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Neal EG, Schimmel S, George Z, Monsour M, Alayli A, Lockard G, Piper K, Maciver S, Vale FL, Bezchlibnyk YB. No change in network connectivity measurements between separate rsfMRI acquisition times. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1342161. [PMID: 38292021 PMCID: PMC10823025 DOI: 10.3389/fnetp.2024.1342161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/05/2024] [Indexed: 02/01/2024]
Abstract
The role of resting state functional MRI (rsfMRI) is increasing in the field of epilepsy surgery because it is possible to interpolate network connectivity patterns across the brain with a high degree of spatial resolution. Prior studies have shown that by rsfMRI with scalp electroencephalography (EEG), an epileptogenic network can be modeled and visualized with characteristic patterns of connectivity that are relevant to both seizure-related and neuropsychological outcomes after surgery. The aim of this study is to show that a 5-min acquisition time provides reproducible results related to the relevant connectivity metrics when compared to a separately acquired 5-min scan. Fourteen separate rsfMRI sessions from ten different patients were used for comparison, comprised of patients with temporal lobe epilepsy both pre- and post-operation. Results showed that there was no significant difference in any of the connectivity metrics when comparing both 5-min scans to each other. These data support the continued use of a 5-min scan for epileptogenic network modeling in future studies because the inter-scan variability is sufficiently low as not to alter the output metrics characterizing the network connectivity.
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Affiliation(s)
- Elliot G. Neal
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Samantha Schimmel
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Zeegan George
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Molly Monsour
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Adam Alayli
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Gavin Lockard
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Keaton Piper
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
| | - Stephanie Maciver
- Department of Neurology, Advent Health Tampa, Tampa, FL, United States
| | - Fernando L. Vale
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Yarema B. Bezchlibnyk
- Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL, United States
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Doss DJ, Johnson GW, Englot DJ. Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery. Neurosurg Clin N Am 2024; 35:61-72. [PMID: 38000842 PMCID: PMC10676462 DOI: 10.1016/j.nec.2023.09.001] [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] [Indexed: 11/26/2023]
Abstract
Epilepsy surgery is a potentially curative treatment of drug-resistant epilepsy that has remained underutilized both due to inadequate referrals and incomplete localization hypotheses. The complexity of patients evaluated for epilepsy surgery has increased, thus new approaches are necessary to treat these patients. The paradigm of epilepsy surgery has evolved to match this challenge, now considering the entire seizure network with the goal of disrupting it through resection, ablation, neuromodulation, or a combination. The network paradigm has the potential to aid in identification of the seizure network as well as treatment selection.
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Affiliation(s)
- Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA; Department of Neurological Surgery, Vanderbilt University Medical Center, 1161 21st Avenue South, T4224 Medical Center North, Nashville, TN 37232, USA; Department of Electrical and Computer Engineering, Vanderbilt University, PMB 351824, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Department of Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, Nashville, TN 37232, USA.
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Syed M, Miao J, Sathe A, Kang K, Manmatharayan A, Kogan M, Matias CM, Sharan A, Alizadeh M. Profiles of resting state functional connectivity in temporal lobe epilepsy associated with post-laser interstitial thermal therapy seizure outcomes and semiologies. FRONTIERS IN NEUROIMAGING 2023; 2:1201682. [PMID: 38025313 PMCID: PMC10665565 DOI: 10.3389/fnimg.2023.1201682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 10/06/2023] [Indexed: 12/01/2023]
Abstract
Introduction It is now understood that in focal epilepsy, impacted neural regions are not limited to the epileptogenic zone. As such, further investigation into the underlying functional connectivity (FC) patterns in those enduring Temporal Lobe Epilepsy (TLE) with Mesial Temporal Sclerosis (MTS) is imperative to understanding the intricacies of the disease. Methods The rsfMRIs of 17 healthy participants, 10 left-sided TLE-MTS patients with a pre-operative history of focal impaired awareness seizures (FIA), and 13 left-sided TLE-MTS patients with a pre-operative history of focal aware seizures (FA) were compared to determine the existence of distinct FC patterns with respect to seizure types. Similarly, the rsfMRIs of the above-mentioned healthy participants, 16 left-sided TLE-MTS individuals who were seizure-free (SF) 12 months postoperatively, and 16 left-sided TLE-MTS persons without seizure freedom (nSF) were interrogated. The ROI-to-ROI connectivity analysis included a total of 175 regions of interest (ROIs) and accounted for both age and duration of epileptic activity. Significant correlations were determined via two-sample t-tests and Bonferroni correction (α = 0.05). Results Comparisons of FA and FIA groups depicted significant correlations between the contralateral anterior cingulate gyrus, subgenual region, and the contralateral cerebellum, lobule III (p-value = 2.26e-4, mean z-score = -0.05 ± 0.28, T = -4.23). Comparisons of SF with nSF depicted two significantly paired-ROIs; the contralateral amygdala and the contralateral precuneus (p-value = 2.9e-5, mean z-score = -0.12 ± 0.19, T = 4.98), as well as the contralateral locus coeruleus and the ipsilateral intralaminar nucleus (p-value= 1.37e-4, mean z-score = 0.06 ± 0.17, T = -4.41). Significance FC analysis proves to be a lucrative modality for exploring unique signatures with respect to seizure types and postoperative outcomes. By furthering our understanding of the differences between epileptic phenotypes, we can achieve improvement in future treatment modalities not limited to targeting advancements.
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Affiliation(s)
- Mashaal Syed
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Jingya Miao
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Anish Sathe
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Kichang Kang
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Arichena Manmatharayan
- Department of Neurology, Detroit Medical Center, University Health Center, Detroit, MI, United States
| | - Michael Kogan
- Department of Neurological Surgery, University of New Mexico, Albuquerque, NM, United States
| | - Caio M. Matias
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Ashwini Sharan
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Mahdi Alizadeh
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
- Thomas Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
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Jiang JW, Narasimhan S, Johnson GW, González HFJ, Doss DJ, Shless JS, Paulo DL, Terry DP, Chang C, Morgan VL, Englot DJ. Abnormal functional connectivity of the posterior hypothalamus and other arousal regions in surgical temporal lobe epilepsy. J Neurosurg 2023; 139:640-650. [PMID: 36807210 PMCID: PMC10432570 DOI: 10.3171/2023.1.jns221452] [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: 07/28/2022] [Accepted: 01/05/2023] [Indexed: 02/23/2023]
Abstract
OBJECTIVE This study sought to characterize resting-state functional MRI (fMRI) connectivity patterns of the posterior hypothalamus (pHTH) and the nucleus basalis of Meynert (NBM) in surgical patients with mesial temporal lobe epilepsy (mTLE), and to investigate potential correlations between functional connectivity of these arousal regions and neurocognitive performance. METHODS The study evaluated resting-state fMRI in 60 patients with preoperative mTLE and in 95 healthy controls. The authors first conducted voxel-wise connectivity analyses seeded from the pHTH, combined anterior and tuberal hypothalamus (atHTH; i.e., the rest of the hypothalamus), and the NBM ipsilateral (ipsiNBM) and contralateral (contraNBM) to the epileptogenic zone. Based on these results, the authors included the pHTH, ipsiNBM, and frontoparietal neocortex in a network-based statistic (NBS) analysis to elucidate a network that best distinguishes patients from controls. The connections involving the pHTH and ipsiNBM from this network were included in age-corrected pairwise region of interest (ROI) analysis, along with connections between arousal structures, including the pHTH, ipsiNBM, and brainstem arousal regions. Finally, patient functional connectivity was correlated with clinical neurocognitive testing scores for IQ as well as attention and concentration tests. RESULTS The voxel-wise analysis demonstrated that the pHTH, when compared with the atHTH, showed more widespread functional connectivity decreases in surgical mTLE patients when compared with controls. It was also observed that the ipsiNBM, but not the contraNBM, showed decreased functional connectivity in mTLE. The NBS analysis uncovered a perturbed network of frontoparietal regions, the pHTH, and ipsiNBM that distinguishes patients from controls. Age-corrected ROI analysis revealed functional connectivity decreases between the pHTH and bilateral superior frontal gyri, medial orbitofrontal cortices, rostral anterior cingulate cortices, and inferior parietal cortices in mTLE when compared with controls. For the ipsiNBM, there was reduced connectivity with bilateral medial orbitofrontal and rostral anterior cingulate cortices. Age-corrected ROI analysis also demonstrated upstream connectivity decreases from controls between the pHTH and the brainstem arousal regions, cuneiform/subcuneiform (CSC) nuclei, and ventral tegmental area, as well as the ipsiNBM and CSC nuclei. Reduced functional connectivity was also detected between the pHTH and ipsiNBM. Lastly, neurocognitive test scores for attention and concentration were found to be positively correlated with the functional connectivity between the pHTH and ipsiNBM, suggesting worse performance associated with connectivity perturbations. CONCLUSIONS This study demonstrated perturbed resting-state functional connectivity of arousal regions in surgical mTLE and is one of the first investigations to demonstrate decreased functional connectivity of the pHTH with frontoparietal regions and other arousal regions. Connectivity disturbances in arousal regions may contribute to neurocognitive deficits in surgical mTLE patients.
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Affiliation(s)
- Jasmine W. Jiang
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
| | - Saramati Narasimhan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
| | - Graham W. Johnson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Hernán F. J. González
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Derek J. Doss
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Jared S. Shless
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
| | - Douglas P. Terry
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
| | - Catie Chang
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee
| | - Victoria L. Morgan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Neurology, Vanderbilt University Medical Center, Nashville
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville
| | - Dario J. Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee
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Lucas A, Cornblath EJ, Sinha N, Caciagli L, Hadar P, Tranquille A, Stein JM, Das S, Davis KA. Improved Seizure Onset-Zone Lateralization in Temporal Lobe Epilepsy using 7T Resting-State fMRI: A Direct Comparison with 3T. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.06.23291025. [PMID: 37333141 PMCID: PMC10275004 DOI: 10.1101/2023.06.06.23291025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Objective Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high-field strengths (≥7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI. Methods We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs-fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths. Results Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (pFDR=0.008) than at 3T (pFDR=0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism. Significance We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
| | | | | | | | - Peter Hadar
- Department of Neurology, Massachussets General Hospital (work conducted while at the University of Pennsylvania)
| | | | - Joel M Stein
- Department of Radiology, University of Pennsylvania
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Gholipour T, DeMarco A, You X, Englot DJ, Turkeltaub PE, Koubeissi MZ, Gaillard WD, Morgan VL. Functional anomaly mapping lateralizes temporal lobe epilepsy with high accuracy in individual patients. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.05.23285034. [PMID: 36798218 PMCID: PMC9934715 DOI: 10.1101/2023.02.05.23285034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE) is associated with variable dysfunction beyond the temporal lobe. We used functional anomaly mapping (FAM), a multivariate machine learning approach to resting state fMRI analysis to measure subcortical and cortical functional aberrations in patients with mTLE. We also examined the value of individual FAM in lateralizing the hemisphere of seizure onset in mTLE patients. Methods: Patients and controls were selected from an existing imaging and clinical database. After standard preprocessing of resting state fMRI, time-series were extracted from 400 cortical and 32 subcortical regions of interest (ROIs) defined by atlases derived from functional brain organization. Group-level aberrations were measured by contrasting right (RTLE) and left (LTLE) patient groups to controls in a support vector regression models, and tested for statistical reliability using permutation analysis. Individualized functional anomaly maps (FAMs) were generated by contrasting individual patients to the control group. Half of patients were used for training a classification model, and the other half for estimating the accuracy to lateralize mTLE based on individual FAMs. Results: Thirty-two right and 14 left mTLE patients (33 with evidence of hippocampal sclerosis on MRI) and 94 controls were included. At group levels, cortical regions affiliated with limbic and somatomotor networks were prominent in distinguishing RTLE and LTLE from controls. At individual levels, most TLE patients had high anomaly in bilateral mesial temporal and medial parietooccipital default mode regions. A linear support vector machine trained on 50% of patients could accurately lateralize mTLE in remaining patients (median AUC =1.0 [range 0.97-1.0], median accuracy = 96.87% [85.71-100Significance: Functional anomaly mapping confirms widespread aberrations in function, and accurately lateralizes mTLE from resting state fMRI. Future studies will evaluate FAM as a non-invasive localization method in larger datasets, and explore possible correlations with clinical characteristics and disease course.
