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Zanao TA, Seitz‐Holland J, O'Donnell LJ, Zhang F, Rathi Y, Lopes TM, Pimentel‐Silva LR, Yassuda CL, Makris N, Shenton ME, Bouix S, Lyall AE, Cendes F. Exploring the impact of hippocampal sclerosis on white matter tracts and memory in individuals with mesial temporal lobe epilepsy. Epilepsia Open 2023; 8:1111-1122. [PMID: 37469213 PMCID: PMC10472386 DOI: 10.1002/epi4.12793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 07/14/2023] [Indexed: 07/21/2023] Open
Abstract
OBJECTIVE To investigate how the presence/side of hippocampal sclerosis (HS) are related to the white matter structure of cingulum bundle (CB), arcuate fasciculus (AF), and inferior longitudinal fasciculus (ILF) in mesial temporal lobe epilepsy (MTLE). METHODS We acquired diffusion-weighted magnetic resonance imaging (MRI) from 86 healthy and 71 individuals with MTLE (22 righ-HS; right-HS, 34 left-HS; left-HS, and 15 nonlesional MTLE). We utilized two-tensor tractography and fiber clustering to compare fractional anisotropy (FA) of each side/tract between groups. Additionally, we examined the association between FA and nonverbal (WMS-R) and verbal (WMS-R, RAVLT codification) memory performance for MTLE individuals. RESULTS White matter abnormalities depended on the side and presence of HS. The left-HS demonstrated widespread abnormalities for all tracts, the right-HS showed lower FA for ipsilateral tracts and the nonlesional MTLE group did not differ from healthy individuals. Results indicate no differences in verbal/nonverbal memory performance between the groups, but trend-level associations between higher FA of visual memory and the left CB (r = 0.286, P = 0.018), verbal memory (RAVLT) and -left CB (r = 0.335, P = 0.005), -right CB (r = 0.286, P = 0.016), and -left AF (r = 0.287, P = 0.017). SIGNIFICANCE Our results highlight that the presence and side of HS are crucial to understand the pathophysiology of MTLE. Specifically, left-sided HS seems to be related to widespread bilateral white matter abnormalities. Future longitudinal studies should focus on developing diagnostic and treatment strategies dependent on HS's presence/side.
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Affiliation(s)
- Tamires A. Zanao
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
| | - Johanna Seitz‐Holland
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lauren J. O'Donnell
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Tátila M. Lopes
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
| | | | - Clarissa L. Yassuda
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Sylvain Bouix
- Département de génie logiciel et TI, École de technologie supérieureUniversité du QuébecMontrealQuebecCanada
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fernando Cendes
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
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Jiang Y, Li W, Qin Y, Zhang L, Tong X, Xiao F, Jiang S, Li Y, Gong Q, Zhou D, An D, Yao D, Luo C. In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy. Hum Brain Mapp 2023; 44:2323-2335. [PMID: 36692056 PMCID: PMC10028664 DOI: 10.1002/hbm.26212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1-weighted and T2-weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel-wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1-weighted and T2-weighted MRI to investigate in vivo the myelin-related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Le Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Xin Tong
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Fenglai Xiao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Yunfang Li
- Southern Medical District, Chinese People's Liberation Army General Hospital, Beijing, People's Republic of China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, People's Republic of China
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, People's Republic of China
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3
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Zhang Y, Liu Z, Dou W, Wei J, Lv Y, Hou B, You H, Feng F. Study of the microstructure of brain white matter in medial temporal lobe epilepsy based on diffusion tensor imaging. Brain Behav 2023; 13:e2919. [PMID: 36880299 PMCID: PMC10097073 DOI: 10.1002/brb3.2919] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 01/02/2023] [Accepted: 01/07/2023] [Indexed: 03/08/2023] Open
Abstract
OBJECTIVES To compare the white matter (WM) asymmetry in left and right medial temporal lobe epilepsy (mTLE) with and without hippocampal sclerosis (HS+, HS-) and assess the correlation of preoperative asymmetry and the dynamics of WM fibers with surgical outcomes. MATERIALS AND METHODS Preoperative MRI scans were collected from 58 mTLE patients (40 HS+, 18 HS-); 15 (11 HS+, 4 HS-) then underwent postoperative MRI scans. DTI parameters, including the fractional anisotropy (FA), mean diffusion coefficient (MD), axial diffusion coefficient (AD), and radial diffusion coefficient (RD), were extracted from 20 paired WM tracts by PANDA based on the JHU WM tractography atlas. The bilateral cerebral parameters and the pre- to postoperative changes in the DTI parameters of specific fiber tracts were compared. The asymmetry indexes (AIs) of paired fibers were also analyzed. RESULTS There were fewer asymmetrical WM fibers in HS- patients than in HS+ patients. The pattern of WM asymmetry differed between left and right mTLE patients. Differences in the FA AI of the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus (ILF) were found in left HS+ patients with different surgical outcomes. All mTLE patients exhibited decreases in FA and increases in MD and RD in specific ipsilateral WM fibers. In International League Against Epilepsy (ILAE) grade 1 patients, the MD values in the ipsilateral CGH increased over time, whereas the RD values in the ipsilateral ILF and the AD values in the ipsilateral ILF and UNC decreased. In ILAE grade 2-5 patients, the FA values in the ipsilateral cingulate gyrus part of the cingulum (CGC) increased over time. CONCLUSION The WM tract asymmetry was more extensive in HS+ patients than in HS- patients. The preoperative WM fiber AIs in left HS+ patients may be useful for surgical prognosis. Additionally, pre- to postoperative changes in WM fibers may help predict surgical outcomes.
