Evidence map›Paper›PMID 37090233›Full record

ArticleArXiv2023

Interictal MEG abnormalities to guide intracranial electrode implantation and predict surgical outcome.

Tom Owen, Vytene Janiukstyte, Gerard R Hall, Fahmida A Chowdhury, Beate Diehl, Andrew McEvoy, Anna Miserocchi, Jane de Tisi, John S Duncan, Fergus Rugg-Gunn and 2 more

Open access · greenAbstract readPreprint
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Tom OwenCNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
Vytene JaniukstyteCNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
Gerard R HallCNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
Fahmida A ChowdhuryUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
Beate DiehlUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
Andrew McEvoyUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
Anna MiserocchiUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
Jane de TisiUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
John S DuncanUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
Fergus Rugg-GunnUCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
Yujiang WangCNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
Peter Neal TaylorCNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
University College London · GBNational Hospital for Neurology and Neurosurgery · GBNewcastle University · GB

Funding

SUDEP Translational Research Alliance (SUTRA): Autonomic and Imaging Biomarkers of SUDEP; SUTRA 3 of 7U01NS090407 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI DIEHL, BEATE, HARPER, RONALD MARVEN · 2014 to 2018
$7.3M
NINDS NIH HHS U01 NS090407Wellcome Trust
6 · The paper itself

Abstract

Intracranial EEG (iEEG) is the gold standard technique for epileptogenic zone (EZ) localisation, but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography (MEG). Quantitative abnormality mapping using MEG has recently been shown to have potential clinical value. We hypothesised that if quantifiable MEG abnormalities were sampled by iEEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent MEG and subsequent iEEG recordings as part of pre-surgical evaluation. Eyes-closed resting-state interictal MEG band power abnormality maps were derived from 70 healthy controls as a normative baseline. MEG abnormality maps were compared to iEEG electrode implantation, with the spatial overlap of iEEG electrode placement and cerebral MEG abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue, and subsequent resection of the strongest abnormalities determined by MEG and iEEG corresponded to surgical success. Intracranial electrodes were implanted in brain tissue with the most abnormal MEG findings - in individuals that were seizure-free post-operatively (T=3.9, p=0.003), but not in those who did not become seizure free. The overlap between MEG abnormalities and electrode placement distinguished surgical outcome groups moderately well (AUC=0.68). In isolation, the resection of the strongest abnormalities as defined by MEG and iEEG separated surgical outcome groups well, AUC=0.71, AUC=0.74 respectively. A model incorporating all three features separated surgical outcome groups best (AUC=0.80). Intracranial EEG is a key tool to delineate the EZ and help render individuals seizure-free post-operatively. We showed that data-driven abnormality maps derived from resting-state MEG recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of post-operative seizure-freedom, which leverages both MEG and iEEG recordings, could aid patient counselling of expected outcome.

Identifiers

PMID37090233
PMCPMC10120748
OpenAlexW4366821856

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.