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Kenyon KH, Strik M, Noffs G, Morgan A, Kolbe S, Harding IH, Vogel AP, Boonstra FMC, van der Walt A. Volumetric and diffusion MRI abnormalities associated with dysarthria in multiple sclerosis. Brain Commun 2024; 6:fcae177. [PMID: 38846538 PMCID: PMC11154149 DOI: 10.1093/braincomms/fcae177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 04/16/2024] [Accepted: 05/21/2024] [Indexed: 06/09/2024] Open
Abstract
Up to half of all people with multiple sclerosis experience communication difficulties due to dysarthria, a disorder that impacts the motor aspects of speech production. Dysarthria in multiple sclerosis is linked to cerebellar dysfunction, disease severity and lesion load, but the neuroanatomical substrates of these symptoms remain unclear. In this study, 52 participants with multiple sclerosis and 14 age- and sex-matched healthy controls underwent structural and diffusion MRI, clinical assessment of disease severity and cerebellar dysfunction and a battery of motor speech tasks. Assessments of regional brain volume and white matter integrity, and their relationships with clinical and speech measures, were undertaken. White matter tracts of interest included the interhemispheric sensorimotor tract, cerebello-thalamo-cortical tract and arcuate fasciculus, based on their roles in motor and speech behaviours. Volumetric analyses were targeted to Broca's area, Wernicke's area, the corpus callosum, thalamus and cerebellum. Our results indicated that multiple sclerosis participants scored worse on all motor speech tasks. Fixel-based diffusion MRI analyses showed significant evidence of white matter tract atrophy in each tract of interest. Correlational analyses further indicated that higher speech naturalness-a perceptual measure of dysarthria-and lower reading rate were associated with axonal damage in the interhemispheric sensorimotor tract and left arcuate fasciculus in people with multiple sclerosis. Axonal damage in all tracts of interest also correlated with clinical scales sensitive to cerebellar dysfunction. Participants with multiple sclerosis had lower volumes of the thalamus and corpus callosum compared with controls, although no brain volumetrics correlated with measures of dysarthria. These findings indicate that axonal damage, particularly when measured using diffusion metrics, underpin dysarthria in multiple sclerosis.
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Affiliation(s)
- Katherine H Kenyon
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
| | - Myrte Strik
- Spinoza Centre for Neuroimaging, Netherlands Institute for Neuroscience, Royal Academy for Arts and Sciences, KNAW, Amsterdam 1105 BK, The Netherlands
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC 3052, Australia
| | - Gustavo Noffs
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
- Department of Neurology, Royal Melbourne Hospital, Parkville, VIC 3052, Australia
- Redenlab Inc, Melbourne, VIC 3000, Australia
| | - Angela Morgan
- Murdoch Children’s Research Institute, Genomic Medicine, Speech and Language Group, Parkville 3052, Australia
- Department of Speech Pathology and Audiology, University of Melbourne, Parkville 3052, Australia
| | - Scott Kolbe
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Ian H Harding
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Adam P Vogel
- Centre for Neuroscience of Speech, University of Melbourne, Parkville, VIC 3052, Australia
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC 3052, Australia
- Redenlab Inc, Melbourne, VIC 3000, Australia
- Division of Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
- Center for Neurology, University Hospital Tübingen, Tübingen 72076, Germany
- The Bionics Institute, East Melbourne, VIC 3002, Australia
| | - Frederique M C Boonstra
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Anneke van der Walt
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC 3004, Australia
- Spinoza Centre for Neuroimaging, Netherlands Institute for Neuroscience, Royal Academy for Arts and Sciences, KNAW, Amsterdam 1105 BK, The Netherlands
- The Bionics Institute, East Melbourne, VIC 3002, Australia
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Gharaylou Z, Shahbodaghy F, Kolivand P, Kolivand M, Azizzadeh F, Rostampour M. Reduced White Matter Fiber Density in Patients with Multiple Sclerosis. Brain Connect 2024; 14:172-181. [PMID: 38308478 DOI: 10.1089/brain.2023.0068] [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: 02/04/2024] Open
Abstract
Introduction: Improved understanding of multiple sclerosis (MS) symptomatology, disease mechanisms, and clinical effectiveness can be achieved by investigating microstructural damage. The aim was to gain deeper insights into changes in white matter (WM) tracts in MS patients. Methods: Diffusion magnetic resonance imaging-based tractography was utilized to segment WM tracts into regions of interest for further quantitative analysis. However, tractography is susceptible to false-positive findings, reducing its specificity and clinical feasibility. To address these limitations, the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) technique was used. COMMIT was used to derive measures of intracellular compartment (IC) and isotropic compartments from multishell diffusion data of 40 healthy controls (HCs) and 40 MS patients. Results: The analysis revealed a widespread pattern of significantly decreased IC values in MS patients compared with HCs across 61,581 voxels (pFWE < 0.05, threshold-free cluster enhancement [TFCE] corrected). Similar WM structures studied using the fractional anisotropy (FA) value also showed a reduction in FA among MS patients compared with HCs across 57,304 voxels (pFWE < 0.05, TFCE corrected). Out of the 61,581 voxels exhibiting lower IC, a substantial overlap of 47,251 voxels (76.72%) also demonstrated lower FA in MS patients compared with HCs. Discussion: The data suggested that lower IC values contributed to the explanation of FA reductions. In addition, IC showed promising potential for evaluating microstructural abnormalities in WM in MS, potentially being more sensitive than the frequently used FA value.
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Affiliation(s)
| | - Fatemeh Shahbodaghy
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
| | - Pirhossein Kolivand
- Department of Health Economics, School of Medicine, Shahed University, Tehran, Iran
| | - Maryam Kolivand
- Medical School, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Azizzadeh
- Medical School, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Masoumeh Rostampour
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
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3
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Gloor M, Andelova M, Gaetano L, Papadopoulou A, Burguet Villena F, Sprenger T, Radue EW, Kappos L, Bieri O, Garcia M. Longitudinal analysis of new multiple sclerosis lesions with magnetization transfer and diffusion tensor imaging. Eur Radiol 2024; 34:1680-1691. [PMID: 37658894 PMCID: PMC10873225 DOI: 10.1007/s00330-023-10173-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/02/2023] [Accepted: 07/12/2023] [Indexed: 09/05/2023]
Abstract
OBJECTIVE The potential of magnetization transfer imaging (MTI) and diffusion tensor imaging (DTI) for the detection and evolution of new multiple sclerosis (MS) lesions was analyzed. METHODS Nineteen patients with MS obtained conventional MRI, MTI, and DTI examinations bimonthly for 12 months and again after 24 months at 1.5 T MRI. MTI was acquired with balanced steady-state free precession (bSSFP) in 10 min (1.3 mm3 isotropic resolution) yielding both magnetization transfer ratio (MTR) and quantitative magnetization transfer (qMT) parameters (pool size ratio (F), exchange rate (kf), and relaxation times (T1/T2)). DTI provided fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). RESULTS At the time of their appearance on MRI, the 21 newly detected MS lesions showed significantly reduced MTR/F/kf and prolonged T1/T2 parameters, as well as significantly reduced FA and increased AD/MD/RD. Significant differences were already observed for MTR 4 months and for qMT parameters 2 months prior to lesions' detection on MRI. DTI did not show any significant pre-lesional differences. Slightly reversed trends were observed for most lesions up to 8 months after their detection for qMT and less pronounced for MTR and three diffusion parameters, while appearing unchanged on MRI. CONCLUSIONS MTI provides more information than DTI in MS lesions and detects tissue changes 2 to 4 months prior to their appearance on MRI. After lesions' detection, qMT parameter changes promise to be more sensitive than MTR for the lesions' evolutional assessment. Overall, bSSFP-based MTI adumbrates to be more sensitive than MRI and DTI for the early detection and follow-up assessment of MS lesions. CLINICAL RELEVANCE STATEMENT When additionally acquired in routine MRI, fast bSSFP-based MTI can complement the MRI/DTI longitudinal lesion assessment by detecting MS lesions 2-4 months earlier than with MRI, which could implicate earlier clinical decisions and better follow-up/treatment assessment in MS patients. KEY POINTS • Magnetization transfer imaging provides more information than DTI in multiple sclerosis lesions and can detect tissue changes 2 to 4 months prior to their appearance on MRI. • After lesions' detection, quantitative magnetization transfer changes are more pronounced than magnetization transfer ratio changes and therefore promise to be more sensitive for the lesions' evolutional assessment. • Balanced steady-state free precession-based magnetization transfer imaging is more sensitive than MRI and DTI for the early detection and follow-up assessment of multiple sclerosis lesions.
