-
Something wrong with this record ?
Single-subject structural cortical networks in clinically isolated syndrome
S. Collorone, F. Prados, MH. Hagens, C. Tur, B. Kanber, CH. Sudre, C. Lukas, C. Gasperini, C. Oreja-Guevara, M. Andelova, O. Ciccarelli, MP. Wattjes, S. Ourselin, DR. Altmann, BM. Tijms, F. Barkhof, AT. Toosy, MAGNIMS Study Group
Language English Country Great Britain
Document type Journal Article, Multicenter Study, Research Support, Non-U.S. Gov't
- MeSH
- Demyelinating Diseases * diagnostic imaging MeSH
- Cognition MeSH
- Humans MeSH
- Magnetic Resonance Imaging MeSH
- Brain diagnostic imaging MeSH
- Neural Pathways diagnostic imaging MeSH
- Prospective Studies MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas, and they present the advantage of being extracted from previously acquired clinical magnetic resonance imaging (MRI) scans. SCNs have shown pathophysiological changes in many brain disorders, including multiple sclerosis. OBJECTIVE: To investigate alterations of SCNs at the individual level in patients with clinically isolated syndrome (CIS), thereby assessing their clinical relevance. METHODS: We analyzed baseline data collected in a prospective multicenter (MAGNIMS) study. CIS patients (n = 60) and healthy controls (n = 38) underwent high-resolution 3T MRI. Measures of disability and cognitive processing were obtained for patients. Single-subject SCNs were extracted from brain 3D-T1 weighted sequences; global and local network parameters were computed. RESULTS: Compared to healthy controls, CIS patients showed altered small-world topology, an efficient network organization combining dense local clustering with relatively few long-distance connections. These disruptions were worse for patients with higher lesion load and worse cognitive processing speed. Alterations of centrality measures and clustering of connections were observed in specific cortical areas in CIS patients when compared with healthy controls. CONCLUSION: Our study indicates that SCNs can be used to demonstrate clinically relevant alterations of connectivity in CIS.
Department of Diagnostic and Interventional Neuroradiology Hannover Medical School Hannover Germany
Department of Neurosciences San Camillo Forlanini Hospital Rome Italy
London School of Hygiene and Tropical Medicine London UK
UCL Medical Physics and Biomedical Engineering University College London London UK
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc21026540
- 003
- CZ-PrNML
- 005
- 20211026132822.0
- 007
- ta
- 008
- 211013s2020 xxk f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1177/1352458519865739 $2 doi
- 035 __
- $a (PubMed)31339446
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxk
- 100 1_
- $a Collorone, Sara $u NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- 245 10
- $a Single-subject structural cortical networks in clinically isolated syndrome / $c S. Collorone, F. Prados, MH. Hagens, C. Tur, B. Kanber, CH. Sudre, C. Lukas, C. Gasperini, C. Oreja-Guevara, M. Andelova, O. Ciccarelli, MP. Wattjes, S. Ourselin, DR. Altmann, BM. Tijms, F. Barkhof, AT. Toosy, MAGNIMS Study Group
- 520 9_
- $a BACKGROUND: Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas, and they present the advantage of being extracted from previously acquired clinical magnetic resonance imaging (MRI) scans. SCNs have shown pathophysiological changes in many brain disorders, including multiple sclerosis. OBJECTIVE: To investigate alterations of SCNs at the individual level in patients with clinically isolated syndrome (CIS), thereby assessing their clinical relevance. METHODS: We analyzed baseline data collected in a prospective multicenter (MAGNIMS) study. CIS patients (n = 60) and healthy controls (n = 38) underwent high-resolution 3T MRI. Measures of disability and cognitive processing were obtained for patients. Single-subject SCNs were extracted from brain 3D-T1 weighted sequences; global and local network parameters were computed. RESULTS: Compared to healthy controls, CIS patients showed altered small-world topology, an efficient network organization combining dense local clustering with relatively few long-distance connections. These disruptions were worse for patients with higher lesion load and worse cognitive processing speed. Alterations of centrality measures and clustering of connections were observed in specific cortical areas in CIS patients when compared with healthy controls. CONCLUSION: Our study indicates that SCNs can be used to demonstrate clinically relevant alterations of connectivity in CIS.
- 650 _2
- $a mozek $x diagnostické zobrazování $7 D001921
- 650 _2
- $a kognice $7 D003071
- 650 12
- $a demyelinizační nemoci $x diagnostické zobrazování $7 D003711
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a magnetická rezonanční tomografie $7 D008279
- 650 _2
- $a nervové dráhy $x diagnostické zobrazování $7 D009434
- 650 _2
- $a prospektivní studie $7 D011446
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a multicentrická studie $7 D016448
- 655 _2
- $a práce podpořená grantem $7 D013485
- 700 1_
- $a Prados, Ferran $u NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK/Centre for Medical Image Computing (CMIC), UCL Medical Physics and Biomedical Engineering, University College London, London, UK/Universitat Oberta de Catalunya, Barcelona, Spain
- 700 1_
- $a Hagens, Marloes Hj $u MS Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- 700 1_
- $a Tur, Carmen $u NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- 700 1_
- $a Kanber, Baris $u Centre for Medical Image Computing (CMIC), UCL Medical Physics and Biomedical Engineering, University College London, London, UK
- 700 1_
- $a Sudre, Carole H $u UCL Medical Physics and Biomedical Engineering, University College London, London, UK
- 700 1_
- $a Lukas, Carsten $u Department of Diagnostic and Interventional Radiology and Nuclear Medicine, St. Josef Hospital, Ruhr-University Bochum, Bochum, Germany
- 700 1_
- $a Gasperini, Claudio $u Department of Neurosciences, San Camillo-Forlanini Hospital, Rome, Italy
- 700 1_
- $a Oreja-Guevara, Celia $u Department of Neurology, Hospital Clinico San Carlos, Instituto de Investigacion Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
- 700 1_
- $a Andelova, Micaela $u Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland/Charles University and General University Hospital, Prague, Czech Republic
- 700 1_
- $a Ciccarelli, Olga $u NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK/NIHR University College London Hospitals Biomedical Research Centre, London, UK
- 700 1_
- $a Wattjes, Mike P $u MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
- 700 1_
- $a Ourselin, Sebastian $u UCL Medical Physics and Biomedical Engineering, University College London, London, UK/School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- 700 1_
- $a Altmann, Daniel R $u London School of Hygiene & Tropical Medicine, London, UK
- 700 1_
- $a Tijms, Betty M $u Alzheimer Center Amsterdam, Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- 700 1_
- $a Barkhof, Frederik $u Centre for Medical Image Computing (CMIC), UCL Medical Physics and Biomedical Engineering, University College London, London, UK/NIHR University College London Hospitals Biomedical Research Centre, London, UK/Alzheimer Center Amsterdam, Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands/UCL Institute of Healthcare Engineering and UCL Queen Square Institute of Neurology, University College London, London, UK
- 700 1_
- $a Toosy, Ahmed T
- 710 2_
- $a MAGNIMS Study Group
- 773 0_
- $w MED00006389 $t Multiple sclerosis (Houndmills, Basingstoke, England) $x 1477-0970 $g Roč. 26, č. 11 (2020), s. 1392-1401
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/31339446 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20211013 $b ABA008
- 991 __
- $a 20211026132828 $b ABA008
- 999 __
- $a ok $b bmc $g 1715307 $s 1147047
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2020 $b 26 $c 11 $d 1392-1401 $e 20190724 $i 1477-0970 $m Multiple sclerosis $n Mult Scler $x MED00006389
- LZP __
- $a Pubmed-20211013