Single-subject structural cortical networks in clinically isolated syndrome. (October 2020)

• Record Type: Journal Article
• Authors: Collorone, Sara; Prados, Ferran; Hagens, Marloes HJ; Tur, Carmen; Kanber, Baris; Sudre, Carole H; Lukas, Carsten; Gasperini, Claudio; Oreja-Guevara, Celia; Andelova, Micaela; Ciccarelli, Olga; Wattjes, Mike P; Ourselin, Sebastian; Altmann, Daniel R; Tijms, Betty M; Barkhof, Frederik; Toosy, Ahmed T
• Is Part Of: Multiple sclerosis. Volume 26:Number 11(2020)
• Page Start: 1392
• Page End: 1401
• Publication Date: 2020-10
• Subjects: Magnetic resonance imaging -- multiple sclerosis -- clinically isolated syndrome -- gray matter -- graph theory -- structural cortical networks -- multicenter study; Central nervous system -- Diseases -- Periodicals; Myelin sheath -- Diseases -- Periodicals; Inflammation -- Periodicals; Multiple sclerosis -- Periodicals; Central Nervous System Diseases -- Periodicals; Demyelinating Diseases -- Periodicals; Inflammation -- Periodicals; Multiple Sclerosis -- Periodicals; Système nerveux central -- Maladies -- Périodiques; Gaine de myéline -- Maladies -- Périodiques; Inflammation (Pathologie) -- Périodiques; Sclérose en plaques -- Périodiques; Electronic journals; 616.834005
• DOI: 10.1177/1352458519865739
• Languages: English
• ISSNs: 1352-4585

Abstract

Background: Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas, and they present the advantage of being extracted from previously acquired clinical magnetic resonance imaging (MRI) scans. SCNs have shown pathophysiological changes in many brain disorders, including multiple sclerosis. Objective: To investigate alterations of SCNs at the individual level in patients with clinically isolated syndrome (CIS), thereby assessing their clinical relevance. Methods: We analyzed baseline data collected in a prospective multicenter (MAGNIMS) study. CIS patients ( n = 60) and healthy controls ( n = 38) underwent high-resolution 3T MRI. Measures of disability and cognitive processing were obtained for patients. Single-subject SCNs were extracted from brain 3D-T1 weighted sequences; global and local network parameters were computed. Results: Compared to healthy controls, CIS patients showed altered small-world topology, an efficient network organization combining dense local clustering with relatively few long-distance connections. These disruptions were worse for patients with higher lesion load and worse cognitive processing speed. Alterations of centrality measures and clustering of connections were observed in specific cortical areas in CIS patients when compared with healthy controls. Conclusion: Our study indicates that SCNs can be used to demonstrate clinically relevant alterations of connectivity in CIS.