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Akıncı T, Gündüz A, Özkara Ç, Kızıltan ME. The Thalamic and Intracortical Inhibitory Function of Somatosensory System Is Unchanged in Mesial Temporal Lobe Epilepsy With Hippocampal Sclerosis. J Clin Neurophysiol 2023; 40:45-52. [PMID: 33675312 DOI: 10.1097/wnp.0000000000000839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
PURPOSE In mesial temporal lobe epilepsy with hippocampal sclerosis, there is parietal atrophy and cognitive involvement in related domains. In this context, we hypothesized that inhibitory input into somatosensory cortex and thalamus may be increased in these patients, which could improve after epilepsy surgery. Thus, we analyzed the inhibitory function of somatosensory system by studying surround inhibition (SI) and recovery function of somatosensory evoked potentials in patients with mesial temporal lobe epilepsy with hippocampal sclerosis. METHODS Nine patients with unoperated mesial temporal lobe epilepsy with hippocampal sclerosis, 10 patients who underwent epilepsy surgery, and 12 healthy subjects were included. For SI of somatosensory evoked potentials, we recorded somatosensory evoked potentials after stimulating median or ulnar nerve at wrist separately and after median and ulnar nerves simultaneously and calculated SI% in all participants. For recovery function of somatosensory evoked potentials, paired stimulation of median nerve at 40- and 100-millisecond intervals was performed. We compared the findings among groups. As a secondary analysis, we determined the outliers in the patient group and analyzed the relation to the clinical findings. RESULTS The mean SI% or recovery function was similar among three groups. However, there were five patients with SI loss on normal side in the patient group, which was related to the antiseizure drugs. CONCLUSIONS In contrast to our hypothesis, both intracortical (SI) and thalamic/striatal (recovery function) inhibitory modulation of the somatosensory cortex was not altered in mesial temporal lobe epilepsy with hippocampal sclerosis and did not differ in surgical and nonsurgical groups.
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Affiliation(s)
- Tuba Akıncı
- Department of Neurology, Cerrahpaşa Medical Faculty, Istanbul University-Cerrahpaşa (I.U.C), Istanbul, Turkey
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Narasimhan S, González HFJ, Johnson GW, Wills KE, Paulo DL, Morgan VL, Englot DJ. Functional connectivity between mesial temporal and default mode structures may help lateralize surgical temporal lobe epilepsy. J Neurosurg 2022; 137:1571-1581. [PMID: 35364587 PMCID: PMC9525455 DOI: 10.3171/2022.1.jns212031] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 01/31/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The most common surgically treatable epilepsy syndrome is mesial temporal lobe epilepsy (mTLE). Preoperative noninvasive lateralization of mTLE is challenging in part due to rapid contralateral seizure spread. Abnormal connections in both the mesial temporal lobe and resting-state networks have been described in mTLE, but it is unclear if connectivity between these networks may aid in lateralization. METHODS In 52 patients with left mTLE (LmTLE) or right mTLE (RmTLE) and 52 matched control subjects, the authors acquired 20 minutes of resting-state functional MRI (fMRI) and evaluated functional connectivity of bilateral hippocampi and amygdalae with selected resting-state networks. They used Pearson correlation, network-based statistic, and dynamic causal modeling. Also, to evaluate the clinical utility of a resting-state connectivity model in lateralizing unilateral presurgical mTLE patients, they used receiver operating characteristic curve analysis. RESULTS RmTLE patients demonstrated decreased nondirected connectivity between the right hippocampus and default mode network compared with LmTLE patients and control subjects. Network-based statistic analysis revealed that the network with most decreased connectivity that distinguished LmTLE from RmTLE patients included the right hippocampus and amygdala, right lateral orbitofrontal cortices, and bilateral inferior parietal lobules, precuneus, and medial orbitofrontal cortices. Dynamic causal modeling analysis revealed that cross-hemispheric connectivity between hippocampi and amygdalae was predominantly inward toward the epileptogenic side. A regression model incorporating these connectivity patterns was used to accurately lateralize mTLE patients with an area under the receiver operating characteristic curve of 0.87. CONCLUSIONS Evaluating fMRI connectivity between mesial temporal structures and default mode network may aid in mTLE lateralization, reduce need for intracranial monitoring, and guide surgical planning.
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Affiliation(s)
- Saramati Narasimhan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Hernán F. J. González
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Graham W. Johnson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Kristin E. Wills
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Victoria L. Morgan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Dario J. Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
- Department of Electrical Engineering and Computer Science at Vanderbilt University, Nashville, Tennessee
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Amplitude synchronization of spontaneous activity of medial and lateral temporal gyri reveals altered thalamic connectivity in patients with temporal lobe epilepsy. Sci Rep 2022; 12:18389. [PMID: 36319701 PMCID: PMC9626490 DOI: 10.1038/s41598-022-23297-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 10/29/2022] [Indexed: 12/02/2022] Open
Abstract
In this study, we examined whether amplitude synchronization of medial (MTL) and lateral (LTL) temporal lobes can detect unique alterations in patients with MTL epilepsy (mTLE) with mesial temporal sclerosis (MTS). This was a retrospective study of preoperative resting-state fMRI (rsfMRI) data from 31 patients with mTLE with MTS (age 23-69) and 16 controls (age 21-35). fMRI data were preprocessed based on a multistep preprocessing pipeline and registered to a standard space. Using each subject's T1-weighted scan, the MTL and LTL were automatically segmented, manually revised and then fit to a standard space using a symmetric normalization registration algorithm. Dual regression analysis was applied on preprocessed rsfMRI data to detect amplitude synchronization of medial and lateral temporal segments with the rest of the brain. We calculated the overlapped volume ratio of synchronized voxels within specific target regions including the thalamus (total and bilateral). A general linear model was used with Bonferroni correction for covariates of epilepsy duration and age of patient at scan to statistically compare synchronization in patients with mTLE with MTS and controls, as well as with respect to whether patients remained seizure-free (SF) or not (NSF) after receiving epilepsy surgery. We found increased ipsilateral positive connectivity between the LTLs and the thalamus and contralateral negative connectivity between the MTLs and the thalamus in patients with mTLE with MTS compared to controls. We also found increased asymmetry of functional connectivity between temporal lobe subregions and the thalamus in patients with mTLE with MTS, with increased positive connectivity between the LTL and the lesional-side thalamus as well as increased negative connectivity between the MTL and the nonlesional-side thalamus. This asymmetry was also seen in NSF patients but was not seen in SF patients and controls. Amplitude synchronization was an effective method to detect functional connectivity alterations in patients with mTLE with MTS. Patients with mTLE with MTS overall showed increased temporal-thalamic connectivity. There was increased functional involvement of the thalamus in MTS, underscoring its role in seizure spread. Increased functional thalamic asymmetry patterns in NSF patients may have a potential role in prognosticating patient response to surgery. Elucidating regions with altered functional connectivity to temporal regions can improve understanding of the involvement of different regions in the disease to potentially target for intervention or use for prognosis for surgery. Future studies are needed to examine the effectiveness of using patient-specific abnormalities in patterns to predict surgical outcome.
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Middlebrooks EH, He X, Grewal SS, Keller SS. Neuroimaging and thalamic connectomics in epilepsy neuromodulation. Epilepsy Res 2022; 182:106916. [PMID: 35367691 DOI: 10.1016/j.eplepsyres.2022.106916] [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: 01/11/2022] [Revised: 03/05/2022] [Accepted: 03/27/2022] [Indexed: 11/03/2022]
Abstract
Neuromodulation is an increasingly utilized therapy for the treatment of people with drug-resistant epilepsy. To date, the most common and effective target has been the thalamus, which is known to play a key role in multiple forms of epilepsy. Neuroimaging has facilitated rapid developments in the understanding of functional targets, surgical and programming techniques, and the effects of thalamic stimulation. In this review, the role of neuroimaging in neuromodulation is explored. First, the structural and functional changes of the thalamus in common epilepsy syndromes are discussed as the rationale for neuromodulation of the thalamus. Next, methods for imaging different thalamic nuclei are presented, as well as rationale for the need of direct surgical targeting rather than reliance on traditional stereotactic coordinates. Lastly, we discuss the potential role of neuroimaging in assessing the effects of thalamic stimulation and as a potential biomarker for neuromodulation outcomes.
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Affiliation(s)
- Erik H Middlebrooks
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA; Department of Neurosurgery, Mayo Clinic, Jacksonville, FL, USA.
| | - Xiaosong He
- Department of Psychology, University of Science and Technology of China, Hefei, Anhui, China
| | | | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK
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11
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Gholipour T, You X, Stufflebeam SM, Loew M, Koubeissi MZ, Morgan VL, Gaillard WD. Common functional connectivity alterations in focal epilepsies identified by machine learning. Epilepsia 2022; 63:629-640. [PMID: 34984672 PMCID: PMC9022014 DOI: 10.1111/epi.17160] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 02/04/2023]
Abstract
OBJECTIVE This study was undertaken to identify shared functional network characteristics among focal epilepsies of different etiologies, to distinguish epilepsy patients from controls, and to lateralize seizure focus using functional connectivity (FC) measures derived from resting state functional magnetic resonance imaging (MRI). METHODS Data were taken from 103 adult and 65 pediatric focal epilepsy patients (with or without lesion on MRI) and 109 controls across four epilepsy centers. We used three whole-brain FC measures: parcelwise connectivity matrix, mean FC, and degree of FC. We trained support vector machine models with fivefold cross-validation (1) to distinguish patients from controls and (2) to lateralize the hemisphere of seizure onset in patients. We reported the regions and connections with the highest importance from each model as the common FC differences between the compared groups. RESULTS FC measures related to the default mode and limbic networks had higher importance relative to other networks for distinguishing epilepsy patients from controls. In lateralization models, regions related to somatosensory, visual, default mode, and basal ganglia showed higher importance. The epilepsy versus control classification model trained using a 400-parcel connectivity matrix achieved a median testing accuracy of 75.6% (median area under the curve [AUC] = .83) in repeated independent testing. Lateralization accuracy using the 400-parcel connectivity matrix reached a median accuracy of 64.0% (median AUC = .69). SIGNIFICANCE Machine learning models revealed common FC alterations in a heterogeneous group of patients with focal epilepsies. The distribution of the most altered regions supports the hypothesis that shared functional alteration exists beyond the seizure onset zone and its epileptic network. We showed that FC measures can distinguish patients from controls, and further lateralize focal epilepsies. Future studies are needed to confirm these findings by using larger numbers of epilepsy patients.
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Affiliation(s)
- Taha Gholipour
- Department of Neurology, George Washington University, Washington, District of Columbia, USA.,Center for Neuroscience, Children's National Hospital, Washington, District of Columbia, USA.,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Xiaozhen You
- Center for Neuroscience, Children's National Hospital, Washington, District of Columbia, USA
| | - Steven M Stufflebeam
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Murray Loew
- Department of Biomedical Engineering, George Washington University, Washington, District of Columbia, USA
| | - Mohamad Z Koubeissi
- Department of Neurology, George Washington University, Washington, District of Columbia, USA
| | | | - William D Gaillard
- Department of Neurology, George Washington University, Washington, District of Columbia, USA.,Center for Neuroscience, Children's National Hospital, Washington, District of Columbia, USA
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12
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Functional connectivity of hippocampus in temporal lobe epilepsy depends on hippocampal dominance: a systematic review of the literature. J Neurol 2022; 269:221-232. [PMID: 33564915 DOI: 10.1007/s00415-020-10391-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 12/27/2020] [Accepted: 12/28/2020] [Indexed: 01/03/2023]
Abstract
BACKGROUND Lateralized alterations in hippocampal function in the resting-state have been demonstrated for patients with temporal lobe epilepsy (TLE). However, resting-state fMRI of the hippocampus has yet to be substantiated as an adjunct to standard pre-operative assessments of the seizure focus. OBJECTIVE Here we report the results of a systematic review of resting-state fMRI studies investigating laterality of hippocampal network connectivity in TLE patients. METHODS A search of the PubMed, SCOPUS, Web of Science, and Embase databases for full-length articles written in English was conducted through June 2020 using the following terms: 'resting state fMRI,' 'hippocampus,' 'epilepsy,' and 'laterality.' RESULTS Our literature search yielded a total of 42 papers. After excluding studies that did not include patients with epilepsy, utilize resting-state fMRI, or explore the relationship between functional connectivity and disease lateralization, 20 publications were selected for inclusion. From these studies, a total of 528 patients, 258 with left TLE and 270 with right TLE, and 447 healthy controls were included. Of the 20 studies included, 18 found that patients with TLE demonstrated decreased hippocampal functional connectivity ipsilateral to the epileptogenic focus and 10 additionally reported increased hippocampal functional connectivity contralateral to the epileptogenic focus. Several studies demonstrated that the duration of disease was correlated with these changes in functional connectivity. This implies that a compensatory mechanism may be present in patients with treatment-refractory TLE. CONCLUSION The consistency of this hippocampal connectivity pattern across multiple studies suggests resting-state fMRI may be useful as a non-invasive diagnostic tool for preoperative evaluation of TLE patients.