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Affiliation(s)
- Yiwei Zhang
- Department of Radiology, Peking University First Hospital, Beijing, China.,Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhaoxi Liu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wanchen Dou
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Juan Wei
- GE Healthcare, MR Research China, Beijing, China
| | - Yuelei Lv
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Department of Radiology, Beijing CHAO-YANG Hospital, Capital Medical University, Beijing, China
| | - Bo Hou
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hui You
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,State Key Laboratory of Difficult, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
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Lim SC, Oh J, Hong BY, Lim SH. Changes in the Brain in Temporal Lobe Epilepsy with Unilateral Hippocampal Sclerosis: An Initial Case Series. Healthcare (Basel) 2022; 10:healthcare10091648. [PMID: 36141260 PMCID: PMC9498839 DOI: 10.3390/healthcare10091648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/27/2022] [Indexed: 11/29/2022] Open
Abstract
Temporal lobe epilepsy (TLE) is a network disorder of the brain. Network disorders predominately involve dysregulation of hippocampal function caused by neuronal hyperexcitability. However, the relationship between the macro- and microscopic changes in specific brain regions is uncertain. In this study, the pattern of brain atrophy in patients with TLE and hippocampal sclerosis (HS) was investigated using volumetry, and microscopic changes in specific lesions were observed to examine the anatomical correspondence with specific target lesions using diffusion tensor imaging (DTI) with statistical parametric mapping (SPM). This retrospective cross-sectional study enrolled 17 patients with TLE and HS. We manually measured the volumes of the hippocampus (HC), amygdala (AMG), entorhinal cortex, fornix, and thalamus (TH) bilaterally. The mean diffusivity and fractional anisotropy of each patient were then quantified and analyzed by a voxel-based statistical correlation method using SPM8. In right TLE with HS, there was no evidence of any abnormal diffusion properties associated with the volume reduction in specific brain regions. In left TLE with HS, there were significant changes in the volumes of the AMG, HC, and TH. Despite the small sample size, these differences in conditions were considered meaningful. Chronic left TLE with HS might cause structural changes in the AMG, HC, and TH, unlike right TLE with HS.
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Affiliation(s)
- Sung Chul Lim
- Department of Neurology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
| | - Juhee Oh
- Department of Neurology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
| | - Bo Young Hong
- Department of Rehabilitation Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
| | - Seong Hoon Lim
- Department of Rehabilitation Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
- Correspondence: ; Tel.: +82-31-249-8952; Fax: +82-31-251-4481
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Zhou B, An D, Xiao F, Niu R, Li W, Li W, Tong X, Kemp GJ, Zhou D, Gong Q, Lei D. Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging. Front Med 2020; 14:630-641. [PMID: 31912429 DOI: 10.1007/s11684-019-0718-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Accepted: 09/07/2019] [Indexed: 02/04/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE), the most common type of focal epilepsy, is associated with functional and structural brain alterations. Machine learning (ML) techniques have been successfully used in discriminating mTLE from healthy controls. However, either functional or structural neuroimaging data are mostly used separately as input, and the opportunity to combine both has not been exploited yet. We conducted a multimodal ML study based on functional and structural neuroimaging measures. We enrolled 37 patients with left mTLE, 37 patients with right mTLE, and 74 healthy controls and trained a support vector ML model to distinguish them by using each measure and the combinations of the measures. For each single measure, we obtained a mean accuracy of 74% and 69% for discriminating left mTLE and right mTLE from controls, respectively, and 64% when all patients were combined. We achieved an accuracy of 78% by integrating functional data and 79% by integrating structural data for left mTLE, and the highest accuracy of 84% was obtained when all functional and structural measures were combined. These findings suggest that combining multimodal measures within a single model is a promising direction for improving the classification of individual patients with mTLE.
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Affiliation(s)
- Baiwan Zhou
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Dongmei An
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Fenglai Xiao
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China.,Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, WC1E 6BT, UK
| | - Running Niu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Wei Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xin Tong
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Graham J Kemp
- Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, L9 7AL, UK
| | - Dong Zhou
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, 610041, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China.,Department of Psychology, School of Public Administration, Sichuan University, Chengdu, 610041, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China. .,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK. .,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, 45219, USA.