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Affiliation(s)
- Monika Gloor
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Michaela Andelova
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Laura Gaetano
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC) AG, Basel, Switzerland
- Novartis Institutes for BioMedical Research Basel, Basel, Switzerland
| | - Athina Papadopoulou
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Federico Burguet Villena
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Till Sprenger
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- University Hospital Zürich, Zurich, Switzerland
| | | | - Ludwig Kappos
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Meritxell Garcia
- Division of Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland.
- Department of Neuroradiology, University Hospital Zürich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
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Ravano V, Piredda GF, Krasensky J, Andelova M, Uher T, Srpova B, Havrdova EK, Vodehnalova K, Horakova D, Nytrova P, Disselhorst JA, Hilbert T, Maréchal B, Thiran JP, Kober T, Richiardi J, Vaneckova M. Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis. J Neurol 2024; 271:631-641. [PMID: 37819462 PMCID: PMC10827809 DOI: 10.1007/s00415-023-12023-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/21/2023] [Accepted: 09/24/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVES Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas. METHODS We quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years. RESULTS In early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor. CONCLUSIONS We showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging.
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Affiliation(s)
- Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karolina Vodehnalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Petra Nytrova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jonathan A Disselhorst
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
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5
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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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Andelova M, Vodehnalova K, Krasensky J, Hardubejova E, Hrnciarova T, Srpova B, Uher T, Menkyova I, Stastna D, Friedova L, Motyl J, Lizrova Preiningerova J, Kubala Havrdova E, Maréchal B, Fartaria MJ, Kober T, Horakova D, Vaneckova M. Brainstem lesions are associated with diffuse spinal cord involvement in early multiple sclerosis. BMC Neurol 2022; 22:270. [PMID: 35854235 PMCID: PMC9297663 DOI: 10.1186/s12883-022-02778-z] [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: 05/27/2021] [Accepted: 06/29/2022] [Indexed: 11/13/2022] Open
Abstract
Background Early infratentorial and focal spinal cord lesions on magnetic resonance imaging (MRI) are associated with a higher risk of long-term disability in patients with multiple sclerosis (MS). The role of diffuse spinal cord lesions remains less understood. The purpose of this study was to evaluate focal and especially diffuse spinal cord lesions in patients with early relapsing-remitting MS and their association with intracranial lesion topography, global and regional brain volume, and spinal cord volume. Methods We investigated 58 MS patients with short disease duration (< 5 years) from a large academic MS center and 58 healthy controls matched for age and sex. Brain, spinal cord, and intracranial lesion volumes were compared among patients with- and without diffuse spinal cord lesions and controls. Binary logistic regression models were used to analyse the association between the volume and topology of intracranial lesions and the presence of focal and diffuse spinal cord lesions. Results We found spinal cord involvement in 75% of the patients (43/58), including diffuse changes in 41.4% (24/58). Patients with diffuse spinal cord changes exhibited higher volumes of brainstem lesion volume (p = 0.008). The presence of at least one brainstem lesion was associated with a higher probability of the presence of diffuse spinal cord lesions (odds ratio 47.1; 95% confidence interval 6.9–321.6 p < 0.001) as opposed to focal spinal cord lesions (odds ratio 0.22; p = 0.320). Patients with diffuse spinal cord lesions had a lower thalamus volume compared to patients without diffuse spinal cord lesions (p = 0.007) or healthy controls (p = 0.002). Conclusions Diffuse spinal cord lesions are associated with the presence of brainstem lesions and with a lower volume of the thalamus. This association was not found in patients with focal spinal cord lesions. If confirmed, thalamic atrophy in patients with diffuse lesions could increase our knowledge on the worse prognosis in patients with infratentorial and SC lesions. Supplementary Information The online version contains supplementary material available at 10.1186/s12883-022-02778-z.
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Affiliation(s)
- Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic.
| | - Karolina Vodehnalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eliska Hardubejova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tereza Hrnciarova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Ingrid Menkyova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic.,2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| | - Dominika Stastna
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Lucie Friedova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Jiri Motyl
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Jana Lizrova Preiningerova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, Praha 2, Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
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An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis. THE CEREBELLUM 2022:10.1007/s12311-022-01435-y. [PMID: 35761144 PMCID: PMC9244122 DOI: 10.1007/s12311-022-01435-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/15/2022] [Indexed: 12/03/2022]
Abstract
Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.
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8
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Vaneckova M, Piredda GF, Andelova M, Krasensky J, Uher T, Srpova B, Havrdova EK, Vodehnalova K, Horakova D, Hilbert T, Maréchal B, Fartaria MJ, Ravano V, Kober T. Periventricular gradient of T 1 tissue alterations in multiple sclerosis. Neuroimage Clin 2022; 34:103009. [PMID: 35561554 PMCID: PMC9112026 DOI: 10.1016/j.nicl.2022.103009] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/24/2022] [Accepted: 04/12/2022] [Indexed: 01/12/2023]
Abstract
T1 relaxation times alterations were assessed based on a study-specific atlas. T1 alterations depend on distance from lateral ventricles (“periventricular gradient”). Gradient parameters correlate better with disability compared to conventional MRI.
Objective Pathology in multiple sclerosis is not homogenously distributed. Recently, it has been shown that structures adjacent to CSF are more severely affected. A gradient of brain tissue involvement was shown with more severe pathology in periventricular areas and in proximity to brain surfaces such as the subarachnoid spaces and ependyma, and hence termed the “surface–in” gradient. Here, we study whether (i) the surface-in gradient of periventricular tissue alteration measured by T1 relaxometry is already present in early multiple sclerosis patients, (ii) how it differs between early and progressive multiple sclerosis patients, and (iii) whether the gradient-derived metrics in normal-appearing white matter and lesions correlate better with physical disability than conventional MRI-based metrics. Methods Forty-seven patients with early multiple sclerosis, 52 with progressive multiple sclerosis, and 92 healthy controls were included in the study. Isotropic 3D T1 relaxometry maps were obtained using the Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes sequence at 3 T. After spatially normalizing the T1 maps into a study-specific common space, T1 inter-subject variability within the healthy cohort was modelled voxel-wise, yielding a normative T1 atlas. Individual comparisons of each multiple sclerosis patient against the atlas were performed by computing z-scores. Equidistant bands of voxels were defined around the ventricles in the supratentorial white matter; the z-scores in these bands were analysed and compared between the early and progressive multiple sclerosis cohorts. Correlations between both conventional and z-score-gradient-derived MRI metrics and the Expanded Disability Status Scale were assessed. Results Patients with early and progressive multiple sclerosis demonstrated a periventricular gradient of T1 relaxation time z-scores. In progressive multiple sclerosis, z-score-derived metrics reflecting the gradient of tissue abnormality in normal-appearing white matter were more strongly correlated with disability (maximal rho = 0.374) than the conventional lesion volume and count (maximal rho = 0.189 and 0.21 respectively). In early multiple sclerosis, the gradient of normal-appearing white matter volume with z-scores > 2 at baseline correlated with clinical disability assessed at two years follow-up. Conclusion Our results suggest that the surface-in white matter gradient of tissue alteration is detectable with T1 relaxometry and is already present at clinical disease onset. The periventricular gradients correlate with clinical disability. The periventricular gradient in normal-appearing white matter may thus qualify as a promising biomarker for monitoring of disease activity from an early stage in all phenotypes of multiple sclerosis.
