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Irastorza-Valera L, Soria-Gómez E, Benitez JM, Montáns FJ, Saucedo-Mora L. Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM). Biomimetics (Basel) 2024; 9:362. [PMID: 38921242 PMCID: PMC11202129 DOI: 10.3390/biomimetics9060362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 05/28/2024] [Accepted: 06/05/2024] [Indexed: 06/27/2024] Open
Abstract
The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.
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Affiliation(s)
- Luis Irastorza-Valera
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
- PIMM Laboratory, ENSAM–Arts et Métiers ParisTech, 151 Bd de l’Hôpital, 75013 Paris, France
| | - Edgar Soria-Gómez
- Achúcarro Basque Center for Neuroscience, Barrio Sarriena, s/n, 48940 Leioa, Spain;
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi, 5, 48009 Bilbao, Spain
- Department of Neurosciences, University of the Basque Country UPV/EHU, Barrio Sarriena, s/n, 48940 Leioa, Spain
| | - José María Benitez
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
| | - Francisco J. Montáns
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
- Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Luis Saucedo-Mora
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
- Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PJ, UK
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology (MIT), 77 Massachusetts Ave, Cambridge, MA 02139, USA
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De Roeck L, Blommaert J, Dupont P, Sunaert S, Sleurs C, Lambrecht M. Brain network topology and its cognitive impact in adult glioma survivors. Sci Rep 2024; 14:12782. [PMID: 38834633 DOI: 10.1038/s41598-024-63716-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 05/31/2024] [Indexed: 06/06/2024] Open
Abstract
Structural brain network topology can be altered in case of a brain tumor, due to both the tumor itself and its treatment. In this study, we explored the role of structural whole-brain and nodal network metrics and their association with cognitive functioning. Fifty WHO grade 2-3 adult glioma survivors (> 1-year post-therapy) and 50 matched healthy controls underwent a cognitive assessment, covering six cognitive domains. Raw cognitive assessment scores were transformed into w-scores, corrected for age and education. Furthermore, based on multi-shell diffusion-weighted MRI, whole-brain tractography was performed to create weighted graphs and to estimate whole-brain and nodal graph metrics. Hubs were defined based on nodal strength, betweenness centrality, clustering coefficient and shortest path length in healthy controls. Significant differences in these metrics between patients and controls were tested for the hub nodes (i.e. n = 12) and non-hub nodes (i.e. n = 30) in two mixed-design ANOVAs. Group differences in whole-brain graph measures were explored using Mann-Whitney U tests. Graph metrics that significantly differed were ultimately correlated with the cognitive domain-specific w-scores. Bonferroni correction was applied to correct for multiple testing. In survivors, the bilateral putamen were significantly less frequently observed as a hub (pbonf < 0.001). These nodes' assortativity values were positively correlated with attention (r(90) > 0.573, pbonf < 0.001), and proxy IQ (r(90) > 0.794, pbonf < 0.001). Attention and proxy IQ were significantly more often correlated with assortativity of hubs compared to non-hubs (pbonf < 0.001). Finally, the whole-brain graph measures of clustering coefficient (r = 0.685), global (r = 0.570) and local efficiency (r = 0.500) only correlated with proxy IQ (pbonf < 0.001). This study demonstrated potential reorganization of hubs in glioma survivors. Assortativity of these hubs was specifically associated with cognitive functioning, which could be important to consider in future modeling of cognitive outcomes and risk classification in glioma survivors.
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Affiliation(s)
- Laurien De Roeck
- Department of Radiotherapy and Oncology, University Hospitals Leuven, Herestraat 49, 3000, Leuven, Belgium.
- Department of Oncology, KU Leuven, Leuven, Belgium.
| | - Jeroen Blommaert
- Department of Oncology, KU Leuven, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Patrick Dupont
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Stefan Sunaert
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Charlotte Sleurs
- Department of Oncology, KU Leuven, Leuven, Belgium
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands
| | - Maarten Lambrecht
- Department of Radiotherapy and Oncology, University Hospitals Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
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Alshehri A, Koussis N, Al-Iedani O, Khormi I, Lea R, Ramadan S, Lechner-Scott J. Improvement of the thalamocortical white matter network in people with stable treated relapsing-remitting multiple sclerosis over time. NMR IN BIOMEDICINE 2024; 37:e5119. [PMID: 38383137 DOI: 10.1002/nbm.5119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/28/2023] [Accepted: 01/18/2024] [Indexed: 02/23/2024]
Abstract
Advanced imaging techniques (tractography) enable the mapping of white matter (WM) pathways and the understanding of brain connectivity patterns. We combined tractography with a network-based approach to examine WM microstructure on a network level in people with relapsing-remitting multiple sclerosis (pw-RRMS) and healthy controls (HCs) over 2 years. Seventy-six pw-RRMS matched with 43 HCs underwent clinical assessments and 3T MRI scans at baseline (BL) and 2-year follow-up (2-YFU). Probabilistic tractography was performed, accounting for the effect of lesions, producing connectomes of 25 million streamlines. Network differences in fibre density across pw-RRMS and HCs at BL and 2-YFU were quantified using network-based statistics (NBS). Longitudinal network differences in fibre density were quantified using NBS in pw-RRMS, and were tested for correlations with disability, cognition and fatigue scores. Widespread network reductions in fibre density were found in pw-RRMS compared with HCs at BL in cortical regions, with more reductions detected at 2-YFU. Pw-RRMS had reduced fibre density at BL in the thalamocortical network compared to 2-YFU. This effect appeared after correction for age, was robust across different thresholds, and did not correlate with lesion volume or disease duration. Pw-RRMS demonstrated a robust and long-distance improvement in the thalamocortical WM network, regardless of age, disease burden, duration or therapy, suggesting a potential locus of neuroplasticity in MS. This network's role over the disease's lifespan and its potential implications in prognosis and treatment warrants further investigation.
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Affiliation(s)
- Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Department of Radiology, King Fahd University Hospital, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Nikitas Koussis
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Psychological Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW, Australia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
| | - Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Rodney Lea
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Department of Neurology, John Hunter Hospital, New Lambton Heights, NSW, Australia
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
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Bontempi P, Piccolantonio G, Busato A, Conti A, Angelini G, Lopez N, Bani A, Constantin G, Marzola P. Resting-state functional magnetic resonance imaging reveals functional connectivity alteration in the experimental autoimmune encephalomyelitis model of multiple sclerosis. NMR IN BIOMEDICINE 2024; 37:e5127. [PMID: 38450807 DOI: 10.1002/nbm.5127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 01/08/2024] [Accepted: 01/25/2024] [Indexed: 03/08/2024]
Abstract
Multiple sclerosis (MS) is an autoimmune degenerative disease targeting white matter in the central nervous system. The most common animal model that mimics MS is experimental autoimmune encephalomyelitis (EAE) and it plays a crucial role in pharmacological research, from the identification of a therapeutic target to the in vivo validation of efficacy. Magnetic resonance imaging (MRI) is largely used to detect MS lesions, and resting-state functional MRI (rsfMRI) to investigate alterations in the brain functional connectivity (FC). MRI was mainly used in EAE studies to detect lesions in the spinal cord and brain. The current longitudinal MRI study aims to validate rsfMRI as a biomarker of the disease progression in the myelin oligodendrocyte glycoprotein 35-55 induced EAE animal model of MS. MR images were acquired 14, 25, and 50 days postimmunization. Seed-based analysis was used to investigate the whole-brain FC with some predefined areas, such as the thalamic regions, cerebellum, motor and somatosensory cortex. When compared with the control group, the EAE group exhibited a slightly altered FC and a decreasing trend in the total number of activated voxels along the disease progression. The most interesting result regards the whole-brain FC with the cerebellum. A hyperconnectivity behavior was found at an early phase and a significant reduced connectivity at a late phase. Moreover, we found a negative correlation between the total number of activated voxels during the late phase and the cumulative disease index. The results obtained provide a clinically relevant experimental platform that may be pivotal for the elucidation of the key mechanisms of accumulation of irreversible disability, as well as the development of innovative therapies for MS. Moreover, the negative correlation between the disease severity and the size of the activated area suggests a possible research pathway to follow for the resolution of the clinico-radiological paradox.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Giusi Piccolantonio
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Alice Busato
- Department of Computer Science, University of Verona, Verona, Italy
- Evotec Company, Verona, Italy
| | - Anita Conti
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | | | - Nicola Lopez
- Department of Medicine, University of Verona, Verona, Italy
| | | | | | - Pasquina Marzola
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
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Caranova M, Soares JF, Batista S, Castelo-Branco M, Duarte JV. A systematic review of microstructural abnormalities in multiple sclerosis detected with NODDI and DTI models of diffusion-weighted magnetic resonance imaging. Magn Reson Imaging 2023; 104:61-71. [PMID: 37775062 DOI: 10.1016/j.mri.2023.09.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/31/2023] [Accepted: 09/25/2023] [Indexed: 10/01/2023]
Abstract
Multiple sclerosis (MS), namely the phenotype of the relapsing-remitting form, is the most common white matter disease and is mostly characterized by demyelination and inflammation, which lead to neurodegeneration and cognitive decline. Its diagnosis and monitoring are performed through conventional structural MRI, in which T2-hyperintense lesions can be identified, but this technique lacks sensitivity and specificity, mainly in detecting damage to normal appearing tissues. Models of diffusion-weighted MRI such as diffusion-tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) allow to uncover microstructural abnormalities that occur in MS, mainly in normal appearing tissues such as the normal appearing white matter (NAWM), which allows to overcome limitations of conventional MRI. DTI is the standard method used for modelling this kind of data, but it has limitations, which can be tackled by using more complex diffusion models, such as NODDI, which provides additional information on morphological properties of tissues. Although there are several studies in MS using both diffusion models, there is no formal assessment that summarizes the findings of both methods in lesioned and normal appearing tissues, and whether one is more advantageous than the other. Hence, this systematic review aims to identify what microstructural abnormalities are seen in lesions and/or NAWM in relapsing-remitting MS while using two different approaches to modelling diffusion data, namely DTI and NODDI, and if one of them is more appropriate than the other or if they are complementary to each other. The search was performed using PubMed, which was last searched on November 2022, and aimed at finding studies that either utilized both DTI and NODDI in the same dataset, or only one of the methods. Eleven articles were included in this review, which included cohorts with a relatively low sample size (total number of patients = 254, total number of healthy controls = 240), and patients with a moderate disease duration, all with relapsing-remitting MS. Overall, studies found decreased fractional anisotropy (FA), neurite density index (NDI) and orientation dispersion index (ODI), and increased mean, axial and radial diffusivities (MD, AD and RD, respectively) in lesions, when compared to contralateral NAWM and healthy controls' white matter. Compared to healthy controls' white matter, NAWM showed lower FA and NDI and higher MD, AD, RD, and ODI. Results from the included articles confirm that there is active demyelination and inflammation in both lesions and NAWM, as well as loss in neurites, and that structural damage is not confined to focal lesions, which is in concordance with histological findings and results from other imaging techniques. Furthermore, NODDI is suggested to have higher sensitivity and specificity, as seen by inspecting imaging results, compared to DTI, while still being clinically feasible. The use of biomarkers derived from such advanced diffusion models in clinical practice could imply a better understanding of treatment efficacy and disease progression, without relying on the manifestation of clinical symptoms, such as relapses.
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Affiliation(s)
- Maria Caranova
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal.
| | - Júlia F Soares
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Sónia Batista
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal; Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal; Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - João Valente Duarte
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal; Faculty of Medicine, University of Coimbra, Coimbra, Portugal
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Shahbodaghy F, Shafaghi L, Rostampour M, Rostampour A, Kolivand P, Gharaylou Z. Symmetry differences of structural connectivity in multiple sclerosis and healthy state. Brain Res Bull 2023; 205:110816. [PMID: 37972899 DOI: 10.1016/j.brainresbull.2023.110816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 10/27/2023] [Accepted: 11/13/2023] [Indexed: 11/19/2023]
Abstract
Focal and diffuse cerebral damages occur in Multiple Sclerosis (MS) that promotes profound shifts in local and global structural connectivity parameters, mainly derived from diffusion tensor imaging. Most of the reconstruction analyses have applied conventional tracking algorithms largely based on the controversial streamline count. For a more credible explanation of the diffusion MRI signal, we used convex optimization modeling for the microstructure-informed tractography2 (COMMIT2) framework. All multi-shell diffusion data from 40 healthy controls (HCs) and 40 relapsing-remitting MS (RRMS) patients were transformed into COMMIT2-weighted matrices based on the Schefer-200 parcels atlas (7 networks) and 14 bilateral subcortical regions. The success of the classification process between MS and healthy state was efficiently predicted by the left DMN-related structures and visual network-associated pathways. Additionally, the lesion volume and age of onset were remarkably correlated with the components of the left DMN. Using complementary approaches such as global metrics revealed differences in WM microstructural integrity between MS and HCs (efficiency, strength). Our findings demonstrated that the cutting-edge diffusion MRI biomarkers could hold the potential for interpreting brain abnormalities in a more distinctive way.