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Chen CL, Shih YC, Liou HH, Hsu YC, Lin FH, Tseng WYI. Premature white matter aging in patients with right mesial temporal lobe epilepsy: A machine learning approach based on diffusion MRI data. NEUROIMAGE-CLINICAL 2019; 24:102033. [PMID: 31795060 PMCID: PMC6978225 DOI: 10.1016/j.nicl.2019.102033] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Revised: 09/17/2019] [Accepted: 09/21/2019] [Indexed: 01/24/2023]
Abstract
A brain age prediction model was developed based on diffusion MRI data. Patients with right MTLE exhibited older brain age than those with left MTLE. Predicted age difference (PAD) was correlated with seizure frequency in right MTLE. Right uncinate fasciculus had highest contribution to the observed PAD in right MTLE.
Brain age prediction based on machine learning has been applied to various neurological diseases to discover its clinical values. By this innovative approach, it has been reported that the patients with refractory epilepsy had premature brain aging. Of refractory epilepsy, right and left subtypes of mesial temporal lobe epilepsy (MTLE) are the most common forms and exhibit distinct patterns in white matter alterations. So far, it is unclear whether these two subtypes of MTLE would have difference in white matter aging due to distinct white matter alterations. To address this issue, a machine learning based brain age model using diffusion MRI data was established to investigate biological age of white matter tracts. All diffusion MRI datasets were obtained from the same 3-Tesla MRI scanner. To build the brain age prediction model, diffusion MRI datasets of 300 healthy participants were processed to extract age-relevant diffusion indices from 76 major white matter tracts. The extracted diffusion indices underwent Gaussian process regression to build the prediction model for white matter brain age. The model was validated in an independent testing set (N = 40) to ensure no overfitting of the model. The model was then applied to patients with right and left MTLE and matched controls (right MTLE: N = 17, left MTLE: N = 18, controls: N = 37), and predicted age difference (PAD) was obtained by calculating the difference between each individual's predicted brain age and chronological age. The higher PAD score indicated older brain age. The results showed that right MTLE exhibited older predicted brain age than the other two groups (PAD of right MTLE = 10.9 years [p < 0.05 against left MTLE; p < 0.001 against control]; PAD of left MTLE = 2.2 years [p > 0.1 against control]; PAD of controls = 0.82 years). Patients with right and left MTLE showed strong correlations of the PAD scores with age of onset and duration of illness, but both groups showed opposite directions of correlations. In right MTLE, positive correlation of PAD with seizure frequency was found, and the right uncinate fasciculus was the most attributable tract to the increase in PAD. In conclusion, the present study found that patients with right MTLE exhibited premature white matter brain aging and their PAD scores were correlated with seizure frequency. Therefore, PAD is a potentially useful indicator of white matter impairment and disease severity in patients with right MTLE.
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Affiliation(s)
- Chang-Le Chen
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yao-Chia Shih
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan; Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
| | - Horng-Huei Liou
- Department of Neurology, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.
| | | | - Fa-Hsuan Lin
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
| | - Wen-Yih Isaac Tseng
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Medical Imaging, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan.
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7
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Barnett AJ, Man V, McAndrews MP. Parcellation of the Hippocampus Using Resting Functional Connectivity in Temporal Lobe Epilepsy. Front Neurol 2019; 10:920. [PMID: 31507522 PMCID: PMC6714062 DOI: 10.3389/fneur.2019.00920] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 08/07/2019] [Indexed: 12/20/2022] Open
Abstract
We have previously shown that the connectivity of the hippocampus to other regions of the default mode network (DMN) is a strong indicator of memory ability in people with temporal lobe epilepsy (TLE). Recent work in the cognitive neuroscience literature has suggested that the anterior and posterior aspects of the hippocampus have distinct connections to the rest of the DMN and may support different memory operations. Further, structural analysis of epileptogenic hippocampi has found greater atrophy, characterized by mesial temporal sclerosis, in the anterior region of the hippocampus. Here, we used resting state FMRI data to parcellate the hippocampus according to its functional connectivity to the rest of the brain in people with left lateralized TLE (LTLE) and right lateralized TLE (RTLE), and in a group of neurologically healthy controls. We found similar anterior and posterior compartments in all groups. However, there was weaker connectivity of the epileptogenic hippocampus to multiple regions of the DMN. Both TLE groups showed reduced connectivity of the posterior hippocampus to key hubs of the DMN, the posterior cingulate cortex (PCC) and the medial pre-frontal cortex (mPFC). In the LTLE group, the anterior hippocampus also showed reduced connectivity to the DMN, and this effect was influenced by the presence of mesial temporal sclerosis. When we explored brain-behavior relationships, we found that reduced connectivity of the left anterior hippocampus to the DMN hubs related to poorer verbal memory ability in people with LTLE, and reduced connectivity of the right posterior hippocampus to the PCC related to poorer visual memory ability in those with RTLE. These findings may inform models regarding functional distinctions of the hippocampal anteroposterior axis.
