Remodeling of brain morphology in temporal lobe epilepsy.


Journal

Brain and behavior
ISSN: 2162-3279
Titre abrégé: Brain Behav
Pays: United States
ID NLM: 101570837

Informations de publication

Date de publication:
11 2020
Historique:
received: 27 04 2020
revised: 10 08 2020
accepted: 14 08 2020
pubmed: 19 9 2020
medline: 25 6 2021
entrez: 18 9 2020
Statut: ppublish

Résumé

Mesial temporal lobe epilepsy (TLE) is one of the most widespread neurological network disorders. Computational anatomy MRI studies demonstrate a robust pattern of cortical volume loss. Most statistical analyses provide information about localization of significant focal differences in a segregationist way. Multivariate Bayesian modeling provides a framework allowing inferences about inter-regional dependencies. We adopt this approach to answer following questions: Which structures within a pattern of dynamic epilepsy-associated brain anatomy reorganization best predict TLE pathology. Do these structures differ between TLE subtypes? We acquire clinical and MRI data from TLE patients with and without hippocampus sclerosis (n = 128) additional to healthy volunteers (n = 120). MRI data were analyzed in the computational anatomy framework of SPM12 using classical mass-univariate analysis followed by multivariate Bayesian modeling. After obtaining TLE-associated brain anatomy pattern, we estimate predictive power for disease and TLE subtypes using Bayesian model selection and comparison. We show that ipsilateral para-/hippocampal regions contribute most to disease-related differences between TLE and healthy controls independent of TLE laterality and subtype. Prefrontal cortical changes are more discriminative for left-sided TLE, whereas thalamus and temporal pole for right-sided TLE. The presence of hippocampus sclerosis was linked to stronger involvement of thalamus and temporal lobe regions; frontoparietal involvement was predominant in absence of sclerosis. Our topology inferences on brain anatomy demonstrate a differential contribution of structures within limbic and extralimbic circuits linked to main effects of TLE and hippocampal sclerosis. We interpret our results as evidence for TLE-related spatial modulation of anatomical networks.

Sections du résumé

BACKGROUND
Mesial temporal lobe epilepsy (TLE) is one of the most widespread neurological network disorders. Computational anatomy MRI studies demonstrate a robust pattern of cortical volume loss. Most statistical analyses provide information about localization of significant focal differences in a segregationist way. Multivariate Bayesian modeling provides a framework allowing inferences about inter-regional dependencies. We adopt this approach to answer following questions: Which structures within a pattern of dynamic epilepsy-associated brain anatomy reorganization best predict TLE pathology. Do these structures differ between TLE subtypes?
METHODS
We acquire clinical and MRI data from TLE patients with and without hippocampus sclerosis (n = 128) additional to healthy volunteers (n = 120). MRI data were analyzed in the computational anatomy framework of SPM12 using classical mass-univariate analysis followed by multivariate Bayesian modeling.
RESULTS
After obtaining TLE-associated brain anatomy pattern, we estimate predictive power for disease and TLE subtypes using Bayesian model selection and comparison. We show that ipsilateral para-/hippocampal regions contribute most to disease-related differences between TLE and healthy controls independent of TLE laterality and subtype. Prefrontal cortical changes are more discriminative for left-sided TLE, whereas thalamus and temporal pole for right-sided TLE. The presence of hippocampus sclerosis was linked to stronger involvement of thalamus and temporal lobe regions; frontoparietal involvement was predominant in absence of sclerosis.
CONCLUSIONS
Our topology inferences on brain anatomy demonstrate a differential contribution of structures within limbic and extralimbic circuits linked to main effects of TLE and hippocampal sclerosis. We interpret our results as evidence for TLE-related spatial modulation of anatomical networks.

Identifiants

pubmed: 32945137
doi: 10.1002/brb3.1825
pmc: PMC7667340
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e01825

Subventions

Organisme : The Swiss National Science Foundation
ID : 32003B_135679
Organisme : The Swiss National Science Foundation
ID : 32003B_159780
Organisme : The Swiss National Science Foundation
ID : SPUM 33CM30_140332/1
Organisme : The Swiss National Science Foundation
ID : 324730_192755
Organisme : The Swiss National Science Foundation
ID : CRSK-3_190185
Organisme : The Leenaards Foundation
Organisme : H2020-EU Morphemic project
ID : 871643
Organisme : The Intelligence Advanced Research Projects Activity (IARPA)
Organisme : The European Union Seventh Framework Programme (FP7/2007-2013)
ID : 604102
Organisme : The Roger de Spoelberch and Partridge Foundations

Informations de copyright

© 2020 The Authors. Brain and Behavior published by Wiley Periodicals LLC.

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Auteurs

Elisabeth Roggenhofer (E)

Neurology Department, Department of Clinical Neuroscience, HUG, University Hospitals and Faculty of Medicine Geneva, Geneva, Switzerland.
Department of Clinical Neurosciences, LREN, CHUV, University of Lausanne, Lausanne, Switzerland.

Sandrine Muller (S)

Department of Clinical Neurosciences, LREN, CHUV, University of Lausanne, Lausanne, Switzerland.

Emiliano Santarnecchi (E)

Berenson-Allen Center for Non-Invasive Brain Stimulation, Cognitive Neurology Department, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA.
Siena Brain Investigation and Neuromodulation Lab, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.

Lester Melie-Garcia (L)

Department of Clinical Neurosciences, LREN, CHUV, University of Lausanne, Lausanne, Switzerland.
Applied Signal Processing Group, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.

Roland Wiest (R)

Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital, University of Bern, Bern, Switzerland.

Ferath Kherif (F)

Department of Clinical Neurosciences, LREN, CHUV, University of Lausanne, Lausanne, Switzerland.

Bogdan Draganski (B)

Department of Clinical Neurosciences, LREN, CHUV, University of Lausanne, Lausanne, Switzerland.
Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, Germany.

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