Evidence map›Paper›PMID 41540374›Full record

ArticleBMC neurology2026

A network-based EEG source imaging framework for noninvasive localization of epileptogenic zones in MRI-negative focal drug-resistant epilepsy.

Shicun Huang, Xiaowei Hu, Yiqing Wang, Wei Gao, Qi Fang

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Article in BMC neurology, 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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5 authors.

Shicun Huang *Department of Neurology, The First Affiliated Hospital of Soochow University, 899 PingHai Road, Gusu District, Suzhou, Jiangsu, 215000, China.
Xiaowei Hu *Department of Neurology, The First Affiliated Hospital of Soochow University, 899 PingHai Road, Gusu District, Suzhou, Jiangsu, 215000, China.
Yiqing Wang *Department of Neurology, The First Affiliated Hospital of Soochow University, 899 PingHai Road, Gusu District, Suzhou, Jiangsu, 215000, China.
Wei GaoDepartment of Neurosurgery, The First Affiliated Hospital of Soochow University, 899 PingHai Road, Gusu District, Suzhou, Jiangsu, 215000, China. gaowei@suda.edu.cn.
Qi FangDepartment of Neurology, The First Affiliated Hospital of Soochow University, 899 PingHai Road, Gusu District, Suzhou, Jiangsu, 215000, China. fangqi_008@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and evaluate a dynamic brain network analysis framework integrating electroencephalography (EEG) source imaging (ESI) for non-invasive localization of the epileptogenic zone (EZ) in patients with magnetic resonance imaging (MRI)-negative focal drug-resistant epilepsy (DRE).

methodsWe retrospectively analyzed 15 patients with MRI-negative focal DRE who underwent resective surgery. Preictal scalp EEG data were processed using ESI, followed by power spectral density and directed transfer function analyses to construct epileptic brain networks. Network metrics, including seizure index (SI), degree centrality (DC), out-degree centrality (DCout), and in-degree centrality (DCin), were calculated and evaluated for spatial concordance with postoperative resection zones and clinical outcomes.

resultsAmong the evaluated metrics, SI demonstrated the highest overall diagnostic performance, with a sensitivity of 60% and a specificity of 80%. DC and DCout showed high specificity (83.3%) but lower sensitivity, whereas DCin exhibited comparatively reduced sensitivity and accuracy.

conclusionThis non-invasive ESI-based network framework is capable of localizing epileptogenic regions in MRI-negative focal DRE. SI provided the most balanced performance across sensitivity and specificity, while DC and DCout contributed complementary information regarding epileptic network cores. SIGNIFICANCE: The proposed framework offers a clinically feasible and non-invasive approach to support preoperative EZ localization, with potential value for presurgical evaluation in patients with MRI-negative epilepsy.

Indexed as

BrainDrug Resistant EpilepsyElectroencephalographyAdolescentAdultBrain MappingFemaleHumansMagnetic Resonance ImagingMaleRetrospective StudiesSensitivity and SpecificityYoung AdultDrug-resistant epilepsyEEG source imagingEpileptogenic zoneMRI-negative epilepsyNetwork analysis

Identifiers

PMID41540374
PMCPMC12892749

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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.