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Affiliation(s)
- Alexander J Barnett
- Krembil Research Institute, University Health Network, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Vincent Man
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, United States
| | - Mary Pat McAndrews
- Krembil Research Institute, University Health Network, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
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8
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Bird LJ, Jackson GD, Wilson SJ. Music training is neuroprotective for verbal cognition in focal epilepsy. Brain 2019; 142:1973-1987. [PMID: 31074775 DOI: 10.1093/brain/awz124] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 02/18/2019] [Accepted: 03/07/2019] [Indexed: 12/21/2022] Open
Abstract
Focal epilepsy is a unilateral brain network disorder, providing an ideal neuropathological model with which to study the effects of focal neural disruption on a range of cognitive processes. While language and memory functions have been extensively investigated in focal epilepsy, music cognition has received less attention, particularly in patients with music training or expertise. This represents a critical gap in the literature. A better understanding of the effects of epilepsy on music cognition may provide greater insight into the mechanisms behind disease- and training-related neuroplasticity, which may have implications for clinical practice. In this cross-sectional study, we comprehensively profiled music and non-music cognition in 107 participants; musicians with focal epilepsy (n = 35), non-musicians with focal epilepsy (n = 39), and healthy control musicians and non-musicians (n = 33). Parametric group comparisons revealed a specific impairment in verbal cognition in non-musicians with epilepsy but not musicians with epilepsy, compared to healthy musicians and non-musicians (P = 0.029). This suggests a possible neuroprotective effect of music training against the cognitive sequelae of focal epilepsy, and implicates potential training-related cognitive transfer that may be underpinned by enhancement of auditory processes primarily supported by temporo-frontal networks. Furthermore, our results showed that musicians with an earlier age of onset of music training performed better on a composite score of melodic learning and memory compared to non-musicians (P = 0.037), while late-onset musicians did not differ from non-musicians. For most composite scores of music cognition, although no significant group differences were observed, a similar trend was apparent. We discuss these key findings in the context of a proposed model of three interacting dimensions (disease status, music expertise, and cognitive domain), and their implications for clinical practice, music education, and music neuroscience research.
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Affiliation(s)
- Laura J Bird
- Melbourne School of Psychological Sciences, The University of Melbourne, Grattan Street, Parkville, Victoria, Australia.,The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, 245 Burgundy Street, Heidelberg, Victoria, Australia
| | - Graeme D Jackson
- The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, 245 Burgundy Street, Heidelberg, Victoria, Australia.,Department of Medicine, The University of Melbourne, Grattan Street, Parkville, Victoria, Australia
| | - Sarah J Wilson
- Melbourne School of Psychological Sciences, The University of Melbourne, Grattan Street, Parkville, Victoria, Australia.,The Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, 245 Burgundy Street, Heidelberg, Victoria, Australia
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9
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Fan X, Gaspard N, Legros B, Lucchetti F, Ercek R, Nonclercq A. Seizure evolution can be characterized as path through synaptic gain space of a neural mass model. Eur J Neurosci 2018; 48:3097-3112. [PMID: 30194874 DOI: 10.1111/ejn.14142] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 08/08/2018] [Accepted: 08/29/2018] [Indexed: 11/30/2022]
Abstract
Physiologically based models could facilitate better understanding of mechanisms underlying epileptic seizures. In this paper, we attempt to reveal the dynamic evolution of intracranial EEG activity during epileptic seizures based on synaptic gain identification procedure of a neural mass model. The distribution of average excitatory, slow and fast inhibitory synaptic gain in the parameter space and their temporal evolution, i.e., the path through the model parameter space, were analyzed in thirty seizures from ten temporal lobe epileptic patients. Results showed that the synaptic gain values located roughly on a plane before seizure onset, dispersed during seizure and returned to the plane when seizure terminated. Cluster analysis was performed on seizure paths and demonstrated consistency in synaptic gain evolution across different seizures from the individual patient. Furthermore, two patient groups were identified, each one corresponding to a specific synaptic gain evolution in the parameter space during a seizure. Results were validated by a bootstrapping approach based on comparison with random paths. The differences in the path revealed variations in EEG dynamics for patients despite showing identical seizure onset pattern. Our approach may have the potential to classify the epileptic patients into subgroups based on different mechanisms revealed by subtle changes in synaptic gains and further enable more robust decisions regarding treatment strategy.
