Dataset Information

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy.

ABSTRACT: Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

SUBMITTER: Park BY

PROVIDER: S-EPMC9128824 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy.

Park Bo-Yong BY Larivière Sara S Rodríguez-Cruces Raul R Royer Jessica J Tavakol Shahin S Wang Yezhou Y Caciagli Lorenzo L Caligiuri Maria Eugenia ME Gambardella Antonio A Concha Luis L Keller Simon S SS Cendes Fernando F Alvim Marina K M MKM Yasuda Clarissa C Bonilha Leonardo L Gleichgerrcht Ezequiel E Focke Niels K NK Kreilkamp Barbara A K BAK Domin Martin M von Podewils Felix F Langner Soenke S Rummel Christian C Rebsamen Michael M Wiest Roland R Martin Pascal P Kotikalapudi Raviteja R Bender Benjamin B O'Brien Terence J TJ Law Meng M Sinclair Benjamin B Vivash Lucy L Kwan Patrick P Desmond Patricia M PM Malpas Charles B CB Lui Elaine E Alhusaini Saud S Doherty Colin P CP Cavalleri Gianpiero L GL Delanty Norman N Kälviäinen Reetta R Jackson Graeme D GD Kowalczyk Magdalena M Mascalchi Mario M Semmelroch Mira M Thomas Rhys H RH Soltanian-Zadeh Hamid H Davoodi-Bojd Esmaeil E Zhang Junsong J Lenge Matteo M Guerrini Renzo R Bartolini Emanuele E Hamandi Khalid K Foley Sonya S Weber Bernd B Depondt Chantal C Absil Julie J Carr Sarah J A SJA Abela Eugenio E Richardson Mark P MP Devinsky Orrin O Severino Mariasavina M Striano Pasquale P Parodi Costanza C Tortora Domenico D Hatton Sean N SN Vos Sjoerd B SB Duncan John S JS Galovic Marian M Whelan Christopher D CD Bargalló Núria N Pariente Jose J Conde-Blanco Estefania E Vaudano Anna Elisabetta AE Tondelli Manuela M Meletti Stefano S Kong Xiang-Zhen XZ Francks Clyde C Fisher Simon E SE Caldairou Benoit B Ryten Mina M Labate Angelo A Sisodiya Sanjay M SM Thompson Paul M PM McDonald Carrie R CR Bernasconi Andrea A Bernasconi Neda N Bernhardt Boris C BC

Brain : a journal of neurology 20220501 4

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have ...[more]

PMID: 35333312

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Project description:Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data are captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-centre study for model development; two-centre study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using several interictal EEG features derived from recent publications. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. Forty-seven patients (30 female; ages 20-69; 20 left-sided, 10 right-sided and 17 bilateral seizure onsets) were analysed for model development and internal validation. Nineteen patients (10 female; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analysed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. We replicated the finding that right temporal lobe epilepsy was harder to distinguish in a separate modality of resting-state functional MRI. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome. A potential clinical application of these findings could be to either support or oppose a hypothesis of unilateral temporal lobe epilepsy when deciding to pursue surgical resection or ablation as opposed to device implantation.

Project description:Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data is captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal (between-seizure) intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-center study for model development; two-center study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using interictal EEG. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. 47 patients (30 women; ages 20-69; 20 left-sided, 10 right-sided, and 17 bilateral seizure onsets) were analyzed for model development and internal validation. 19 patients (10 women; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analyzed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome.

Project description:Episodic memory is the ability to remember events from our past accurately. The process of pattern separation is hypothesized to underpin this ability and is defined as the capacity to orthogonalize memory traces, to maximize the features that make them unique. Contemporary cognitive neuroscience suggests that pattern separation entails complex interactions between the hippocampus and neocortex, where specific hippocampal subregions shape neural reinstatement in the neocortex. To test this hypothesis, the current work studied both healthy controls and patients with temporal lobe epilepsy who presented with hippocampal structural anomalies. We measured neural activity in all participants using functional MRI while they retrieved memorized items or lure items, which shared features with the target. Behaviourally, patients with temporal lobe epilepsy were less able to exclude lures than controls and showed a reduction in pattern separation. To assess the hypothesized relationship between neural patterns in the hippocampus and neocortex, we identified the topographic gradients of intrinsic connectivity along neocortical and hippocampal subfield surfaces and determined the topographic profile of the neural activity accompanying pattern separation. In healthy controls, pattern separation followed a graded topography of neural activity, both along the hippocampal long axis (and peaked in anterior segments that are more heavily engaged in transmodal processing) and along the neocortical hierarchy running from unimodal to transmodal regions (peaking in transmodal default mode regions). In patients with temporal lobe epilepsy, however, this concordance between task-based functional activations and topographic gradients was markedly reduced. Furthermore, person-specific measures of concordance between task-related activity and connectivity gradients in patients and controls were related to inter-individual differences in behavioural measures of pattern separation and episodic memory, highlighting the functional relevance of the observed topographic motifs. Our work is consistent with an emerging understanding that successful discrimination between memories with similar features entails a shift in the locus of neural activity away from sensory systems, a pattern that is mirrored along the hippocampal long axis and with respect to neocortical hierarchies. More broadly, our study establishes topographic profiling using intrinsic connectivity gradients, capturing the functional underpinnings of episodic memory processes in a manner that is sensitive to their reorganization in pathology.

Project description:PurposeTo determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE).Materials and methodsThis study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration-cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus.ResultsQuantitative MR imaging-derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%-89.5%) and specificity (92.2%-94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies.ConclusionQuantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice.

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Dataset Information

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy.

Publications

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy.

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