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Record W3081310575 · doi:10.1093/brain/awaa200

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study

2020· article· en· W3081310575 on OpenAlexafffund
Sean N. Hatton, Khoa H Huynh, Leonardo Bonilha, Eugenio Abela, Saud Alhusaini, André Altmann, Marina K. M. Alvim, Akshara R. Balachandra, Emanuele Bartolini, Benjamin Bender, Neda Bernasconi, Andrea Bernasconi, Boris C. Bernhardt, Núria Bargalló, Benoît Caldairou, Maria Eugenia Caligiuri, Sarah J. A. Carr, Gianpiero L. Cavalleri, Fernando Cendes, Luis Concha, Esmaeil Davoodi‐Bojd, Patricia Desmond, Orrin Devinsky, Colin P. Doherty, Martin Domín, John S. Duncan, Niels K. Focke, Sonya Foley, Antonio Gambardella, Ezequiel Gleichgerrcht, Renzo Guerrini, Khalid Hamandi, Akari Ishikawa, Simon S. Keller, Peter Kochunov, Raviteja Kotikalapudi, Barbara A. K. Kreilkamp, Patrick Kwan, Angelo Labate, Sönke Langner, Matteo Lenge, Min Liu, Elaine Lui, Pascal Martin, Mario Mascalchi, José C.V. Moreira, Marcia Morita‐Sherman, Terence J. O’Brien, Heath Pardoe, José C. Pariente, Letícia Ribeiro, Mark P. Richardson, Cristiane S. Rocha, Raúl Rodríguez‐Cruces, Felix Rosenow, Mariasavina Severino, Benjamin Sinclair, Hamid Soltanian‐Zadeh, Pasquale Striano, Peter N. Taylor, Rhys H. Thomas, Domenico Tortora, Dennis Velakoulis, Annamaria Vezzani, Lucy Vivash, Felix von Podewils, Sjoerd B. Vos, Bernd Weber, Gavin P. Winston, Clarissa Lin Yasuda, Alyssa H. Zhu, Paul M. Thompson, Christopher D. Whelan, Neda Jahanshad, Sanjay M. Sisodiya, Carrie R. McDonald

Bibliographic record

VenueBrain · 2020
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsQueen's UniversityMcGill UniversityTrinity CollegeMontreal Neurological Institute and Hospital
FundersNational Institute of Neurological Disorders and StrokeFundação de Amparo à Pesquisa do Estado de São PauloNational Health and Medical Research CouncilNatural Sciences and Engineering Research Council of CanadaNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchEuropean Regional Development FundEberhard Karls Universität TübingenUniversity College London Hospitals NHS Foundation TrustNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchMedical Research Council Centre for Neurodevelopmental DisordersCanada Research ChairsConselho Nacional de Desenvolvimento Científico e TecnológicoConsejo Nacional de Ciencia y TecnologíaFinding A Cure for Epilepsy and SeizuresScience Foundation IrelandMedical Research CouncilNational Institute of Mental HealthNational Institute on Handicapped ResearchCardiff UniversityNational Institutes of HealthEpilepsy Research UKUniversity College LondonNational Institute on AgingNational Institute for Health and Care ResearchSick Kids FoundationHealth and Care Research Wales
KeywordsEpilepsyWhite matterMedicineNeurosciencePsychologyPsychiatryMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.322
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations233
Published2020
Admission routes2
Has abstractyes

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