Structural Connectivity Alterations in Operculo-Insular Epilepsy.
Sami ObaidFrançois RheaultManon EddeGuido I GubermanEtienne St-OngeJasmeen SidhuAlain BouthillierAlessandro DaducciJimmy GhaziriMichel W BojanowskiDang K NguyenEmmanuel MandonnetPublished in: Brain sciences (2021)
Operculo-insular epilepsy (OIE) is an under-recognized condition that can mimic temporal and extratemporal epilepsies. Previous studies have revealed structural connectivity changes in the epileptic network of focal epilepsy. However, most reports use the debated streamline-count to quantify 'connectivity strength' and rely on standard tracking algorithms. We propose a sophisticated cutting-edge method that is robust to crossing fibers, optimizes cortical coverage, and assigns an accurate microstructure-reflecting quantitative conectivity marker, namely the COMMIT (Convex Optimization Modeling for Microstructure Informed Tractography)-weight. Using our pipeline, we report the connectivity alterations in OIE. COMMIT-weighted matrices were created in all participants (nine patients with OIE, eight patients with temporal lobe epilepsy (TLE), and 22 healthy controls (HC)). In the OIE group, widespread increases in 'connectivity strength' were observed bilaterally. In OIE patients, 'hyperconnections' were observed between the insula and the pregenual cingulate gyrus (OIE group vs. HC group) and between insular subregions (OIE vs. TLE). Graph theoretic analyses revealed higher connectivity within insular subregions of OIE patients (OIE vs. TLE). We reveal, for the first time, the structural connectivity distribution in OIE. The observed pattern of connectivity in OIE likely reflects a diffuse epileptic network incorporating insular-connected regions and may represent a structural signature and diagnostic biomarker.
Keyphrases
- white matter
- resting state
- functional connectivity
- end stage renal disease
- multiple sclerosis
- newly diagnosed
- chronic kidney disease
- ejection fraction
- temporal lobe epilepsy
- peritoneal dialysis
- prognostic factors
- single cell
- patient reported outcomes
- physical activity
- healthcare
- deep learning
- high resolution
- magnetic resonance
- gene expression
- weight gain
- computed tomography
- low grade
- network analysis
- dna methylation
- peripheral blood
- affordable care act