Evidence map›Paper›PMID 42470542›Full record

ArticleActa neurochirurgica2026

Automated preoperative volumetric analysis as a marker of the seizure irritative zone.

Dorian M Kusyk, Stephen Jaffee, Christopher Sanfilippo, Trent Kite, Nicholas Blaney, Jenna Li, Timothy Quezada, Tyson Tragon, Alexander C Whiting

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Article in Acta neurochirurgica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Dorian M KusykDepartment of Neurosurgery, Neurosciences Institute, Allegheny Health Network, Allegheny General Hospital Tower, 320 East North Avenue, Suite 208, Pittsburgh, PA, 15212, USA.
Stephen JaffeeDepartment of Neurosurgery, Neurosciences Institute, Allegheny Health Network, Allegheny General Hospital Tower, 320 East North Avenue, Suite 208, Pittsburgh, PA, 15212, USA.
Christopher SanfilippoDepartment of Neurology, Neurosciences Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Trent KiteDepartment of Neurosurgery, Neurosciences Institute, Allegheny Health Network, Allegheny General Hospital Tower, 320 East North Avenue, Suite 208, Pittsburgh, PA, 15212, USA.
Nicholas BlaneyCollege of Medicine, Drexel University, Philadelphia, PA, USA.
Jenna LiDepartment of Neurosurgery, Neurosciences Institute, Allegheny Health Network, Allegheny General Hospital Tower, 320 East North Avenue, Suite 208, Pittsburgh, PA, 15212, USA.
Timothy QuezadaDepartment of Neurology, Neurosciences Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Tyson TragonDepartment of Neuroradiology, Neurosciences Institute, Allegheny Health Network, Pittsburgh, PA, USA.
Alexander C WhitingDepartment of Neurosurgery, Neurosciences Institute, Allegheny Health Network, Allegheny General Hospital Tower, 320 East North Avenue, Suite 208, Pittsburgh, PA, 15212, USA. Alexander.whiting@ahn.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStereo-electroencephalography (SEEG) is increasingly utilized in surgical epilepsy evaluations, however, more robust preoperative data can aid in localizing and focusing SEEG electrode placement. Automated MRI volumetric analysis in patients with drug-resistant epilepsy may help predict aspects of the seizure network, as confirmed with invasive SEEG analysis.

methodsPre-operative MRIs of patients undergoing SEEG investigation were analyzed using an automated volumetric platform and compared to age- and sex-matched controls. The patient's seizure network was parsed into subcomponents based on the SEEG investigation and compared to volumetric data.

resultsNineteen patients were analyzed. On logistic regression, each one standard deviation increase in regional volume increased the odds that a region was part of the irritative zone (OR 1.36, 95% CI = [1.08, 1.71], p = 0.009), though this estimate should be considered exploratory given the non-independence of regions within patients. In patients with temporal lobe epilepsy (15/19), increased volume was associated with the irritative zone (OR 1.49, CI = [1.16,1.93], p = 0.002) and the seizure network overall (OR 1.31, CI = [1.04, 1.65], p = 0.023), while decreased volume was suggestive of non-involvement with the network (OR 0.76, CI = [0.60, 0.96], p = 0.023).

conclusionsRegions with an increased cortical volume as determined by rapid, automated volumetric analysis were more likely to be part of the seizure network irritative zone. This may represent a novel avenue for a low-cost, non-invasive analysis of patients' seizure networks. Further work is needed to better elucidate the relationship between cortical volumes and seizure networks and determine the potential of using automated volumetric analysis as a non-invasive tool in the preoperative work-up.

Indexed as

Cerebral CortexDrug Resistant EpilepsyEpilepsy, Temporal LobeMagnetic Resonance ImagingSeizuresAdolescentAdultElectroencephalographyFemaleHumansMalePreoperative CareYoung AdultIrritative ZoneMRI VolumetricsSEEGSeizure network

Identifiers

PMID42470542
PMCPMC13661638

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