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Affiliation(s)
- Fatemeh Shahbodaghy
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
| | - Lida Shafaghi
- Department of Neuroscience, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Massoumeh Rostampour
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Ali Rostampour
- Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran
| | - Pirhossein Kolivand
- Department of Health Economics, School of Medicine, Shahed University, Tehran, Iran
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Zimek D, Miklusova M, Mares J. Overview of the Current Pathophysiology of Fatigue in Multiple Sclerosis, Its Diagnosis and Treatment Options - Review Article. Neuropsychiatr Dis Treat 2023; 19:2485-2497. [PMID: 38029042 PMCID: PMC10674653 DOI: 10.2147/ndt.s429862] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 11/03/2023] [Indexed: 12/01/2023] Open
Abstract
Fatigue is a common, debilitating and often underestimated symptom in patients with multiple sclerosis (MS). The exact pathophysiological mechanism of fatigue in MS is still unknown. However, there are many theories involving different immunological, metabolic and inflammatory mechanisms of fatigue. Owing to the subjective nature of this symptom, its diagnosis is still very limited and is still based only on diagnostic questionnaires. Although several therapeutic agents have been used in the past to try to influence fatigue in MS patients, no single effective approach for the treatment of fatigue has yet been found. This review article aims to provide the reader with information on the current theories on the origin and mechanism of fatigue in MS, as well as diagnostic procedures and, finally, current therapeutic strategies for the management of fatigue in MS patients.
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Affiliation(s)
- Dalibor Zimek
- Department of Neurology, Palacky University Hospital Olomouc, Olomouc, Czech Republic
| | - Martina Miklusova
- Department of Neurology, Palacky University Hospital Olomouc, Olomouc, Czech Republic
| | - Jan Mares
- Department of Neurology, Palacky University Hospital Olomouc, Olomouc, Czech Republic
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Zhou F, Wu L, Qian L, Kuang H, Zhan J, Li J, Cheung GL, Ding A, Gong H. The Relationship Between Cortical Morphological and Functional Topological Properties and Clinical Manifestations in Patients with Posttraumatic Diffuse Axonal Injury: An Individual Brain Network Study. Brain Topogr 2023; 36:936-945. [PMID: 37615797 DOI: 10.1007/s10548-023-00964-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 04/15/2023] [Indexed: 08/25/2023]
Abstract
To evaluate the altered network topological properties and their clinical relevance in patients with posttraumatic diffuse axonal injury (DAI). Forty-seven participants were recruited in this study, underwent 3D T1-weighted and resting-state functional MRI, and had single-subject morphological brain networks (MBNs) constructed by Kullback-Leibler divergence and functional brain networks (FBNs) constructed by Pearson correlation measurement interregional similarity. The global and regional properties were analyzed and compared using graph theory and network-based statistics (NBS), and the relationship with clinical manifestations was assessed. Compared with those of the healthy subjects, MBNs of patients with DAI showed a higher path length ([Formula: see text]: P = 0.021, [Formula: see text]: P = 0.011), lower clustering ([Formula: see text]: P = 0.002) and less small-worldness ([Formula: see text]: P = 0.002), but there was no significant difference in the global properties of FBNs (P: 0.161-0.216). For nodal properties of MBNs and FBNs, several regions showed significant differences between patients with DAI and healthy controls (HCs) (P < 0.05, FDR corrected). NBS analysis revealed that MBNs have more altered morphological connections in the frontal parietal control network and interhemispheric connections (P < 0.05). DAI-related global or nodal properties of MBNs were correlated with physical disability or dyscognition (P < 0.05/7, with Bonferroni correction), and the alteration of functional topology properties mediates this relationship. Our results suggested that disrupted morphological topology properties, which are mediated by FBNs and correlated with clinical manifestations of DAI, play a critical role in the short-term and medium-term phases after trauma.
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Affiliation(s)
- Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi, China
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, 330006, China
| | - Lin Wu
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi, China
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, 330006, China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering, Peking University, No.60 Yannan Yuan, Beijing, 100871, China
| | - Hongmei Kuang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi, China
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, 330006, China
| | - Jie Zhan
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi, China
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, 330006, China
| | - Jian Li
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi, China
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, 330006, China
| | - Gerald L Cheung
- Spin Imaging Technology Co., Ltd, No.6 Fengxin Road, Nanjing, 210012, China
| | - Aimin Ding
- Department of Radiology, The First People's Hospital of Fuzhou and The Fifth Affiliated Hospital, Nanchang University, Fuzhou, 344000, China.
| | - Honghan Gong
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi, China.
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, 330006, China.
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Carter SL, Patel R, Fisk JD, Figley CR, Marrie RA, Mazerolle EL, Uddin MN, Wong K, Graff LA, Bolton JM, Marriott JJ, Bernstein CN, Kornelsen J. Differences in resting state functional connectivity relative to multiple sclerosis and impaired information processing speed. Front Neurol 2023; 14:1250894. [PMID: 37928146 PMCID: PMC10625423 DOI: 10.3389/fneur.2023.1250894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/05/2023] [Indexed: 11/07/2023] Open
Abstract
Background Fifty-one percent of individuals with multiple sclerosis (MS) develop cognitive impairment (CI) in information processing speed (IPS). Although IPS scores are associated with health and well-being, neural changes that underlie IPS impairments in MS are not understood. Resting state fMRI can provide insight into brain function changes underlying impairment in persons with MS. Objectives We aimed to assess functional connectivity (FC) differences in (i) persons with MS compared to healthy controls (HC), (ii) persons with both MS and CI (MS-CI) compared to HC, (iii) persons with MS that are cognitively preserved (MS-CP) compared to HC, (iv) MS-CI compared to MS-CP, and (v) in relation to cognition within the MS group. Methods We included 107 participants with MS (age 49.5 ± 12.9, 82% women), and 94 controls (age 37.9 ± 15.4, 66% women). Each participant was administered the Symbol Digit Modalities Test (SDMT) and underwent a resting state fMRI scan. The MS-CI group was created by applying a z-score cut-off of ≤ -1.5 to locally normalized SDMT scores. The MS-CP group was created by applying a z-score of ≥0. Control groups (HCMS-CI and HCMS-CP) were based on the nearest age-matched HC participants. A whole-brain ROI-to-ROI analysis was performed followed by specific contrasts and a regression analysis. Results Individuals with MS showed FC differences compared to HC that involved the cerebellum, visual and language-associated brain regions, and the thalamus, hippocampus, and basal ganglia. The MS-CI showed FC differences compared to HCMS-CI that involved the cerebellum, visual and language-associated areas, thalamus, and caudate. SDMT scores were correlated with FC between the cerebellum and lateral occipital cortex in MS. No differences were observed between the MS-CP and HCMS-CP or MS-CI and MS-CP groups. Conclusion Our findings emphasize FC changes of cerebellar, visual, and language-associated areas in persons with MS. These differences were apparent for (i) all MS participants compared to HC, (ii) MS-CI subgroup and their matched controls, and (iii) the association between FC and SDMT scores within the MS group. Our findings strongly suggest that future work that examines the associations between FC and IPS impairments in MS should focus on the involvement of these regions.
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Affiliation(s)
- Sean L. Carter
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
| | - Ronak Patel
- Department of Clinical Health Psychology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - John D. Fisk
- Nova Scotia Health and the Departments of Psychiatry, Psychology & Neuroscience, and Medicine, Dalhousie University, Halifax, NS, Canada
| | - Chase R. Figley
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Departments of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ruth Ann Marrie
- Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Erin L. Mazerolle
- Department of Psychology, St. Francis Xavier University, Antigonish, NS, Canada
| | - Md Nasir Uddin
- Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, School of Medicine & Dentistry, University of Rochester, Rochester, NY, United States
- Department of Biomedical Engineering, Hajim School of Engineering & Applied Sciences, University of Rochester, Rochester, NY, United States
| | - Kaihim Wong
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Lesley A. Graff
- Department of Clinical Health Psychology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James M. Bolton
- Department of Psychiatry, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James J. Marriott
- Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Charles N. Bernstein
- Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Winnipeg Health Sciences Centre, Winnipeg, MB, Canada
- Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Departments of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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10
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Corrêa DG, van Duinkerken E, Farinhas JGD, Pereira VC, Gasparetto EL, Alves-Leon SV, Lopes FCR. Influence of natalizumab on resting-state connectivity in patients with multiple sclerosis. J Cent Nerv Syst Dis 2023; 15:11795735231195775. [PMID: 37600237 PMCID: PMC10433731 DOI: 10.1177/11795735231195775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/22/2023] Open
Abstract
Background Changes in brain connectivity occur in patients with multiple sclerosis (MS), even in patients under disease-modifying therapies. Using magnetic resonance imaging (MRI) to asses patients treated with disease-modifying therapies, such as natalizumab, can elucidate the mechanisms involved in clinical deterioration in MS. Objectives To evaluate differences in resting-state functional connectivity among MS patients treated with natalizumab, MS patients not treated with natalizumab, and controls. Design Single-center retrospective cross-sectional study. Methods Twenty-three MS patients being treated with natalizumab were retrospectively compared with 23 MS patients who were naïve for natalizumab, and were using first-line medications (interferon-β and/or glatiramer acetate), and 17 gender- and age-matched control subjects. The MS patient groups were also matched for time since diagnosis and hyperintense lesion volume on FLAIR. All participants underwent brain MRI using a 3 Tesla scanner. Independent component analysis and dual regression were used to identify resting-state functional connectivity using the FMRIB Software Library. Results In comparison to controls, the MS patients treated with natalizumab presented decreased connectivity in the left orbitofrontal cortex, in the anterior cingulate and orbitofrontal cortex network. The patients not treated with natalizumab presented increased connectivity in the secondary visual, sensorimotor, and ventral attention networks in comparison to controls.Compared to patients treated with natalizumab, the patients not using natalizumab presented increased connectivity in the left Heschl's gyrus and in the right superior frontal gyrus in the ventral attention network. Conclusion Differences in brain connectivity between MS patients not treated with natalizumab, healthy controls, and patients treated with natalizumab may be secondary to suboptimal neuronal compensation due to prior less efficient treatments, or due to a compensation in response to maladaptive plasticity.
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Affiliation(s)
- Diogo G. Corrêa
- Department of Radiology, Clínica de Diagnóstico por Imagem (CDPI)/DASA, Barra da Tijuca, Brazil
- Department of Radiology, Federal Fluminense University, Niterói, Brazil
| | - Eelco van Duinkerken
- Department of Medical Psychology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
- Post-Graduate Program in Neurology, Hospital Universitário Gaffrée e Guinle, Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
| | - João Gabriel D. Farinhas
- Post-Graduate Program in Neurology, Hospital Universitário Gaffrée e Guinle, Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
- Department of Neurology, Hospital Universitário Clementino Fraga Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Valéria C. Pereira
- Department of Neurology, Hospital Universitário Clementino Fraga Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Emerson L. Gasparetto
- Department of Radiology, Clínica de Diagnóstico por Imagem (CDPI)/DASA, Barra da Tijuca, Brazil
| | - Soniza V. Alves-Leon
- Post-Graduate Program in Neurology, Hospital Universitário Gaffrée e Guinle, Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
- Department of Neurology, Hospital Universitário Clementino Fraga Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Fernanda Cristina R. Lopes
- Department of Radiology, Clínica de Diagnóstico por Imagem (CDPI)/DASA, Barra da Tijuca, Brazil
- Department of Radiology, Federal Fluminense University, Niterói, Brazil
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11
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Mantwill M, Asseyer S, Chien C, Kuchling J, Schmitz-Hübsch T, Brandt AU, Haynes JD, Paul F, Finke C. Functional connectome fingerprinting and stability in multiple sclerosis. Mult Scler J Exp Transl Clin 2023; 9:20552173231195879. [PMID: 37641618 PMCID: PMC10460476 DOI: 10.1177/20552173231195879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 08/02/2023] [Indexed: 08/31/2023] Open
Abstract
Background Functional connectome fingerprinting can identify individuals based on their functional connectome. Previous studies relied mostly on short intervals between fMRI acquisitions. Objective This cohort study aimed to determine the stability of connectome-based identification and their underlying signatures in patients with multiple sclerosis and healthy individuals with long follow-up intervals. Methods We acquired resting-state fMRI in 70 patients with multiple sclerosis and 273 healthy individuals with long follow-up times (up to 4 and 9 years, respectively). Using functional connectome fingerprinting, we examined the stability of the connectome and additionally investigated which regions, connections and networks supported individual identification. Finally, we predicted cognitive and behavioural outcome based on functional connectivity. Results Multiple sclerosis patients showed connectome stability and identification accuracies similar to healthy individuals, with longer time delays between imaging sessions being associated with accuracies dropping from 89% to 76%. Lesion load, brain atrophy or cognitive impairment did not affect identification accuracies within the range of disease severity studied. Connections from the fronto-parietal and default mode network were consistently most distinctive, i.e., informative of identity. The functional connectivity also allowed the prediction of individual cognitive performances. Conclusion Our results demonstrate that discriminatory signatures in the functional connectome are stable over extended periods of time in multiple sclerosis, resulting in similar identification accuracies and distinctive long-lasting functional connectome fingerprinting signatures in patients and healthy individuals.