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Affiliation(s)
- Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karolina Vodehnalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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9
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Zhang F, Daducci A, He Y, Schiavi S, Seguin C, Smith RE, Yeh CH, Zhao T, O'Donnell LJ. Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review. Neuroimage 2022; 249:118870. [PMID: 34979249 PMCID: PMC9257891 DOI: 10.1016/j.neuroimage.2021.118870] [Citation(s) in RCA: 102] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/03/2021] [Accepted: 12/31/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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10
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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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11
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Radetz A, Mladenova K, Ciolac D, Gonzalez-Escamilla G, Fleischer V, Ellwardt E, Krämer J, Bittner S, Meuth SG, Muthuraman M, Groppa S. Linking Microstructural Integrity and Motor Cortex Excitability in Multiple Sclerosis. Front Immunol 2021; 12:748357. [PMID: 34712236 PMCID: PMC8546169 DOI: 10.3389/fimmu.2021.748357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/23/2021] [Indexed: 11/15/2022] Open
Abstract
Motor skills are frequently impaired in multiple sclerosis (MS) patients following grey and white matter damage with cortical excitability abnormalities. We applied advanced diffusion imaging with 3T magnetic resonance tomography for neurite orientation dispersion and density imaging (NODDI), as well as diffusion tensor imaging (DTI) in 50 MS patients and 49 age-matched healthy controls to quantify microstructural integrity of the motor system. To assess excitability, we determined resting motor thresholds using non-invasive transcranial magnetic stimulation. As measures of cognitive-motor performance, we conducted neuropsychological assessments including the Nine-Hole Peg Test, Trail Making Test part A and B (TMT-A and TMT-B) and the Symbol Digit Modalities Test (SDMT). Patients were evaluated clinically including assessments with the Expanded Disability Status Scale. A hierarchical regression model revealed that lower neurite density index (NDI) in primary motor cortex, suggestive for axonal loss in the grey matter, predicted higher motor thresholds, i.e. reduced excitability in MS patients (p = .009, adjusted r² = 0.117). Furthermore, lower NDI was indicative of decreased cognitive-motor performance (p = .007, adjusted r² = .142 for TMT-A; p = .009, adjusted r² = .129 for TMT-B; p = .006, adjusted r² = .142 for SDMT). Motor WM tracts of patients were characterized by overlapping clusters of lowered NDI (p <.05, Cohen's d = 0.367) and DTI-based fractional anisotropy (FA) (p <.05, Cohen's d = 0.300), with NDI exclusively detecting a higher amount of abnormally appearing voxels. Further, orientation dispersion index of motor tracts was increased in patients compared to controls, suggesting a decreased fiber coherence (p <.05, Cohen's d = 0.232). This study establishes a link between microstructural characteristics and excitability of neural tissue, as well as cognitive-motor performance in multiple sclerosis. We further demonstrate that the NODDI parameters neurite density index and orientation dispersion index detect a larger amount of abnormally appearing voxels in patients compared to healthy controls, as opposed to the classical DTI parameter FA. Our work outlines the potential for microstructure imaging using advanced biophysical models to forecast excitability alterations in neuroinflammation.
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Affiliation(s)
- Angela Radetz
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Kalina Mladenova
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chişinău, Moldova
- Department of Neurology, Institute of Emergency Medicine, Chişinău, Moldova
| | - Gabriel Gonzalez-Escamilla
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Vinzenz Fleischer
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Erik Ellwardt
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Julia Krämer
- Department of Neurology, Institute of Translational Neurology, University Hospital Münster, Münster, Germany
| | - Stefan Bittner
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sven G. Meuth
- Department of Neurology, Institute of Translational Neurology, University Hospital Münster, Münster, Germany
- Department of Neurology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Muthuraman Muthuraman
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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12
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Deverdun J, Coget A, Ayrignac X, Carra-Dalliere C, Krainik A, Metzger A, Labauge P, Menjot de Champfleur N, Le Bars E. Cerebral Vasoreactivity as an Indirect MRI Marker of White Matter Tracts Alterations in Multiple Sclerosis. Brain Topogr 2021; 34:245-255. [PMID: 33484378 DOI: 10.1007/s10548-021-00819-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 01/06/2021] [Indexed: 02/02/2023]
Abstract
Patients with multiple sclerosis (MS) show a diffuse cerebral perfusion decrease, presumably related to multiple metabolism and vascular alterations. It is assumed that white matter fiber alterations cause a localized cerebral vasoreactivity (CVR) disruption through astrocytes metabolism alteration, leading to hypoperfusion. We proposed to (1) evaluate the CVR disruptions in MS, (2) in relation to white matter lesions and (3) compare CVR disruptions maps with standard imaging biomarkers. Thirty-five MS patients (10 progressive, 25 relapsing-remitting) and 22 controls underwent MRI with hypercapnic challenge, DTI imaging and neuropsychological assessment. Areas with disrupted CVR were assessed using a general linear model. Resulting maps were associated with clinical scores, compared between groups, and related to DTI metrics and white matter lesions. MS patients showed stronger disrupted CVR within supratentorial white matter, linking the left anterior insula to both the precentral gyrus and the right middle and superior frontal gyrus through the corpus callosum (P < 0.05, FWE corrected). Patient's verbal intellectual quotient was negatively associated with a pathway linking both hippocampi to the ispilateral prefrontal cortex (P < 0.05, FWE corrected). Disrupted CVR maps unrelated to DTI metrics and white matter lesions. We have demonstrated for the first time that white matter alterations can be indirectly identified through surrounding vessel alterations, and are related to clinical signs of MS. This offers a new, likely independent marker to monitor MS and supports a mediator role of the astrocytes in the fibers/vessels relationship.
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Affiliation(s)
- Jeremy Deverdun
- Department of Neuroradiology, University Hospital Center, I2FH, Institut d'Imagerie Fonctionnelle Humaine, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34295 Cedex 5, Montpellier, France.
| | - Arthur Coget
- Department of Neuroradiology, University Hospital Center, I2FH, Institut d'Imagerie Fonctionnelle Humaine, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34295 Cedex 5, Montpellier, France
- Department of Neuroradiology, Montpellier University Hospital, Gui de Chauliac Hospital, Montpellier, France
- Laboratoire Charles Coulomb, University of Montpellier, 34095, Montpellier, France
| | - Xavier Ayrignac
- Department of Neurology, MS Center and National Reference Center of Adult Leukodystrophies, Montpellier University Hospital, 34 295 Cedex 5, Montpellier, France
| | - Clarisse Carra-Dalliere
- Department of Neurology, MS Center and National Reference Center of Adult Leukodystrophies, Montpellier University Hospital, 34 295 Cedex 5, Montpellier, France
| | - Alexandre Krainik
- Department of Neuroradiology and MRI, Grenoble Institute of Neurosciences, INSERM U836, UMS IRMaGe, Grenoble University Hospital, University Grenoble Alps, Grenoble, France
- Department of Pediatrics, Bordeaux University Hospital, Bordeaux, France
| | - Aude Metzger
- Department of neuro -ophthalmology and neuro cognition, Pierre Wertheimer University Hospital, 69500, Bron, France
| | - Pierre Labauge
- Department of Neurology, MS Center and National Reference Center of Adult Leukodystrophies, Montpellier University Hospital, 34 295 Cedex 5, Montpellier, France
| | - Nicolas Menjot de Champfleur
- Department of Neuroradiology, University Hospital Center, I2FH, Institut d'Imagerie Fonctionnelle Humaine, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34295 Cedex 5, Montpellier, France
- Department of Neuroradiology, Montpellier University Hospital, Gui de Chauliac Hospital, Montpellier, France
- Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
- Laboratoire Charles Coulomb, University of Montpellier, 34095, Montpellier, France
| | - Emmanuelle Le Bars
- Department of Neuroradiology, University Hospital Center, I2FH, Institut d'Imagerie Fonctionnelle Humaine, Gui de Chauliac Hospital, 80 Avenue Augustin Fliche, 34295 Cedex 5, Montpellier, France
- Department of Neuroradiology, Montpellier University Hospital, Gui de Chauliac Hospital, Montpellier, France
- Laboratoire Charles Coulomb, University of Montpellier, 34095, Montpellier, France
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13
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Naser Moghadasi A. The role of the brain in the treatment of multiple sclerosis as a connectomopathy. Med Hypotheses 2020; 143:110090. [PMID: 32679428 DOI: 10.1016/j.mehy.2020.110090] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 06/18/2020] [Accepted: 07/05/2020] [Indexed: 12/14/2022]
Abstract
Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS) causing a variety of symptoms. Although MS is recognized by the demyelinating process, the axonal injury can occur from the start of the disease and lead to neurodegenerative process in the disease. Although MS appears to damage the brain locally, the progressive and neurodegenerative nature of the disease indicate the general and global brain damage. Various studies have indicated this global damage at all areas of white and gray matter. Moreover, the earlier stages of mentioned disease can affect the structural and functional brain connections. Demyelinating lesions, which are local at first glance, lead to a global damage to the functional connections of the brain. Therefore, it seems that the brain network or brain connectome are broadly affected by this disease; therefore, MS can be referred as a connectomopathy. The drugs used in this disease all seek to suppress or regulate the immune system, and the human brain has always been considered as a therapeutic target. However, if the brain is generally involved in the disease, so the treatment should be general. In fact, the treatment process should target the connectomopathy. One of the methods that can be used to achieve the mentioned goal is attending to the role of the brain in its treatment.
