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Fleischer V, Gonzalez-Escamilla G, Pareto D, Rovira A, Sastre-Garriga J, Sowa P, Høgestøl EA, Harbo HF, Bellenberg B, Lukas C, Ruggieri S, Gasperini C, Uher T, Vaneckova M, Bittner S, Othman AE, Collorone S, Toosy AT, Meuth SG, Zipp F, Barkhof F, Ciccarelli O, Groppa S. Prognostic value of single-subject grey matter networks in early multiple sclerosis. Brain 2024; 147:135-146. [PMID: 37642541 PMCID: PMC10766234 DOI: 10.1093/brain/awad288] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/17/2023] [Accepted: 08/02/2023] [Indexed: 08/31/2023] Open
Abstract
The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.
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Affiliation(s)
- Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology/Neuroimmunology, Multiple Sclerosis Centre of Catalonia, Hospital Universitari Vall d'Hebron, 08035 Barcelona, Spain
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Einar A Høgestøl
- Institute of Clinical Medicine, University of Oslo, NO-0316 Oslo, Norway
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Hanne F Harbo
- Institute of Clinical Medicine, University of Oslo, NO-0316 Oslo, Norway
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Barbara Bellenberg
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Serena Ruggieri
- Department of Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Claudio Gasperini
- Department of Neurosciences, San Camillo-Forlanini Hospital, 00152 Rome, Italy
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, 121 08 Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, 121 08 Prague, Czech Republic
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Ahmed E Othman
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sara Collorone
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Ahmed T Toosy
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225 Düsseldorf, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Frederik Barkhof
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, 1100 DD Amsterdam, Netherlands
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
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