matter in patients with MTLE. References [1] Ashburner J, Friston KJ. Voxel-based morphometry—the methods. Neuroimage 2000;11:805–21.
[2] Bernasconi N, Duchesne S, Janke A, et al. Whole-brain voxel-based statistical analysis of gray matter and white matter in temporal lobe epilepsy. Neuroimage 2004;23:717–23. [3] Karas GB, Burton EJ, Rombouts SA, et al. A comprehensive study of gray matter loss in patients with Alzheimer’s disease using optimized voxelbased morphometry. Neuroimage 2003;18:895–907. [4] Kubicki M, Shenton ME, Salisbury DF, et al. Voxel-based morphometric analysis of gray matter in first episode schizophrenia. Neuroimage 2002;17:1711–9. [5] Hao J, Li KC, Li K, et al. A voxel-based MRI morphometric study of Alzheimer’s disease. Chin J Radiol 2005;39:1028–33. [6] McMillan AB, Hermann BP, Johnson SC, et al. Voxel-based morphometry of unilateral temporal lobe epilepsy reveals abnormalities in cerebral white matter. Neuroimage 2004;23:167–74. [7] Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain. New York: Thieme Medical; 1988. [8] Friston KJ, Holmes AP, Poline JB, et al. Analysis of fMRI time-series revisited. Neuroimage 1995;2:45–53. [9] Bernasconi N, Bernasconi A, Caramanos Z, et al. Morphometric MRI analysis of the parahippocampal region in temporal lobe epilepsy. Ann N Y Acad Sci 2000;911:495–500. [10] Bernasconi N, Bernasconi A, Caramanos Z, et al. Entorhinal cortex atrophy in epilepsy patients exhibiting normal hippocampal volumes. Neurology 2001;56:1335–9. [11] Sandok EK, O’Brien TJ, Jack CR, et al. Significance of cerebellar atrophy in intractable temporal lobe epilepsy: a quantitative MRI study. Epilepsia 2000;41:1315–20. [12] Good CD, Scahill RI, Fox NC, et al. Automatic differentiation of anatomical patterns in the human brain: validation with studies of degenerative dementias. Neuroimage 2002;17:29–46. [13] Woermann FG, Barker GJ, Brinie KD, et al. Regional changes in hippocampal T2 relaxation and volume: a quantitative magnetic resonance imaging study of hippocampal sclerosis. J Neurosurg Psychiatry 1998;65: 656–64. [14] Keller SS, Wilke M, Wieshmann UC, et al. Comparison of standard and optimized voxel-based morphometry for analysis of brain changes associated with temporal lobe epilepsy. Neuroimage 2004;23: 860–8. [15] Keller SS, Wieshmann UC, Mackay CE, et al. Voxel based morphometry of grey matter abnormalities in patients with medically intractable temporal lobe epilepsy: effects of side of seizure onset and epilepsy duration. J Neurol Neurosurg Psychiatry 2002;73:648–55. [16] Ng KK, Tang KW, Cheung YL, et al. Brain MRI of hippocampal volumetry in patients with refractory temporal lobe epilepsy. Chin Med J 2000;113:254–6. [17] Hermann B, Hansen R, Seidenberg M, et al. Neurodevelopmental vulnerability of the corpus callosum to childhood onset localization-related epilepsy. Neuroimage 2003;18:284–92. [18] Arfanakis K, Hermann BP, Rogers BP, et al. Diffusion tensor MRI in temporal lobe epilepsy. Magn Reson Imaging 2002;20:511– 9. [19] Dumas de la Roque A, Oppenheim C, Chassoux F, et al. Diffusion tensor imaging of partial intractable epilepsy. Eur Radiol 2005;15: 279–85. [20] Cormack F, Gadian DG, Vargha-Khadem F, et al. Extra-hippocampal grey matter density abnormalities in paediatric mesial temporal sclerosis. Neuroimage 2005;27:635–43. [21] Martin RC, Sawrie SM, Edwards R, et al. Investigation of executive function change following anterior temporal lobectomy: selective normalization of verbal fluency. Neuropsychology 2000;14:501–8. [22] Holmes GL, Ben Ari Y. The neurobiology and consequences of epilepsy in the developing brain. Pediatr Res 2001;49:320–5. [23] Helmstaedter C, Kurthen M, Lux S, et al. Chronic epilepsy and cognition: a longitudinal study in temporal lobe epilepsy. Ann Neurol 2003;54: 425–32. [24] Hermann BP, Seidenberg M, Bell B, et al. Extratemporal quantitative MRI volumetrics and neuropsychological function in temporal lobe epilepsy. J Int Neuropsychol Soc 2003;9:353–62.