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Affiliation(s)
- Maron Mantwill
- Maron Mantwill, Hertzbergstraße 12, 12055 Berlin, Germany.
| | - Susanna Asseyer
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Claudia Chien
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Charitéplatz, Berlin, Germany
| | - Joseph Kuchling
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Tanja Schmitz-Hübsch
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Alexander U Brandt
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Department of Neurology, University of California, Irvine, CA, USA
| | - John-Dylan Haynes
- Faculty of Philosophy, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Berlin, Germany
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12
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Antypa D, Simos NJ, Panou T, Spyridaki E, Kagialis A, Kosteletou E, Kavroulakis E, Mastorodemos V, Papadaki E. Distinct hemodynamic and functional connectivity features of fatigue in clinically isolated syndrome and multiple sclerosis: accounting for the confounding effect of concurrent depression symptoms. Neuroradiology 2023:10.1007/s00234-023-03174-1. [PMID: 37301785 DOI: 10.1007/s00234-023-03174-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 06/04/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE This study aims to identify common and distinct hemodynamic and functional connectivity (FC) features for self-rated fatigue and depression symptoms in patients with clinically isolated syndrome (CIS) and relapsing-remitting multiple sclerosis (RR-MS). METHODS Twenty-four CIS, 29 RR-MS patients, and 39 healthy volunteers were examined using resting-state fMRI (rs-fMRI) to obtain whole-brain maps of (i) hemodynamic response patterns (through time shift analysis), (ii) FC (via intrinsic connectivity contrast maps), and (iii) coupling between hemodynamic response patterns and FC. Each regional map was correlated with fatigue scores, controlling for depression, and with depression scores, controlling for fatigue. RESULTS In CIS patients, the severity of fatigue was associated with accelerated hemodynamic response in the insula, hyperconnectivity of the superior frontal gyrus, and evidence of reduced hemodynamics-FC coupling in the left amygdala. In contrast, depression severity was associated with accelerated hemodynamic response in the right limbic temporal pole, hypoconnectivity of the anterior cingulate gyrus, and increased hemodynamics-FC coupling in the left amygdala. In RR-MS patients, fatigue was associated with accelerated hemodynamic response in the insula and medial superior frontal cortex, increased functional role of the left amygdala, and hypoconnectivity of the dorsal orbitofrontal cortex, while depression symptom severity was linked to delayed hemodynamic response in the medial superior frontal gyrus; hypoconnectivity of the insula, ventromedial thalamus, dorsolateral prefrontal cortex, and posterior cingulate; and decreased hemodynamics-FC coupling of the medial orbitofrontal cortex. CONCLUSION There are distinct FC and hemodynamic responses, as well as different magnitude and topography of hemodynamic connectivity coupling, associated with fatigue and depression in early and later stages of MS.
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Affiliation(s)
- Despina Antypa
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Nicholas John Simos
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece
| | - Theodora Panou
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eirini Spyridaki
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Antonios Kagialis
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Emmanouela Kosteletou
- Institute of Applied Mathematics, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece
| | - Eleftherios Kavroulakis
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Vasileios Mastorodemos
- Department of Neurology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Efrosini Papadaki
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece.
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece.
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13
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Nair G, Nair SS, Arun KM, Camacho P, Bava E, Ajayaghosh P, Menon RN, Nair M, Kesavadas C, Anteraper SA. Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study. Brain Connect 2023; 13:89-96. [PMID: 36006365 DOI: 10.1089/brain.2021.0182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.
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Affiliation(s)
- Gowthami Nair
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Sruthi S Nair
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Karumattu Manattu Arun
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Paul Camacho
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Department of Bioengineering, Interdisciplinary Health Science Institute, Urbana, Illinois, USA
| | - Elshal Bava
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Priya Ajayaghosh
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Ramshekhar N Menon
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Muralidharan Nair
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Chandrasekharan Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
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De Rosa AP, Esposito F, Valsasina P, d'Ambrosio A, Bisecco A, Rocca MA, Tommasin S, Marzi C, De Stefano N, Battaglini M, Pantano P, Cirillo M, Tedeschi G, Filippi M, Gallo A. Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative. J Neurol 2023; 270:1047-1066. [PMID: 36350401 PMCID: PMC9886598 DOI: 10.1007/s00415-022-11479-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/11/2022]
Abstract
The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.
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Affiliation(s)
- Alessandro Pasquale De Rosa
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy.
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
| | - Alessandro d'Ambrosio
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Alvino Bisecco
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy
| | - Silvia Tommasin
- Department of Human Neurosciences, Sapienza University of Rome, Viale Dell'Università, 30, 00185, Rome, Italy
| | - Chiara Marzi
- Institute of Applied Physics "Nello Cararra" (IFAC), National Research Council (CNR), Via Madonna del Piano, 10, Sesto Fiorentino, 50019, Florence, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Viale Dell'Università, 30, 00185, Rome, Italy
| | - Mario Cirillo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina 58, 20132, Milan, Italy
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Piazza Luigi Miraglia, 2, 80138, Naples, Italy
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Tran K, Salazar BH, Boone TB, Khavari R, Karmonik C. Classification of multiple sclerosis women with voiding dysfunction using machine learning: Is functional connectivity or structural connectivity a better predictor? BJUI COMPASS 2023; 4:277-284. [PMID: 37025479 PMCID: PMC10071087 DOI: 10.1002/bco2.217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/19/2022] [Accepted: 12/30/2022] [Indexed: 01/29/2023] Open
Abstract
Introduction Machine learning (ML) is an established technique that uses sets of training data to develop algorithms and perform data classification without using human intervention/supervision. This study aims to determine how functional and anatomical brain connectivity (FC and SC) data can be used to classify voiding dysfunction (VD) in female MS patients using ML. Methods Twenty-seven ambulatory MS individuals with lower urinary tract dysfunction were recruited and divided into two groups (Group 1: voiders [V, n = 14]; Group 2: VD [n = 13]). All patients underwent concurrent functional MRI/urodynamics testing. Results Best-performing ML algorithms, with highest area under the curve (AUC), were partial least squares (PLS, AUC = 0.86) using FC alone and random forest (RF) when using SC alone (AUC = 0.93) and combined (AUC = 0.96) as inputs. Our results show 10 predictors with the highest AUC values were associated with FC, indicating that although white matter was affected, new connections may have formed to preserve voiding initiation. Conclusions MS patients with and without VD exhibit distinct brain connectivity patterns when performing a voiding task. Our results demonstrate FC (grey matter) is of higher importance than SC (white matter) for this classification. Knowledge of these centres may help us further phenotype patients to appropriate centrally focused treatments in the future.
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Affiliation(s)
- Khue Tran
- EnMed Program Texas A&M School of Engineering Medicine Houston Texas USA
| | - Betsy H. Salazar
- Department of Urology Houston Methodist Hospital Houston Texas USA
| | - Timothy B. Boone
- Department of Urology Houston Methodist Hospital Houston Texas USA
| | - Rose Khavari
- Department of Urology Houston Methodist Hospital Houston Texas USA
| | - Christof Karmonik
- Translational Imaging Center Houston Methodist Research Institute Houston Texas USA
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Dünschede J, Ruschil C, Bender B, Mengel A, Lindig T, Ziemann U, Kowarik MC. Clinical-Radiological Mismatch in Multiple Sclerosis Patients during Acute Relapse: Discrepancy between Clinical Symptoms and Active, Topographically Fitting MRI Lesions. J Clin Med 2023; 12:jcm12030739. [PMID: 36769392 PMCID: PMC9917396 DOI: 10.3390/jcm12030739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/11/2022] [Accepted: 01/07/2023] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Relapses in multiple sclerosis (MS) patients are usually defined as subacute clinical symptoms that last for at least 24 h. To validate a clinical relapse on magnetic resonance imaging (MRI), an anatomically fitting lesion with gadolinium enhancement in the central nervous system (CNS) would be mandatory. The aim of this study was to validate clinical relapses in regard to the concomitant detection of active, anatomically fitting MRI lesions. METHODS We performed a retrospective analysis of 199 MS patients with acute relapse who had received an MRI scan before the initiation of methylprednisolone (MPS) therapy. Clinical data and MRIs were systematically reanalyzed by correlating clinical symptoms with their anatomical representation in the CNS. Patients were then categorized into subgroups with a clinical-radiological match (group 1) or clinical-radiological mismatch (group 2) between symptoms and active, topographically fitting lesions and further analyzed in regard to clinical characteristics. RESULTS In 43% of our patients, we observed a clinical-radiological mismatch (group 2). Further analysis of patient characteristics showed that these patients were significantly older at the time of relapse. MS patients in group 2 also showed a significantly longer disease duration and significantly more previous relapses when compared to group 1. Comparing symptom clusters, the appearance of motor dysfunction during the current relapse was significantly more frequent in group 2 than in group 1. The overall dose of MPS treatment was significantly lower in group 2 than in group 1 with a similar treatment response in both groups. CONCLUSIONS The substantial clinical-radiological mismatch during acute relapse in our study could be explained by several factors, including a psychosomatic component or disturbance of network connectivity. Alternatively, secondary progression or a diffuse neuro-inflammatory process might cause clinical symptoms, especially in older patients with a longer disease duration. As a consequence, treatment of clinical relapses and the definition of breakthrough disease should be reconsidered in regard to combined clinical and MRI criteria and/or additional biomarkers. Further studies are necessary to address the contribution of diffuse neuro-inflammation to the clinical presentation of symptoms.
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Affiliation(s)
- Jutta Dünschede
- Department of Neurology & Stroke, Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
| | - Christoph Ruschil
- Department of Neurology & Stroke, Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
| | - Benjamin Bender
- Department of Neuroradiology, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
| | - Annerose Mengel
- Department of Neurology & Stroke, Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
| | - Tobias Lindig
- Department of Neuroradiology, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
| | - Ulf Ziemann
- Department of Neurology & Stroke, Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
| | - Markus C. Kowarik
- Department of Neurology & Stroke, Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, 72076 Tübingen, Germany
- Correspondence:
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Howlett-Prieto Q, Oommen C, Carrithers MD, Wunsch DC, Hier DB. Subtypes of relapsing-remitting multiple sclerosis identified by network analysis. Front Digit Health 2023; 4:1063264. [PMID: 36714613 PMCID: PMC9874946 DOI: 10.3389/fdgth.2022.1063264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 12/22/2022] [Indexed: 01/12/2023] Open
Abstract
We used network analysis to identify subtypes of relapsing-remitting multiple sclerosis subjects based on their cumulative signs and symptoms. The electronic medical records of 113 subjects with relapsing-remitting multiple sclerosis were reviewed, signs and symptoms were mapped to classes in a neuro-ontology, and classes were collapsed into sixteen superclasses by subsumption. After normalization and vectorization of the data, bipartite (subject-feature) and unipartite (subject-subject) network graphs were created using NetworkX and visualized in Gephi. Degree and weighted degree were calculated for each node. Graphs were partitioned into communities using the modularity score. Feature maps visualized differences in features by community. Network analysis of the unipartite graph yielded a higher modularity score (0.49) than the bipartite graph (0.25). The bipartite network was partitioned into five communities which were named fatigue, behavioral, hypertonia/weakness, abnormal gait/sphincter, and sensory, based on feature characteristics. The unipartite network was partitioned into five communities which were named fatigue, pain, cognitive, sensory, and gait/weakness/hypertonia based on features. Although we did not identify pure subtypes (e.g., pure motor, pure sensory, etc.) in this cohort of multiple sclerosis subjects, we demonstrated that network analysis could partition these subjects into different subtype communities. Larger datasets and additional partitioning algorithms are needed to confirm these findings and elucidate their significance. This study contributes to the literature investigating subtypes of multiple sclerosis by combining feature reduction by subsumption with network analysis.
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Affiliation(s)
- Quentin Howlett-Prieto
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United States
| | - Chelsea Oommen
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United States
| | - Michael D. Carrithers
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United States
| | - Donald C. Wunsch
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, United States
| | - Daniel B. Hier
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United States,Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, United States,Correspondence: Daniel B. Hier
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18
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Naser Moghadasi A. Treatment of Multiple Sclerosis as a single disease based on the body-pathology-environment model. Mult Scler Relat Disord 2022; 68:104223. [PMID: 36270250 DOI: 10.1016/j.msard.2022.104223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/06/2022] [Indexed: 11/07/2022]
Affiliation(s)
- Abdorreza Naser Moghadasi
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
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19
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Reaction-diffusion models in weighted and directed connectomes. PLoS Comput Biol 2022; 18:e1010507. [DOI: 10.1371/journal.pcbi.1010507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 11/23/2022] [Accepted: 08/22/2022] [Indexed: 11/07/2022] Open
Abstract
Connectomes represent comprehensive descriptions of neural connections in a nervous system to better understand and model central brain function and peripheral processing of afferent and efferent neural signals. Connectomes can be considered as a distinctive and necessary structural component alongside glial, vascular, neurochemical, and metabolic networks of the nervous systems of higher organisms that are required for the control of body functions and interaction with the environment. They are carriers of functional epiphenomena such as planning behavior and cognition, which are based on the processing of highly dynamic neural signaling patterns. In this study, we examine more detailed connectomes with edge weighting and orientation properties, in which reciprocal neuronal connections are also considered. Diffusion processes are a further necessary condition for generating dynamic bioelectric patterns in connectomes. Based on our high-precision connectome data, we investigate different diffusion-reaction models to study the propagation of dynamic concentration patterns in control and lesioned connectomes. Therefore, differential equations for modeling diffusion were combined with well-known reaction terms to allow the use of connection weights, connectivity orientation and spatial distances.
