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Distinct gray matter and metabolic characteristics in hypothalamic hamartoma network with different semiology

Lookup NU author(s): Professor Peter TaylorORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

© 2025 The Author(s). Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy. Objective: Hypothalamic hamartomas (HHs) are developmental malformations associated with focal epilepsy. We investigated the patterns of gray matter morphology and cerebral metabolism in individuals with HHs, with and without focal to bilateral tonic–clonic seizures (FBTCSs), aiming to clarify the accompanying network abnormalities. Methods: We analyzed magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (PET) data from 59 patients with HHs (28 with FBTCSs, 31 without), as well as MRI data from 30 healthy controls (HCs) and PET data from 45 HCs. We assessed gray matter voxel-based morphometry and quantitative analysis of cerebral glucose uptake in HH patients and controls, with age, sex, and total intracranial volume as covariates, and drew correlations with duration of epilepsy and seizure semiology and frequency. Results: Compared to HCs, HH patients had significantly increased gray matter volume (GMV) in the ipsilateral amygdala, piriform cortex, hypothalamus, and bilateral temporal cortices; patients with FBTCSs primarily showed increased GMV in the HH stalk, whereas those without FBTCSs showed increased GMV prominently in the amygdala. GMVs of amygdala and piriform cortex were greater and the ipsilateral midtemporal cortex was more hypometabolic the longer the duration of epilepsy and the greater the seizure frequency. No significant GMV or cerebral glucose uptake differences were found between HH patients with and without FBTCSs. Significance: HH-related epilepsy is a network disorder characterized by widespread abnormalities beyond the lesion. This highlights the importance of considering the whole network when formulating diagnosis and treatment plans.


Publication metadata

Author(s): Wang Y, Feng T, Xiao F, Yang Y, Fleury MN, Binding LP, Giampiccolo D, Taylor P, Koepp MJ, Duncan JS, Wei P, Shan Y, Zhao G

Publication type: Article

Publication status: Published

Journal: Epilepsia

Year: 2025

Volume: 66

Issue: 8

Pages: 2853-2863

Print publication date: 01/08/2025

Online publication date: 29/04/2025

Acceptance date: 17/04/2025

Date deposited: 01/09/2025

ISSN (print): 0013-9580

ISSN (electronic): 1528-1167

Publisher: John Wiley and Sons Inc.

URL: https://doi.org/10.1111/epi.18438

DOI: 10.1111/epi.18438

Data Access Statement: The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

PubMed id: 40299305


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Funding

Funder referenceFunder name
Beijing Municipal Science & Technology Commission (Z221100007422016, Z221100002722007)
Epilepsy Research UK (P1904)
Epilepsy Society
National Natural Science Foundation of China (82030037)
STI2030-Major Projects (2021ZD0201801)
Translational and Application Project of Brain-Inspired and Network Neuroscience on Brain Disorders, Beijing Municipal Health Commission (11000023 T000002036286)

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