MétaCan
Menu
Back to cohort
Record W4410398837 · doi:10.1111/epi.18459

No association between histopathology and neurophysiology in surgical specimens from pediatric focal epilepsy patients

2025· article· en· W4410398837 on OpenAlexafffund
Nicolás von Ellenrieder, Mariam Al-Rashid, Kenneth A. Myers, Bradley Osterman, Elisabeth Simard‐Tremblay, Jason Karamchandani, Marie‐Christine Guiot, Jean Gotman, Roy Dudley

Bibliographic record

VenueEpilepsia · 2025
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsMcGill University Health CentreMontreal Children's HospitalMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsStereoelectroencephalographyIctalHistopathologyEpilepsyMedicinePathologicalMagnetic resonance imagingEpilepsy surgeryPathologyNeurophysiologyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Focal epilepsy is caused by focal brain pathologies sometimes with involvement of surrounding or distant tissue. However, within the epileptogenic zone (EZ), which can be resected to cure epilepsy, the contribution of histopathological cells to epileptogenicity remains unknown. We hypothesized that areas showing neurophysiological biomarkers of epileptogenicity would more often contain histopathological cells compared to areas without such biomarkers. METHODS: Pediatric epilepsy patients with nonlesional magnetic resonance imaging (MRI), or with lesions with unclear borders, underwent stereoelectroencephalographic (SEEG) exploration followed by resective surgery of the suspected EZ. Tissue specimens were taken from locations where the SEEG contacts had been, using intraoperative MRI-guided precise neuronavigation. Then, we explored the association between histopathology and rates of interictal epileptic discharges, ripples, and fast ripples (FRs), and the channels of the seizure onset zone (SOZ). RESULTS: The association between histopathology and ictal/interictal activity was low and not statistically significant in 260 specimens from 20 surgeries. Rates of interictal events were slightly lower for pathological samples than in normal tissue (low effect size, Cliff |d| < .15, p > .1). The classification accuracy of tissue as normal or pathological based on interictal activity/SOZ was low (accuracy ≤ 54%). As a secondary outcome, SEEG events were excellent predictors of surgical outcome, FRs leading to perfect prediction (20/20). SIGNIFICANCE: Histopathological tissue initiates epileptogenicity in focal epilepsy. However, our findings suggest that the EZ is not strictly a histopathological entity but a hybrid of abnormal cells and normal-appearing cells. Thus, SEEG events are biomarkers of epileptogenicity and not histopathology. Resecting of electrophysiological biomarkers of epileptogenicity may be more important than resecting all histopathology.

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)0.004
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.273
Teacher spread0.264 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueEpilepsiaSame topicEpilepsy research and treatmentFrench-language works237,207