Three reaction-diffusion systems Gray-Scott, Gierer-Meinhardt and Mimura-Murray were investigated. For this purpose, implicit solvers were implemented in a numerically stable reaction-diffusion system within the framework of neuroVIISAS. The implemented reaction-diffusion systems were applied to a subconnectome which shapes the mechanosensitive pathway that is strongly affected in the multiple sclerosis demyelination disease. It was found that demyelination modeling by connectivity weight modulation changes the oscillations of the target region, i.e. the primary somatosensory cortex, of the mechanosensitive pathway.
In conclusion, a new application of reaction-diffusion systems to weighted and directed connectomes has been realized. Because the implementation were performed in the neuroVIISAS framework many possibilities for the study of dynamic reaction-diffusion processes in empirical connectomes as well as specific randomized network models are available now.
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20
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Shirani S, Mohebbi M. Brain functional connectivity analysis in patients with relapsing-remitting multiple sclerosis: A graph theory approach of EEG resting state. Front Neurosci 2022; 16:801774. [PMID: 36161167 PMCID: PMC9500502 DOI: 10.3389/fnins.2022.801774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 07/29/2022] [Indexed: 11/13/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune disease related to the central nervous system (CNS). This study aims to investigate the effects of MS on the brain's functional connectivity network using the electroencephalogram (EEG) resting-state signals and graph theory approach. Resting-state eyes-closed EEG signals were recorded from 20 patients with relapsing-remitting MS (RRMS) and 18 healthy cases. In this study, the prime objective is to calculate the connectivity between EEG channels to assess the differences in brain functional network global features. The results demonstrated lower cortical activity in the alpha frequency bands and higher activity for the gamma frequency bands in patients with RRMS compared to the healthy group. In this study, graph metric calculations revealed a significant difference in the diameter of the functional brain network based on the directed transfer function (DTF) measure between the two groups, indicating a higher diameter in RRMS cases for the alpha frequency band. A higher diameter for the functional brain network in MS cases can result from anatomical damage. In addition, considerable differences between the networks' global efficiency and transitivity based on the imaginary part of the coherence (iCoh) measure were observed, indicating higher global efficiency and transitivity in the delta, theta, and beta frequency bands for RRMS cases, which can be related to the compensatory functional reaction from the brain. This study indicated that in RRMS cases, some of the global characteristics of the brain's functional network, such as diameter and global efficiency, change and can be illustrated even in the resting-state condition when the brain is not under cognitive load.
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Affiliation(s)
- Sepehr Shirani
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
- Department of Computer Science, Nottingham Trent University, Nottingham, United Kingdom
| | - Maryam Mohebbi
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
- *Correspondence: Maryam Mohebbi
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21
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Ashtiani SNM, Behnam H, Daliri MR. Diagnosis of Multiple Sclerosis Using Graph-Theoretic Measures of Cognitive-Task-Based Functional Connectivity Networks. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2021.3081605] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Seyedeh Naghmeh Miri Ashtiani
- Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Hamid Behnam
- Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Mohammad Reza Daliri
- Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
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22
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Guo B, Zhou F, Zou G, Jiang J, Gao JH, Zou Q. Reorganizations of latency structures within the white matter from wakefulness to sleep. Magn Reson Imaging 2022; 93:52-61. [DOI: 10.1016/j.mri.2022.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 06/30/2022] [Accepted: 08/02/2022] [Indexed: 11/24/2022]
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23
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Koubiyr I, Broeders TA, Deloire M, Brochet B, Tourdias T, Geurts JJ, Schoonheim MM, Ruet A. Altered functional brain states predict cognitive decline 5 years after a clinically isolated syndrome. Mult Scler 2022; 28:1973-1982. [PMID: 35735004 DOI: 10.1177/13524585221101470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cognitive impairment occurs in the earliest stages of multiple sclerosis (MS) together with altered functional connectivity (FC). OBJECTIVE The aim of this study was to investigate the evolution of dynamic FC states in early MS and their role in shaping cognitive decline. METHODS Overall, 32 patients were enrolled after their first neurological episode suggestive of MS and underwent cognitive evaluation and resting-state functional MRI (fMRI) over 5 years. In addition, 28 healthy controls were included at baseline. RESULTS Cognitive performance was stable during the first year and declined after 5 years.At baseline, the number of transitions between states was lower in MS compared to controls (p = 0.01). Over time, frequency of high FC states decreased in patients (p = 0.047) and increased in state with low FC (p = 0.035). Cognitive performance at Year 5 was best predicted by the mean connectivity of high FC state at Year 1. CONCLUSION Patients with early MS showed reduced functional network dynamics at baseline. Longitudinal changes showed longer time spent in a state of low FC but less time spent and more connectivity disturbance in more integrative states with high within- and between-network FC. Disturbed FC within this more integrative state was predictive of future cognitive decline.
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Affiliation(s)
- Ismail Koubiyr
- Univ. Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France
| | - Tommy Aa Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Bruno Brochet
- Univ. Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France
| | - Thomas Tourdias
- Univ. Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France; CHU de Bordeaux, Bordeaux, France
| | - Jeroen Jg Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Menno Michiel Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Aurélie Ruet
- Univ. Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France; CHU de Bordeaux, Bordeaux, France
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24
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Chitnis T, Vandercappellen J, King M, Brichetto G. Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes. Neurol Ther 2022; 11:1043-1070. [PMID: 35680693 PMCID: PMC9338216 DOI: 10.1007/s40120-022-00368-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/16/2022] [Indexed: 11/18/2022] Open
Abstract
Introduction Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms. Methods A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest. Results Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment. Conclusion The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection. Supplementary Information The online version contains supplementary material available at 10.1007/s40120-022-00368-2.
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Affiliation(s)
- Tanuja Chitnis
- Department of Neurology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
| | | | - Miriam King
- Novartis Pharma AG, Fabrikstrasse 12-2, 4056, Basel, Switzerland
| | - Giampaolo Brichetto
- Associazione Italiana Sclerosi Multipla Rehabilitation Center, Via Operai, 30, 16149, Genoa, GE, Italy
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25
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Leavitt VM, Dworkin JD, Buyukturkoglu K, Riley CS, Ritchey M. Summary metrics of memory subnetwork functional connectivity alterations in multiple sclerosis. Mult Scler 2022; 28:1963-1972. [PMID: 35658737 DOI: 10.1177/13524585221099169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Memory dysfunction is common in multiple sclerosis (MS); mechanistic understanding of its causes is lacking. Large-scale network resting-state functional connectivity (RSFC) is sensitive to memory dysfunction. OBJECTIVE We derived and tested summary metrics of memory network RSFC. METHODS Cognitive data and 3T magnetic resonance imaging (MRI) scans were collected from 235 MS patients and 35 healthy controls (HCs). Index scores were calculated as RSFC within (anteriority index, AntI) and between (integration index, IntI) dorsomedial anterior temporal and medial temporal memory subnetworks. Group differences in index expression were evaluated. Associations between index scores and memory/non-memory cognition were evaluated; relationships between T2 lesion volume (T2LV) and index scores were assessed. RESULTS Index scores were related to memory and T2LV in MS patients, who showed marginally elevated AntI relative to HC (p = 0.06); no group differences were found for IntI. Better memory was associated with higher AntI (β = 0.15, p = 0.018) and IntI (β = 0.16, p = 0.014). No associations were found for non-memory cognition. Higher T2LV was associated with higher AntI and IntI; exploratory mediation analysis revealed significant inconsistent mediation, that is, higher index scores partially suppressed the negative association between T2LV and memory. CONCLUSION Summary, within-subject metrics permit replication and circumvent challenges of traditional (incommensurate) RSFC variables to advance development of mechanistic models of memory dysfunction in MS.
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Affiliation(s)
- Victoria M Leavitt
- Translational Cognitive Neuroscience Laboratory, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA/Multiple Sclerosis Center, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jordan D Dworkin
- Department of Psychiatry, Columbia University and the New York State Psychiatric Institute, New York, NY, USA
| | - Korhan Buyukturkoglu
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Claire S Riley
- Multiple Sclerosis Center, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA/Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Maureen Ritchey
- Department of Psychology, Boston College, Chestnut Hill, MA, USA
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26
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Broeders TA, Douw L, Eijlers AJ, Dekker I, Uitdehaag BM, Barkhof F, Hulst HE, Vinkers CH, Geurts JJ, Schoonheim MM. A more unstable resting-state functional network in cognitively declining multiple sclerosis. Brain Commun 2022; 4:fcac095. [PMID: 35620116 PMCID: PMC9128379 DOI: 10.1093/braincomms/fcac095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 02/14/2022] [Accepted: 04/11/2022] [Indexed: 11/24/2022] Open
Abstract
Cognitive impairment is common in people with multiple sclerosis and strongly
affects their daily functioning. Reports have linked disturbed cognitive
functioning in multiple sclerosis to changes in the organization of the
functional network. In a healthy brain, communication between brain regions and
which network a region belongs to is continuously and dynamically adapted to
enable adequate cognitive function. However, this dynamic network adaptation has
not been investigated in multiple sclerosis, and longitudinal network data
remain particularly rare. Therefore, the aim of this study was to longitudinally
identify patterns of dynamic network reconfigurations that are related to the
worsening of cognitive decline in multiple sclerosis. Resting-state functional
MRI and cognitive scores (expanded Brief Repeatable Battery of
Neuropsychological tests) were acquired in 230 patients with multiple sclerosis
and 59 matched healthy controls, at baseline (mean disease duration: 15 years)
and at 5-year follow-up. A sliding-window approach was used for functional MRI
analyses, where brain regions were dynamically assigned to one of seven
literature-based subnetworks. Dynamic reconfigurations of subnetworks were
characterized using measures of promiscuity (number of subnetworks switched to),
flexibility (number of switches), cohesion (mutual switches) and disjointedness
(independent switches). Cross-sectional differences between cognitive groups and
longitudinal changes were assessed, as well as relations with structural damage
and performance on specific cognitive domains. At baseline, 23% of
patients were cognitively impaired (≥2/7 domains
Z < −2) and 18% were mildly
impaired (≥2/7 domains
Z < −1.5). Longitudinally,
28% of patients declined over time (0.25 yearly change on ≥2/7
domains based on reliable change index). Cognitively impaired patients displayed
more dynamic network reconfigurations across the whole brain compared with
cognitively preserved patients and controls, i.e. showing higher promiscuity
(P = 0.047), flexibility
(P = 0.008) and cohesion
(P = 0.008). Over time, cognitively
declining patients showed a further increase in cohesion
(P = 0.004), which was not seen in stable
patients (P = 0.544). More cohesion was
related to more severe structural damage (average
r = 0.166,
P = 0.015) and worse verbal memory
(r = −0.156,
P = 0.022), information processing speed
(r = −0.202,
P = 0.003) and working memory
(r = −0.163,
P = 0.017). Cognitively impaired multiple
sclerosis patients exhibited a more unstable network reconfiguration compared to
preserved patients, i.e. brain regions switched between subnetworks more often,
which was related to structural damage. This shift to more unstable network
reconfigurations was also demonstrated longitudinally in patients that showed
cognitive decline only. These results indicate the potential relevance of a
progressive destabilization of network topology for understanding cognitive
decline in multiple sclerosis.
