Structural connectivity in multiple sclerosis and modeling of disconnection
| Autor: | Maria A. Rocca, Ermelinda De Meo, Mark A. Horsfield, Elisabetta Pagani, Mariaemma Rodegher, Massimo Filippi, Bruno Colombo, Giancarlo Comi |
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| Přispěvatelé: | Pagani, Elisabetta, Rocca, Maria A, De Meo, Ermelinda, Horsfield, Mark A, Colombo, Bruno, Rodegher, Mariaemma, Comi, Giancarlo, Filippi, Massimo |
| Rok vydání: | 2019 |
| Předmět: |
Adult
Male Multiple Sclerosis Adolescent Computer science graph theory simulation of disconnection computer.software_genre diffusion MRI White matter Young Adult 03 medical and health sciences 0302 clinical medicine fiber bundle transection Image Interpretation Computer-Assisted Neural Pathways medicine Humans Multiple sclerosi Aged 030304 developmental biology Brain Mapping 0303 health sciences Thesaurus (information retrieval) business.industry Multiple sclerosis clinical phenotype Middle Aged medicine.disease Diffusion Magnetic Resonance Imaging medicine.anatomical_structure Neurology Female Neurology (clinical) Artificial intelligence Disconnection Nerve Net business computer 030217 neurology & neurosurgery Natural language processing Diffusion MRI |
| Zdroj: | Multiple Sclerosis Journal. 26:220-232 |
| ISSN: | 1477-0970 1352-4585 |
| DOI: | 10.1177/1352458518820759 |
| Popis: | Background: Multiple sclerosis (MS) is characterized by focal white matter damage, and when the brain is modeled as a network, lesions can be treated as disconnection events. Objective: To evaluate whether modeling disconnection caused by lesions helps explain motor and cognitive impairment in MS. Methods: Pathways connecting 116 cortical regions were reconstructed with magnetic resonance imaging (MRI) tractography from diffusion tensors averaged across healthy controls (HCs); maps of pathways were applied to 227 relapse-onset MS patients and 50 HCs to derive structural connectivity. Then, the likelihood of individual connections passing through lesions was used to model disconnection. Patients were grouped according to clinical phenotype (113 relapsing-remitting multiple sclerosis (RRMS), 69 secondary progressive multiple sclerosis (SPMS), 45 benign MS), and then network metrics were compared between groups (analysis of variance (ANOVA)) and correlated with motor and cognitive scores (linear regression). Results: Global metrics differentiated RRMS from SPMS and benign MS patients, but not benign from SPMS patients. Nodal connectivity strength replicated global results. After disconnection, few nodes were significantly different between benign MS and RRMS patients. Correlations revealed nodes pertinent to motor and cognitive dysfunctions; these became slightly stronger after disconnection. Conclusion: Connectivity did not change greatly after modeled disconnection, suggesting that the brain network is robust against damage caused by MS lesions. |
| Databáze: | OpenAIRE |
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