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Affiliation(s)
- Xiaoya Fan
- Bio, Electro And Mechanical Systems (BEAMS), Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Nicolas Gaspard
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Benjamin Legros
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Federico Lucchetti
- Bio, Electro And Mechanical Systems (BEAMS), Université Libre de Bruxelles (ULB), Brussels, Belgium.,Laboratoire de Neurophysiologie Sensorielle et Cognitive, Hôpital Brugmann, Brussels, Belgium
| | - Rudy Ercek
- Laboratories of Image, Signal Processing and Acoustics (LISA), Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Antoine Nonclercq
- Bio, Electro And Mechanical Systems (BEAMS), Université Libre de Bruxelles (ULB), Brussels, Belgium
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A Yassine I, M Eldeeb W, A Gad K, A Ashour Y, A Yassine I, O Hosny A. Cognitive functions, electroencephalographic and diffusion tensor imaging changes in children with active idiopathic epilepsy. Epilepsy Behav 2018; 84:135-141. [PMID: 29800799 DOI: 10.1016/j.yebeh.2018.04.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2018] [Revised: 03/12/2018] [Accepted: 04/29/2018] [Indexed: 10/16/2022]
Abstract
INTRODUCTION Neurocognitive impairment represents one of the most common comorbidities occurring in children with idiopathic epilepsy. Diagnosis of the idiopathic form of epilepsy requires the absence of any macrostructural abnormality in the conventional MRI. Though changes can be seen at the microstructural level imaged using advanced techniques such as the Diffusion Tensor Imaging (DTI). AIM OF THE WORK The aim of this work is to study the correlation between the microstructural white matter DTI findings, the electroencephalographic changes and the cognitive dysfunction in children with active idiopathic epilepsy. METHODS A comparative cross-sectional study, included 60 children with epilepsy based on the Stanford-Binet 5th Edition Scores was conducted. Patients were equally assigned to normal cognitive function or cognitive dysfunction groups. The history of the epileptic condition was gathered via personal interviews. All patients underwent brain Electroencephalography (EEG) and DTI, which was analyzed using FSL. RESULTS The Fractional Anisotropy (FA) was significantly higher whereas the Mean Diffusivity (MD) was significantly lower in the normal cognitive function group than in the cognitive dysfunction group. This altered microstructure was related to the degree of the cognitive performance of the studied children with epilepsy. The microstructural alterations of the neural fibers in children with epilepsy and cognitive dysfunction were significantly related to the younger age of onset of epilepsy, the poor control of the clinical seizures, and the use of multiple antiepileptic medications. CONCLUSION Children with epilepsy and normal cognitive functions differ in white matter integrity, measured using DTI, compared with children with cognitive dysfunction. These changes have important cognitive consequences.
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Affiliation(s)
- Imane A Yassine
- Neurology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.
| | - Waleed M Eldeeb
- Neurology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
| | - Khaled A Gad
- Diagnostic Radiology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
| | - Yossri A Ashour
- Neurology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
| | - Inas A Yassine
- Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Egypt
| | - Ahmed O Hosny
- Neurology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
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Deleo F, Thom M, Concha L, Bernasconi A, Bernhardt BC, Bernasconi N. Histological and MRI markers of white matter damage in focal epilepsy. Epilepsy Res 2017; 140:29-38. [PMID: 29227798 DOI: 10.1016/j.eplepsyres.2017.11.010] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 11/10/2017] [Accepted: 11/20/2017] [Indexed: 12/21/2022]
Abstract
Growing evidence highlights the importance of white matter in the pathogenesis of focal epilepsy. Ex vivo and post-mortem studies show pathological changes in epileptic patients in white matter myelination, axonal integrity, and cellular composition. Diffusion-weighted MRI and its analytical extensions, particularly diffusion tensor imaging (DTI), have been the most widely used technique to image the white matter in vivo for the last two decades, and have shown microstructural alterations in multiple tracts both in the vicinity and at distance from the epileptogenic focus. These techniques have also shown promising ability to predict cognitive status and response to pharmacological or surgical treatments. More recently, the hypothesis that focal epilepsy may be more adequately described as a system-level disorder has motivated a shift towards the study of macroscale brain connectivity. This review will cover emerging findings contributing to our understanding of white matter alterations in focal epilepsy, studied by means of histological and ultrastructural analyses, diffusion MRI, and large-scale network analysis. Focus is put on temporal lobe epilepsy and focal cortical dysplasia. This topic was addressed in a special interest group on neuroimaging at the 70th annual meeting of the American Epilepsy Society, held in Houston December 2-6, 2016.
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Affiliation(s)
- Francesco Deleo
- NeuroImaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Canada
| | - Maria Thom
- Division of Neuropathology and Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Luis Concha
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Andrea Bernasconi
- NeuroImaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Canada
| | - Boris C Bernhardt
- NeuroImaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Canada; Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute, McGill University, Canada
| | - Neda Bernasconi
- NeuroImaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Canada.