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13
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Elisevich K, Davoodi-Bojd E, Heredia JG, Soltanian-Zadeh H. Prospective Quantitative Neuroimaging Analysis of Putative Temporal Lobe Epilepsy. Front Neurol 2021; 12:747580. [PMID: 34803885 PMCID: PMC8602195 DOI: 10.3389/fneur.2021.747580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 09/20/2021] [Indexed: 11/22/2022] Open
Abstract
Purpose: A prospective study of individual and combined quantitative imaging applications for lateralizing epileptogenicity was performed in a cohort of consecutive patients with a putative diagnosis of mesial temporal lobe epilepsy (mTLE). Methods: Quantitative metrics were applied to MRI and nuclear medicine imaging studies as part of a comprehensive presurgical investigation. The neuroimaging analytics were conducted remotely to remove bias. All quantitative lateralizing tools were trained using a separate dataset. Outcomes were determined after 2 years. Of those treated, some underwent resection, and others were implanted with a responsive neurostimulation (RNS) device. Results: Forty-eight consecutive cases underwent evaluation using nine attributes of individual or combinations of neuroimaging modalities: 1) hippocampal volume, 2) FLAIR signal, 3) PET profile, 4) multistructural analysis (MSA), 5) multimodal model analysis (MMM), 6) DTI uncertainty analysis, 7) DTI connectivity, and 9) fMRI connectivity. Of the 24 patients undergoing resection, MSA, MMM, and PET proved most effective in predicting an Engel class 1 outcome (>80% accuracy). Both hippocampal volume and FLAIR signal analysis showed 76% and 69% concordance with an Engel class 1 outcome, respectively. Conclusion: Quantitative multimodal neuroimaging in the context of a putative mTLE aids in declaring laterality. The degree to which there is disagreement among the various quantitative neuroimaging metrics will judge whether epileptogenicity can be confined sufficiently to a particular temporal lobe to warrant further study and choice of therapy. Prediction models will improve with continued exploration of combined optimal neuroimaging metrics.
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Affiliation(s)
- Kost Elisevich
- Department of Clinical Neurosciences, Spectrum Health, Grand Rapids, MI, United States
- Department of Surgery, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
| | - Esmaeil Davoodi-Bojd
- Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
| | - John G. Heredia
- Imaging Physics, Department of Radiology, Spectrum Health, Grand Rapids, MI, United States
| | - Hamid Soltanian-Zadeh
- Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
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14
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Caldairou B, Foit NA, Mutti C, Fadaie F, Gill R, Lee HM, Demerath T, Urbach H, Schulze-Bonhage A, Bernasconi A, Bernasconi N. MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy. Neurology 2021; 97:e1583-e1593. [PMID: 34475125 DOI: 10.1212/wnl.0000000000012699] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 07/30/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND AND OBJECTIVES MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of covert hippocampal pathology in TLE. METHODS We trained a surface-based linear discriminant classifier that uses T1-weighted (morphology) and T2-weighted and fluid-attenuated inversion recovery (FLAIR)/T1 (intensity) features. The classifier was trained on 60 patients with TLE (mean age 35.6 years, 58% female) with histologically verified hippocampal sclerosis (HS). Images were deemed to be MRI negative in 42% of cases on the basis of neuroradiologic reading (40% based on hippocampal volumetry). The predictive model automatically labeled patients as having left or right TLE. Lateralization accuracy was compared to electroclinical data, including side of surgery. Accuracy of the classifier was further assessed in 2 independent TLE cohorts with similar demographics and electroclinical characteristics (n = 57, 58% MRI negative). RESULTS The overall lateralization accuracy was 93% (95% confidence interval 92%-94%), regardless of HS visibility. In MRI-negative TLE, the combination of T2 and FLAIR/T1 intensities provided the highest accuracy in both the training (84%, area under the curve [AUC] 0.95 ± 0.02) and validation (cohort 1 90%, AUC 0.99; cohort 2 76%, AUC 0.94) cohorts. DISCUSSION This prediction model for TLE lateralization operates on readily available conventional MRI contrasts and offers gain in accuracy over visual radiologic assessment. The combined contribution of decreased T1- and increased T2-weighted intensities makes the synthetic FLAIR/T1 contrast particularly effective in MRI-negative HS, setting the basis for broad clinical translation. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in people with TLE and MRI-negative HS, an automated MRI-based classifier accurately determines the side of pathology.
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Affiliation(s)
- Benoit Caldairou
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Niels A Foit
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Carlotta Mutti
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Fatemeh Fadaie
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Ravnoor Gill
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Hyo Min Lee
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Theo Demerath
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Horst Urbach
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Andreas Schulze-Bonhage
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Andrea Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany.
| | - Neda Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany.
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15
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Cheong EN, Park JE, Jung DE, Shim WH. Extrahippocampal Radiomics Analysis Can Potentially Identify Laterality in Patients With MRI-Negative Temporal Lobe Epilepsy. Front Neurol 2021; 12:706576. [PMID: 34421804 PMCID: PMC8372821 DOI: 10.3389/fneur.2021.706576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 06/30/2021] [Indexed: 11/14/2022] Open
Abstract
Objective: The objective of the study was to investigate whether radiomics features of extrahippocampal regions differ between patients with epilepsy and healthy controls, and whether any differences can identify patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE). Methods: Data from 36 patients with hippocampal sclerosis (HS) and 50 healthy controls were used to construct a radiomics model. A total of 1,618 radiomics features from the affected hippocampal and extrahippocampal regions were compared with features from healthy controls and the unaffected side of patients. Using a stepwise selection method with a univariate t-test and elastic net penalization, significant predictors for identifying TLE were separately selected for the hippocampus (H+) and extrahippocampal region (H–). Each model was independently validated with an internal set of MRI-negative adult TLE patients (n = 22) and pediatric validation cohort with MRI-negative TLE (n = 20) from another tertiary center; diagnostic performance was calculated using area under the curve (AUC) of the receiver-operating-characteristic curve analysis. Results: Forty-eight significant H+ radiomic features and 99 significant H– radiomic features were selected from the affected side of patients and used to create a hippocampus model and an extrahippocampal model, respectively. Texture features were the most frequently selected feature. Training set showed slightly higher accuracy between hippocampal (AUC = 0.99) and extrahippocampal model (AUC = 0.97). In the internal validation and external validation sets, the extrahippocampal model (AUC = 0.80 and 0.92, respectively) showed higher diagnostic performance for identifying the affected side of patients than the hippocampus model (AUC = 0.67 and 0.69). Significance: Radiomics revealed extrahippocampal abnormality in the affected side of patients with TLE and could potentially help to identify MRI-negative TLE. Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.
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Affiliation(s)
- E-Nae Cheong
- Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Da Eun Jung
- Department of Pediatrics, Ajou University School of Medicine, Suwon, South Korea
| | - Woo Hyun Shim
- Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.,Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
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16
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Cui W, Shang K, Qiu B, Lu J, Gao JH. White matter network disorder in mesial temporal epilepsy: An fMRI study. Epilepsy Res 2021; 172:106590. [PMID: 33639419 DOI: 10.1016/j.eplepsyres.2021.106590] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/11/2020] [Accepted: 02/16/2021] [Indexed: 01/13/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE) has been considered a network disorder disease in which brain regions extending beyond the epileptogenic zones are always affected. However, abnormalities in white matter (WM) functional networks and their associations with widespread network dysfunction are still being identified in mTLE. Accordingly, we investigated the altered functional activities in WM networks in mTLE using fMRI, which has recently been used to probe WM function. We collected resting-state fMRI data from 39 unilateral mTLE patients with hippocampal sclerosis and 29 healthy controls. Eleven WM networks were clustered according to temporal correlation profile. The functional connectivity (FC) of the WM networks were evaluated and compared between the two groups. Furthermore, we assessed the capacity of WM FC for seizure lateralization. According to our analysis, mTLE led to decreased FC within deep WM networks. In addition, the cortical regions involved in seizure propagation and several brain regions displaying interhemispheric disruption showed enhanced functional coupling with deep WM networks. FCs between the ipsilateral deep WM networks and the insula, temporal lobe, and supramarginal gyrus demonstrated positive correlation with seizure frequency. Moreover, the seizure onset zones of 33 patients out of 39 patients could be correctly lateralized. Our findings reveal functional disruptions in WM networks extending to extratemporal regions, supporting the network disorder hypothesis and suggesting that deep WM networks are key network nodes associated with massive dysfunction in mTLE. Moreover, the FC of the WM represents a potentially useful functional imaging measure for the diagnosis of mTLE.
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Affiliation(s)
- Wei Cui
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Kun Shang
- Department of Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Bensheng Qiu
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Jie Lu
- Department of Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, China.
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; Beijing City Key Laboratory for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.
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17
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González HFJ, Narasimhan S, Johnson GW, Wills KE, Haas KF, Konrad PE, Chang C, Morgan VL, Rubinov M, Englot DJ. Role of the Nucleus Basalis as a Key Network Node in Temporal Lobe Epilepsy. Neurology 2021; 96:e1334-e1346. [PMID: 33441453 DOI: 10.1212/wnl.0000000000011523] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 11/18/2020] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE To determine whether the nucleus basalis of Meynert (NBM) may be a key network structure of altered functional connectivity in temporal lobe epilepsy (TLE), we examined fMRI with network-based analyses. METHODS We acquired resting-state fMRI in 40 adults with TLE and 40 matched healthy control participants. We calculated functional connectivity of NBM and used multiple complementary network-based analyses to explore the importance of NBM in TLE networks without biasing our results by our approach. We compared patients to controls and examined associations of network properties with disease metrics and neurocognitive testing. RESULTS We observed marked decreases in connectivity between NBM and the rest of the brain in patients with TLE (0.91 ± 0.88, mean ± SD) vs controls (1.96 ± 1.13, p < 0.001, t test). Larger decreases in connectivity between NBM and fronto-parietal-insular regions were associated with higher frequency of consciousness-impairing seizures (r = -0.41, p = 0.008, Pearson). A core network of altered nodes in TLE included NBM ipsilateral to the epileptogenic side and bilateral limbic structures. Furthermore, normal community affiliation of ipsilateral NBM was lost in patients, and this structure displayed the most altered clustering coefficient of any node examined (3.46 ± 1.17 in controls vs 2.23 ± 0.93 in patients). Abnormal connectivity between NBM and subcortical arousal community was associated with modest neurocognitive deficits. Finally, a logistic regression model incorporating connectivity properties of ipsilateral NBM successfully distinguished patients from control datasets with moderately high accuracy (78%). CONCLUSIONS These results suggest that while NBM is rarely studied in epilepsy, it may be one of the most perturbed network nodes in TLE, contributing to widespread neural effects in this disabling disorder.