Whole-brain voxel-based morphometry of white matter in medial temporal lobe epilepsy Aihong Yu a , Kuncheng Li a,∗ , Lin Li b , Baoci Shan b , Yuping Wang c , Sufang Xue c a
Department of Radiology, Xuanwu Hospital, Capital University of Medical Sciences, Beijing 100053, China b Institute of High Energy Physics, Chinese Academy of Sciences, China c Department of Neurology, Xuanwu Hospital, Capital University of Medical Sciences, China Received 27 July 2006; received in revised form 27 January 2007; accepted 10 April 2007
Abstract Purpose: The purpose of this study was to analyze whole-brain white matter changes in medial temporal lobe epilepsy (MTLE). Materials and methods: We studied 23 patients with MTLE and 13 age- and sex-matched healthy control subjects using voxel-based morphometry (VBM) on T1-weighted 3D datasets. The seizure focus was right sided in 11 patients and left sided in 12. The data were collected on a 1.5 T MR system and analyzed by SPM 99 to generate white matter density maps. Results: Voxel-based morphometry revealed diffusively reduced white matter in MTLE prominently including bilateral frontal lobes, bilateral temporal lobes and corpus callosum. White matter reduction was also found in the bilateral cerebellar hemispheres in the left MTLE group. Conclusion: VBM is a simple and automated approach that is able to identify diffuse whole-brain white matter reduction in MTLE. © 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Epilepsy; White matter; Magnetic resonance imaging; Voxel-based morphometry
1. Introduction To date, most MRI morphometric studies have been based on manual delineation of single brain structures, namely ROIbased morphometry. This procedure, which is rater-dependent, suffers from difficulties related to defining reliable anatomical boundaries, and to obtaining results with low reproducibility and objectivity. Voxel-based morphometry (VBM) is a fully automated technique allowing identification of regional differences in gray matter or white matter with no a priori region of interest, enabling an objective analysis of the whole brain [1,2]. This technique has showed promise in revealing pathological changes of gray matter in various neurological conditions including Alzheimer’s disease, schizophrenia and medial temporal lobe epilepsy (MTLE) [2–5]. However, few studies using VBM investigate white matter abnormalities [2,6]. Much remains to be clarified regarding the nature and distribution of white matter
∗
Corresponding author. Tel.: +86 10 83198376; fax: +86 10 83198376. E-mail address: [email protected] (K. Li).
0720-048X/$ – see front matter © 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejrad.2007.04.011
abnormalities. The purpose of this study was to investigate white matter changes in MTLE using VBM.
2. Materials and methods 2.1. Clinical material Subjects were 23 patients with MTLE (10 men and 13 women, mean age 24.1 years ± 9.6, range 11–43 years). Selection criteria for MTLE patients included the following: The diagnosis of unilateral MTLE was based on the combined review of clinical history, EEG findings (including video-EEG) and high-resolution MR images, with absence of MRI abnormalities other than hippocampal sclerosis and atrophy. All patients had been treated by internal medicine for more than 2 years, but seizures could not be controlled. No other neurological disorder was known to be present. The control group included 13 sexand age-matched healthy volunteers (mean age 25.2 years ± 8.9, range 14–42 years). Informed consent was obtained from all subjects.
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
Lateralization of the seizure focus was determined by a comprehensive evaluation including detailed clinical history, neurological examination, review of medical records, and neuropsychological testing, but interictal EEG and prolonged
87
video-EEG monitoring were the principle methods. Based on these criteria, 11 right-sided seizure foci and 12 left-sided seizure foci were determined. The epileptogenic site was concordant with the site of hippocampal sclerosis or atrophy in all patients.
