Evidence map›Paper›PMID 42033243›Full record

ArticleCNS neuroscience & therapeutics2026

Clinical Utility of Z-Score Distribution Mapping in Epileptogenic Zone Localizations.

Jinkun Han, Penghu Wei, Sichang Chen, Yanfeng Yang, Yongzhi Shan, Guoguang Zhao

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jinkun HanDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China.ORCID https://orcid.org/0009-0005-7235-6799
Penghu WeiDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-4529-7691
Sichang ChenDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China.
Yanfeng YangDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China.
Yongzhi ShanDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0001-5510-1026
Guoguang ZhaoDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, China.ORCID https://orcid.org/0000-0002-7569-5252

Funding

Beijing Municipal Administration of Hospitals ZLRK202319
6 · The paper itself

Abstract

objectivesThis study aimed to evaluate the clinical utility of positron emission tomography (PET)-based Z-score distribution mapping (Z-map) in the noninvasive presurgical localization of seizure onset zones (SOZs), with a particular focus on regional differences in performance and methodological robustness.

methodsWe analyzed a cohort of 120 patients with drug-resistant epilepsy who underwent stereoelectroencephalography (SEEG) implantation between 2021 and 2024. Multimodal imaging data, including PET and structural MRI, were processed using FreeSurfer and 3D Slicer to reconstruct electrodes, segment gray matter, and generate Z-maps. Hypometabolic regions were defined as the bottom 0.5% of Z-scores. The classification performance of the Z-map was validated against SEEG-defined SOZs.

resultsThe Z-map showed high classification performance in the frontal and parietal lobes (sensitivity: 0.74/0.72; κ: 0.68/0.65), but reduced effectiveness in the temporal and insular lobes (sensitivity: 0.41/0.65; κ: 0.44/0.47). The overall specificity (0.94) and negative predictive value (0.91) indicated strong exclusionary capability. Regional disparities were primarily attributed to anatomical complexity and technical limitations.

conclusionZ-map offers clinically valuable support for localizing SOZs in the frontal and parietal cortex and optimizing SEEG implantation, particularly in patients with inconclusive noninvasive findings. However, its limited sensitivity in temporal and insular regions and high dependency on preprocessing quality underscore the need for standardized pipelines and multimodal integration. Future research should focus on improving robustness and reproducibility to facilitate clinical translation.

Indexed as

Brain MappingDrug Resistant EpilepsyPositron-Emission TomographyAdolescentAdultCohort StudiesElectroencephalographyFemaleHumansMagnetic Resonance ImagingMaleYoung Adultepilepsypositron emission tomography (PET)seizure onset zoneZ‐score distribution mapping

Identifiers

PMID42033243
PMCPMC13109840

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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.