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Affiliation(s)
- Abdorreza Naser Moghadasi
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
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14
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Cerina M, Muthuraman M, Gallus M, Koirala N, Dik A, Wachsmuth L, Hundehege P, Schiffler P, Tenberge JG, Fleischer V, Gonzalez-Escamilla G, Narayanan V, Krämer J, Faber C, Budde T, Groppa S, Meuth SG. Myelination- and immune-mediated MR-based brain network correlates. J Neuroinflammation 2020; 17:186. [PMID: 32532336 PMCID: PMC7293122 DOI: 10.1186/s12974-020-01827-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/24/2020] [Indexed: 11/23/2022] Open
Abstract
Background Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS), characterized by inflammatory and neurodegenerative processes. Despite demyelination being a hallmark of the disease, how it relates to neurodegeneration has still not been completely unraveled, and research is still ongoing into how these processes can be tracked non-invasively. Magnetic resonance imaging (MRI) derived brain network characteristics, which closely mirror disease processes and relate to functional impairment, recently became important variables for characterizing immune-mediated neurodegeneration; however, their histopathological basis remains unclear. Methods In order to determine the MRI-derived correlates of myelin dynamics and to test if brain network characteristics derived from diffusion tensor imaging reflect microstructural tissue reorganization, we took advantage of the cuprizone model of general demyelination in mice and performed longitudinal histological and imaging analyses with behavioral tests. By introducing cuprizone into the diet, we induced targeted and consistent demyelination of oligodendrocytes, over a period of 5 weeks. Subsequent myelin synthesis was enabled by reintroduction of normal food. Results Using specific immune-histological markers, we demonstrated that 2 weeks of cuprizone diet induced a 52% reduction of myelin content in the corpus callosum (CC) and a 35% reduction in the neocortex. An extended cuprizone diet increased myelin loss in the CC, while remyelination commenced in the neocortex. These histologically determined dynamics were reflected by MRI measurements from diffusion tensor imaging. Demyelination was associated with decreased fractional anisotropy (FA) values and increased modularity and clustering at the network level. MRI-derived modularization of the brain network and FA reduction in key anatomical regions, including the hippocampus, thalamus, and analyzed cortical areas, were closely related to impaired memory function and anxiety-like behavior. Conclusion Network-specific remyelination, shown by histology and MRI metrics, determined amelioration of functional performance and neuropsychiatric symptoms. Taken together, we illustrate the histological basis for the MRI-driven network responses to demyelination, where increased modularity leads to evolving damage and abnormal behavior in MS. Quantitative information about in vivo myelination processes is mirrored by diffusion-based imaging of microstructural integrity and network characteristics.
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Affiliation(s)
- Manuela Cerina
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Muthuraman Muthuraman
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.
| | - Marco Gallus
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Nabin Koirala
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Andre Dik
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Lydia Wachsmuth
- Departement of Radiology, University of Münster, Münster, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Petra Hundehege
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Patrick Schiffler
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Jan-Gerd Tenberge
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Vinzenz Fleischer
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Venu Narayanan
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Julia Krämer
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
| | - Cornelius Faber
- Departement of Radiology, University of Münster, Münster, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Thomas Budde
- Institute of Physiology I, University of Münster, Münster, Germany
| | - Sergiu Groppa
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Sven G Meuth
- Department of Neurology with Institute of Translational Neurology, Münster University Hospital, Münster, Germany
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15
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Andersen KW, Lasič S, Lundell H, Nilsson M, Topgaard D, Sellebjerg F, Szczepankiewicz F, Siebner HR, Blinkenberg M, Dyrby TB. Disentangling white-matter damage from physiological fibre orientation dispersion in multiple sclerosis. Brain Commun 2020; 2:fcaa077. [PMID: 32954329 PMCID: PMC7472898 DOI: 10.1093/braincomms/fcaa077] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 04/20/2020] [Accepted: 05/07/2020] [Indexed: 01/23/2023] Open
Abstract
Multiple sclerosis leads to diffuse damage of the central nervous system, affecting also the normal-appearing white matter. Demyelination and axonal degeneration reduce regional fractional anisotropy in normal-appearing white matter, which can be routinely mapped with diffusion tensor imaging. However, the standard fractional anisotropy metric is also sensitive to physiological variations in orientation dispersion of white matter fibres. This complicates the detection of disease-related damage in large parts of cerebral white matter where microstructure physiologically displays a high degree of fibre dispersion. To resolve this ambiguity, we employed a novel tensor-valued encoding method for diffusion MRI, which yields a microscopic fractional anisotropy metric that is unaffected by regional variations in orientation dispersion. In 26 patients with relapsing-remitting multiple sclerosis, 14 patients with primary-progressive multiple sclerosis and 27 age-matched healthy controls, we compared standard fractional anisotropy mapping with the novel microscopic fractional anisotropy mapping method, focusing on normal-appearing white matter. Mean microscopic fractional anisotropy and standard fractional anisotropy of normal-appearing white matter were significantly reduced in both patient groups relative to healthy controls, but microscopic fractional anisotropy yielded a better reflection of disease-related white-matter alterations. The reduction in mean microscopic fractional anisotropy showed a significant positive linear relationship with physical disability, as reflected by the expanded disability status scale. Mean reduction of microscopic fractional anisotropy in normal-appearing white matter also scaled positively with individual cognitive dysfunction, as measured with the symbol digit modality test. Mean microscopic fractional anisotropy reduction in normal-appearing white matter also showed a positive relationship with total white-matter lesion load as well as lesion load in specific tract systems. None of these relationships between normal-appearing white-matter microstructure and clinical, cognitive or structural measures emerged when using mean fractional anisotropy. Together, the results provide converging evidence that microscopic fractional anisotropy mapping substantially advances the assessment of cerebral white matter in multiple sclerosis by disentangling microstructure damage from variations in physiological fibre orientation dispersion at the stage of data acquisition. Since tensor-valued encoding can be implemented in routine diffusion MRI, microscopic fractional anisotropy mapping bears considerable potential for the future assessment of disease progression in normal-appearing white matter in both relapsing-remitting and progressive forms of multiple sclerosis as well as other white-matter-related brain diseases.