Fig. 1. Brain regions of decreased white matter volume in the right MTLE were shown on sagittal view.
88
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
2.2. MRI technique MR imaging was performed with a 1.5-T MR scanner (Sonata Siemens, Germany). For each subject, a T1-weighted, three-
dimensional image using a MPRAGE (magnetization prepared rapid acquisition gradient echo) sequence was acquired with the following parameters: TR/TE/TI = 2200 ms/3.9 ms/1100 ms, flip angle = 15◦ , slice plane: sagittal, slice thickness = 1.70 mm,
Fig. 2. Brain regions of decreased white matter volume in the left MTLE were shown on sagittal view.
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
FOV = 250 mm × 218 mm, slices.
matrix
size = 256 × 179,
128
2.3. Image processing The data were analyzed using SPM 99 (Wellcome Department of Cognitive Neurology, www.fil.ion.ucl.ac.uk) to generate white matter density maps. First, The 3D MR data sets of all patients and controls were preprocessed using the following main steps: (1) Segmentation: Classification of brain tissue into gray matter, white matter and cerebral spinal fluid was performed. (2) Normalization: Segmented white matter images were normalized to the Montreal Neurological Institute (MNI) template [7]. (3) Smoothing: The normalized white matter images were smoothed using a 1.5 mm × 1.5 mm × 5.1 mm fullwidth half-maximum (FWHM) Gaussian kernel for subsequent statistical analysis. Statistical maps of differences in white matter between patients and controls were obtained using a general linear model [8]. Comparisons were made between the white matter of patients with left and right MTLE, and that of the healthy controls. The voxel-wise statistical threshold was at a P-value of <0.05. The output for each comparison was a statistical parametric map that revealed the location of white matter abnormalities in the brain. These areas were superimposed on a T1-weighted template. Spatial locations of the abnormal brain regions were detailed by Talairach coordinates [7]. 3. Results 3.1. Brain regions of decreased white matter volume Figs. 1 and 2 depict areas of reduced white matter volume in the right and left MTLE, respectively. As can be seen, patients with right MTLE or left MTLE exhibited a significant white matter volume decrease predominantly focused in the bilateral frontal lobes, the temporal lobes and the corpus callosum. Additionally, bilateral, parietal and occipital lobes showed decreases in white matter volume. Further white matter reduction in the bilateral cerebellar hemispheres was found in the left MTLE group. 3.2. Brain regions of increased white matter volume The left MTLE patients did not exhibit areas of increased white matter volume compared to the controls. In the right MTLE group small regions of increased white matter were found in the areas of the pyramidal tract at the level of the internal capsule as far as the pons. 4. Discussion 4.1. Comparison of VBM and ROI-based morphometry in MTLE Histological abnormality in MTLE is characterized by hippocampal sclerosis or atrophy. Previously, most studies of
89
hippocampal volume abnormality were performed preoperationally through ROI-based MRI quantitative assessment. Using this method, extrahippocampal abnormalities have been revealed including those in the parahippocampal gyrus, the amygdala, the entorhinal cortex [8,10], the lateral temporal lobe and the cerebellum [11]. However, ROI-based morphometry has some disadvantages [1]: (1) Results are difficult to reproduce due to difficulty in defining accurate anatomical boundaries. (2) Manual delineation has wide inter- and intra-rater variability leading to low objectivity. (3) Quantitative assessment must be limited in some brain areas because of labor intensiveness. These factors make ROI-based morphometry difficult to be applied clinically. In contrast, the VBM technique is fully automated, which allows identification of regional differences in the volume of the gray matter or white matter with no a priori region of interest; thus performing an objective analysis of the whole brain. In this study, we investigated whole-brain white matter changes in MTLE using VBM and found diffuse abnormality of white matter. However, it should be mentioned that the VBM technique is not completely mature because the accuracy and sensitivity of VBM analysis depend on the quality of the underlying preprocessing steps [12], including spatial normalization tissue segmentation and smoothing. For example, the gray matter–white matter interface will be blurred in a patient with MTLE, which can result in reduction in gray matter–white matter contrast. Since the tissue classification algorithms that are commonly used are intensity driven, it is difficult to identify anatomical structure precisely [13]. Fortunately, there is a large body of literature on the MRI quantitative analysis of hippocampal and extrahippocampal brain areas in TLE. ROI- and voxel-based approaches showed a good general consistency in displaying abnormalities of brain anatomical structure in TLE [1,14–16], which implied that VBM is a technique with high validity. 