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Del Gaizo J, Mofrad N, Jensen JH, Clark D, Glenn R, Helpern J, Bonilha L. Using machine learning to classify temporal lobe epilepsy based on diffusion MRI. Brain Behav 2017; 7:e00801. [PMID: 29075561 PMCID: PMC5651385 DOI: 10.1002/brb3.801] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 06/23/2017] [Accepted: 07/06/2017] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND It is common for patients diagnosed with medial temporal lobe epilepsy (TLE) to have extrahippocampal damage. However, it is unclear whether microstructural extrahippocampal abnormalities are consistent enough to enable classification using diffusion MRI imaging. Therefore, we implemented a support vector machine (SVM)-based method to predict TLE from three different imaging modalities: mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA). While MD and FA can be calculated from traditional diffusion tensor imaging (DTI), MK requires diffusion kurtosis imaging (DKI). METHODS Thirty-two TLE patients and 36 healthy controls underwent DKI imaging. To measure predictive capability, a fivefold cross-validation (CV) was repeated for 1000 iterations. An ensemble of SVM models, each with a different regularization value, was trained with the subject images in the training set, and had performance assessed on the test set. The different regularization values were determined using a Bayesian-based method. RESULTS Mean kurtosis achieved higher accuracy than both FA and MD on every iteration, and had far superior average accuracy: 0.82 (MK), 0.68 (FA), and 0.51 (MD). Finally, the MK voxels with the highest coefficients in the predictive models were distributed within the inferior medial aspect of the temporal lobes. CONCLUSION These results corroborate our earlier publications which indicated that DKI shows more promise in identifying TLE-associated pathological features than DTI. Also, the locations of the contributory MK voxels were in areas with high fiber crossing and complex fiber anatomy. These traits result in non-Gaussian water diffusion, and hence render DTI less likely to detect abnormalities. If the location of consistent microstructural abnormalities can be better understood, then it may be possible in the future to identify the various phenotypes of TLE. This is important since treatment outcome varies dependent on type of TLE.
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Affiliation(s)
- John Del Gaizo
- Department of Neurology Medical University of South Carolina Charleston SC USA
| | - Neda Mofrad
- Department of Neurology Medical University of South Carolina Charleston SC USA
| | - Jens H Jensen
- Department of Radiology and Radiological Science Medical University of South Carolina Charleston SC USA
| | - David Clark
- Department of Neurology Medical University of South Carolina Charleston SC USA.,Ralph H. Johnson VA Medical Center Charleston SC USA
| | - Russell Glenn
- Department of Radiology and Radiological Science Medical University of South Carolina Charleston SC USA
| | - Joseph Helpern
- Department of Radiology and Radiological Science Medical University of South Carolina Charleston SC USA
| | - Leonardo Bonilha
- Department of Neurology Medical University of South Carolina Charleston SC USA
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Abstract
In recent years, the field of neuroimaging has undergone dramatic development. Specifically, of importance for clinicians and researchers managing patients with epilepsies, new methods of brain imaging in search of the seizure-producing abnormalities have been implemented, and older methods have undergone additional refinement. Methodology to predict seizure freedom and cognitive outcome has also rapidly progressed. In general, the image data processing methods are very different and more complicated than even a decade ago. In this review, we identify the recent developments in neuroimaging that are aimed at improved management of epilepsy patients. Advances in structural imaging, diffusion imaging, fMRI, structural and functional connectivity, hybrid imaging methods, quantitative neuroimaging, and machine-learning are discussed. We also briefly summarize the potential new developments that may shape the field of neuroimaging in the near future and may advance not only our understanding of epileptic networks as the source of treatment-resistant seizures but also better define the areas that need to be treated in order to provide the patients with better long-term outcomes.
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14
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Slinger G, Sinke MRT, Braun KPJ, Otte WM. White matter abnormalities at a regional and voxel level in focal and generalized epilepsy: A systematic review and meta-analysis. NEUROIMAGE-CLINICAL 2016; 12:902-909. [PMID: 27882296 PMCID: PMC5114611 DOI: 10.1016/j.nicl.2016.10.025] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Revised: 10/25/2016] [Accepted: 10/31/2016] [Indexed: 12/24/2022]
Abstract
Objective Since the introduction of diffusion tensor imaging, white matter abnormalities in epilepsy have been studied extensively. However, the affected areas reported, the extent of abnormalities and the association with relevant clinical parameters are highly variable. We aimed to obtain a more consistent estimate of white matter abnormalities and their association with clinical parameters in different epilepsy types. Methods We systematically searched for differences in white matter fractional anisotropy and mean diffusivity, at regional and voxel level, between people with epilepsy and healthy controls. Meta-analyses were used to quantify the directionality and extent of these differences. Correlations between white matter differences and age of epilepsy onset, duration of epilepsy and sex were assessed with meta-regressions. Results Forty-two studies, with 1027 people with epilepsy and 1122 controls, were included with regional data. Sixteen voxel-based studies were also included. People with temporal or frontal lobe epilepsy had significantly decreased fractional anisotropy (Δ –0.021, 95% confidence interval –0.026 to –0.016) and increased mean diffusivity (Δ0.026 × 10–3 mm2/s, 0.012 to 0.039) in the commissural, association and projection white matter fibers. White matter was much less affected in generalized epilepsy. White matter changes in people with focal epilepsy correlated with age at onset, epilepsy duration and sex. Significance This study provides a better estimation of white matter changes in different epilepsies. Effects are particularly found in people with focal epilepsy. Correlations with the duration of focal epilepsy support the hypothesis that these changes are, at least partly, a consequence of seizures and may warrant early surgery. Future studies need to guarantee adequate group sizes, as white matter differences in epilepsy are small. White matter FA and MD are more affected in focal than in generalized epilepsy. Epilepsy subtypes show distinct patterns of affected white matter regions. White matter integrity is altered both ipsi- and contralaterally in focal epilepsy. White matter changes in focal epilepsy seem to be a consequence of seizures.
