Brain networks and epilepsy development in patients with Alzheimer disease

• Published in: Brain and behavior 2023-08, Vol.13 (8), p.e3152-n/a
• Main Authors: Lee, Dong Ah, Lee, Ho‐Joon, Kim, Si Eun, Park, Kang Min
• Format: Article
• Language: English
• Subjects: Algorithms; Alzheimer's disease; Automation; Communication; Convulsions & seizures; Dementia; Efficiency; Enrollments; Epilepsy; Hospitals; Magnetic resonance imaging; Neurological disorders; Original; Patients; thalamus; Volumetric analysis
• ISSN: 2162-3279; 2162-3279
• DOI: 10.1002/brb3.3152

Introduction This study aimed to investigate the association between brain networks and epilepsy development in patients with Alzheimer disease (AD). Methods We enrolled patients newly diagnosed with AD at our hospital who underwent three‐dimensional T1‐weighted magnetic resonance imaging at the time of AD diagnosis and included healthy controls. We obtained the cortical, subcortical, and thalamic nuclei structural volumes using FreeSurfer and applied graph theory to obtain the global brain network and intrinsic thalamic network based on the structural volumes using BRAPH. Results We enrolled 25 and 56 patients with AD with and without epilepsy development, respectively. We also included 45 healthy controls. The global brain network differed between the patients with AD and healthy controls. The local efficiency (2.026 vs. 3.185, p = .048) and mean clustering coefficient (0.449 vs. 1.321, p = .024) were lower, whereas the characteristic path length (0.449 vs. 1.321, p = .048) was higher in patients with AD than in healthy controls. Both global and intrinsic thalamic networks were significantly different between AD patients with and without epilepsy development. In the global brain network, local efficiency (1.340 vs. 2.401, p = .045), mean clustering coefficient (0.314 vs. 0.491, p = .045), average degree (27.442 vs. 41.173, p = .045), and assortative coefficient (−0.041 vs. −0.011, p = .045) were lower, whereas the characteristic path length (2.930 vs. 2.118, p = .045) was higher in patients with AD with epilepsy development than in those without. In the intrinsic thalamic network, the mean clustering coefficient (0.646 vs. 0.460, p = .048) was higher, whereas the characteristic path length (1.645 vs. 2.232, p = .048) was lower in patients with AD with epilepsy development than in those without. Conclusion We found that the global brain network differs between patients with AD and healthy controls. In addition, we demonstrated significant associations between brain networks (both global brain and intrinsic thalamic networks) and epilepsy development in patients with AD. Patients with AD with and without epilepsy development are similar in terms of clinical characteristics. Global and intrinsic thalamic networks differ between patients with AD with and without epilepsy development. Brain networks might be useful biomarkers for epilepsy development in patients with AD.