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Affiliation(s)
- Kasper Winther Andersen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
| | - Samo Lasič
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
- Random Walk Imaging, AB, 222 24 Lund, Sweden
| | - Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
| | - Markus Nilsson
- Department of Radiology, Clinical Sciences, Lund, Lund University, 221 00 Lund, Sweden
| | - Daniel Topgaard
- Division of Physical Chemistry, Department of Chemistry, Lund University, 221 00 Lund, Sweden
| | - Finn Sellebjerg
- Danish Multiple Sclerosis Center, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark
| | - Filip Szczepankiewicz
- Department of Medical Radiation Physics, Clinical Sciences, Lund, Lund University, 221 00 Lund, Sweden
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
- Department of Neurology, Copenhagen University Hospital Bispebjerg, 2400 Copenhagen NV, Denmark
| | - Morten Blinkenberg
- Danish Multiple Sclerosis Center, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark
| | - Tim B Dyrby
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2700 Kongens Lyngby, Denmark
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16
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Continuous reorganization of cortical information flow in multiple sclerosis: A longitudinal fMRI effective connectivity study. Sci Rep 2020; 10:806. [PMID: 31964982 PMCID: PMC6972853 DOI: 10.1038/s41598-020-57895-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 01/03/2020] [Indexed: 12/02/2022] Open
Abstract
Effective connectivity (EC) is able to explore causal effects between brain areas and can depict mechanisms that underlie repair and adaptation in chronic brain diseases. Thus, the application of EC techniques in multiple sclerosis (MS) has the potential to determine directionality of neuronal interactions and may provide an imaging biomarker for disease progression. Here, serial longitudinal structural and resting-state fMRI was performed at 12-week intervals over one year in twelve MS patients. Twelve healthy subjects served as controls (HC). Two approaches for EC quantification were used: Causal Bayesian Network (CBN) and Time-resolved Partial Directed Coherence (TPDC). The EC strength was correlated with the Expanded Disability Status Scale (EDSS) and Fatigue Scale for Motor and Cognitive functions (FSMC). Our findings demonstrated a longitudinal increase in EC between specific brain regions, detected in both the CBN and TPDC analysis in MS patients. In particular, EC from the deep grey matter, frontal, prefrontal and temporal regions showed a continuous increase over the study period. No longitudinal changes in EC were attested in HC during the study. Furthermore, we observed an association between clinical performance and EC strength. In particular, the EC increase in fronto-cerebellar connections showed an inverse correlation with the EDSS and FSMC. Our data depict continuous functional reorganization between specific brain regions indicated by increasing EC over time in MS, which is not detectable in HC. In particular, fronto-cerebellar connections, which were closely related to clinical performance, may provide a marker of brain plasticity and functional reserve in MS.
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17
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Radetz A, Fleischer V, Groppa S. Dissecting task-specific plasticity capacity in patients with multiple sclerosis with transcranial magnetic stimulation. Clin Neurophysiol 2019; 131:472-473. [PMID: 31866340 DOI: 10.1016/j.clinph.2019.11.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 11/28/2019] [Indexed: 01/07/2023]
Affiliation(s)
- Angela Radetz
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany
| | - Vinzenz Fleischer
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany
| | - Sergiu Groppa
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany.
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18
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Dekker I, Sombekke MH, Balk LJ, Moraal B, Geurts JJ, Barkhof F, Uitdehaag BM, Killestein J, Wattjes MP. Infratentorial and spinal cord lesions: Cumulative predictors of long-term disability? Mult Scler 2019; 26:1381-1391. [PMID: 31373535 PMCID: PMC7543019 DOI: 10.1177/1352458519864933] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Objective: The objective of the study was to determine whether early infratentorial and/or spinal cord lesions are long-term cumulative predictors of disability progression in multiple sclerosis (MS). Methods: We selected 153 MS patients from the longitudinal Amsterdam MS cohort. Lesion analysis was performed at baseline and year 2. Disability progression after 6 and 11 years was measured using the Expanded Disability Status Scale (EDSS) and EDSS-plus (including 25-foot walk and 9-hole peg test). Patients with spinal cord or infratentorial lesions were compared for the risk of 6- and 11-year disability progression to patients without spinal cord or infratentorial lesions, respectively. Subsequently, patients with lesions on both locations were compared to patients with only spinal cord or only infratentorial lesions. Results: Baseline spinal cord lesions show a higher risk of 6-year EDSS progression (odds ratio (OR): 3.6, p = 0.007) and EDSS-plus progression (OR: 2.5, p = 0.028) and 11-year EDSS progression (OR: 2.8, p = 0.047). Patients with both infratentorial and spinal cord lesions did not have a higher risk of 6-year disability progression than patients with only infratentorial or only spinal cord lesions. Conclusion: The presence of early spinal cord lesions seems to be a dominant risk factor of disability progression. Simultaneous presence of early infratentorial and spinal cord lesions did not undisputedly predict disability progression.
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Affiliation(s)
- Iris Dekker
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Madeleine H Sombekke
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Lisanne J Balk
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jeroen Jg Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Bernard Mj Uitdehaag
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Joep Killestein
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Mike P Wattjes
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
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19
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Imaging in mice and men: Pathophysiological insights into multiple sclerosis from conventional and advanced MRI techniques. Prog Neurobiol 2019; 182:101663. [PMID: 31374243 DOI: 10.1016/j.pneurobio.2019.101663] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 06/17/2019] [Accepted: 07/17/2019] [Indexed: 01/16/2023]
Abstract
Magnetic resonance imaging (MRI) is the most important tool for diagnosing multiple sclerosis (MS). However, MRI is still unable to precisely quantify the specific pathophysiological processes that underlie imaging findings in MS. Because autopsy and biopsy samples of MS patients are rare and biased towards a chronic burnt-out end or fulminant acute early stage, the only available methods to identify human disease pathology are to apply MRI techniques in combination with subsequent histopathological examination to small animal models of MS and to transfer these insights to MS patients. This review summarizes the existing combined imaging and histopathological studies performed in MS mouse models and humans with MS (in vivo and ex vivo), to promote a better understanding of the pathophysiology that underlies conventional MRI, diffusion tensor and magnetization transfer imaging findings in MS patients. Moreover, it provides a critical view on imaging capabilities and results in MS patients and mouse models and for future studies recommends how to combine those particular MR sequences and parameters whose underlying pathophysiological basis could be partly clarified. Further combined longitudinal in vivo imaging and histopathological studies on rationally selected, appropriate mouse models are required.
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20
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Blecher T, Miron S, Schneider GG, Achiron A, Ben-Shachar M. Association Between White Matter Microstructure and Verbal Fluency in Patients With Multiple Sclerosis. Front Psychol 2019; 10:1607. [PMID: 31379663 PMCID: PMC6657651 DOI: 10.3389/fpsyg.2019.01607] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Accepted: 06/26/2019] [Indexed: 12/14/2022] Open
Abstract
Verbal fluency refers to the ability to generate words quickly and efficiently according to predefined phonological or semantic criteria. Deficits in verbal fluency limit patients' ability to communicate effectively and to function well in social setups. Multiple sclerosis (MS) patients suffer from various cognitive impairments, and some of them experience language deficits as well. The goal of this study is to examine the contribution of the dorsal and ventral language pathways to verbal fluency in MS patients. All patients (N = 33) underwent diffusion MRI (dMRI) and fluency measurements. Diffusion parameters were calculated along dorsal and ventral language-related pathways and their right-hemispheric homologs, identified individually in each patient. Significant correlations were found between fluency measures and mean fractional anisotropy (FA) in several pathways, including the left fronto-temporal arcuate fasciculus (AFft), bilateral inferior fronto-occipital fasciculus (IFOF), and bilateral frontal aslant tract. Along-tract correlations revealed a more selective pattern of associations: letter-based fluency was associated with FA in a segment of the left AFft (dorsal pathway), while category-based fluency was associated with FA in a segment of the right IFOF (ventral pathway). The observed pattern of associations, mapping letter-based fluency to the dorsal stream and category-based fluency to the ventral stream, fits well within the dual stream framework of language processing. Further studies will be necessary to assess whether these associations generalize to the typical adult population or whether they are tied to the clinical state.