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Affiliation(s)
- Hernán F J González
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA.
| | - Saramati Narasimhan
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Graham W Johnson
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Kristin E Wills
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Kevin F Haas
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Peter E Konrad
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Catie Chang
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Victoria L Morgan
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Mikail Rubinov
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
| | - Dario J Englot
- From the Departments of Biomedical Engineering (H.F.J.G., G.W.J., P.E.K., C.C., V.L.M., M.R., D.J.E.) and Electrical Engineering and Computer Science (C.C., V.L.M., M.R., D.J.E.), Vanderbilt University; Departments of Neurological Surgery (S.N., K.E.W., P.E.K., D.J.E.), Radiology and Radiological Sciences (V.L.M., D.J.E.), and Neurology (K.F.H.) and Vanderbilt University Institute of Imaging Science (H.F.J.G., S.N., G.W.J., K.E.W., C.C., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, TN; and Department of Psychology (M.R.), Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA
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18
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Park YW, Choi YS, Kim SE, Choi D, Han K, Kim H, Ahn SS, Kim SA, Kim HJ, Lee SK, Lee HW. Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls. Sci Rep 2020; 10:19567. [PMID: 33177624 PMCID: PMC7658973 DOI: 10.1038/s41598-020-76283-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 10/16/2020] [Indexed: 12/17/2022] Open
Abstract
To investigative whether radiomics features in bilateral hippocampi from MRI can identify temporal lobe epilepsy (TLE). A total of 131 subjects with MRI (66 TLE patients [35 right and 31 left TLE] and 65 healthy controls [HC]) were allocated to training (n = 90) and test (n = 41) sets. Radiomics features (n = 186) from the bilateral hippocampi were extracted from T1-weighted images. After feature selection, machine learning models were trained. The performance of the classifier was validated in the test set to differentiate TLE from HC and ipsilateral TLE from HC. Identical processes were performed to differentiate right TLE from HC (training set, n = 69; test set; n = 31) and left TLE from HC (training set, n = 66; test set, n = 30). The best-performing model for identifying TLE showed an AUC, accuracy, sensitivity, and specificity of 0.848, 84.8%, 76.2%, and 75.0% in the test set, respectively. The best-performing radiomics models for identifying right TLE and left TLE subgroups showed AUCs of 0.845 and 0.840 in the test set, respectively. In addition, multiple radiomics features significantly correlated with neuropsychological test scores (false discovery rate-corrected p-values < 0.05). The radiomics model from hippocampus can be a potential biomarker for identifying TLE.
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Affiliation(s)
- Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Yun Seo Choi
- Department of Neurology, Epilepsy and Sleep Center, Ewha Womans University School of Medicine and Ewha Medical Research Institute, 1071, Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Korea.,Department of Medical Science, Ewha Womans University School of Medicine and Ewha Medical Research Institute, Seoul, Korea
| | - Song E Kim
- Department of Neurology, Epilepsy and Sleep Center, Ewha Womans University School of Medicine and Ewha Medical Research Institute, 1071, Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Korea.,Department of Medical Science, Ewha Womans University School of Medicine and Ewha Medical Research Institute, Seoul, Korea
| | - Dongmin Choi
- Department of Computer Science, Yonsei University, Seoul, Korea
| | - Kyunghwa Han
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Hwiyoung Kim
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Sol-Ah Kim
- Department of Neurology, Epilepsy and Sleep Center, Ewha Womans University School of Medicine and Ewha Medical Research Institute, 1071, Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Korea.,Department of Medical Science, Ewha Womans University School of Medicine and Ewha Medical Research Institute, Seoul, Korea.,Interdisciplinary Programs of Computational Medicine, System Health & Engineering Major in Graduate School, Ewha Womans University, Seoul, Korea
| | - Hyeon Jin Kim
- Department of Neurology, Epilepsy and Sleep Center, Ewha Womans University School of Medicine and Ewha Medical Research Institute, 1071, Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Korea.,Department of Medical Science, Ewha Womans University School of Medicine and Ewha Medical Research Institute, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Hyang Woon Lee
- Department of Neurology, Epilepsy and Sleep Center, Ewha Womans University School of Medicine and Ewha Medical Research Institute, 1071, Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Korea. .,Department of Medical Science, Ewha Womans University School of Medicine and Ewha Medical Research Institute, Seoul, Korea. .,Interdisciplinary Programs of Computational Medicine, System Health & Engineering Major in Graduate School, Ewha Womans University, Seoul, Korea.
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19
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Foit NA, Bernasconi A, Bernasconi N. Functional Networks in Epilepsy Presurgical Evaluation. Neurosurg Clin N Am 2020; 31:395-405. [PMID: 32475488 DOI: 10.1016/j.nec.2020.03.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Continuing advancements in neuroimaging methodology allow for increasingly detailed in vivo characterization of structural and functional brain networks, leading to the recognition of epilepsy as a disorder of large-scale networks. In surgical candidates, analysis of functional networks has proved invaluable for the identification of eloquent brain areas, such as hemispherical language dominance. More recently, connectome-based biomarkers have demonstrated potential to further inform clinical decision making in drug-refractory epilepsy. This article summarizes current evidence on epilepsy as a network disorder, emphasizing potential benefits of network analysis techniques for preoperative assessments and resection planning.
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Affiliation(s)
- Niels Alexander Foit
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, 3801 Rue Université, Montreal, Quebec H3A 2B4, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, 3801 Rue Université, Montreal, Quebec H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, 3801 Rue Université, Montreal, Quebec H3A 2B4, Canada.
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20
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Tavakol S, Royer J, Lowe AJ, Bonilha L, Tracy JI, Jackson GD, Duncan JS, Bernasconi A, Bernasconi N, Bernhardt BC. Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: From focal lesions to macroscale networks. Epilepsia 2019; 60:593-604. [PMID: 30889276 PMCID: PMC6447443 DOI: 10.1111/epi.14688] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 02/13/2019] [Accepted: 02/14/2019] [Indexed: 01/03/2023]
Abstract
Epilepsy is among the most common chronic neurologic disorders, with 30%-40% of patients having seizures despite antiepileptic drug treatment. The advent of brain imaging and network analyses has greatly improved the understanding of this condition. In particular, developments in magnetic resonance imaging (MRI) have provided measures for the noninvasive characterization and detection of lesions causing epilepsy. MRI techniques can probe structural and functional connectivity, and network analyses have shaped our understanding of whole-brain anomalies associated with focal epilepsies. This review considers the progress made by neuroimaging and connectomics in the study of drug-resistant epilepsies due to focal substrates, particularly temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal lobe epilepsies associated with malformations of cortical development. In these disorders, there is evidence of widespread disturbances of structural and functional connectivity that may contribute to the clinical and cognitive prognosis of individual patients. It is hoped that studying the interplay between macroscale network anomalies and lesional profiles will improve our understanding of focal epilepsies and assist treatment choices.
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Affiliation(s)
- Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Alexander J Lowe
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina
| | - Joseph I Tracy
- Cognitive Neuroscience and Brain Mapping Laboratory, Thomas Jefferson University Hospitals/Sidney Kimmel Medical College, Philadelphia, Pennsylvania
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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21
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Shah P, Bassett DS, Wisse LEM, Detre JA, Stein JM, Yushkevich PA, Shinohara RT, Elliott MA, Das SR, Davis KA. Structural and functional asymmetry of medial temporal subregions in unilateral temporal lobe epilepsy: A 7T MRI study. Hum Brain Mapp 2019; 40:2390-2398. [PMID: 30666753 DOI: 10.1002/hbm.24530] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 01/11/2019] [Indexed: 12/24/2022] Open
Abstract
Mesial temporal lobe epilepsy (TLE) is a common neurological disorder affecting the hippocampus and surrounding medial temporal lobe (MTL). Although prior studies have analyzed whole-brain network distortions in TLE patients, the functional network architecture of the MTL at the subregion level has not been examined. In this study, we utilized high-resolution 7T T2-weighted magnetic resonance imaging (MRI) and resting-state BOLD-fMRI to characterize volumetric asymmetry and functional network asymmetry of MTL subregions in unilateral medically refractory TLE patients and healthy controls. We subdivided the TLE group into mesial temporal sclerosis patients (TLE-MTS) and MRI-negative nonlesional patients (TLE-NL). Using an automated multi-atlas segmentation pipeline, we delineated 10 MTL subregions per hemisphere for each subject. We found significantly different patterns of volumetric asymmetry between the two groups, with TLE-MTS exhibiting volumetric asymmetry corresponding to decreased volumes ipsilaterally in all hippocampal subfields, and TLE-NL exhibiting no significant volumetric asymmetries other than a mild decrease in whole-hippocampal volume ipsilaterally. We also found significantly different patterns of functional network asymmetry in the CA1 subfield and whole hippocampus, with TLE-NL patients exhibiting asymmetry corresponding to increased connectivity ipsilaterally and TLE-MTS patients exhibiting asymmetry corresponding to decreased connectivity ipsilaterally. Our findings provide initial evidence that functional neuroimaging-based network properties within the MTL can distinguish between TLE subtypes. High-resolution MRI has potential to improve localization of underlying brain network disruptions in TLE patients who are candidates for surgical resection.
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Affiliation(s)
- Preya Shah
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania.,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - John A Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Center for Functional Neuroimaging, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Joel M Stein
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mark A Elliott
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sandhitsu R Das
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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22
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Tsougos I, Kousi E, Georgoulias P, Kapsalaki E, Fountas KN. Neuroimaging methods in Epilepsy of Temporal Origin. Curr Med Imaging 2018; 15:39-51. [DOI: 10.2174/1573405613666170622114920] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Revised: 05/04/2017] [Accepted: 05/11/2017] [Indexed: 11/22/2022]
Abstract
Background:
Temporal Lobe Epilepsy (TLE) comprises the most common form of
symptomatic refractory focal epilepsy in adults. Accurate lateralization and localization of the
epileptogenic focus are a significant prerequisite for determining surgical candidacy once the
patient has been deemed medically intractable. Structural MR imaging, clinical,
electrophysiological, and neurophysiological data have an established role in the localization of the
epileptogenic foci. Nevertheless, hippocampal sclerosis cannot be detected on MR images in more
than 30% of patients with TLE, and the presurgical assessment remains controversial.
</P><P>
Discussion: In the last years, advanced MR imaging techniques, such as 1H-MRS, DWI, DTI,
DSCI, and fMRI, may provide valuable additional information regarding the physiological and
metabolic characterization of brain tissue. MR imaging has shifted towards functional and
molecular imaging, thus, promising to improve the accuracy regarding the lateralization and the
localization of the epileptogenic focus. Additionally, nuclear medicine studies, such as SPECT and
PET imaging modalities, have become an asset for the decoding of brain function and activity, and
can be diagnostically helpful as well, since they provide valuable data regarding the altered
metabolic activity of the seizure foci.
Conclusion:
Overall, advanced MRI, SPECT, and PET imaging techniques are increasingly
becoming an essential part of TLE diagnostics, when the epileptogenic area is not identified on
structural MRI or when structural MRI, clinical, and electrophysiological findings are not in
concordance.
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Affiliation(s)
- Ioannis Tsougos
- Department of Medical Physics, School of Medicine, University of Thessaly, Larisa, Greece
| | - Evanthia Kousi
- The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Panagiotis Georgoulias
- Department of Medical Physics, School of Medicine, University of Thessaly, Larisa, Greece
| | - Eftychia Kapsalaki
- Department of Medical Physics, School of Medicine, University of Thessaly, Larisa, Greece
| | - Kostas N. Fountas
- Department of Medical Physics, School of Medicine, University of Thessaly, Larisa, Greece
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23
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Grassia F, Poliakov AV, Poliachik SL, Casimo K, Friedman SD, Shurtleff H, Giussani C, Novotny EJ, Ojemann JG, Hauptman JS. Changes in resting-state connectivity in pediatric temporal lobe epilepsy. J Neurosurg Pediatr 2018; 22:270-275. [PMID: 29932365 DOI: 10.3171/2018.3.peds17701] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE Functional connectivity magnetic resonance imaging (fcMRI) is a form of fMRI that allows for analysis of blood oxygen level-dependent signal changes within a task-free, resting paradigm. This technique has been shown to have efficacy in evaluating network connectivity changes with epilepsy. Presurgical data from patients with unilateral temporal lobe epilepsy were evaluated using the fcMRI technique to define connectivity changes within and between the diseased and healthy temporal lobes using a within-subjects design. METHODS Using presurgical fcMRI data from pediatric patients with unilateral temporal lobe epilepsy, the authors performed seed-based analyses within the diseased and healthy temporal lobes. Connectivity within and between temporal lobe seeds was measured and compared. RESULTS In the cohort studied, local ipsilateral temporal lobe connectivity was significantly increased on the diseased side compared to the healthy temporal lobe. Connectivity of the diseased side to the healthy side, on the other hand, was significantly reduced when compared to connectivity of the healthy side to the diseased temporal lobe. A statistically significant regression was observed when comparing the changes in local ipsilateral temporal lobe connectivity to the changes in inter-temporal lobe connectivity. A statistically significant difference was also noted in ipsilateral connectivity changes between patients with and those without mesial temporal sclerosis. CONCLUSIONS Using fcMRI, significant changes in ipsilateral temporal lobe and inter-temporal lobe connectivity can be appreciated in unilateral temporal lobe epilepsy. Furthermore, fcMRI may have a role in the presurgical evaluation of patients with intractable temporal lobe epilepsy.