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Affiliation(s)
- Tommy A.A. Broeders
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda Douw
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anand J.C. Eijlers
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Iris Dekker
- Departments of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bernard M.J. Uitdehaag
- Departments of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, UK
| | - Hanneke E. Hulst
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Christiaan H. Vinkers
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Departments of Psychiatry, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J.G. Geurts
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Menno M. Schoonheim
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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27
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Ye C, Huang J, Liang L, Yan Z, Qi Z, Kang X, Liu Z, Dong H, Lv H, Ma T, Lu J. Coupling of brain activity and structural network in multiple sclerosis: A graph frequency analysis study. J Neurosci Res 2022; 100:1226-1238. [PMID: 35184336 DOI: 10.1002/jnr.25028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 12/06/2021] [Accepted: 01/27/2022] [Indexed: 11/10/2022]
Affiliation(s)
| | - Jing Huang
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
| | - Li Liang
- Department of Electronic and Information Engineering Harbin Institute of Technology at Shenzhen Shenzhen China
| | - Zehong Yan
- Department of Electronic and Information Engineering Harbin Institute of Technology at Shenzhen Shenzhen China
| | - Zhigang Qi
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
| | - Xiong Kang
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
| | - Zheng Liu
- Department of Neurology Xuanwu Hospital, Capital Medical University Beijing China
| | - Huiqing Dong
- Department of Neurology Xuanwu Hospital, Capital Medical University Beijing China
| | - Haiyan Lv
- Mindsgo Life Science Shenzhen Co. Ltd Shenzhen China
| | - Ting Ma
- Peng Cheng Laboratory Shenzhen China
- Department of Electronic and Information Engineering Harbin Institute of Technology at Shenzhen Shenzhen China
- Advanced Innovation Center for Human Brain Protection Capital Medical University Beijing China
- National Clinical Research Center for Geriatric Disorders Xuanwu Hospital Capital Medical University Beijing China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
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28
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Optimizing EEG Source Reconstruction with Concurrent fMRI-Derived Spatial Priors. Brain Topogr 2022; 35:282-301. [PMID: 35142957 PMCID: PMC9098592 DOI: 10.1007/s10548-022-00891-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 01/31/2022] [Indexed: 02/01/2023]
Abstract
Reconstructing EEG sources involves a complex pipeline, with the inverse problem being the most challenging. Multiple inversion algorithms are being continuously developed, aiming to tackle the non-uniqueness of this problem, which has been shown to be partially circumvented by including prior information in the inverse models. Despite a few efforts, there are still current and persistent controversies regarding the inversion algorithm of choice and the optimal set of spatial priors to be included in the inversion models. The use of simultaneous EEG-fMRI data is one approach to tackle this problem. The spatial resolution of fMRI makes fMRI derived spatial priors very convenient for EEG reconstruction, however, only task activation maps and resting-state networks (RSNs) have been explored so far, overlooking the recent, but already accepted, notion that brain networks exhibit dynamic functional connectivity fluctuations. The lack of a systematic comparison between different source reconstruction algorithms, considering potentially more brain-informative priors such as fMRI, motivates the search for better reconstruction models. Using simultaneous EEG-fMRI data, here we compared four different inversion algorithms (minimum norm, MN; low resolution electromagnetic tomography, LORETA; empirical Bayes beamformer, EBB; and multiple sparse priors, MSP) under a Bayesian framework (as implemented in SPM), each with three different sets of priors consisting of: (1) those specific to the algorithm; (2) those specific to the algorithm plus fMRI task activation maps and RSNs; and (3) those specific to the algorithm plus fMRI task activation maps and RSNs and network modules of task-related dFC states estimated from the dFC fluctuations. The quality of the reconstructed EEG sources was quantified in terms of model-based metrics, namely the expectation of the posterior probability P(model|data) and variance explained of the inversion models, and the overlap/proportion of brain regions known to be involved in the visual perception tasks that the participants were submitted to, and RSN templates, with/within EEG source components. Model-based metrics suggested that model parsimony is preferred, with the combination MSP and priors specific to this algorithm exhibiting the best performance. However, optimal overlap/proportion values were found using EBB and priors specific to this algorithm and fMRI task activation maps and RSNs or MSP and considering all the priors (algorithm priors, fMRI task activation maps and RSNs and dFC state modules), respectively, indicating that fMRI spatial priors, including dFC state modules, might contain useful information to recover EEG source components reflecting neuronal activity of interest. Our main results show that providing fMRI spatial derived priors that reflect the dynamics of the brain might be useful to map neuronal activity more accurately from EEG-fMRI. Furthermore, this work paves the way towards a more informative selection of the optimal EEG source reconstruction approach, which may be critical in future studies.
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29
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Giurgola S, Casati C, Stampatori C, Perucca L, Mattioli F, Vallar G, Bolognini N. Abnormal multisensory integration in relapsing–remitting multiple sclerosis. Exp Brain Res 2022; 240:953-968. [PMID: 35094114 PMCID: PMC8918188 DOI: 10.1007/s00221-022-06310-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 01/15/2022] [Indexed: 12/22/2022]
Abstract
Temporal Binding Window (TBW) represents a reliable index of efficient multisensory integration process, which allows individuals to infer which sensory inputs from different modalities pertain to the same event. TBW alterations have been reported in some neurological and neuropsychiatric disorders and seem to negatively affects cognition and behavior. So far, it is still unknown whether deficits of multisensory integration, as indexed by an abnormal TBW, are present even in Multiple Sclerosis. We addressed this issue by testing 25 participants affected by relapsing–remitting Multiple Sclerosis (RRMS) and 30 age-matched healthy controls. Participants completed a simultaneity judgment task (SJ2) to assess the audio-visual TBW; two unimodal SJ2 versions were used as control tasks. Individuals with RRMS showed an enlarged audio-visual TBW (width range = from − 166 ms to + 198 ms), as compared to healthy controls (width range = − 177/ + 66 ms), thus showing an increased tendency to integrate temporally asynchronous visual and auditory stimuli. Instead, simultaneity perception of unimodal (visual or auditory) events overall did not differ from that of controls. These results provide first evidence of a selective deficit of multisensory integration in individuals affected by RRMS, besides the well-known motor and cognitive impairments. The reduced multisensory temporal acuity is likely caused by a disruption of the neural interplay between different sensory systems caused by multiple sclerosis.
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Affiliation(s)
- Serena Giurgola
- Department of Psychology and NeuroMI, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
| | - Carlotta Casati
- Neuropsychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
- Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | | | - Laura Perucca
- Neurorehabilitation Sciences, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Flavia Mattioli
- Neuropsychology Unit, Spedali Civili of Brescia, Brescia, Italy
| | - Giuseppe Vallar
- Department of Psychology and NeuroMI, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
- Neuropsychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Nadia Bolognini
- Department of Psychology and NeuroMI, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
- Neuropsychology Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
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30
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Giovannoni G, Popescu V, Wuerfel J, Hellwig K, Iacobaeus E, Jensen MB, García-Domínguez JM, Sousa L, De Rossi N, Hupperts R, Fenu G, Bodini B, Kuusisto HM, Stankoff B, Lycke J, Airas L, Granziera C, Scalfari A. Smouldering multiple sclerosis: the ‘real MS’. Ther Adv Neurol Disord 2022; 15:17562864211066751. [PMID: 35096143 PMCID: PMC8793117 DOI: 10.1177/17562864211066751] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/28/2021] [Indexed: 12/25/2022] Open
Abstract
Using a philosophical approach or deductive reasoning, we challenge the dominant
clinico-radiological worldview that defines multiple sclerosis (MS) as a focal
inflammatory disease of the central nervous system (CNS). We provide a range of
evidence to argue that the ‘real MS’ is in fact driven primarily by a
smouldering pathological disease process. In natural history studies and
clinical trials, relapses and focal activity revealed by magnetic resonance
imaging (MRI) in MS patients on placebo or on disease-modifying therapies (DMTs)
were found to be poor predictors of long-term disease evolution and were
dissociated from disability outcomes. In addition, the progressive accumulation
of disability in MS can occur independently of relapse activity from early in
the disease course. This scenario is underpinned by a more diffuse smouldering
pathological process that may affect the entire CNS. Many putative pathological
drivers of smouldering MS can be potentially modified by specific therapeutic
strategies, an approach that may have major implications for the management of
MS patients. We hypothesise that therapeutically targeting a state of ‘no
evident inflammatory disease activity’ (NEIDA) cannot sufficiently prevent
disability accumulation in MS, meaning that treatment should also focus on other
brain and spinal cord pathological processes contributing to the slow loss of
neurological function. This should also be complemented with a holistic approach
to the management of other systemic disease processes that have been shown to
worsen MS outcomes.
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Affiliation(s)
| | - Veronica Popescu
- Universitair MS Centrum, Hasselt, Belgium;
Noorderhart Hospital, Pelt, Belgium; Hasselt University, Hasselt,
Belgium
| | - Jens Wuerfel
- MIAC AG, Department of Biomedical Engineering,
University of Basel, Basel, Switzerland; Charité – University Medicine
Berlin, Berlin, Germany
| | - Kerstin Hellwig
- Katholisches Klinikum Bochum, Klinikum der
Ruhr-Universität, Bochum, Germany
| | | | | | | | - Livia Sousa
- Centro Hospitalar e Universitário de Coimbra,
Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
| | | | - Raymond Hupperts
- Zuyderland Medisch Centrum, Sittard-Geleen,
The Netherlands; Maastricht University Medical Center, Maastricht, The
Netherlands
| | - Giuseppe Fenu
- Department of Neurology, Brotzu Hospital,
Cagliari, Italy
| | - Benedetta Bodini
- Paris Brain Institute, Sorbonne University,
Paris, France; Department of Neurology, APHP, Saint-Antoine Hospital, Paris,
France
| | - Hanna-Maija Kuusisto
- Department of Neurology, Tampere University
Hospital, Tampere, Finland; Department of Customer and Patient Safety,
University of Eastern Finland, Kuopio, Finland
| | - Bruno Stankoff
- Paris Brain Institute, Sorbonne University,
ICM, CNRS, Inserm, Paris, France; APHP, Saint-Antoine Hospital, Paris,
France
| | - Jan Lycke
- Institute of Neuroscience and Physiology,
University of Gothenburg, Gothenburg, Sweden
| | | | - Cristina Granziera
- Neurologic Clinic and Policlinic, Departments
of Medicine, Clinical Research and Biomedical Engineering, University
Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk)
Basel, Department of Biomedical Engineering, University Hospital Basel and
University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology
and Neuroscience Basel (RC2NB), University Hospital Basel and University of
Basel, Basel, Switzerland
| | - Antonio Scalfari
- Centre for Neuroscience, Department of
Medicine, Charing Cross Hospital, Imperial College London, London, UK
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31
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Preliminary Analysis of Brain Footprints in Multiple Sclerosis Females with Detrusor Sphincter Dyssynergia: A Concurrent Urodynamic and Functional Magnetic Resonance Imaging Study. Int Neurourol J 2021; 26:S38-46. [PMID: 34856727 PMCID: PMC8896778 DOI: 10.5213/inj.2142012.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 03/29/2021] [Indexed: 11/08/2022] Open
Abstract
Purpose This study evaluates the grey and white brain matter characteristics in women with multiple sclerosis (MS) and detrusor sphincter dyssynergia (DSD). Grey matter is assessed via the functional connectivity (FC) of brain regions activated during voiding, using functional magnetic resonance imaging (fMRI). Two white matter tracts involved in bladder function, the anterior thalamic radiation (ATR) and superior longitudinal fasciculus (SLF), were evaluated using diffusion tensor imaging (DTI). Methods Twenty-seven women with MS (two groups: no-DSD (n=23) or DSD (n=4)), and eight healthy controls (HC) underwent concurrent urodynamic-fMRI evaluation with four cycles of bladder filling and emptying. A FC similarity measure (FC_sim) was calculated for each subject to express the similarity of individual FC at voiding initiation compared to all FC patterns. ATR and SLF tracts were traced and their fractional anisotropy (FA) and mean diffusivity (MD) were recorded. Results Mean FC_sim values were significantly different among the three groups indicating distinct FC patterns; however, no significant difference was found between DSD and no-DSD groups. DSD group showed trends of lower FA and higher MD - indicating loss of coherence - in all tracts compared to HCs, and in the left and right ATR when compared to MS women with neither DSD nor voiding dysfunction (VD), suggesting more damage in these tracts for MS women with DSD. Conclusions Women with MS show distinctly different FC patterns compared to HCs. There are trends showing more damage in the ATR in women with MS and DSD compared to those with neither DSD nor VD.
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Veréb D, Kovács MA, Kocsis K, Tóth E, Bozsik B, Király A, Kincses B, Faragó P, Fricska-Nagy Z, Bencsik K, Klivényi P, Kincses ZT, Szabó N. Functional Connectivity Lateralisation Shift of Resting State Networks is Linked to Visuospatial Memory and White Matter Microstructure in Relapsing-Remitting Multiple Sclerosis. Brain Topogr 2021; 35:268-275. [PMID: 34807323 PMCID: PMC8860794 DOI: 10.1007/s10548-021-00881-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 11/05/2021] [Indexed: 11/28/2022]
Abstract
Laterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing–remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman’s correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = − 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing–remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.
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Affiliation(s)
- Dániel Veréb
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary.,Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Márton Attila Kovács
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztián Kocsis
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Eszter Tóth
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bence Bozsik
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - András Király
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bálint Kincses
- Department of Psychiatry, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary.,Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Péter Faragó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsanett Fricska-Nagy
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztina Bencsik
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Péter Klivényi
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsigmond Tamás Kincses
- Neuroimaging Research Group, Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Semmelweis u. 6, 6725, Hungary.
| | - Nikoletta Szabó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
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Groppa S, Gonzalez-Escamilla G, Eshaghi A, Meuth SG, Ciccarelli O. Linking immune-mediated damage to neurodegeneration in multiple sclerosis: could network-based MRI help? Brain Commun 2021; 3:fcab237. [PMID: 34729480 PMCID: PMC8557667 DOI: 10.1093/braincomms/fcab237] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2021] [Indexed: 01/04/2023] Open
Abstract
Inflammatory demyelination characterizes the initial stages of multiple sclerosis, while progressive axonal and neuronal loss are coexisting and significantly contribute to the long-term physical and cognitive impairment. There is an unmet need for a conceptual shift from a dualistic view of multiple sclerosis pathology, involving either inflammatory demyelination or neurodegeneration, to integrative dynamic models of brain reorganization, where, glia-neuron interactions, synaptic alterations and grey matter pathology are longitudinally envisaged at the whole-brain level. Functional and structural MRI can delineate network hallmarks for relapses, remissions or disease progression, which can be linked to the pathophysiology behind inflammatory attacks, repair and neurodegeneration. Here, we aim to unify recent findings of grey matter circuits dynamics in multiple sclerosis within the framework of molecular and pathophysiological hallmarks combined with disease-related network reorganization, while highlighting advances from animal models (in vivo and ex vivo) and human clinical data (imaging and histological). We propose that MRI-based brain networks characterization is essential for better delineating ongoing pathology and elaboration of particular mechanisms that may serve for accurate modelling and prediction of disease courses throughout disease stages.