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Affiliation(s)
- Tal Blecher
- Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
| | - Shmuel Miron
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Israel
| | | | - Anat Achiron
- Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Michal Ben-Shachar
- Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
- Department of English Literature and Linguistics, Bar-Ilan University, Ramat Gan, Israel
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21
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Schmidt P, Pongratz V, Küster P, Meier D, Wuerfel J, Lukas C, Bellenberg B, Zipp F, Groppa S, Sämann PG, Weber F, Gaser C, Franke T, Bussas M, Kirschke J, Zimmer C, Hemmer B, Mühlau M. Automated segmentation of changes in FLAIR-hyperintense white matter lesions in multiple sclerosis on serial magnetic resonance imaging. NEUROIMAGE-CLINICAL 2019; 23:101849. [PMID: 31085465 PMCID: PMC6517532 DOI: 10.1016/j.nicl.2019.101849] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 05/01/2019] [Indexed: 11/30/2022]
Abstract
Longitudinal analysis of white matter lesion changes on serial MRI has become an important parameter to study diseases with white-matter lesions. Here, we build on earlier work on cross-sectional lesion segmentation; we present a fully automatic pipeline for serial analysis of FLAIR-hyperintense white matter lesions. Our algorithm requires three-dimensional gradient echo T1- and FLAIR- weighted images at 3 Tesla as well as available cross-sectional lesion segmentations of both time points. Preprocessing steps include lesion filling and intrasubject registration. For segmentation of lesion changes, initial lesion maps of different time points are fused; herein changes in intensity are analyzed at the voxel level. Significance of lesion change is estimated by comparison with the difference distribution of FLAIR intensities within normal appearing white matter. The method is validated on MRI data of two time points from 40 subjects with multiple sclerosis derived from two different scanners (20 subjects per scanner). Manual segmentation of lesion increases served as gold standard. Across all lesion increases, voxel-wise Dice coefficient (0.7) as well as lesion-wise detection rate (0.8) and false-discovery rate (0.2) indicate good overall performance. Analysis of scans from a repositioning experiment in a single patient with multiple sclerosis did not yield a single false positive lesion. We also introduce the lesion change plot as a descriptive tool for the lesion change of individual patients with regard to both number and volume. An open source implementation of the algorithm is available at http://www.statistical-modeling.de/lst.html. Quantification of white matter lesion changes is important in multiple sclerosis. We developed and validated an algorithm for automated detection of lesion changes. Our algorithm requires T1-weighted and FLAIR images derived at 3 T as well as available cross-sectional lesion segmentations. With data from 2 different scanners, the tool showed good agreement with manual tracing. An open-source application is available.
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Affiliation(s)
- Paul Schmidt
- Neurology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany; TUM-Neuroimaging Center, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany
| | - Viola Pongratz
- Neurology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany; TUM-Neuroimaging Center, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany
| | - Pascal Küster
- Medical Image Analysis Center, MIAC AG, Mittlere Strasse 83, CH-4031 Basel, Switzerland; Biomedical Engineering, University Basel, Switzerland
| | - Dominik Meier
- Medical Image Analysis Center, MIAC AG, Mittlere Strasse 83, CH-4031 Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, MIAC AG, Mittlere Strasse 83, CH-4031 Basel, Switzerland; Biomedical Engineering, University Basel, Switzerland
| | - Carsten Lukas
- Diagnostic and Interventional Radiology, St. Josef Hospital, Ruhr-University of Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Barbara Bellenberg
- Diagnostic and Interventional Radiology, St. Josef Hospital, Ruhr-University of Bochum, Gudrunstr. 56, 44791 Bochum, Germany
| | - Frauke Zipp
- Neurology, University Medical Centre of the Johannes Gutenberg University Mainz and Neuroimaging Center of the Focus Program Translational Neuroscience (FTN-NIC), Langenbeckstr. 1, 55131 Mainz, Germany
| | - Sergiu Groppa
- Neurology, University Medical Centre of the Johannes Gutenberg University Mainz and Neuroimaging Center of the Focus Program Translational Neuroscience (FTN-NIC), Langenbeckstr. 1, 55131 Mainz, Germany
| | - Philipp G Sämann
- Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Frank Weber
- Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany; Neurology, Sana Kliniken des Landkreises Cham, August-Holz-Straße 1, 93413 Cham, Germany
| | - Christian Gaser
- Department of Psychiatry and Department of Neurology, Jena University Hospital, Jena, Germany
| | - Thomas Franke
- Medical Informatics, University Medical Center Göttingen, Germany
| | - Matthias Bussas
- Neurology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany; TUM-Neuroimaging Center, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany
| | - Jan Kirschke
- Neuroradiology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany
| | - Claus Zimmer
- Neuroradiology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany
| | - Bernhard Hemmer
- Neurology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Str. 17, 81377 Munich, Germany
| | - Mark Mühlau
- Neurology, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany; TUM-Neuroimaging Center, Technische Universität München, Ismaninger Str. 22, 81541 Munich, Germany.
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22
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Cooper G, Finke C, Chien C, Brandt AU, Asseyer S, Ruprecht K, Bellmann-Strobl J, Paul F, Scheel M. Standardization of T1w/T2w Ratio Improves Detection of Tissue Damage in Multiple Sclerosis. Front Neurol 2019; 10:334. [PMID: 31024428 PMCID: PMC6465519 DOI: 10.3389/fneur.2019.00334] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 03/19/2019] [Indexed: 01/24/2023] Open
Abstract
Normal appearing white matter (NAWM) damage develops early in multiple sclerosis (MS) and continues in the absence of new lesions. The ratio of T1w and T2w (T1w/T2w ratio), a measure of white matter integrity, has previously shown reduced intensity values in MS NAWM. We evaluate the validity of a standardized T1w/T2w ratio (sT1w/T2w ratio) in MS and whether this method is sensitive in detecting MS-related differences in NAWM. T1w and T2w scans were acquired at 3 Tesla in 47 patients with relapsing-remitting MS and 47 matched controls (HC). T1w/T2w and sT1w/T2w ratios were then calculated. We compared between-group variability between T1w/T2w and sT1w/T2w ratio in HC and MS and assessed for group differences. We also evaluated the relationship between the T1w/T2w and sT1w/T2w ratios and clinically relevant variables. Compared to the classic T1w/T2w ratio, the between-subject variability in sT1w/T2w ratio showed a significant reduction in MS patients (p < 0.001) and HC (p < 0.001). However, only sT1w/T2w ratio values were reduced in patients compared to HC (p < 0.001). The sT1w/T2w ratio intensity values were significantly influenced by age, T2 lesion volume and group status (MS vs. HC) (adjusted R2 = 0.30, p < 0.001). We demonstrate the validity of the sT1w/T2w ratio in MS and that it is more sensitive to MS-related differences in NAWM compared to T1w/T2w ratio. The sT1w/T2w ratio shows promise as an easily-implemented measure of NAWM in MS using readily available scans and simple post-processing methods.
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Affiliation(s)
- Graham Cooper
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Carsten Finke
- Einstein Center for Neurosciences, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Claudia Chien
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Susanna Asseyer
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Judith Bellmann-Strobl
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Einstein Center for Neurosciences, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
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23
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Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts. Neuroscience 2019; 403:35-53. [DOI: 10.1016/j.neuroscience.2017.10.033] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 10/22/2017] [Accepted: 10/24/2017] [Indexed: 12/11/2022]
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24
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Sharma S, Laule C, Moore GRW, Li DKB, Zhang Y. Correlating new directional measures of myelin and axonal integrity in T2-weighted MRI with quantitative histology in multiple sclerosis. J Neurosci Methods 2019; 311:369-376. [PMID: 30240805 DOI: 10.1016/j.jneumeth.2018.09.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 09/17/2018] [Accepted: 09/17/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND Imaging measurement of structure alignment has shown increasing importance in determining tissue properties. It is not known if a similar ability for characterizing neuropathology exists. NEW METHODS This study aimed to validate a new alignment-assessing method for measuring myelin and axonal properties using quantitative histological metrics. The new method involved analysis of the Fourier transform (FT) power spectrum in standard magnetic resonance imaging (MRI). T2-weighted MRI were collected from 10 post-mortem multiple sclerosis (MS) brain samples. Three tissue types were examined: lesions, diffusely abnormal white matter, and normal appearing white matter. MRI analysis included computing the FT power spectrum; extracting alignment histograms; and calculating dominant orientation and alignment complexity (angular entropy). Post MRI, the brain samples were processed for myelin and axonal staining, and the stained images were used to derive quantitative orientation measures using structure tensor analysis for MRI comparison. RESULTS There were significant differences in orientation metrics between tissue types in both MRI and histology, and MRI measurements correlated strongly with histological indices. Moreover, the joint effect of myelin and axonal entropy explained over 95% of the variance of MRI angular entropy. COMPARISON WITH EXISTING METHOD There is no established method for characterizing myelin and axonal pathology using standard MRI. Advanced MRI methods have the potential to do this but are still in research development and are not yet routinely acquired in clinical practice. CONCLUSIONS Alignment measurement using clinical MRI scans may become a valuable new method for characterizing myelin and axonal properties in MS patients.
