Evidence map›Paper›PMID 37750611›Full record

ArticleHuman brain mapping2023

Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling.

Zhengchen Cai, Nicolás von Ellenrieder, Andreas Koupparis, Hui Ming Khoo, Satoru Ikemoto, Masataka Tanaka, Chifaou Abdallah, Saba Rammal, Francois Dubeau, Jean Gotman

Abstract read
In one paragraph

Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Zhengchen CaiThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.
Nicolás von EllenriederThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.
Andreas KoupparisThe Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.
Hui Ming KhooDepartment of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan.
Satoru IkemotoThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.
Masataka TanakaDepartment of Neurosurgery, Yao Municipal Hospital, Yao-city, Osaka, Japan.
Chifaou AbdallahThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.
Saba RammalThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.
Francois DubeauThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.
Jean GotmanThe Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada.

Funding

CIHR FDN 143208
6 · The paper itself

Abstract

Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a unique and noninvasive method for epilepsy presurgical evaluation. When selecting voxels by null-hypothesis tests, the conventional analysis may overestimate fMRI response amplitudes related to interictal epileptic discharges (IEDs), especially when IEDs are rare. We aimed to estimate fMRI response amplitudes represented by blood oxygen level dependent (BOLD) percentage changes related to IEDs using a hierarchical model. It involves the local and distributed hemodynamic response homogeneity to regularize estimations. Bayesian inference was applied to fit the model. Eighty-two epilepsy patients who underwent EEG-fMRI and subsequent surgery were included in this study. A conventional voxel-wise general linear model was compared to the hierarchical model on estimated fMRI response amplitudes and on the concordance between the highest response cluster and the surgical cavity. The voxel-wise model overestimated fMRI responses compared to the hierarchical model, evidenced by a practically and statistically significant difference between the estimated BOLD percentage changes. Only the hierarchical model differentiated brief and long-lasting IEDs with significantly different BOLD percentage changes. Overall, the hierarchical model outperformed the voxel-wise model on presurgical evaluation, measured by higher prediction performance. When compared with a previous study, the hierarchical model showed higher performance metric values, but the same or lower sensitivity. Our results demonstrated the capability of the hierarchical model of providing more physiologically reasonable and more accurate estimations of fMRI response amplitudes induced by IEDs. To enhance the sensitivity of EEG-fMRI for presurgical evaluation, it may be necessary to incorporate more appropriate spatial priors and bespoke decision strategies.

Indexed as

EpilepsyMagnetic Resonance ImagingBayes TheoremBrainBrain MappingElectroencephalographyHumansOxygenOxygenBayesian workflowBOLD percentage changeEEG-fMRIepilepsyhierarchical modelIEDspresurgical evaluation

Identifiers

PMID37750611
PMCPMC10619415

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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.