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Affiliation(s)
- Geertruida Slinger
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, The Netherlands
| | - Michel R T Sinke
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, The Netherlands
| | - Kees P J Braun
- Department of Pediatric Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, The Netherlands; Department of Pediatric Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
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Doucet GE, He X, Sperling M, Sharan A, Tracy JI. Gray Matter Abnormalities in Temporal Lobe Epilepsy: Relationships with Resting-State Functional Connectivity and Episodic Memory Performance. PLoS One 2016; 11:e0154660. [PMID: 27171178 PMCID: PMC4865085 DOI: 10.1371/journal.pone.0154660] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 04/15/2016] [Indexed: 11/19/2022] Open
Abstract
Temporal lobe epilepsy (TLE) affects multiple brain regions through evidence from both structural (gray matter; GM) and functional connectivity (FC) studies. We tested whether these structural abnormalities were associated with FC abnormalities, and assessed the ability of these measures to explain episodic memory impairments in this population. A resting-state and T1 sequences were acquired on 94 (45 with mesial temporal pathology) TLE patients and 50 controls, using magnetic resonance imaging (MRI) technique. A voxel-based morphometry analysis was computed to determine the GM volume differences between groups (right, left TLE, controls). Resting-state FC between the abnormal GM volume regions was computed, and compared between groups. Finally, we investigated the relation between EM, GM and FC findings. Patients with and without temporal pathology were analyzed separately. The results revealed reduced GM volume in multiple regions in the patients relative to the controls. Using FC, we found the abnormal GM regions did not display abnormal functional connectivity. Lastly, we found in left TLE patients, verbal episodic memory was associated with abnormal left posterior hippocampus volume, while in right TLE, non-verbal episodic memory was better predicted by resting-state FC measures. This study investigated TLE abnormalities using a multi-modal approach combining GM, FC and neurocognitive measures. We did not find that the GM abnormalities were functionally or abnormally connected during an inter-ictal resting state, which may reflect a weak sensitivity of functional connectivity to the epileptic network. We provided evidence that verbal and non-verbal episodic memory in left and right TLE patients may have distinct relationships with structural and functional measures. Lastly, we provide data suggesting that in the setting of occult, non-lesional right TLE pathology, a coupling of structural and functional abnormalities in extra-temporal/non-ictal regions is necessary to produce reductions in episodic memory recall. The latter, in particular, demonstrates the complex structure/function interactions at work when trying to understand cognition in TLE, suggesting that subtle network effects can emerge bearing specific relationships to hemisphere and the type of pathology.
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Affiliation(s)
- Gaelle E. Doucet
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Xiaosong He
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Michael Sperling
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Ashwini Sharan
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Joseph I. Tracy
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
- * E-mail:
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Sone D, Ota M, Yokoyama K, Sumida K, Kimura Y, Imabayashi E, Matsuda H, Sato N. Noninvasive evaluation of the correlation between regional cerebral blood flow and intraventricular brain temperature in temporal lobe epilepsy. Magn Reson Imaging 2016; 34:451-4. [DOI: 10.1016/j.mri.2015.12.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 12/14/2015] [Indexed: 11/16/2022]
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Whelan CD, Alhusaini S, O'Hanlon E, Cheung M, Iyer PM, Meaney JF, Fagan AJ, Boyle G, Delanty N, Doherty CP, Cavalleri GL. White matter alterations in patients with MRI-negative temporal lobe epilepsy and their asymptomatic siblings. Epilepsia 2015; 56:1551-61. [DOI: 10.1111/epi.13103] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/06/2015] [Indexed: 12/27/2022]
Affiliation(s)
- Christopher D. Whelan
- Molecular and Cellular Therapeutics Department; Royal College of Surgeons in Ireland; Dublin Ireland
- Imaging Genetics Center; Mark and Mary Stevens Neuroimaging and Informatics Institute; University of Southern California; Los Angeles California U.S.A
| | - Saud Alhusaini
- Molecular and Cellular Therapeutics Department; Royal College of Surgeons in Ireland; Dublin Ireland
| | - Erik O'Hanlon
- Department of Psychiatry; Royal College of Surgeons in Ireland; Dublin 2 Ireland
| | - Maria Cheung
- Molecular and Cellular Therapeutics Department; Royal College of Surgeons in Ireland; Dublin Ireland
| | | | - James F. Meaney
- Centre for Advanced Medical Imaging (CAMI); St. James's Hospital; Dublin Ireland
| | - Andrew J. Fagan
- Centre for Advanced Medical Imaging (CAMI); St. James's Hospital; Dublin Ireland
| | - Gerard Boyle
- Centre for Advanced Medical Imaging (CAMI); St. James's Hospital; Dublin Ireland
| | - Norman Delanty
- Molecular and Cellular Therapeutics Department; Royal College of Surgeons in Ireland; Dublin Ireland
- Division of Neurology; Beaumont Hospital; Dublin Ireland
| | | | - Gianpiero L. Cavalleri
- Molecular and Cellular Therapeutics Department; Royal College of Surgeons in Ireland; Dublin Ireland