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Affiliation(s)
- Shrushrita Sharma
- Department of Radiology, University of Calgary, Alberta, Canada; Department of Clinical Neurosciences, University of Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, British Columbia, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, British Columbia, Canada; Department of Physics & Astronomy, University of British Columbia, British Columbia, Canada
| | - G R Wayne Moore
- Department of Pathology and Laboratory Medicine, University of British Columbia, British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, British Columbia, Canada
| | - David K B Li
- Department of Radiology, University of British Columbia, British Columbia, Canada
| | - Yunyan Zhang
- Department of Radiology, University of Calgary, Alberta, Canada; Department of Clinical Neurosciences, University of Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Alberta, Canada.
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Huang J, Liu Y, Zhao T, Shu N, Duan Y, Ren Z, Sun Z, Liu Z, Chen H, Dong H, Li K. White matter microstructural alterations in clinically isolated syndrome and multiple sclerosis. J Clin Neurosci 2018; 53:27-33. [PMID: 29754967 DOI: 10.1016/j.jocn.2018.01.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 10/26/2017] [Accepted: 01/07/2018] [Indexed: 10/16/2022]
Abstract
This study aims to determine whether and how diffusion alteration occurs in the earliest stage of multiple sclerosis (MS) and the differences in diffusion metrics between CIS and MS by using the tract-based spatial statistics (TBSS) method based on diffusion tensor imaging (DTI). Thirty-six CIS patients (mean age ± SD: 34.0 years ± 12.6), 36 relapsing-remitting multiple sclerosis (RRMS) patients (mean age ± SD: 35.0 years ± 9.4) and 36 age- and gender-matched normal controls (NCs) were included in this study. Voxel-wise analyses were performed with TBSS using multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1) and radial diffusivity (λ23). In the CIS patients, TBSS analyses revealed diffusion alterations in a few white matter (WM) regions including the anterior thalamic radiation, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, body and splenium of the corpus callosum, internal capsule, external capsule, and cerebral peduncle. MS patients showed more widespread diffusion changes (decreased FA, increased λ1, λ23 and MD) than CIS. Exploratory analyses also revealed the possible associations between WM diffusion metrics and clinical variables (Expanded Disability Status Scale and disease duration) in the patients. This study provided imaging evidence for DTI abnormalities in CIS and MS and suggested that DTI can improve our knowledge of the path physiology of CIS and MS and clinical progression.
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Affiliation(s)
- Jing Huang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Brain Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Yaou Liu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Brain Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research Beijing Normal University, Beijing 100857, PR China
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research Beijing Normal University, Beijing 100857, PR China
| | - Yunyun Duan
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Brain Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Zhuoqiong Ren
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Brain Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Zheng Sun
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Brain Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Zheng Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China
| | - Hai Chen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China
| | - Huiqing Dong
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Brain Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China.
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26
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Filli L, Sutter T, Easthope CS, Killeen T, Meyer C, Reuter K, Lörincz L, Bolliger M, Weller M, Curt A, Straumann D, Linnebank M, Zörner B. Profiling walking dysfunction in multiple sclerosis: characterisation, classification and progression over time. Sci Rep 2018; 8:4984. [PMID: 29563533 PMCID: PMC5862880 DOI: 10.1038/s41598-018-22676-0] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 02/27/2018] [Indexed: 01/28/2023] Open
Abstract
Gait dysfunction is a common and relevant symptom in multiple sclerosis (MS). This study aimed to profile gait pathology in gait-impaired patients with MS using comprehensive 3D gait analysis and clinical walking tests. Thirty-seven patients with MS walked on the treadmill at their individual, sustainable speed while 20 healthy control subjects walked at all the different patient's paces, allowing for comparisons independent of walking velocity. Kinematic analysis revealed pronounced restrictions in knee and ankle joint excursion, increased gait variability and asymmetry along with impaired dynamic stability in patients. The most discriminative single gait parameter, differentiating patients from controls with an accuracy of 83.3% (χ2 test; p = 0.0001), was reduced knee range of motion. Based on hierarchical cluster and principal component analysis, three principal pathological gait patterns were identified: a spastic-paretic, an ataxia-like, and an unstable gait. Follow-up assessments after 1 year indicated deterioration of walking function, particularly in patients with spastic-paretic gait patterns. Our findings suggest that impaired knee/ankle control is common in patients with MS. Personalised gait profiles and clustering algorithms may be promising tools for stratifying patients and to inform patient-tailored exercise programs. Responsive, objective outcome measures are important for monitoring disease progression and treatment effects in MS trials.
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Affiliation(s)
- Linard Filli
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland.
| | - Tabea Sutter
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Christopher S Easthope
- Spinal Cord Injury Center, Balgrist University Hospital, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Tim Killeen
- Spinal Cord Injury Center, Balgrist University Hospital, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Christian Meyer
- Spinal Cord Injury Center, Balgrist University Hospital, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Katja Reuter
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Lilla Lörincz
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Marc Bolliger
- Spinal Cord Injury Center, Balgrist University Hospital, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Armin Curt
- Spinal Cord Injury Center, Balgrist University Hospital, Forchstrasse 340, 8008, Zurich, Switzerland
| | - Dominik Straumann
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Michael Linnebank
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurology, Helios-Klinik Hagen-Ambrock, /University Witten/Herdecke, Ambrocker Weg 60, 58091, Hagen, Germany
| | - Björn Zörner
- Department of Neurology, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, Forchstrasse 340, 8008, Zurich, Switzerland
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27
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Droby A, Yuen KSL, Muthuraman M, Reitz SC, Fleischer V, Klein J, Gracien RM, Ziemann U, Deichmann R, Zipp F, Groppa S. Changes in brain functional connectivity patterns are driven by an individual lesion in MS: a resting-state fMRI study. Brain Imaging Behav 2017; 10:1117-1126. [PMID: 26553579 DOI: 10.1007/s11682-015-9476-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Diffuse inflammation in multiple sclerosis (MS) extends beyond focal lesion sites, affecting interconnected regions; however, little is known about the impact of an individual lesion affecting major white matter (WM) pathways on brain functional connectivity (FC). Here, we longitudinally assessed the effects of acute and chronic lesions on FC in relapsing-remitting MS (RRMS) patients using resting-state fMRI. 45 MRI data sets from 9 RRMS patients were recorded using 3T MR scanner over 5 time points at 8 week intervals. Patients were divided into two groups based on the presence (n = 5; MS+) and absence (n = 4; MS-) of a lesion at a predilection site for MS. While FC levels were found not to fluctuate significantly in the overall patient group, the MS+ patient group showed increased FC in the contralateral cuneus and precuneus and in the ipsilateral precuneus (p < 0.01, corrected). This can be interpreted as the recruitment of intact cortical regions to compensate for tissue damage. During the study, one patient developed an acute WM lesion in the left posterior periventricular space. A marked increase in FC in the right pre-, post-central gyrus, right superior frontal gyrus, the left cuneus, the vermis and the posterior and anterior lobes of the cerebellum was noted following the clinical relapse, which gradually decreased in subsequent follow-ups, suggesting short-term functional reorganization during the acute phase. This strongly suggests that the lesion-related network changes observed in patients with chronic lesions occur as a result of reorganization processes following the initial appearance of an acute lesion.