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Affiliation(s)
- Fabio Grassia
- 1Department of Neurological Surgery, University of Milano-Bicocca, San Gerardo Hospital, Monza, Italy
| | - Andrew V Poliakov
- Departments of2Radiology and.,4Department of Neurological Surgery, University of Washington; and
| | - Sandra L Poliachik
- Departments of2Radiology and.,4Department of Neurological Surgery, University of Washington; and
| | | | | | | | - Carlo Giussani
- 1Department of Neurological Surgery, University of Milano-Bicocca, San Gerardo Hospital, Monza, Italy
| | | | - Jeffrey G Ojemann
- 4Department of Neurological Surgery, University of Washington; and.,5Department of Neurosurgery, Seattle Children's Hospital, Seattle, Washington
| | - Jason S Hauptman
- 4Department of Neurological Surgery, University of Washington; and.,5Department of Neurosurgery, Seattle Children's Hospital, Seattle, Washington
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24
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Brain network alteration in patients with temporal lobe epilepsy with cognitive impairment. Epilepsy Behav 2018; 81:41-48. [PMID: 29475172 DOI: 10.1016/j.yebeh.2018.01.024] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 01/15/2018] [Accepted: 01/18/2018] [Indexed: 02/02/2023]
Abstract
The aims of this study were to investigate the brain network alternation in patients with temporal lobe epilepsy (TLE) with and without cognitive impairment (CI) using functional magnetic resonance imaging (fMRI) and to further explore the potential mechanisms of epilepsy-induced CI. Forty patients with TLE and nineteen healthy controls (HCs) were recruited for this study. All participants received the Montreal Cognitive Assessment (MoCA) test, and the patients were divided into CI (n=21) and cognitive nonimpairment (CNI) groups (n=19) according to MoCA performance. Functional connectivity (FC) differences of resting state networks (RSNs) were compared among the CI, CNI, and HC groups. Correlation between FC and MoCA scores was also observed. When compared with the HC group, significantly decreased FC between medial visual network (mVN) and left frontoparietal network (lFPN) as well as between visuospatial network (VSN) and the anterior default mode network (aDMN) were revealed in both CI and CNI groups. In addition, significantly decreased FC between lFPN and executive control network (ECN) and increased FC between ECN and sensorimotor-related network (SMN) were found in CNI and CI groups, respectively. When compared with the CNI group, the CI group exhibited significant increased FC between ECN and lFPN as well as between ECN and SMN. Moreover, in the CI group, FC between ECN and lFPN showed negative correlation with attention scores. Our findings suggested that cognitive networks are different from epileptic networks, and the increased FC between RSNs closely related to cognitive function changes may help us to further understand the mechanism of CI in TLE.
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25
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Maccotta L, Lopez MA, Adeyemo B, Ances BM, Day BK, Eisenman LN, Dowling JL, Leuthardt EC, Schlaggar BL, Hogan RE. Postoperative seizure freedom does not normalize altered connectivity in temporal lobe epilepsy. Epilepsia 2017; 58:1842-1851. [PMID: 28776646 DOI: 10.1111/epi.13867] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/17/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVES Specific changes in the functional connectivity of brain networks occur in patients with epilepsy. Yet whether such changes reflect a stable disease effect or one that is a function of active seizure burden remains unclear. Here, we longitudinally assessed the connectivity of canonical cognitive functional networks in patients with intractable temporal lobe epilepsy (TLE), both before and after patients underwent epilepsy surgery and achieved seizure freedom. METHODS Seventeen patients with intractable TLE who underwent epilepsy surgery with Engel class I outcome and 17 matched healthy controls took part in the study. The functional connectivity of a set of cognitive functional networks derived from typical cognitive tasks was assessed in patients, preoperatively and postoperatively, as well as in controls, using stringent methods of artifact reduction. RESULTS Preoperatively, functional networks in TLE patients differed significantly from healthy controls, with differences that largely, but not exclusively, involved the default mode and temporal/auditory subnetworks. However, undergoing epilepsy surgery and achieving seizure freedom did not lead to significant changes in network connectivity, with postoperative functional network abnormalities closely mirroring the preoperative state. SIGNIFICANCE This result argues for a stable chronic effect of the disease on brain connectivity, with changes that are largely "burned in" by the time a patient with intractable TLE undergoes epilepsy surgery, which typically occurs years after the initial diagnosis. The result has potential implications for the treatment of intractable epilepsy, suggesting that delaying surgical intervention that may achieve seizure freedom may lead to functional network changes that are no longer reversible by the time of epilepsy surgery.
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Affiliation(s)
- Luigi Maccotta
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Mayra A Lopez
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Brian K Day
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Lawrence N Eisenman
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Joshua L Dowling
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, Missouri, U.S.A.,Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri, U.S.A.,Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Bradley L Schlaggar
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A.,Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, Missouri, U.S.A.,Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, U.S.A.,Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, U.S.A.,Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, U.S.A
| | - Robert Edward Hogan
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, U.S.A
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26
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Chiosa V, Groppa SA, Ciolac D, Koirala N, Mişina L, Winter Y, Moldovanu M, Muthuraman M, Groppa S. Breakdown of Thalamo-Cortical Connectivity Precedes Spike Generation in Focal Epilepsies. Brain Connect 2017; 7:309-320. [DOI: 10.1089/brain.2017.0487] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Vitalie Chiosa
- Department of Neurology, Neuroimaging and Neurostimulation, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
- Department of Neurology and Neurosurgery, National Center of Epileptology, Institute of Emergency Medicine, Chisinau, Moldova
- Laboratory of Neurobiology and Medical Genetics, State University of Medicine and Pharmacy “Nicolae Testemiţanu,” Chisinau, Moldova
| | - Stanislav A. Groppa
- Department of Neurology and Neurosurgery, National Center of Epileptology, Institute of Emergency Medicine, Chisinau, Moldova
- Laboratory of Neurobiology and Medical Genetics, State University of Medicine and Pharmacy “Nicolae Testemiţanu,” Chisinau, Moldova
| | - Dumitru Ciolac
- Department of Neurology, Neuroimaging and Neurostimulation, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
- Department of Neurology and Neurosurgery, National Center of Epileptology, Institute of Emergency Medicine, Chisinau, Moldova
- Laboratory of Neurobiology and Medical Genetics, State University of Medicine and Pharmacy “Nicolae Testemiţanu,” Chisinau, Moldova
| | - Nabin Koirala
- Department of Neurology, Neuroimaging and Neurostimulation, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Liudmila Mişina
- Department of Neurology and Neurosurgery, National Center of Epileptology, Institute of Emergency Medicine, Chisinau, Moldova
- Laboratory of Neurobiology and Medical Genetics, State University of Medicine and Pharmacy “Nicolae Testemiţanu,” Chisinau, Moldova
| | - Yaroslav Winter
- Department of Neurology, Neuroimaging and Neurostimulation, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | | | - Muthuraman Muthuraman
- Department of Neurology, Neuroimaging and Neurostimulation, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, Neuroimaging and Neurostimulation, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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He X, Doucet GE, Pustina D, Sperling MR, Sharan AD, Tracy JI. Presurgical thalamic "hubness" predicts surgical outcome in temporal lobe epilepsy. Neurology 2017; 88:2285-2293. [PMID: 28515267 DOI: 10.1212/wnl.0000000000004035] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 03/14/2017] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE To characterize the presurgical brain functional architecture presented in patients with temporal lobe epilepsy (TLE) using graph theoretical measures of resting-state fMRI data and to test its association with surgical outcome. METHODS Fifty-six unilateral patients with TLE, who subsequently underwent anterior temporal lobectomy and were classified as obtaining a seizure-free (Engel class I, n = 35) vs not seizure-free (Engel classes II-IV, n = 21) outcome at 1 year after surgery, and 28 matched healthy controls were enrolled. On the basis of their presurgical resting-state functional connectivity, network properties, including nodal hubness (importance of a node to the network; degree, betweenness, and eigenvector centralities) and integration (global efficiency), were estimated and compared across our experimental groups. Cross-validations with support vector machine (SVM) were used to examine whether selective nodal hubness exceeded standard clinical characteristics in outcome prediction. RESULTS Compared to the seizure-free patients and healthy controls, the not seizure-free patients displayed a specific increase in nodal hubness (degree and eigenvector centralities) involving both the ipsilateral and contralateral thalami, contributed by an increase in the number of connections to regions distributed mostly in the contralateral hemisphere. Simulating removal of thalamus reduced network integration more dramatically in not seizure-free patients. Lastly, SVM models built on these thalamic hubness measures produced 76% prediction accuracy, while models built with standard clinical variables yielded only 58% accuracy (both were cross-validated). CONCLUSIONS A thalamic network associated with seizure recurrence may already be established presurgically. Thalamic hubness can serve as a potential biomarker of surgical outcome, outperforming the clinical characteristics commonly used in epilepsy surgery centers.
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Affiliation(s)
- Xiaosong He
- From the Departments of Neurology (X.H., M.R.S., J.I.T.) and Neurosurgery (A.D.S.), Thomas Jefferson University, Philadelphia, PA; Department of Psychiatry (G.E.D.), Icahn School of Medicine at Mount Sinai, New York, NY; and Departments of Neurology and Radiology (D.P.), University of Pennsylvania, Philadelphia
| | - Gaelle E Doucet
- From the Departments of Neurology (X.H., M.R.S., J.I.T.) and Neurosurgery (A.D.S.), Thomas Jefferson University, Philadelphia, PA; Department of Psychiatry (G.E.D.), Icahn School of Medicine at Mount Sinai, New York, NY; and Departments of Neurology and Radiology (D.P.), University of Pennsylvania, Philadelphia
| | - Dorian Pustina
- From the Departments of Neurology (X.H., M.R.S., J.I.T.) and Neurosurgery (A.D.S.), Thomas Jefferson University, Philadelphia, PA; Department of Psychiatry (G.E.D.), Icahn School of Medicine at Mount Sinai, New York, NY; and Departments of Neurology and Radiology (D.P.), University of Pennsylvania, Philadelphia
| | - Michael R Sperling
- From the Departments of Neurology (X.H., M.R.S., J.I.T.) and Neurosurgery (A.D.S.), Thomas Jefferson University, Philadelphia, PA; Department of Psychiatry (G.E.D.), Icahn School of Medicine at Mount Sinai, New York, NY; and Departments of Neurology and Radiology (D.P.), University of Pennsylvania, Philadelphia
| | - Ashwini D Sharan
- From the Departments of Neurology (X.H., M.R.S., J.I.T.) and Neurosurgery (A.D.S.), Thomas Jefferson University, Philadelphia, PA; Department of Psychiatry (G.E.D.), Icahn School of Medicine at Mount Sinai, New York, NY; and Departments of Neurology and Radiology (D.P.), University of Pennsylvania, Philadelphia
| | - Joseph I Tracy
- From the Departments of Neurology (X.H., M.R.S., J.I.T.) and Neurosurgery (A.D.S.), Thomas Jefferson University, Philadelphia, PA; Department of Psychiatry (G.E.D.), Icahn School of Medicine at Mount Sinai, New York, NY; and Departments of Neurology and Radiology (D.P.), University of Pennsylvania, Philadelphia.
