Evidence map›Paper›PMID 34455445›Full record

ArticleChild's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery2022

Global and intertuberal epileptic networks in tuberous sclerosis based on stereoelectroencephalographic (sEEG) findings: a quantitative EEG analysis in pediatric subjects and surgical implications.

H Alexander, R B Govindan, T Anwar, V C Chirumamilla, I Fayed, R F Keating, W D Gaillard, C O Oluigbo

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Article in Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
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  7. Seizure reduction in TSC2-mutant mouse model by an mTOR catalytic inhibitor.Annals of clinical and translational neurology · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

H AlexanderDivision of Neurosurgery, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
R B GovindanDivision of Fetal and Transitional Medicine, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
T AnwarDivision of Neurology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
V C ChirumamillaDivision of Fetal and Transitional Medicine, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
I FayedDivision of Neurosurgery, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
R F KeatingDivision of Neurosurgery, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
W D GaillardGeorge Washington University School of Medicine and Health Sciences, 2300 I St NW, Washington, DC, 20052, USA.
C O OluigboDivision of Neurosurgery, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA. coluigbo@cnmc.org.ORCID 0000-0002-7851-3792
Children's National · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveRecent evidence favors a network concept in tuberous sclerosis (TSC) with seizure generation and propagation related to changes in global and regional connectivity between multiple, anatomically distant tubers. Direct exploration of network dynamics in TSC has been made possible through intracranial sampling with stereoelectroencephalography (sEEG). The objective of this study is to define epileptic networks in TSC using quantitative analysis of sEEG recordings. We also discuss the impact of the definition of these epileptic networks on surgical decision-making.

methodsIntracranial sEEG recordings were obtained from four pediatric patients who presented with medically refractory epilepsy secondary to TSC and subjected to quantitative signal analysis methods. Cortical connectivity was quantified by calculating pairwise coherence between all contacts and constructing an association matrix. The global coherence, defined as the ratio of the largest eigenvalue to the sum of all the eigenvalues, was calculated for each frequency band (delta, theta, alpha, beta, gamma). Spatial distribution of the connectivity was identified by plotting the leading principal component (product of the largest eigenvalue and its corresponding eigenvector).

resultsFour pediatric subjects with TSC underwent invasive intracranial monitoring with sEEG, comprising 31 depth electrodes and 250 contacts, for localization of the epileptogenic focus and guidance of subsequent surgical intervention. Quantitative connectivity analysis revealed a change in global coherence during the ictal period in the beta/low gamma (14-30 Hz) and high gamma (31-80 Hz) bands. Our results corroborate findings from existing literature, which implicate higher frequencies as a driver of synchrony and desynchrony.

conclusionsCoordinated high-frequency activity in the beta/low gamma and high gamma bands among spatially distant sEEG define the ictal period in TSC. This time-dependent change in global coherence demonstrates evidence for intra-tuberal and inter-tuberal connectivity in TSC. This observation has surgical implications. It suggests that targeting multiple tubers has a higher chance of seizure control as there is a higher chance of disrupting the epileptic network. The use of laser interstitial thermal therapy (LITT) allowed us to target multiple disparately located tubers in a minimally invasive manner with good seizure control outcomes.

Indexed as

EpilepsyTuberous SclerosisChildElectroencephalographyHumansStereotaxic TechniquesTreatment OutcomeEpileptic networksGlobal coherencePediatricQuantitative analysisStereoelectroencephalography (sEEG)Tuberous sclerosis complex (TSC)

Identifiers

PMID34455445
OpenAlexW3197147046

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.