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Affiliation(s)
- Sergiu Groppa
- Imaging and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Gabriel Gonzalez-Escamilla
- Imaging and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Arman Eshaghi
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London WC1E 6BT, UK.,Department of Computer Science, Centre for Medical Image Computing (CMIC), University College London, London WC1E 6BT, UK
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London WC1E 6BT, UK
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34
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Tavazzi E, Cazzoli M, Pirastru A, Blasi V, Rovaris M, Bergsland N, Baglio F. Neuroplasticity and Motor Rehabilitation in Multiple Sclerosis: A Systematic Review on MRI Markers of Functional and Structural Changes. Front Neurosci 2021; 15:707675. [PMID: 34690670 PMCID: PMC8526725 DOI: 10.3389/fnins.2021.707675] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/03/2021] [Indexed: 01/10/2023] Open
Abstract
Background: Motor rehabilitation is routinely used in clinical practice as an effective method to reduce progressive disability gain in multiple sclerosis (MS), but rehabilitation approaches are typically unstandardized, and only few studies have investigated the impact of rehabilitation on brain neuroplasticity. Objective: To summarize and critically analyze studies applying MRI markers of functional connectivity and structural changes to assess the effect of motor rehabilitation on brain neuroplasticity in MS. Methods: Literature search was performed using PubMed and EMBASE, selecting studies having as a subject motor rehabilitation and advanced MRI techniques investigating neuroplasticity in adult patients affected by MS. Results: Seventeen out of 798 papers were selected, of which 5 applied structural MRI (4 diffusion tensor imaging, 1 volumetric measurements), 7 applied functional fMRI (5 task-related fMRI, 2 resting-state fMRI) whereas the remaining 5 applied both structural and functional imaging. Discussion: The considerable data heterogeneity and the small sample sizes characterizing the studies limit interpretation and generalization of the results. Overall, motor rehabilitation promotes clinical improvement, paralleled by positive adaptive brain changes, whose features and extent depend upon different variables, including the type of rehabilitation approach. MRI markers of functional and structural connectivity should be implemented in studies testing the efficacy of motor rehabilitation. They allow for a better understanding of neuroplastic mechanisms underlying rehabilitation-mediated clinical achievements, facilitating the identification of rehabilitation strategies tailored to patients' needs and abilities.
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Affiliation(s)
- Eleonora Tavazzi
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.,Department of Neurology, Buffalo Neuroimaging Analysis Center, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Marta Cazzoli
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | | | - Valeria Blasi
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Marco Rovaris
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Niels Bergsland
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.,Department of Neurology, Buffalo Neuroimaging Analysis Center, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
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35
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Khan H, Sami MB, Litvak V. The utility of Magnetoencephalography in multiple sclerosis - A systematic review. NEUROIMAGE-CLINICAL 2021; 32:102814. [PMID: 34537682 PMCID: PMC8455859 DOI: 10.1016/j.nicl.2021.102814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 01/29/2023]
Abstract
We conducted a Systematic Review of studies, looking at 30 studies from 13 centres. MS patients had reduced power in some induced responses (motor beta, visual gamma). Increased latency and reduced connectivity were seen for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive function. MEG shows promise, although work is too preliminary to recommend current clinical use.
Introduction Magnetoencephalography (MEG), allows for a high degree temporal and spatial accuracy in recording cortical oscillatory activity and evoked fields. To date, no review has been undertaken to synthesise all MEG studies in Multiple Sclerosis (MS). We undertook a Systematic Review of the utility of MEG in MS. Methods We identified MEG studies carried out in MS using EMBASE, Medline, Cochrane, TRIP and Psychinfo databases. We included original research articles with a cohort of minimum of five multiple sclerosis patients and quantifying of at least one MEG parameter. We used a modified version of the JBI (mJBI) for case-control studies to assess for risk of bias. Results We identified 30 studies from 13 centres involving at least 433 MS patients and 347 controls. We found evidence that MEG shows perturbed activity (most commonly reduced power modulations), reduced connectivity and association with altered clinical function in Multiple Sclerosis. Specific replicated findings were decreased motor induced responses in the beta band, diminished increase of gamma power after visual stimulation, increased latency and reduced connectivity for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive measures in people with MS. Overall studies were of moderate quality (mean mJBI score 6.7). Discussion We find evidence for the utility of MEG in Multiple Sclerosis. Event-related designs are of particular value and show replicability between centres. At this stage, it is not clear whether these changes are specific to Multiple Sclerosis or are also observable in other diseases. Further studies should look to explore cognitive control in more depth using in-task designs and undertake longitudinal studies to determine whether these changes have prognostic value.
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Affiliation(s)
- H Khan
- UCL Queen's Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom; Queen's Medical Centre Nottingham, Clifton Boulevard, Derby Rd, Nottingham NG7 2UH, United Kingdom.
| | - M B Sami
- Institute of Mental Health, Jubilee Campus, University of Nottingham Innovation Park, Triumph Road, Nottingham NG7 2TU, United Kingdom
| | - V Litvak
- UCL Queen's Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
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36
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Saadat N, Mayo CD, Lacey C, Gawryluk JR. Functional connectivity pre-post exercise intervention in individuals with relapsing-remitting multiple sclerosis. Neuroreport 2021; 32:1100-1105. [PMID: 34284447 DOI: 10.1097/wnr.0000000000001702] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Exercise interventions have emerged as a promising approach for managing symptoms associated with multiple sclerosis (MS). However, changes in brain function underlying exercise-related improvements in symptoms of MS have not been fully investigated, and in no instances have they been investigated using a graph theory approach. For the first time, the effects of an exercise intervention on functional brain network connectivity were examined using graph theory analyses of resting-state functional MRI (fMRI) data among individuals with relapsing-remitting MS (RRMS). METHODS Resting-state fMRI data were obtained from 10 participants before and after 12 weeks of a speeded walking intervention. Functional connectivity data were preprocessed in Data Processing Assistant for Resting-State fMRI Advanced (DPARSF A version 4.2) and analyzed in GraphVar2.02 to compute global and local graph theory metrics. To examine differences in graph metrics before and after the intervention, one-sample permutation tests were performed. RESULTS There were no significant pre to post exercise intervention changes in global metrics. Changes in local metrics (i.e. clustering coefficient, local efficiency, degree centrality and betweenness centrality) were mixed, with both increases and decreases observed. CONCLUSION Following a 12-week speeded walking exercise intervention, there were no significant increases or decreases in global graph metrics and results at the level of local metrics were equivocal in individuals with RRMS. Further research with experimental designs that include baseline and longitudinal follow-up, as well as larger sample sizes, is needed to understand the underlying mechanisms of symptom improvement following exercise in RRMS.
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Affiliation(s)
| | - Chantel D Mayo
- Department of Psychology
- Institute on Aging and Lifelong Health
| | - Colleen Lacey
- Department of Psychology
- Institute on Aging and Lifelong Health
| | - Jodie R Gawryluk
- Department of Psychology
- Institute on Aging and Lifelong Health
- Division of Medical Sciences, University of Victoria, Victoria, British Columbia
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37
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Beaudoin AM, Rheault F, Theaud G, Laberge F, Whittingstall K, Lamontagne A, Descoteaux M. Modern Technology in Multi-Shell Diffusion MRI Reveals Diffuse White Matter Changes in Young Adults With Relapsing-Remitting Multiple Sclerosis. Front Neurosci 2021; 15:665017. [PMID: 34447292 PMCID: PMC8383891 DOI: 10.3389/fnins.2021.665017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 07/20/2021] [Indexed: 11/13/2022] Open
Abstract
Objective To characterize microstructural white matter changes related to relapsing-remitting multiple sclerosis using advanced diffusion MRI modeling and tractography. The association between imaging data and patient’s cognitive performance, fatigue severity and depressive symptoms is also explored. Methods In this cross-sectional study, 24 relapsing-remitting multiple sclerosis patients and 11 healthy controls were compared using high angular resolution diffusion imaging (HARDI). The imaging method includes a multi-shell scheme, free water correction to obtain tissue-specific measurements, probabilistic tracking algorithm robust to crossing fibers and white matter lesions, automatic streamlines and bundle dissection and tract-profiling with tractometry. The neuropsychological evaluation included the Symbol Digit Modalities Test, Paced Auditory Serial Addition Test, Modified Fatigue Impact Scale and Beck Depression Inventory-II. Results Bundle-wise analysis by tractometry revealed a difference between patients and controls for 11 of the 14 preselected white matter bundles. In patients, free water corrected fractional anisotropy was significantly reduced while radial and mean diffusivities were increased, consistent with diffuse demyelination. The fornix and left inferior fronto-occipital fasciculus exhibited a higher free water fraction. Eight bundles showed an increase in total apparent fiber density and four bundles had a higher number of fiber orientations, suggesting axonal swelling and increased organization complexity, respectively. In the association study, depressive symptoms were associated with diffusion abnormalities in the right superior longitudinal fasciculus. Conclusion Tissue-specific diffusion measures showed abnormalities along multiple cerebral white matter bundles in patients with relapsing-remitting multiple sclerosis. The proposed methodology combines free-water imaging, advanced bundle dissection and tractometry, which is a novel approach to investigate cerebral pathology in multiple sclerosis. It opens a new window of use for HARDI-derived measures and free water corrected diffusion measures. Advanced diffusion MRI provides a better insight into cerebral white matter changes in relapsing-remitting multiple sclerosis, namely diffuse demyelination, edema and increased fiber density and complexity.
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Affiliation(s)
- Ann-Marie Beaudoin
- Department of Neurology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - François Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Frédéric Laberge
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Kevin Whittingstall
- Department of Radiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Albert Lamontagne
- Department of Neurology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
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Seraji M, Mohebbi M, Safari A, Krekelberg B. Multiple sclerosis reduces synchrony of the magnocellular pathway. PLoS One 2021; 16:e0255324. [PMID: 34437558 PMCID: PMC8389379 DOI: 10.1371/journal.pone.0255324] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 07/15/2021] [Indexed: 02/01/2023] Open
Abstract
Multiple Sclerosis (MS) is an autoimmune demyelinating disease that damages the insulation of nerve cell fibers in the brain and spinal cord. In the visual system, this demyelination results in a robust delay of visually evoked potentials (VEPs), even in the absence of overt clinical symptoms such as blurred vision. VEPs, therefore, offer an avenue for early diagnosis, monitoring disease progression, and, potentially, insight into the differential impairment of specific pathways. A primary hypothesis has been that visual stimuli driving the magno-, parvo-, and konio-cellular pathways should lead to differential effects because these pathways differ considerably in terms of myelination. Experimental tests of this hypothesis, however, have led to conflicting results. Some groups reported larger latency effects for chromatic stimuli, while others found equivalent effects across stimulus types. We reasoned that this lack of pathway specificity could, at least in part, be attributed to the relatively coarse measure of pathway impairment afforded by the latency of a VEP. We hypothesized that network synchrony could offer a more sensitive test of pathway impairments. To test this hypothesis, we analyzed the synchrony of occipital electroencephalography (EEG) signals during the presentation of visual stimuli designed to bias activity to one of the three pathways. Specifically, we quantified synchrony in the occipital EEG using two graph-theoretic measures of functional connectivity: the characteristic path length (L; a measure of long-range connectivity) and the clustering coefficient (CC; a measure of short-range connectivity). Our main finding was that L and CC were both smaller in the MS group than in controls. Notably, this change in functional connectivity was limited to the magnocellular pathway. The effect sizes (Hedge's g) were 0.89 (L) and 1.26 (CC) measured with magno stimuli. Together, L and CC define the small-world nature of a network, and our finding can be summarized as a reduction in the small-worldness of the magnocellular network. We speculate that the reduced efficiency of information transfer associated with a reduction in small-worldness could underlie visual deficits in MS. Relating these measures to differential diagnoses and disease progression is an important avenue for future work.
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Affiliation(s)
- Masoud Seraji
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, New Jersey, United States of America
- Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, New Jersey, United States of America
- * E-mail:
| | - Maryam Mohebbi
- School of Electrical Engineering, K.N.Toosi University of Technology, Tehran, Iran
| | - Amirhossein Safari
- School of Electrical Engineering, K.N.Toosi University of Technology, Tehran, Iran
| | - Bart Krekelberg
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, New Jersey, United States of America
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Jandric D, Doshi A, Scott R, Paling D, Rog D, Chataway J, Schoonheim M, Parker G, Muhlert N. A systematic review of resting state functional MRI connectivity changes and cognitive impairment in multiple sclerosis. Brain Connect 2021; 12:112-133. [PMID: 34382408 DOI: 10.1089/brain.2021.0104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting state functional MRI (rs-fMRI) functional connectivity (FC) . However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology. METHODS Embase, Medline and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS. RESULTS Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different MR metrics. There was no clear link to increased FC during early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings. DISCUSSION These results indicate an urgent need for greater standardisation in the field - in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.