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Xiao F, An D, Zhou D. Functional MRI-based connectivity analysis: A promising tool for the investigation of the pathophysiology and comorbidity of epilepsy. Seizure 2017; 44:37-41. [DOI: 10.1016/j.seizure.2016.10.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Revised: 09/14/2016] [Accepted: 10/03/2016] [Indexed: 12/25/2022] Open
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Nazem-Zadeh MR, Bowyer SM, Moran JE, Davoodi-Bojd E, Zillgitt A, Weiland BJ, Bagher-Ebadian H, Mahmoudi F, Elisevich K, Soltanian-Zadeh H. MEG Coherence and DTI Connectivity in mTLE. Brain Topogr 2016; 29:598-622. [PMID: 27060092 PMCID: PMC5542022 DOI: 10.1007/s10548-016-0488-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 04/04/2016] [Indexed: 12/11/2022]
Abstract
Magnetoencephalography (MEG) is a noninvasive imaging method for localization of focal epileptiform activity in patients with epilepsy. Diffusion tensor imaging (DTI) is a noninvasive imaging method for measuring the diffusion properties of the underlying white matter tracts through which epileptiform activity is propagated. This study investigates the relationship between the cerebral functional abnormalities quantified by MEG coherence and structural abnormalities quantified by DTI in mesial temporal lobe epilepsy (mTLE). Resting state MEG data was analyzed using MEG coherence source imaging (MEG-CSI) method to determine the coherence in 54 anatomical sites in 17 adult mTLE patients with surgical resection and Engel class I outcome, and 17 age- and gender- matched controls. DTI tractography identified the fiber tracts passing through these same anatomical sites of the same subjects. Then, DTI nodal degree and laterality index were calculated and compared with the corresponding MEG coherence and laterality index. MEG coherence laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in insular cortex and both lateral orbitofrontal and superior temporal gyri (p < 0.017). Likewise, DTI nodal degree laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in gyrus rectus, insular cortex, precuneus and superior temporal gyrus (p < 0.017). In insular cortex, MEG coherence laterality correlated with DTI nodal degree laterality ([Formula: see text] in the cases of mTLE. None of these anatomical sites showed statistically significant differences in coherence laterality between right and left sides of the controls. Coherence laterality was in agreement with the declared side of epileptogenicity in insular cortex (in 82 % of patients) and both lateral orbitofrontal (88 %) and superior temporal gyri (88 %). Nodal degree laterality was also in agreement with the declared side of epileptogenicity in gyrus rectus (in 88 % of patients), insular cortex (71 %), precuneus (82 %) and superior temporal gyrus (94 %). Combining all significant laterality indices improved the lateralization accuracy to 94 % and 100 % for the coherence and nodal degree laterality indices, respectively. The associated variations in diffusion properties of fiber tracts quantified by DTI and coherence measures quantified by MEG with respect to epileptogenicity possibly reflect the chronic microstructural cerebral changes associated with functional interictal activity. The proposed methodology for using MEG and DTI to investigate diffusion abnormalities related to focal epileptogenicity and propagation may provide a further means of noninvasive lateralization.
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Affiliation(s)
| | - Susan M. Bowyer
- Neurology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - John E. Moran
- Neurology, Henry Ford Health System, Detroit, MI, 48202, USA
| | | | - Andrew Zillgitt
- Neurology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Barbara J. Weiland
- Institute of Cognitive Science University of Colorado Boulder, Boulder, CO, 80309 USA,
| | - Hassan Bagher-Ebadian
- Research Administration, Henry Ford Health System, Detroit, MI, 48202, USA
- Radiation Oncology Departments, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Fariborz Mahmoudi
- Research Administration, Henry Ford Health System, Detroit, MI, 48202, USA
- Computer and IT engineering Faculty, Islamic Azad University, Qazvin Branch, Iran
| | - Kost Elisevich
- Department of Clinical Neurosciences, Spectrum Health System, Division of Neurosurgery, Michigan State University, Grand Rapids, MI, 49503, USA,
| | - Hamid Soltanian-Zadeh
- Research Administration, Henry Ford Health System, Detroit, MI, 48202, USA
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,
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Insights into Intrinsic Brain Networks based on Graph Theory and PET in right- compared to left-sided Temporal Lobe Epilepsy. Sci Rep 2016; 6:28513. [PMID: 27349503 PMCID: PMC4923886 DOI: 10.1038/srep28513] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 06/03/2016] [Indexed: 11/08/2022] Open
Abstract
The human brain exhibits marked hemispheric differences, though it is not fully understood to what extent lateralization of the epileptic focus is relevant. Preoperative [(18)F]FDG-PET depicts lateralization of seizure focus in patients with temporal lobe epilepsy and reveals dysfunctional metabolic brain connectivity. The aim of the present study was to compare metabolic connectivity, inferred from inter-regional [(18)F]FDG PET uptake correlations, in right-sided (RTLE; n = 30) and left-sided TLE (LTLE; n = 32) with healthy controls (HC; n = 31) using graph theory based network analysis. Comparing LTLE and RTLE and patient groups separately to HC, we observed higher lobar connectivity weights in RTLE compared to LTLE for connections of the temporal and the parietal lobe of the contralateral hemisphere (CH). Moreover, especially in RTLE compared to LTLE higher local efficiency were found in the temporal cortices and other brain regions of the CH. The results of this investigation implicate altered metabolic networks in patients with TLE specific to the lateralization of seizure focus, and describe compensatory mechanisms especially in the CH of patients with RTLE. We propose that graph theoretical analysis of metabolic connectivity using [(18)F]FDG-PET offers an important additional modality to explore brain networks.
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de Campos BM, Coan AC, Lin Yasuda C, Casseb RF, Cendes F. Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy. Hum Brain Mapp 2016; 37:3137-52. [PMID: 27133613 PMCID: PMC5074272 DOI: 10.1002/hbm.23231] [Citation(s) in RCA: 82] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Revised: 04/04/2016] [Accepted: 04/15/2016] [Indexed: 11/11/2022] Open
Abstract
Mesial temporal lobe epilepsy (MTLE) with hippocampus sclerosis (HS) is associated with functional and structural alterations extending beyond the temporal regions and abnormal pattern of brain resting state networks (RSNs) connectivity. We hypothesized that the interaction of large-scale RSNs is differently affected in patients with right- and left-MTLE with HS compared to controls. We aimed to determine and characterize these alterations through the analysis of 12 RSNs, functionally parceled in 70 regions of interest (ROIs), from resting-state functional-MRIs of 99 subjects (52 controls, 26 right- and 21 left-MTLE patients with HS). Image preprocessing and statistical analysis were performed using UF(2) C-toolbox, which provided ROI-wise results for intranetwork and internetwork connectivity. Intranetwork abnormalities were observed in the dorsal default mode network (DMN) in both groups of patients and in the posterior salience network in right-MTLE. Both groups showed abnormal correlation between the dorsal-DMN and the posterior salience, as well as between the dorsal-DMN and the executive-control network. Patients with left-MTLE also showed reduced correlation between the dorsal-DMN and visuospatial network and increased correlation between bilateral thalamus and the posterior salience network. The ipsilateral hippocampus stood out as a central area of abnormalities. Alterations on left-MTLE expressed a low cluster coefficient, whereas the altered connections on right-MTLE showed low cluster coefficient in the DMN but high in the posterior salience regions. Both right- and left-MTLE patients with HS have widespread abnormal interactions of large-scale brain networks; however, all parameters evaluated indicate that left-MTLE has a more intricate bihemispheric dysfunction compared to right-MTLE. Hum Brain Mapp 37:3137-3152, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Brunno Machado de Campos
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, São Paulo, Brazil
| | - Ana Carolina Coan
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, São Paulo, Brazil
| | - Clarissa Lin Yasuda
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, São Paulo, Brazil
| | - Raphael Fernandes Casseb
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, São Paulo, Brazil
| | - Fernando Cendes
- Neuroimaging Laboratory, Department of Neurology, University of Campinas, Campinas, São Paulo, Brazil
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The Significance of the Default Mode Network (DMN) in Neurological and Neuropsychiatric Disorders: A Review. THE YALE JOURNAL OF BIOLOGY AND MEDICINE 2016; 89:49-57. [PMID: 27505016 PMCID: PMC4797836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
The relationship of cortical structure and specific neuronal circuitry to global brain function, particularly its perturbations related to the development and progression of neuropathology, is an area of great interest in neurobehavioral science. Disruption of these neural networks can be associated with a wide range of neurological and neuropsychiatric disorders. Herein we review activity of the Default Mode Network (DMN) in neurological and neuropsychiatric disorders, including Alzheimer's disease, Parkinson's disease, Epilepsy (Temporal Lobe Epilepsy - TLE), attention deficit hyperactivity disorder (ADHD), and mood disorders. We discuss the implications of DMN disruptions and their relationship to the neurocognitive model of each disease entity, the utility of DMN assessment in clinical evaluation, and the changes of the DMN following treatment.
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Lopour BA, Staba RJ, Stern JM, Fried I, Ringach DL. Characterization of long-range functional connectivity in epileptic networks by neuronal spike-triggered local field potentials. J Neural Eng 2016; 13:026031. [PMID: 26975603 DOI: 10.1088/1741-2560/13/2/026031] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Quantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures. APPROACH Broadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges. MAIN RESULTS We detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses. SIGNIFICANCE The results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal data. This technique will enable testing of specific hypotheses regarding functional connectivity in epilepsy and the relationship between functional properties and imaging findings. Beyond epilepsy, we expect that the impulse response could be more broadly applied as a measure of long-range functional connectivity in studies of cognition.
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Affiliation(s)
- Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA
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Resting-state functional connectivity in epilepsy: growing relevance for clinical decision making. Curr Opin Neurol 2015; 28:158-65. [PMID: 25734954 DOI: 10.1097/wco.0000000000000178] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
PURPOSE OF REVIEW Seizures produce dysfunctional, maladaptive networks, making functional connectivity an ideal technique for identifying complex brain effects of epilepsy. We review the current status of resting-state functional connectivity (rsFC) research, highlighting its potential added value to epilepsy surgery programs. RECENT FINDINGS RsFC research has demonstrated that the brain impact of seizures goes beyond the epileptogenic zone, changing connectivity patterns in widespread cortical regions. There is evidence for abnormal connectivity, but the degree to which these represent adaptive or maladaptive plasticity responses is unclear. Empirical associations with cognitive performance and psychiatric symptoms have helped understand deleterious impacts of seizures outside the epileptogenic zone. Studies in the prediction of outcome suggest that there are identifiable presurgical patterns of functional connectivity associated with a greater likelihood of positive cognitive or seizure outcomes. SUMMARY The role of rsFC remains limited in most clinical settings, but shows great promise for identifying epileptic circuits and foci, predicting outcomes following surgery, and explaining cognitive deficits and psychiatric symptoms of epilepsy. RsFC has demonstrated that even focal epilepsies constitute a network and brain systems disorder. By providing a tool to both identify and characterize the brain network impact of epileptiform activity, rsFC can make a strong contribution to presurgical algorithms in epilepsy.
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Li BY, Chen SD. Potential Similarities in Temporal Lobe Epilepsy and Alzheimer’s Disease: From Clinic to Pathology. Am J Alzheimers Dis Other Demen 2015; 30:723-8. [PMID: 24906967 PMCID: PMC10852563 DOI: 10.1177/1533317514537547] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Alzheimer’s disease (AD) is clinically characterized by insidious onset of memory and cognitive impairments, which are also presented in patients with temporal lobe epilepsy (TLE). Many studies have shown that seizures occur in some patients with AD, and AD is a risk factor for epilepsy, mainly complex partial and secondary generalized seizure. Here, we focus on the relationship between TLE and AD in clinical and pathological aspects, as they are having similar comorbidities and mechanisms. In this study, we first reviewed the clinical observations that showed concomitant AD and TLE. Then, we picked up common genetic and pathological changes in both the diseases from neurobiological researches. Although both the diseases have delicate differences in many aspects, their common characteristics intrigue more detailed research to be done by newer technology.
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Affiliation(s)
- Bin-Yin Li
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sheng-Di Chen
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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36
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Li H, Fan W, Yang J, Song S, Liu Y, Lei P, Shrestha L, Mella G, Chen W, Xu H. Asymmetry in cross-hippocampal connectivity in unilateral mesial temporal lobe epilepsy. Epilepsy Res 2015; 118:14-21. [PMID: 26561924 DOI: 10.1016/j.eplepsyres.2015.10.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 09/15/2015] [Accepted: 10/25/2015] [Indexed: 01/06/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE) is mostly characterized by hippocampal sclerosis (HS) changes. Although considerable progress has been made in understanding the altered functional network of mTLE patients, whether one side of the abnormal hippocampal (HP) structure will affect the other healthy side of the hippocampal network is still unclear. Here, we used a seed-based method to explore the commonly alterative hippocampal network in mTLE patients by comparing the bilateral hippocampal network of unilateral mTLE patients with healthy control participants. We observed that both sides of the hippocampal network in unilateral mTLE patients were changed independent of the affected or "healthy" side, which may suggest a common plasticity network for both sides of hippocampal sclerosis mesial temporal lobe epilepsy patients. Furthermore, using the HP as the ROI, we found that the functional connectivity of the intra-HP in the left mTLE-HS group was moderately positively correlated with the duration of the disease, while a strong negative correlation between functional connectivity of the intra-HP and duration were detected in the right mTLE-HS group, which suggested that it was easier for the right HP than the left HP to communicate with the contralateral HP according to the progression of mTLE disease because the hippocampus plays different roles in the communication and compensatory mechanism associated with the contralateral side of the hemisphere. We hope that this potential relevance may help us to better characterize mTLE with hippocampal sclerosis and ultimately assist in providing a better diagnosis and more accurate invasive treatments of mTLE.
