Remodeling of brain morphology in temporal lobe epilepsy
| Autor: | Emiliano Santarnecchi, Ferath Kherif, Bogdan Draganski, Roland Wiest, Lester Melie-Garcia, Elisabeth Roggenhofer, Sandrine Muller |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
hippocampus
network atrophy Hippocampus Hippocampal formation Functional Laterality Behavioral Neuroscience Epilepsy hippocampal 0302 clinical medicine magnetic resonance imaging 610 Medicine & health Original Research mechanisms white-matter 05 social sciences Brain temporal lobe epilepsy organization Computational anatomy classification connectivity Laterality abnormalities Bayes Theorem Brain/diagnostic imaging Brain/pathology Epilepsy Temporal Lobe/diagnostic imaging Hippocampus/diagnostic imaging Hippocampus/pathology Humans Magnetic Resonance Imaging Sclerosis/diagnostic imaging Sclerosis/pathology BMS Bayesian model selection MVB computational anatomy multivariate Bayesian modeling psychological phenomena and processes bayesian model selection behavioral disciplines and activities 050105 experimental psychology lcsh:RC321-571 Temporal lobe 03 medical and health sciences mvb medicine voxel-based morphometry 0501 psychology and cognitive sciences lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Hippocampal sclerosis Sclerosis business.industry Brain morphometry medicine.disease nervous system diseases multivariate bayesian modeling Epilepsy Temporal Lobe nervous system bms progression business Neuroscience 030217 neurology & neurosurgery |
| Zdroj: | Roggenhofer, Elisabeth; Muller, Sandrine; Santarnecchi, Emiliano; Melie-Garcia, Lester; Wiest, Roland; Kherif, Ferath; Draganski, Bogdan (2020). Remodeling of brain morphology in temporal lobe epilepsy. Brain and Behavior, 10(11), e01825. Wiley 10.1002/brb3.1825 Brain and behavior, vol. 10, no. 11, pp. e01825 Sygma Infoscience-EPFL scientific publications PubMed Central Bern Open Repository and Information System (BORIS) Datacite UnpayWall ORCID Microsoft Academic Graph Serveur académique lausannois DOAJ-Articles MPG.PuRe Brain and behavior, pp. e01825 Brain and Behavior, Vol 10, Iss 11, Pp n/a-n/a (2020) Brain and Behavior |
| ISSN: | 2162-3279 |
| DOI: | 10.7892/boris.146656 |
| Popis: | 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. In focal cryptogenic epilepsy, morphological abnormalities often remain undetected at the macroscopic brain level. We use Multivariate Bayesian modeling analysis to link the spatial patterns of brain anatomy remodeling in temporal lobe epilepsy patients with their clinical phenotype. This approach allows detecting the regions which have an impact on the ongoing disease process. Our study could serve as proof‐of‐concept for the added value of topology analysis for detection of focal structural abnormalities in focal epilepsy that can be further implemented for other brain disorders. |
| Databáze: | OpenAIRE |
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