4.2. Pathophysiological mechanism and clinical implications Volume decreases of hippocampal and extra-hippocampal brain gray matter in MTLE were found in some previous studies using VBM [2,3,10,15]. In this study, diffuse reduction of white matter was also shown including the bilateral frontal lobes, the bilateral temporal lobes, the corpus callosum and so on. This result was consistent with a previous close examination of the white matter in patients with chronic TLE [17]. Additionally, some previous studies using diffusion tensor imaging (DTI) also revealed abnormalities of the white matter in patients with TLE. Arfanakis et al. [18] detected lower fractional anisotropy in directions perpendicular to the axons in the corpus callosum in TLE, and Dumas de la Roque et al. found higher diffusivity of white matter around the epileptogenic focus [19]. At present, pathogenesis of the white matter abnormality in MTLE is unclear; however a number of possible presumptions are as follows: First, it is direct tissue damage resulting from recurrent epileptic discharges [20]. Martin et al. [21] reported that prolonged activation of epileptic spikes could result in degeneration
90
A. Yu et al. / European Journal of Radiology 65 (2008) 86–90
of brain tissue and cause a reduction of nervous tissue volume. Secondly, loss of synaptic input from the atrophic hippocampus may impede the normal development of associated structures. Thirdly, because the onset of most refractory epilepsy is in childhood, prolonged activation of epileptic spikes may damage the brain development including that of the white matter [22]. Additionally, antiepileptic drugs may be responsible for diffuse brain volume reductions [11]. Compared with other research studies of white matter in MTLE using VBM [6], there was more diffuse reduction of white matter in our patients, which may be explained by a younger age of onset and by taking more doses of antiepileptic drugs in our patients. Functional imaging, lesional, and behavioral studies have shown that performance on many higher cognitive tasks depends on the coordinated activity of distributed neuronal networks. These distributed networks are linked by projection, association, and commissural white matter fiber tracks that connect cortical–subcortical, cortical–cortical, and interhemisphere regions [17]. Disruption in brain connectivity due to abnormalities in cerebral white matter can be associated with poorer neuropsychological performance. Clinically, many cognitive disorders involving memory, execution and attention can be found in patients with MTLE [21]. Diffuse abnormalities in the white matter may be the underlying mechanism of these cognitive dysfunctions [23,24]. The increase in the concentration of white matter in the right MTLE in this study can be interpreted by the hypothesis that it is due to disorganized white matter secondary to damage of white matter fibers. Further research to support or reject this hypothesis should be done. 4.3. Limitations Some previous research studies as well as this present study showed the ability of VBM technique to display abnormalities in whole-brain neuroanatomical structures for MTLE [2,6,9,10]. As was mentioned above, however, different studies have inconsistent results. These discrepancies between studies probably reflect the great variations in subjects’ age at seizure onset, interictal spike occurrence, duration of epilepsy and presence of febrile convulsions. Therefore, it is necessary to restrict the experiment conditions and increase the number of samples in order to obtain reliable results. In addition, finding reasonable explanations for experiment results is an important problem. 5. Conclusion VBM can be used objectively to assess abnormalities in whole-brain neuroanatomical structures of white matter in vivo. It is able to detect diffuse reductions of white matter in patients with MTLE. References [1] Ashburner J, Friston KJ. Voxel-based morphometry—the methods. Neuroimage 2000;11:805–21.