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Pustina D, Avants B, Sperling M, Gorniak R, He X, Doucet G, Barnett P, Mintzer S, Sharan A, Tracy J. Predicting the laterality of temporal lobe epilepsy from PET, MRI, and DTI: A multimodal study. Neuroimage Clin 2015; 9:20-31. [PMID: 26288753 PMCID: PMC4536304 DOI: 10.1016/j.nicl.2015.07.010] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Revised: 07/11/2015] [Accepted: 07/19/2015] [Indexed: 01/09/2023]
Abstract
Pre-surgical evaluation of patients with temporal lobe epilepsy (TLE) relies on information obtained from multiple neuroimaging modalities. The relationship between modalities and their combined power in predicting the seizure focus is currently unknown. We investigated asymmetries from three different modalities, PET (glucose metabolism), MRI (cortical thickness), and diffusion tensor imaging (DTI; white matter anisotropy) in 28 left and 30 right TLE patients (LTLE and RTLE). Stepwise logistic regression models were built from each modality separately and from all three combined, while bootstrapped methods and split-sample validation verified the robustness of predictions. Among all multimodal asymmetries, three PET asymmetries formed the best predictive model (100% success in full sample, >95% success in split-sample validation). The combinations of PET with other modalities did not perform better than PET alone. Probabilistic classifications were obtained for new clinical cases, which showed correct lateralization for 7/7 new TLE patients (100%) and for 4/5 operated patients with discordant or non-informative PET reports (80%). Metabolism showed closer relationship with white matter in LTLE and closer relationship with gray matter in RTLE. Our data suggest that metabolism is a powerful modality that can predict seizure laterality with high accuracy, and offers high value for automated predictive models. The side of epileptogenic focus can affect the relationship of metabolism with brain structure. The data and tools necessary to obtain classifications for new TLE patients are made publicly available.
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Affiliation(s)
- Dorian Pustina
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Brian Avants
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Michael Sperling
- Department of Neurology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
| | - Richard Gorniak
- Department of Radiology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
| | - Xiaosong He
- Department of Neurology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
| | - Gaelle Doucet
- Department of Neurology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
| | - Paul Barnett
- Department of Neurology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
| | - Scott Mintzer
- Department of Neurology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
| | - Ashwini Sharan
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, USA
| | - Joseph Tracy
- Department of Neurology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
- Department of Radiology, Thomas Jefferson University/Sidney Kimmel Medical College, Philadelphia, PA 19107, USA
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Rodríguez-Cruces R, Concha L. White matter in temporal lobe epilepsy: clinico-pathological correlates of water diffusion abnormalities. Quant Imaging Med Surg 2015; 5:264-78. [PMID: 25853084 DOI: 10.3978/j.issn.2223-4292.2015.02.06] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 02/14/2015] [Indexed: 02/05/2023]
Abstract
Using magnetic resonance imaging, it is possible to measure the behavior of diffusing water molecules, and the metrics derived can be used as indirect markers of tissue micro-architectural properties. Numerous reports have demonstrated that patients with temporal lobe epilepsy (TLE) have water diffusion abnormalities in several white matter structures located within and beyond the epileptogenic temporal lobe, showing that TLE is not a focal disorder, but rather a brain network disease. Differences in severity and spatial extent between patients with or without mesial temporal sclerosis (MTS), as well as differences related to hemispheric seizure onset, are suggestive of different pathophysiological mechanisms behind different forms of TLE, which in turn result in specific cognitive disabilities. The biological interpretation of diffusion abnormalities is based on a wealth of information from animal models of white matter damage, and is supported by recent reports that directly correlate diffusion metrics with histological characteristics of surgical specimens of TLE patients. Thus, there is now more evidence showing that the increased mean diffusivity (MD) and concomitant reductions of diffusion anisotropy that are frequently observed in several white matter bundles in TLE patients reflect reduced axonal density (increased extra-axonal space) due to smaller-caliber axons, and abnormalities in the myelin sheaths of the remaining axons. Whether these histological and diffusion features are a predisposing factor for epilepsy or secondary to seizures is still uncertain; some reports suggest the latter. This article summarizes recent findings in this field and provides a synopsis of the histological features seen most frequently in post-surgical specimens of TLE patients in an effort to aid the interpretation of white matter diffusion abnormalities.
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Affiliation(s)
- Raúl Rodríguez-Cruces
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México
| | - Luis Concha
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México
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