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Affiliation(s)
- Hong Li
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Wenliang Fan
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Jie Yang
- Department of Communication Sciences and Disorders, Massachusetts General Hospital Institute of Health Professions, Boston, MA, USA.
| | - Shuyan Song
- School of Life Science and Technology, Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Yuan Liu
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Ping Lei
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Lochan Shrestha
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Grace Mella
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Wei Chen
- Department of Radiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China; Radiology and Medical Imaging Center, The First People's Hospital of Yibin, Sichuan 644000, China.
| | - Haibo Xu
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
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Yang Z, Choupan J, Reutens D, Hocking J. Lateralization of Temporal Lobe Epilepsy Based on Resting-State Functional Magnetic Resonance Imaging and Machine Learning. Front Neurol 2015; 6:184. [PMID: 26379618 PMCID: PMC4553409 DOI: 10.3389/fneur.2015.00184] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2014] [Accepted: 08/10/2015] [Indexed: 11/13/2022] Open
Abstract
Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.
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Affiliation(s)
- Zhengyi Yang
- School of Information Technology and Electrical Engineering, The University of Queensland , Brisbane, QLD , Australia ; Centre for Advanced Imaging, The University of Queensland , Brisbane, QLD , Australia
| | - Jeiran Choupan
- Centre for Advanced Imaging, The University of Queensland , Brisbane, QLD , Australia ; Queensland Brain Institute, The University of Queensland , Brisbane, QLD , Australia
| | - David Reutens
- Centre for Advanced Imaging, The University of Queensland , Brisbane, QLD , Australia
| | - Julia Hocking
- School of Psychology and Counselling, Queensland University of Technology , Brisbane, QLD , Australia
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Bharath RD, Sinha S, Panda R, Raghavendra K, George L, Chaitanya G, Gupta A, Satishchandra P. Seizure Frequency Can Alter Brain Connectivity: Evidence from Resting-State fMRI. AJNR Am J Neuroradiol 2015; 36:1890-8. [PMID: 26294642 DOI: 10.3174/ajnr.a4373] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 02/25/2015] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The frequency of seizures is an important factor that can alter functional brain connectivity. Analysis of this factor in patients with epilepsy is complex because of disease- and medication-induced confounders. Because patients with hot-water epilepsy generally are not on long-term drug therapy, we used seed-based connectivity analysis in these patients to assess connectivity changes associated with seizure frequency without confounding from antiepileptic drugs. MATERIALS AND METHODS Resting-state fMRI data from 36 patients with hot-water epilepsy (18 with frequent seizures [>2 per month] and 18 with infrequent seizures [≤2 per month]) and 18 healthy age- and sex-matched controls were analyzed for seed-to-voxel connectivity by using 106 seeds. Voxel wise paired t-test analysis (P < .005, corrected for false-discovery rate) was used to identify significant intergroup differences between these groups. RESULTS Connectivity analysis revealed significant differences between the 2 groups (P < .001). Patients in the frequent-seizure group had increased connectivity within the medial temporal structures and widespread areas of poor connectivity, even involving the default mode network, in comparison with those in the infrequent-seizure group. Patients in the infrequent-seizure group had focal abnormalities with increased default mode network connectivity and decreased left entorhinal cortex connectivity. CONCLUSIONS The results of this study suggest that seizure frequency can alter functional brain connectivity, which can be visualized by using resting-state fMRI. Imaging features such as diffuse network abnormalities, involvement of the default mode network, and recruitment of medial temporal lobe structures were seen only in patients with frequent seizures. Future studies in more common epilepsy groups, however, will be required to further establish this finding.
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Affiliation(s)
- R D Bharath
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.) Advanced Brain Imaging Facility (R.D.B., R.P.), Cognitive Neuroscience Center, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India
| | - S Sinha
- Neurology (S.S., K.R., G.C., P.S.)
| | - R Panda
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.) Advanced Brain Imaging Facility (R.D.B., R.P.), Cognitive Neuroscience Center, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India
| | | | - L George
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.)
| | | | - A Gupta
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.)
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Ridley BGY, Rousseau C, Wirsich J, Le Troter A, Soulier E, Confort-Gouny S, Bartolomei F, Ranjeva JP, Achard S, Guye M. Nodal approach reveals differential impact of lateralized focal epilepsies on hub reorganization. Neuroimage 2015; 118:39-48. [PMID: 26070261 DOI: 10.1016/j.neuroimage.2015.05.096] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2014] [Revised: 04/30/2015] [Accepted: 05/21/2015] [Indexed: 02/07/2023] Open
Abstract
The impact of the hemisphere affected by impairment in models of network disease is not fully understood. Among such models, focal epilepsies are characterised by recurrent seizures generated in epileptogenic areas also responsible for wider network dysfunction between seizures. Previous work focusing on functional connectivity within circumscribed networks suggests a divergence of network integrity and compensatory capacity between epilepsies as a function of the laterality of seizure onset. We evaluated the ability of complex network theory to reveal changes in focal epilepsy in global and nodal parameters using graph theoretical analysis of functional connectivity data obtained with resting-state fMRI. Graphs of functional connectivity networks were derived from 19 right and 13 left focal epilepsy patients and 15 controls. Topological metrics (degree, local efficiency, global efficiency and modularity) were computed for a whole-brain, atlas-defined network. We also calculated a hub disruption index for each graph metric, measuring the capacity of the brain network to demonstrate increased connectivity in some nodes for decreased connectivity in others. Our data demonstrate that the patient group as a whole is characterised by network-wide pattern of reorganization, even while global parameters fail to distinguish between groups. Furthermore, multiple metrics indicate that epilepsies with differently lateralized epileptic networks are asymmetric in their burden on functional brain networks; with left epilepsy patients being characterised by reduced efficiency and modularity, while in right epilepsy patients we provide the first evidence that functional brain networks are characterised by enhanced connectivity and efficiency at some nodes whereas reduced in others.
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Affiliation(s)
- Ben Gendon Yeshe Ridley
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Celia Rousseau
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Jonathan Wirsich
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Arnaud Le Troter
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Elisabeth Soulier
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Sylvianne Confort-Gouny
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Fabrice Bartolomei
- APHM, Hôpital de la Timone, Service de Neurophysiologie Clinique, 13005 Marseille, France; Aix-Marseille Université, INSERM, Institut de Neuroscience des Systèmes U1106, 13005 Marseille, France.
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Sophie Achard
- Centre National de la Recherche Scientifique, Grenoble Image Parole Signal Automatique, 38402 Grenoble, France.
| | - Maxime Guye
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
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Hsiao FJ, Yu HY, Chen WT, Kwan SY, Chen C, Yen DJ, Yiu CH, Shih YH, Lin YY. Increased Intrinsic Connectivity of the Default Mode Network in Temporal Lobe Epilepsy: Evidence from Resting-State MEG Recordings. PLoS One 2015; 10:e0128787. [PMID: 26035750 PMCID: PMC4452781 DOI: 10.1371/journal.pone.0128787] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 04/30/2015] [Indexed: 11/23/2022] Open
Abstract
The electrophysiological signature of resting state oscillatory functional connectivity within the default mode network (DMN) during spike-free periods in temporal lobe epilepsy (TLE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in TLE, and we examined the effect of lateralized TLE on functional connectivity. Sixteen medically intractable TLE patients and 22 controls participated in this study. Whole-scalp 306-channel MEG epochs without interictal spikes generated from both MEG and EEG data were analyzed using a minimum norm estimate (MNE) and source-based imaginary coherence analysis. With this processing, we obtained the cortical activation and functional connectivity within the DMN. The functional connectivity was increased between DMN and the right medial temporal (MT) region at the delta band and between DMN and the bilateral anterior cingulate cortex (ACC) regions at the theta band. The functional change was associated with the lateralization of TLE. The right TLE showed enhanced DMN connectivity with the right MT while the left TLE demonstrated increased DMN connectivity with the bilateral MT. There was no lateralization effect of TLE upon the DMN connectivity with ACC. These findings suggest that the resting-state functional connectivity within the DMN is reinforced in temporal lobe epilepsy during spike-free periods. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction and prognosis in patients with TLE.
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Affiliation(s)
- Fu-Jung Hsiao
- Institute of Brain Science, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Brain Research Center, National Yang-Ming University, Taipei, Taiwan
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
- Laboratory of Neurophysiology at Medical Research Division, Taipei Veterans General Hospital, Taipei, Taiwan
- * E-mail: (FJH); (YYL)
| | - Hsiang-Yu Yu
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Wei-Ta Chen
- Institute of Brain Science, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Laboratory of Neurophysiology at Medical Research Division, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Shang-Yeong Kwan
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chien Chen
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Der-Jen Yen
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chun-Hing Yiu
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yang-Hsin Shih
- Institute of Brain Science, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurosurgery, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yung-Yang Lin
- Institute of Brain Science, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Institute of Clinical Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Institute of Physiology, School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Brain Research Center, National Yang-Ming University, Taipei, Taiwan
- Laboratory of Neurophysiology at Medical Research Division, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
- * E-mail: (FJH); (YYL)
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Zhang Z, Xu Q, Liao W, Wang Z, Li Q, Yang F, Zhang Z, Liu Y, Lu G. Pathological uncoupling between amplitude and connectivity of brain fluctuations in epilepsy. Hum Brain Mapp 2015; 36:2756-66. [PMID: 25879781 DOI: 10.1002/hbm.22805] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Revised: 03/23/2015] [Accepted: 03/23/2015] [Indexed: 11/11/2022] Open
Abstract
Amplitude and functional connectivity are two fundamental parameters for describing the spontaneous brain fluctuations. These two parameters present close coupling in physiological state, and present different alteration patterns in epilepsy revealed by functional MRI (fMRI). We hypothesized that the alteration of coupling between these two imaging parameters may be underpinned by specific pathological factors of epilepsy, and can be employed to improve the capability for epileptic focus detection. Forty-seven patients (26 left- and 21 right-sided) with mesial temporal lobe epilepsy (mTLE) and 32 healthy controls underwent resting-state fMRI scans. All patients were detected to have interictal epileptic discharges on simultaneous electroencephalograph (EEG) recordings. Amplitude-connectivity coupling was calculated by correlating amplitude and functional connectivity density of low-frequency brain fluctuations. We observed reduced amplitude-connectivity coupling associated with epileptic discharges in the mesial temporal regions in both groups of patients, and increased coupling associated with epilepsy durations in the posterior regions of the default-mode network in the right-sided patients. Moreover, we proposed a new index of amplitude subtracting connectivity, which elevated imaging contrast for differentiating the patients from the controls. The findings indicated that epileptic discharges and chronic damaging effect of epilepsy might both contribute to alterations of amplitude-connectivity coupling in different pivotal regions in mTLE. Investigation on imaging coupling provides synergistic approach for describing brain functional changing features in epilepsy.
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Affiliation(s)
- Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.,State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China
| | - Qiang Xu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Wei Liao
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.,Center for Cognition and Brain Disorders, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Zhengge Wang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Qian Li
- Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Fang Yang
- Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Zongjun Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Yijun Liu
- Department of Psychiatry and Neuroscience, University of Florida, Gainesville, Florida
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.,State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China
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Bonilha L, Keller SS. Quantitative MRI in refractory temporal lobe epilepsy: relationship with surgical outcomes. Quant Imaging Med Surg 2015; 5:204-24. [PMID: 25853080 DOI: 10.3978/j.issn.2223-4292.2015.01.01] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 01/07/2015] [Indexed: 11/14/2022]
Abstract
Medically intractable temporal lobe epilepsy (TLE) remains a serious health problem. Across treatment centers, up to 40% of patients with TLE will continue to experience persistent postoperative seizures at 2-year follow-up. It is unknown why such a large number of patients continue to experience seizures despite being suitable candidates for resective surgery. Preoperative quantitative MRI techniques may provide useful information on why some patients continue to experience disabling seizures, and may have the potential to develop prognostic markers of surgical outcome. In this article, we provide an overview of how quantitative MRI morphometric and diffusion tensor imaging (DTI) data have improved the understanding of brain structural alterations in patients with refractory TLE. We subsequently review the studies that have applied quantitative structural imaging techniques to identify the neuroanatomical factors that are most strongly related to a poor postoperative prognosis. In summary, quantitative imaging studies strongly suggest that TLE is a disorder affecting a network of neurobiological systems, characterized by multiple and inter-related limbic and extra-limbic network abnormalities. The relationship between brain alterations and postoperative outcome are less consistent, but there is emerging evidence suggesting that seizures are less likely to remit with surgery when presurgical abnormalities are observed in the connectivity supporting brain regions serving as network nodes located outside the resected temporal lobe. Future work, possibly harnessing the potential from multimodal imaging approaches, may further elucidate the etiology of persistent postoperative seizures in patients with refractory TLE. Furthermore, quantitative imaging techniques may be explored to provide individualized measures of postoperative seizure freedom outcome.