[2] Bernasconi N, Duchesne S, Janke A, et al. Whole-brain voxel-based statistical analysis of gray matter and white matter in temporal lobe epilepsy. Neuroimage 2004;23:717–23. [3] Karas GB, Burton EJ, Rombouts SA, et al. A comprehensive study of gray matter loss in patients with Alzheimer’s disease using optimized voxelbased morphometry. Neuroimage 2003;18:895–907. [4] Kubicki M, Shenton ME, Salisbury DF, et al. Voxel-based morphometric analysis of gray matter in first episode schizophrenia. Neuroimage 2002;17:1711–9. [5] Hao J, Li KC, Li K, et al. A voxel-based MRI morphometric study of Alzheimer’s disease. Chin J Radiol 2005;39:1028–33. [6] McMillan AB, Hermann BP, Johnson SC, et al. Voxel-based morphometry of unilateral temporal lobe epilepsy reveals abnormalities in cerebral white matter. Neuroimage 2004;23:167–74. [7] Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain. New York: Thieme Medical; 1988. [8] Friston KJ, Holmes AP, Poline JB, et al. Analysis of fMRI time-series revisited. Neuroimage 1995;2:45–53. [9] Bernasconi N, Bernasconi A, Caramanos Z, et al. Morphometric MRI analysis of the parahippocampal region in temporal lobe epilepsy. Ann N Y Acad Sci 2000;911:495–500. [10] Bernasconi N, Bernasconi A, Caramanos Z, et al. Entorhinal cortex atrophy in epilepsy patients exhibiting normal hippocampal volumes. Neurology 2001;56:1335–9. [11] Sandok EK, O’Brien TJ, Jack CR, et al. Significance of cerebellar atrophy in intractable temporal lobe epilepsy: a quantitative MRI study. Epilepsia 2000;41:1315–20. [12] Good CD, Scahill RI, Fox NC, et al. Automatic differentiation of anatomical patterns in the human brain: validation with studies of degenerative dementias. Neuroimage 2002;17:29–46. [13] Woermann FG, Barker GJ, Brinie KD, et al. Regional changes in hippocampal T2 relaxation and volume: a quantitative magnetic resonance imaging study of hippocampal sclerosis. J Neurosurg Psychiatry 1998;65: 656–64. [14] Keller SS, Wilke M, Wieshmann UC, et al. Comparison of standard and optimized voxel-based morphometry for analysis of brain changes associated with temporal lobe epilepsy. Neuroimage 2004;23: 860–8. [15] Keller SS, Wieshmann UC, Mackay CE, et al. Voxel based morphometry of grey matter abnormalities in patients with medically intractable temporal lobe epilepsy: effects of side of seizure onset and epilepsy duration. J Neurol Neurosurg Psychiatry 2002;73:648–55. [16] Ng KK, Tang KW, Cheung YL, et al. Brain MRI of hippocampal volumetry in patients with refractory temporal lobe epilepsy. Chin Med J 2000;113:254–6. [17] Hermann B, Hansen R, Seidenberg M, et al. Neurodevelopmental vulnerability of the corpus callosum to childhood onset localization-related epilepsy. Neuroimage 2003;18:284–92. [18] Arfanakis K, Hermann BP, Rogers BP, et al. Diffusion tensor MRI in temporal lobe epilepsy. Magn Reson Imaging 2002;20:511– 9. [19] Dumas de la Roque A, Oppenheim C, Chassoux F, et al. Diffusion tensor imaging of partial intractable epilepsy. Eur Radiol 2005;15: 279–85. [20] Cormack F, Gadian DG, Vargha-Khadem F, et al. Extra-hippocampal grey matter density abnormalities in paediatric mesial temporal sclerosis. Neuroimage 2005;27:635–43. [21] Martin RC, Sawrie SM, Edwards R, et al. Investigation of executive function change following anterior temporal lobectomy: selective normalization of verbal fluency. Neuropsychology 2000;14:501–8. [22] Holmes GL, Ben Ari Y. The neurobiology and consequences of epilepsy in the developing brain. Pediatr Res 2001;49:320–5. [23] Helmstaedter C, Kurthen M, Lux S, et al. Chronic epilepsy and cognition: a longitudinal study in temporal lobe epilepsy. Ann Neurol 2003;54: 425–32. [24] Hermann BP, Seidenberg M, Bell B, et al. Extratemporal quantitative MRI volumetrics and neuropsychological function in temporal lobe epilepsy. J Int Neuropsychol Soc 2003;9:353–62.