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Affiliation(s)
- Danka Jandric
- The University of Manchester, 5292, Oxford Road, Manchester, United Kingdom of Great Britain and Northern Ireland, M13 9PL;
| | - Anisha Doshi
- University College London, 4919, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Richelle Scott
- The University of Manchester, 5292, Manchester, United Kingdom of Great Britain and Northern Ireland;
| | - David Paling
- Royal Hallamshire Hospital, 105629, Sheffield, Sheffield, United Kingdom of Great Britain and Northern Ireland;
| | - David Rog
- Salford Royal Hospital, 105621, Salford, Salford, United Kingdom of Great Britain and Northern Ireland;
| | - Jeremy Chataway
- University College London, 4919, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Menno Schoonheim
- Amsterdam UMC Locatie VUmc, 1209, Anatomy & Neurosciences, Amsterdam, Noord-Holland, Netherlands;
| | - Geoff Parker
- University College London, 4919, London, London, United Kingdom of Great Britain and Northern Ireland.,The University of Manchester, 5292, Manchester, United Kingdom of Great Britain and Northern Ireland;
| | - Nils Muhlert
- The University of Manchester, 5292, Manchester, United Kingdom of Great Britain and Northern Ireland;
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40
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Chen Y, Li R, Wu A, Qiu W, Hu X, Hu Z, Yang Q, Zhou Z. Comparison of Thalamus and Basal Ganglia Signs Between Multiple Sclerosis and Primary Angiitis of the Central Nervous System: An Exploratory Study. Front Neurol 2021; 12:513253. [PMID: 34393963 PMCID: PMC8358104 DOI: 10.3389/fneur.2021.513253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 04/30/2021] [Indexed: 12/02/2022] Open
Abstract
Based on the symptoms, especially those affecting small vessels, it is difficult to distinguish multiple sclerosis (MS) from primary angiitis of the central nervous system (PACNS). Magnetic resonance imaging (MRI) helps understand the characteristics of deep gray matter lesions (DGML) in MS and PACNS. We aimed to compare the MRI characteristics of thalamus and basal ganglia lesions between relapsing-remitting MS and PACNS. In our study, 49 relapsing-remitting MS patients and 16 PACNS with MRI-confirmed thalamus or basal ganglia lesions were enrolled. Among the DGMLs in basal ganglia, putamen had significantly higher (P = 0.037) involvement in PACNS than in MS. More importantly, larger lesion sizes in thalamus helps to distinguish PACNS (12.4 ± 4.3 mm) from MS (7.9 ± 3.7 mm) (P = 0.006). But using lesions in basal ganglia, researchers were unable to differentiate the two disorders. Presently, our study shows that MRI performances of deep gray matter differ between MS and PACNS.
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Affiliation(s)
- Ying Chen
- Department of Neurology, Yijishan Hospital, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Rui Li
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Aimin Wu
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wei Qiu
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xueqiang Hu
- Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhaoqi Hu
- Department of Orthopaedics, Wuhu Traditional Chinese Medicine Hospital, Wuhu, China
| | - Qian Yang
- Department of Neurology, Yijishan Hospital, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Zhiming Zhou
- Department of Neurology, Yijishan Hospital, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
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41
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Høgestøl EA, Ghezzo S, Nygaard GO, Espeseth T, Sowa P, Beyer MK, Harbo HF, Westlye LT, Hulst HE, Alnæs D. Functional connectivity in multiple sclerosis modelled as connectome stability: A 5-year follow-up study. Mult Scler 2021; 28:532-540. [PMID: 34259578 PMCID: PMC8961247 DOI: 10.1177/13524585211030212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background: Brain functional connectivity (FC) in multiple sclerosis (MS) is abnormal
compared to healthy controls (HCs). More longitudinal studies in MS are
needed to evaluate whether FC stability is clinically relevant. Objective: To compare functional magnetic resonance imaging (fMRI)-based FC between MS
and HC, and to determine the relationship between longitudinal FC changes
and structural brain damage, cognitive performance and physical
disability. Methods: T1-weighted MPRAGE and resting-state fMRI (1.5T) were acquired from 70
relapsing-remitting MS patients and 94 matched HC at baseline (mean months
since diagnosis 14.0 ± 11) and from 60 MS patients after 5 years.
Independent component analysis and network modelling were used to measure
longitudinal FC stability and cross-sectional comparisons with HC. Linear
mixed models, adjusted for age and sex, were used to calculate
correlations. Results: At baseline, patients with MS showed FC abnormalities both within networks
and in single connections compared to HC. Longitudinal analyses revealed
functional stability and no significant relationships with clinical
disability, cognitive performance, lesion or brain volume. Conclusion: FC abnormalities occur already at the first decade of MS, yet we found no
relevant clinical correlations for these network deviations. Future
large-scale longitudinal fMRI studies across a range of MS subtypes and
outcomes are required.
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Affiliation(s)
- Einar August Høgestøl
- "Department of Neurology, Neuroscience Research Unit, Multiple Sclerosis Research Group University of Oslo & Oslo University Hospital; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Samuele Ghezzo
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway/Department of Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Gro Owren Nygaard
- Department of Neurology, Neuroscience Research Unit, Multiple Sclerosis Research Group University of Oslo & Oslo University Hospital, Oslo, Norway
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway; Bjørknes College, Oslo, Norway
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Mona K Beyer
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway/Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Hanne Flinstad Harbo
- "Department of Neurology, Neuroscience Research Unit, Multiple Sclerosis Research Group University of Oslo & Oslo University Hospital; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway/Department of Psychology, University of Oslo, Oslo, Norway/KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Hanneke E Hulst
- Department of Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands/Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Bjørknes College, Oslo, Norway
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Shahrampour S, Heholt J, Wang A, Vedaei F, Mohamed FB, Alizadeh M, Wang Z, Zabrecky G, Wintering N, Bazzan AJ, Leist TP, Monti DA, Newberg AB. N-acetyl cysteine administration affects cerebral blood flow as measured by arterial spin labeling MRI in patients with multiple sclerosis. Heliyon 2021; 7:e07615. [PMID: 34377857 PMCID: PMC8327674 DOI: 10.1016/j.heliyon.2021.e07615] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/23/2021] [Accepted: 07/14/2021] [Indexed: 10/26/2022] Open
Abstract
BACKGROUND The purpose of this study was to explore if administration of N-acetyl-cysteine (NAC) in patients with multiple sclerosis (MS) resulted in altered cerebral blood flow (CBF) based on Arterial Spin Labeling (ASL) magnetic resonance imaging (MRI). METHODS Twenty-three patients with mild to moderate MS, (17 relapsing remitting and 6 primary progressive) were randomized to either NAC plus standard of care (N = 11), or standard of care only (N = 12). The experimental group received NAC intravenously (50 mg/kg) once per week and orally (500mg 2x/day) the other six days. Patients in both groups were evaluated initially and after 2 months (of receiving the NAC or waitlist control) with ASL MRI to measure CBF. Clinical symptom questionnaires were also completed at both time points. RESULTS The CBF data showed significant differences in several brain regions including the pons, midbrain, left temporal and frontal lobe, left thalamus, right middle frontal lobe and right temporal/hippocampus (p < 0.001) in the MS group after treatment with NAC, when compared to the control group. Self-reported scores related to cognition and attention were also significantly improved in the NAC group as compared to the control group. CONCLUSIONS The results of this study suggest that NAC administration alters resting CBF in MS patients, and this is associated with qualitative improvements in cognition and attention. Given these findings, large scale efficacy studies will be of value to determine the potential clinical impact of NAC over the course of illness in patients with MS, as well as the most effective dosages and differential effects across subpopulations.
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Affiliation(s)
- Shiva Shahrampour
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Justin Heholt
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Andrew Wang
- Charles E. Schmidt College of Medicine, Marcus Institute of Integrative Health at FAU Medicine, Florida Atlantic University, Boca Raton, FL USA
| | - Faezeh Vedaei
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Feroze B. Mohamed
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Mahdi Alizadeh
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Ze Wang
- Department of Radiology, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - George Zabrecky
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Nancy Wintering
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Anthony J. Bazzan
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Thomas P. Leist
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Daniel A. Monti
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Andrew B. Newberg
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
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43
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Alterations in functional connectivity are associated with white matter lesions and information processing efficiency in multiple sclerosis. Brain Imaging Behav 2021; 15:375-388. [PMID: 32114647 DOI: 10.1007/s11682-020-00264-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Functional connectivity (FC) is typically altered in individuals with Multiple Sclerosis (MS). However, in relapsing-remitting multiple sclerosis (RRMS) patients, the relationship between brain FC, tissue integrity and cognitive impairment is still unclear as contradictory findings have been documented. In this exploratory study we compared both the whole brain connectome and resting state networks (RSNs) FC of twenty-one RRMS and seventeen healthy controls (HCs), using combined network based statistics and independent component analyses. The total white matter (WM) lesion volume and information processing efficiency were also correlated with FC in the RRMS group. Both whole brain connectome and individual RSNs FC were diminished in patients with RRMS compared to HC. Additionally, the reduction in FC was found to be a function of the total WM lesion volume, with greatest impact in those harboring the largest lesion volume. Finally, a positive correlation between FC and information processing efficiency was observed in RRMS. This complimentary whole brain and RSNs FC approach can contribute to clarify literature inconsistencies regarding FC alterations and provide new insights on the white matter structural damage in explaining functional abnormalities in RRMS.
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44
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Schoonheim MM, Pinter D, Prouskas SE, Broeders TA, Pirpamer L, Khalil M, Ropele S, Uitdehaag BM, Barkhof F, Enzinger C, Geurts JJ. Disability in multiple sclerosis is related to thalamic connectivity and cortical network atrophy. Mult Scler 2021; 28:61-70. [PMID: 33870779 DOI: 10.1177/13524585211008743] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
BACKGROUND Thalamic atrophy is proposed to be a major predictor of disability progression in multiple sclerosis (MS), while thalamic function remains understudied. OBJECTIVES To study how thalamic functional connectivity (FC) is related to disability and thalamic or cortical network atrophy in two large MS cohorts. METHODS Structural and resting-state functional magnetic resonance imaging (fMRI) was obtained in 673 subjects from Amsterdam (MS: N = 332, healthy controls (HC): N = 96) and Graz (MS: N = 180, HC: N = 65) with comparable protocols, including disability measurements in MS (Expanded Disability Status Scale, EDSS). Atrophy was measured for the thalamus and seven well-recognized resting-state networks. Static and dynamic thalamic FC with these networks was correlated with disability. Significant correlates were included in a backward multivariate regression model. RESULTS Disability was most strongly related (adjusted R2 = 0.57, p < 0.001) to higher age, a progressive phenotype, thalamic atrophy and increased static thalamic FC with the sensorimotor network (SMN). Static thalamus-SMN FC was significantly higher in patients with high disability (EDSS ⩾ 4) and related to network atrophy but not thalamic atrophy or lesion volumes. CONCLUSION The severity of disability in MS was related to increased static thalamic FC with the SMN. Thalamic FC changes were only related to cortical network atrophy, but not to thalamic atrophy.
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Affiliation(s)
- Menno M Schoonheim
- Department of Anatomy and Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | - Daniela Pinter
- Department of Neurology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Stefanos E Prouskas
- Department of Anatomy and Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | - Tommy Aa Broeders
- Department of Anatomy and Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | - Lukas Pirpamer
- Department of Neurology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Michael Khalil
- Department of Neurology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Bernard Mj Uitdehaag
- Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands/Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Christian Enzinger
- Department of Neurology and Department of Radiology, Division of Neuroradiology, Vascular and Inverventional Radiology, Medical University of Graz, Graz, Austria
| | - Jeroen Jg Geurts
- Department of Anatomy and Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
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45
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Jouzizadeh M, Ghaderi AH, Cheraghmakani H, Baghbanian SM, Khanbabaie R. Resting-State Brain Network Deficits in Multiple Sclerosis Participants: Evidence from Electroencephalography and Graph Theoretical Analysis. Brain Connect 2021; 11:359-367. [PMID: 33780635 DOI: 10.1089/brain.2020.0857] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Multiple sclerosis (MS) is a chronic inflammatory disease leading to demyelination and axonal loss in the central nervous system that causes focal lesions of gray and white matter. However, the functional impairments of brain networks in this disease are still unspecified and need to be clearer. Materials and Methods: In the present study, we investigate the resting-state brain network impairments for MS participants in comparison to a normal group using electroencephalography (EEG) and graph theoretical analysis with a source localization method. Thirty-four age- and gender-matched participants from each MS group and normal group participated in this study. We recorded 5 min of EEG in the resting-state eyes open condition for each participant. One min (15 equal 4-sec artifact-free segments) of the EEG signals were selected for each participant, and the Low-Resolution Electromagnetic Tomography software was employed to calculate the functional connectivity among whole cortical regions in six frequency bands (delta, theta, alpha, beta1, beta2, and beta3). Graph theoretical analysis was used to calculate the clustering coefficient (CL), betweenness centrality (BC), shortest path length (SPL), and small-world propensity (SWP) for weighted connectivity matrices. Nonparametric permutation tests were utilized to compare these measures between groups. Results: Significant differences between the MS group and the normal group in the average of BC and SWP were found in the alpha band. The significant differences in the BC were spread over all lobes. Conclusion: These results suggest that the resting-state brain network for the MS group is disrupted in local and global scales, and EEG has the capability of revealing these impairments.