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Affiliation(s)
- Leonardo Bonilha
- 1 Department of Neurology and Neurosurgery, Medical University of South Carolina, Charleston, SC 29425, USA ; 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK ; 3 Department of Radiology, The Walton Centre NHS Foundation Trust, Liverpool, UK ; 4 Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Simon S Keller
- 1 Department of Neurology and Neurosurgery, Medical University of South Carolina, Charleston, SC 29425, USA ; 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK ; 3 Department of Radiology, The Walton Centre NHS Foundation Trust, Liverpool, UK ; 4 Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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43
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Douw L, DeSalvo MN, Tanaka N, Cole AJ, Liu H, Reinsberger C, Stufflebeam SM. Dissociated multimodal hubs and seizures in temporal lobe epilepsy. Ann Clin Transl Neurol 2015; 2:338-52. [PMID: 25909080 PMCID: PMC4402080 DOI: 10.1002/acn3.173] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 12/22/2014] [Accepted: 12/22/2014] [Indexed: 11/16/2022] Open
Abstract
Objective Brain connectivity at rest is altered in temporal lobe epilepsy (TLE), particularly in “hub” areas such as the posterior default mode network (DMN). Although both functional and anatomical connectivity are disturbed in TLE, the relationships between measures as well as to seizure frequency remain unclear. We aim to clarify these associations using connectivity measures specifically sensitive to hubs. Methods Connectivity between 1000 cortical surface parcels was determined in 49 TLE patients and 23 controls with diffusion and resting-state functional magnetic resonance imaging. Two types of hub connectivity were investigated across multiple brain modules (the DMN, motor system, etcetera): (1) within-module connectivity (a measure of local importance that assesses a parcel's communication level within its own subnetwork) and (2) between-module connectivity (a measure that assesses connections across multiple modules). Results In TLE patients, there was lower overall functional integrity of the DMN as well as an increase in posterior hub connections with other modules. Anatomical between-module connectivity was globally decreased. Higher DMN disintegration (DD) coincided with higher anatomical between-module connectivity, whereas both were associated with increased seizure frequency. DD related to seizure frequency through mediating effects of anatomical connectivity, but seizure frequency also correlated with anatomical connectivity through DD, indicating a complex interaction between multimodal networks and symptoms. Interpretation We provide evidence for dissociated anatomical and functional hub connectivity in TLE. Moreover, shifts in functional hub connections from within to outside the DMN, an overall loss of integrative anatomical communication, and the interaction between the two increase seizure frequency.
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Affiliation(s)
- Linda Douw
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Charlestown, Massachusetts ; Department of Radiology, Harvard Medical School Boston, Massachusetts ; Department of Anatomy and Neurosciences, VU University Medical Center Amsterdam, The Netherlands
| | - Matthew N DeSalvo
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Charlestown, Massachusetts ; Department of Radiology, Harvard Medical School Boston, Massachusetts
| | - Naoaki Tanaka
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Charlestown, Massachusetts ; Department of Radiology, Harvard Medical School Boston, Massachusetts
| | - Andrew J Cole
- Department of Neurology, Massachusetts General Hospital Boston, Massachusetts
| | - Hesheng Liu
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Charlestown, Massachusetts ; Department of Radiology, Harvard Medical School Boston, Massachusetts
| | - Claus Reinsberger
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Charlestown, Massachusetts ; Department of Neurology, Brigham and Women's Hospital Boston, Massachusetts
| | - Steven M Stufflebeam
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Charlestown, Massachusetts ; Department of Radiology, Harvard Medical School Boston, Massachusetts
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Lateralization of Epileptic Foci Through Causal Analysis of Scalp-EEG Interictal Spike Activity. J Clin Neurophysiol 2015; 32:57-65. [DOI: 10.1097/wnp.0000000000000120] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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45
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Localizing hand motor area using resting-state fMRI: validated with direct cortical stimulation. Acta Neurochir (Wien) 2014; 156:2295-302. [PMID: 25246146 DOI: 10.1007/s00701-014-2236-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Accepted: 09/08/2014] [Indexed: 10/24/2022]
Abstract
BACKGROUND Resting-state functional magnetic resonance imaging (R-fMRI) is a promising tool in clinical application, especially in presurgical mapping for neurosurgery. This study aimed to investigate the sensitivity and specificity of R-fMRI in the localization of hand motor area in patients with brain tumors validated by direct cortical stimulation (DCS). We also compared this technique to task-based blood oxygenation level-dependent (BOLD) fMRI (T-fMRI). METHODS R-fMRI and T-fMRI were acquired from 17 patients with brain tumors. The cortex sites of the hand motor area were recorded by DCS. Site-by-site comparisons between R-fMRI/T-fMRI and DCS were performed to calculate R-fMRI and T-fMRI sensitivity and specificity using DCS as a "gold standard". R-fMRI and T-fMRI performances were compared statistically RESULTS A total of 609 cortex sites were tested with DCS and compared with R-fMRI findings in 17 patients. For hand motor area localization, R-fMRI sensitivity and specificity were 90.91 and 89.41 %, respectively. Given that two subjects could not comply with T-fMRI, 520 DCS sites were compared with T-fMRI findings in 15 patients. The sensitivity and specificity of T-fMRI were 78.57 and 84.76 %, respectively. In the 15 patients who successfully underwent both R-fMRI and T-fMRI, there was no statistical difference in sensitivity or specificity between the two methods (p = 0.3198 and p = 0.1431, respectively) CONCLUSIONS R-fMRI sensitivity and specificity are high for localizing hand motor area and even equivalent or slightly higher compared with T-fMRI. Given its convenience for patients, R-fMRI is a promising substitute for T-fMRI for presurgical mapping.
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Lang S, Duncan N, Northoff G. Resting-state functional magnetic resonance imaging: review of neurosurgical applications. Neurosurgery 2014; 74:453-64; discussion 464-5. [PMID: 24492661 DOI: 10.1227/neu.0000000000000307] [Citation(s) in RCA: 77] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Recent research in brain imaging has highlighted the role of different neural networks in the resting state (ie, no task) in which the brain displays spontaneous low-frequency neuronal oscillations. These can be indirectly measured with resting-state functional magnetic resonance imaging, and functional connectivity can be inferred as the spatiotemporal correlations of this signal. This technique has proliferated in recent years and has allowed the noninvasive investigation of large-scale, distributed functional networks. In this review, we give a brief overview of resting-state networks and examine the use of resting-state functional magnetic resonance imaging in neurosurgical contexts, specifically with respect to neurooncology, epilepsy surgery, and deep brain stimulation. We discuss the advantages and disadvantages compared with task-based functional magnetic resonance imaging, the limitations of resting-state functional magnetic resonance imaging, and the emerging directions of this relatively new technology.
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Affiliation(s)
- Stefan Lang
- *Department of Neurosurgery, University of Calgary, Calgary, Alberta, Canada; ‡Mind, Brain Imaging, and Neuroethics Unit, Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada; §Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
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Pittau F, Mégevand P, Sheybani L, Abela E, Grouiller F, Spinelli L, Michel CM, Seeck M, Vulliemoz S. Mapping epileptic activity: sources or networks for the clinicians? Front Neurol 2014; 5:218. [PMID: 25414692 PMCID: PMC4220689 DOI: 10.3389/fneur.2014.00218] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Accepted: 10/08/2014] [Indexed: 01/03/2023] Open
Abstract
Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.
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Affiliation(s)
- Francesca Pittau
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Pierre Mégevand
- Laboratory for Multimodal Human Brain Mapping, Hofstra North Shore LIJ School of Medicine , Manhasset, NY , USA
| | - Laurent Sheybani
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Eugenio Abela
- Support Center of Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital , Bern , Switzerland
| | - Frédéric Grouiller
- Radiology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
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Barron DS, Fox PT, Pardoe H, Lancaster J, Price LR, Blackmon K, Berry K, Cavazos JE, Kuzniecky R, Devinsky O, Thesen T. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy. NEUROIMAGE-CLINICAL 2014; 7:273-80. [PMID: 25610790 PMCID: PMC4300013 DOI: 10.1016/j.nicl.2014.08.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2014] [Revised: 07/13/2014] [Accepted: 08/04/2014] [Indexed: 01/07/2023]
Abstract
Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses. A thalamic disease model informed connectivity analyses in temporal lobe epilepsy. No patient vs. control group differences in thalamic connection strength were observed. Yet thalamic functional connection strength predicted seizure onset laterality. Lack of group difference should not deter constrained assessment in individuals. Meta-analytic disease models successfully guide individual patient biomarker development.
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Affiliation(s)
- Daniel S Barron
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA ; Yale University School of Medicine, New Haven, CT, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA ; Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA ; South Texas Veterans Health Care System, San Antonio, TX, USA ; Department of Neurology, University of TX Health Science Center, San Antonio, TX, USA ; State Key Lab for Brain and Cognitive Sciences, University of Hong Kong, Hong Kong
| | - Heath Pardoe
- Department of Neurology, New York University, New York, NY, USA
| | - Jack Lancaster
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA ; Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Larry R Price
- College of Education, Texas State University, San Marcos, TX, USA ; College of Science, Texas State University, San Marcos, TX, USA
| | - Karen Blackmon
- Department of Neurology, New York University, New York, NY, USA
| | - Kristen Berry
- Department of Neurology, New York University, New York, NY, USA
| | - Jose E Cavazos
- Department of Neurology, University of TX Health Science Center, San Antonio, TX, USA ; San Antonio Epilepsy Center of Excellence, South Texas Veterans Health Care System, San Antonio, TX, USA
| | - Ruben Kuzniecky
- Department of Neurology, New York University, New York, NY, USA
| | - Orrin Devinsky
- Department of Neurology, New York University, New York, NY, USA
| | - Thomas Thesen
- Department of Neurology, New York University, New York, NY, USA
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Affiliation(s)
- Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology and Faculty In charge Advanced Brain Imaging Facility, Cognitive Neuroscience Centre, National Institute of Mental Health And Neurosciences, Bangalore, Karnataka, India
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Kucukboyaci NE, Kemmotsu N, Cheng CE, Girard HM, Tecoma ES, Iragui VJ, McDonald CR. Functional connectivity of the hippocampus in temporal lobe epilepsy: feasibility of a task-regressed seed-based approach. Brain Connect 2014; 3:464-74. [PMID: 23869604 DOI: 10.1089/brain.2013.0150] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVE Resting-state functional connectivity (FC) has revealed marked network dysfunction in patients with temporal lobe epilepsy (TLE) compared to healthy controls. However, the nature and the location of these changes have not been fully elucidated nor confirmed by other methodologies. We assessed the presence of hippocampal FC changes in TLE based on the low frequency residuals of task-related functional magnetic resonance imaging data after the removal of task-related activation [i.e., task-regressed functional connectivity MRI (fcMRI)]. METHOD We employed a novel, task-regressed approach to quantify hippocampal FC, and compare hippocampal FC in 17 patients with unilateral TLE (9 left) with 17 healthy controls. RESULTS Our results suggest widespread FC reductions in the mesial cortex associated with the default mode network (DMN), and some local FC increases in the lateral portions of the right hemisphere. We found more pronounced FC decreases in the left hemisphere than in the right, and these FC decreases were greatest in patients with left TLE. Moreover, the FC reductions observed between the hippocampus and posterior cingulate, inferior parietal, paracentral regions are in agreement with previous resting state studies. CONCLUSIONS Consistent with the existing literature, FC reductions in TLE appear widespread with prominent reductions in the medial portion of the DMN. Our data expand the literature by demonstrating that reductions in FC may be greatest in the left hemisphere and in patients with left TLE. Overall, our findings suggest that task-regressed FC is a viable alternative to resting state and that future studies may extract similar information on network connectivity from already existing datasets.
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