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Affiliation(s)
- Mojtaba Jouzizadeh
- Department of Physics, Babol Noshirvani University of Technology, Babol, Iran
| | - Amir Hossein Ghaderi
- Department of Psychology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Hamed Cheraghmakani
- Department of Neurology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | | | - Reza Khanbabaie
- Department of Physics, Babol Noshirvani University of Technology, Babol, Iran.,Department of Physics, I.K. Barber School of Arts and Sciences, University of British Columbia, Kelowna, British Columbia, Canada
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46
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Aloizou AM, Pateraki G, Anargyros K, Siokas V, Bakirtzis C, Liampas I, Nousia A, Nasios G, Sgantzos M, Peristeri E, Dardiotis E. Transcranial magnetic stimulation (TMS) and repetitive TMS in multiple sclerosis. Rev Neurosci 2021; 32:723-736. [PMID: 33641274 DOI: 10.1515/revneuro-2020-0140] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 02/05/2021] [Indexed: 01/02/2023]
Abstract
Multiple sclerosis (MS) is the most well-known autoimmune disorder of the central nervous system, and constitutes a major cause of disability, especially in young individuals. A wide array of pharmacological treatments is available, but they have often been proven to be ineffective in ameliorating disease symptomatology or slowing disease progress. As such, non-invasive and non-pharmacological techniques have been gaining more ground. Transcranial magnetic stimulation (TMS) utilizes the electric field generated by a magnetic coil to stimulate neurons and has been applied, usually paired with electroencephalography, to study the underlying pathophysiology of MS, and in repetitive trains, in the form of repetitive transcranial magnetic stimulation (rTMS), to induce long-lasting changes in neuronal circuits. In this review, we present the available literature on the application of TMS and rTMS in the context of MS, with an emphasis on its therapeutic potential on various clinical aspects, while also naming the ongoing trials, whose results are anticipated in the future.
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Affiliation(s)
- Athina-Maria Aloizou
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Georgia Pateraki
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Konstantinos Anargyros
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Vasileios Siokas
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Christos Bakirtzis
- B' Department of Neurology, AHEPA University Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Ioannis Liampas
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Anastasia Nousia
- Department of Speech and Language Therapy, University of Ioannina, Ioannina, Greece
| | - Grigorios Nasios
- Department of Speech and Language Therapy, University of Ioannina, Ioannina, Greece
| | - Markos Sgantzos
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Eleni Peristeri
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
| | - Efthimios Dardiotis
- Department of Neurology,Laboratory of Neurogenetics, University of Thessaly, University Hospital of Larissa, Biopolis, Mezourlo Hill, 41100Larissa, Greece
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Bagnato F, Gauthier SA, Laule C, Moore GRW, Bove R, Cai Z, Cohen-Adad J, Harrison DM, Klawiter EC, Morrow SA, Öz G, Rooney WD, Smith SA, Calabresi PA, Henry RG, Oh J, Ontaneda D, Pelletier D, Reich DS, Shinohara RT, Sicotte NL. Imaging Mechanisms of Disease Progression in Multiple Sclerosis: Beyond Brain Atrophy. J Neuroimaging 2021; 30:251-266. [PMID: 32418324 DOI: 10.1111/jon.12700] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 02/04/2020] [Accepted: 02/18/2020] [Indexed: 12/11/2022] Open
Abstract
Clinicians involved with different aspects of the care of persons with multiple sclerosis (MS) and scientists with expertise on clinical and imaging techniques convened in Dallas, TX, USA on February 27, 2019 at a North American Imaging in Multiple Sclerosis Cooperative workshop meeting. The aim of the workshop was to discuss cardinal pathobiological mechanisms implicated in the progression of MS and novel imaging techniques, beyond brain atrophy, to unravel these pathologies. Indeed, although brain volume assessment demonstrates changes linked to disease progression, identifying the biological mechanisms leading up to that volume loss are key for understanding disease mechanisms. To this end, the workshop focused on the application of advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging techniques to assess and measure disease progression in both the brain and the spinal cord. Clinical translation of quantitative MRI was recognized as of vital importance, although the need to maintain a relatively short acquisition time mandated by most radiology departments remains the major obstacle toward this effort. Regarding PET, the panel agreed upon its utility to identify ongoing pathological processes. However, due to costs, required expertise, and the use of ionizing radiation, PET was not considered to be a viable option for ongoing care of persons with MS. Collaborative efforts fostering robust study designs and imaging technique standardization across scanners and centers are needed to unravel disease mechanisms leading to progression and discovering medications halting neurodegeneration and/or promoting repair.
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Affiliation(s)
- Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Susan A Gauthier
- Judith Jaffe Multiple Sclerosis Center, Department of Neurology, Feil Family Brain and Mind Institute, and Department of Radiology, Weill Cornell Medicine, New York, NY
| | - Cornelia Laule
- Department of Radiology, Pathology, and Laboratory Medicine, Department of Physics and Astronomy, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - George R Wayne Moore
- Department of Pathology and Laboratory Medicine, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - Riley Bove
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA
| | - Zhengxin Cai
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, CT
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal and Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada
| | - Daniel M Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD
| | - Eric C Klawiter
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Sarah A Morrow
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
| | - Gülin Öz
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - William D Rooney
- Advanced Imaging Research Center, Departments of Biomedical Engineering, Neurology, and Behavioral Neuroscience, Oregon Health & Science University, Portland, OR
| | - Seth A Smith
- Radiology and Radiological Sciences and Vanderbilt University Imaging Institute, Vanderbilt University Medical Center, and Biomedical Engineering, Vanderbilt University, Nashville, TN
| | - Peter A Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Roland G Henry
- Departments of Neurology, Radiology and Biomedical Imaging, and the UC San Francisco & Berkeley Bioengineering Graduate Group, University of California San Francisco, San Francisco, CA
| | - Jiwon Oh
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD.,Division of Neurology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Daniel Pelletier
- Department of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA
| | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
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- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
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48
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Chiang FL, Feng M, Romero RS, Price L, Franklin CG, Deng S, Gray JP, Yu FF, Tantiwongkosi B, Huang SY, Fox PT. Disruption of the Atrophy-based Functional Network in Multiple Sclerosis Is Associated with Clinical Disability: Validation of a Meta-Analytic Model in Resting-State Functional MRI. Radiology 2021; 299:159-166. [PMID: 33529135 DOI: 10.1148/radiol.2021203414] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Background In multiple sclerosis (MS), gray matter (GM) atrophy exhibits a specific pattern, which correlates strongly with clinical disability. However, the mechanism of regional specificity in GM atrophy remains largely unknown. Recently, the network degeneration hypothesis (NDH) was quantitatively defined (using coordinate-based meta-analysis) as the atrophy-based functional network (AFN) model, which posits that localized GM atrophy in MS is mediated by functional networks. Purpose To test the NDH in MS in a data-driven manner using the AFN model to direct analyses in an independent test sample. Materials and Methods Model fit testing was conducted with structural equation modeling, which is based on the computation of semipartial correlations. Model verification was performed in coordinate-based data of healthy control participants from the BrainMap database (https://www.brainmap.org). Model validation was conducted in prospectively acquired resting-state functional MRI in participants with relapsing-remitting MS who were recruited between September 2018 and January 2019. Correlation analyses of model fit indices and volumetric measures with Expanded Disability Status Scale (EDSS) scores and disease duration were performed. Results Model verification of healthy control participants included 80 194 coordinates from 9035 experiments. Model verification in healthy control data resulted in excellent model fit (root mean square error of approximation, 0.037; 90% CI: 0.036, 0.039). Twenty participants (mean age, 36 years ± 9 [standard deviation]; 12 women) with relapsing-remitting MS were evaluated. Model validation in resting-state functional MRI in participants with MS resulted in deviation from optimal model fit (root mean square error of approximation, 0.071; 90% CI: 0.070, 0.072), which correlated with EDSS scores (r = 0.68; P = .002). Conclusion The atrophy-based functional network model predicts functional network disruption in multiple sclerosis (MS), thereby supporting the network degeneration hypothesis. On resting-state functional MRI scans, reduced functional network integrity in participants with MS had a strong positive correlation with clinical disability. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Florence L Chiang
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Max Feng
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Rebecca S Romero
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Larry Price
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Crystal G Franklin
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Shengwen Deng
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Jodie P Gray
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Fang F Yu
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Bundhit Tantiwongkosi
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Susie Y Huang
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
| | - Peter T Fox
- From the Department of Radiology (F.L.C., B.T., P.T.F.), Research Imaging Institute (F.L.C., C.G.F., S.D., J.P.G., P.T.F.), Joe R. and Teresa Lozano Long School of Medicine (F.L.C., M.F., R.S.R., B.T., P.T.F.), and Department of Neurology (R.S.R., P.T.F.), The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, MC7800, San Antonio, TX 78229-3900; Division of Methodology, Measurement and Statistical Analysis, Texas State University, San Marcos, Tex (L.P.); Department of Radiology, Division of Neuroradiology, The University of Texas Southwestern Medical Center, Dallas, Tex (F.F.Y.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Mass (S.Y.H.); Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Boston, Mass (S.Y.H.); and South Texas Veteran Health Care System, Research Service, San Antonio, Tex (P.T.F.)
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49
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Veréb D, Tóth E, Bozsik B, Király A, Szabó N, Kincses B, Kocsis K, Faragó P, László V, Bencsik K, Klivényi P, Kincses ZT. Altered brain network function during attention-modulated visual processing in multiple sclerosis. Mult Scler 2020; 27:1341-1349. [PMID: 33016839 DOI: 10.1177/1352458520958360] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce. OBJECTIVE To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance. METHODS A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery. RESULTS TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032, p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48, p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012, p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53, p < 0.02, R = 0.46, p < 0.049). CONCLUSION Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.
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Affiliation(s)
- Dániel Veréb
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Eszter Tóth
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bence Bozsik
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - András Király
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Nikoletta Szabó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bálint Kincses
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztián Kocsis
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Péter Faragó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Vécsei László
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztina Bencsik
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Péter Klivényi
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsigmond Tamás Kincses
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary/Neuroimaging Research Group, Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
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50
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Lin SJ, Kolind S, Liu A, McMullen K, Vavasour I, Wang ZJ, Traboulsee A, McKeown MJ. Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis. Front Neurol 2020; 11:407. [PMID: 32581993 PMCID: PMC7287147 DOI: 10.3389/fneur.2020.00407] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 04/20/2020] [Indexed: 01/04/2023] Open
Abstract
Although functional connectivity has been extensively studied in MS, robust estimates of both stationary (static connectivity at the time) and dynamic (connectivity variation across time) functional connectivity has not been commonly evaluated and neither has its association to cognition. In this study, we focused on interhemispheric connections as previous research has shown links between anatomical homologous connections and cognition. We examined functional interhemispheric connectivity (IC) in MS during resting-state functional MRI using both stationary and dynamic strategies and related connectivity measures to processing speed performance. Twenty-five patients with relapsing-remitting MS and 41 controls were recruited. Stationary functional IC was assessed between homologous Regions of Interest (ROIs) using correlation. For dynamic IC, a sliding window approach was used to quantify changes between homologous ROIs across time. We related IC measures to cognitive performance with correlation and regression. Compared to control subjects, MS demonstrated increased IC across homologous regions, which accurately predicted performance on the symbol digit modalities test (SDMT) (R 2 = 0.96) and paced auditory serial addition test (PASAT) (R 2 = 0.59). Dynamic measures were not different between the 2 groups, but dynamic IC was related to PASAT scores. The associations between stationary/dynamic connectivity and cognitive tests demonstrated that different aspects of functional IC were associated with cognitive processes. Processing speed measured in SDMT was associated with static interhemispheric connections and better PASAT performance, which requires working memory, sustain attention, and processing speed, was more related to rigid IC, underlining the neurophysiological mechanism of cognition in MS.
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Affiliation(s)
- Sue-Jin Lin
- Graduate Program in Neuroscience, University of British Columbia, Vancouver, BC, Canada
| | - Shannon Kolind
- Division of Neurology, Department of Medicine, UBC Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Aiping Liu
- Department of Electrical and Computer Engineering Program, University of British Columbia, Vancouver, BC, Canada
| | - Katrina McMullen
- Division of Neurology, Department of Medicine, UBC Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Irene Vavasour
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Z Jane Wang
- Department of Electrical and Computer Engineering Program, University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Division of Neurology, Department of Medicine, UBC Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Martin J McKeown
- Graduate Program in Neuroscience, University of British Columbia, Vancouver, BC, Canada.,Division of Neurology, Department of Medicine, UBC Hospital, University of British Columbia, Vancouver, BC, Canada
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