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Affiliation(s)
- Amgad Droby
- Department of Neurology, University Medical Centre of the Johannes Gutenberg University Mainz, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Kenneth S L Yuen
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, University Medical Centre of the Johannes Gutenberg University Mainz, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Sarah-Christina Reitz
- Department of Neurology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Brain Imaging Center (BIC), Goethe University, Frankfurt am Main, Germany
| | - Vinzenz Fleischer
- Department of Neurology, University Medical Centre of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Johannes Klein
- Department of Neurology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Brain Imaging Center (BIC), Goethe University, Frankfurt am Main, Germany
| | - René-Maxime Gracien
- Department of Neurology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Brain Imaging Center (BIC), Goethe University, Frankfurt am Main, Germany
| | - Ulf Ziemann
- Department of Neurology and Stroke, Hertie Institute for Clinical Brain Research, Eberhard-Karls-University, Tübingen, Germany
| | - Ralf Deichmann
- Brain Imaging Center (BIC), Goethe University, Frankfurt am Main, Germany
| | - Frauke Zipp
- Department of Neurology, University Medical Centre of the Johannes Gutenberg University Mainz, Mainz, Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, University Medical Centre of the Johannes Gutenberg University Mainz, Mainz, Germany.
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
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28
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Stellmann JP, Hodecker S, Cheng B, Wanke N, Young KL, Hilgetag C, Gerloff C, Heesen C, Thomalla G, Siemonsen S. Reduced rich-club connectivity is related to disability in primary progressive MS. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2017; 4:e375. [PMID: 28804744 PMCID: PMC5532749 DOI: 10.1212/nxi.0000000000000375] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 05/17/2017] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To investigate whether the structural connectivity of the brain's rich-club organization is altered in patients with primary progressive MS and whether such changes to this fundamental network feature are associated with disability measures. METHODS We recruited 37 patients with primary progressive MS and 21 healthy controls for an observational cohort study. Structural connectomes were reconstructed based on diffusion-weighted imaging data using probabilistic tractography and analyzed with graph theory. RESULTS We observed the same topological organization of brain networks in patients and controls. Consistent with the originally defined rich-club regions, we identified superior frontal, precuneus, superior parietal, and insular cortex in both hemispheres as rich-club nodes. Connectivity within the rich club was significantly reduced in patients with MS (p = 0.039). The extent of reduced rich-club connectivity correlated with clinical measurements of mobility (Kendall rank correlation coefficient τ = -0.20, p = 0.047), hand function (τ = -0.26, p = 0.014), and information processing speed (τ = -0.20, p = 0.049). CONCLUSIONS In patients with primary progressive MS, the fundamental organization of the structural connectome in rich-club and peripheral nodes was preserved and did not differ from healthy controls. The proportion of rich-club connections was altered and correlated with disability measures. Thus, the rich-club organization of the brain may be a promising network phenotype for understanding the patterns and mechanisms of neurodegeneration in MS.
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Affiliation(s)
- Jan-Patrick Stellmann
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Sibylle Hodecker
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Bastian Cheng
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Nadine Wanke
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Kim Lea Young
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Claus Hilgetag
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Christian Gerloff
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Christoph Heesen
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Götz Thomalla
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
| | - Susanne Siemonsen
- Institut für Neuroimmunologie und Multiple Sklerose (INIMS) (J.-P.S., S.H., N.W., K.L.Y., C.G., C. Heesen, S.S.), Klinik und Poliklinik für Neurologie (J.-P.S., S.H., B.C., N.W., K.L.Y., C. Heesen, G.T.), Institute of Computational Neuroscience (C. Hilgetag), and Department of Diagnostic and Interventional Neuroradiology (S.S.), University Medical Center Hamburg-Eppendorf, Germany
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29
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Quantification of normal-appearing white matter tract integrity in multiple sclerosis: a diffusion kurtosis imaging study. J Neurol 2016; 263:1146-55. [PMID: 27094571 DOI: 10.1007/s00415-016-8118-z] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2016] [Revised: 04/02/2016] [Accepted: 04/04/2016] [Indexed: 10/21/2022]
Abstract
Our aim was to characterize the nature and extent of pathological changes in the normal-appearing white matter (NAWM) of patients with multiple sclerosis (MS) using novel diffusion kurtosis imaging-derived white matter tract integrity (WMTI) metrics and to investigate the association between these WMTI metrics and clinical parameters. Thirty-two patients with relapsing-remitting MS and 19 age- and gender-matched healthy controls underwent MRI and neurological examination. Maps of mean diffusivity, fractional anisotropy and WMTI metrics (intra-axonal diffusivity, axonal water fraction, tortuosity and axial and radial extra-axonal diffusivity) were created. Tract-based spatial statistics analysis was performed to assess for differences in the NAWM between patients and controls. A region of interest analysis of the corpus callosum was also performed to assess for group differences and to evaluate correlations between WMTI metrics and measures of disease severity. Mean diffusivity and radial extra-axonal diffusivity were significantly increased while fractional anisotropy, axonal water fraction, intra-axonal diffusivity and tortuosity were decreased in MS patients compared with controls (p values ranging from <0.001 to <0.05). Axonal water fraction in the corpus callosum was significantly associated with the expanded disability status scale score (ρ = -0.39, p = 0.035). With the exception of the axial extra-axonal diffusivity, all metrics were correlated with the symbol digits modality test score (p values ranging from 0.001 to <0.05). WMTI metrics are thus sensitive to changes in the NAWM of MS patients and might provide a more pathologically specific, clinically meaningful and practical complement to standard diffusion tensor imaging-derived metrics.
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30
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Fox J, Kraemer M, Schormann T, Dabringhaus A, Hirsch J, Eisele P, Szabo K, Weiss C, Amann M, Weier K, Naegelin Y, Kappos L, Gass A. Individual Assessment of Brain Tissue Changes in MS and the Effect of Focal Lesions on Short-Term Focal Atrophy Development in MS: A Voxel-Guided Morphometry Study. Int J Mol Sci 2016; 17:489. [PMID: 27043553 PMCID: PMC4848945 DOI: 10.3390/ijms17040489] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Revised: 02/22/2016] [Accepted: 02/25/2016] [Indexed: 11/21/2022] Open
Abstract
We performed voxel-guided morphometry (VGM) investigating the mechanisms of brain atrophy in multiple sclerosis (MS) related to focal lesions. VGM maps detect regional brain changes when comparing 2 time points on high resolution T1-weighted (T1w) magnetic resonace imaging (MRI). Two T1w MR datasets from 92 relapsing-remitting MS patients obtained 12 months apart were analysed with VGM. New lesions and volume changes of focal MS lesions as well as in the surrounding tissue were identified by visual inspection on colour coded VGM maps. Lesions were dichotomized in active and inactive lesions. Active lesions, defined by either new lesions (NL) (volume increase > 5% in VGM), chronic enlarging lesions (CEL) (pre-existent T1w lesions with volume increase > 5%), or chronic shrinking lesions (CSL) (pre-existent T1w lesions with volume reduction > 5%) in VGM, were accompanied by tissue shrinkage in surrounding and/or functionally related regions. Volume loss within the corpus callosum was highly correlated with the number of lesions in its close proximity. Volume loss in the lateral geniculate nucleus was correlated with lesions along the optic radiation. VGM analysis provides strong evidence that all active lesion types (NL, CEL, and CSL) contribute to brain volume reduction in the vicinity of lesions and/or in anatomically and functionally related areas of the brain.
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Affiliation(s)
- Jan Fox
- Universitätsmedizin Mannheim, Department of Neurology, Theodor-Kutzer-Ufer 1-3, Mannheim 68167, Germany.
| | - Matthias Kraemer
- Hospital zum Heiligen Geist, Department for Early Rehabilitation, Kempen 47906, Germany.
| | - Thorsten Schormann
- Institute for Anatomy, Heinrich-Heine-University Düsseldorf, Universitätsstr. 1, Düsseldorf 40001, Germany.
| | - Andreas Dabringhaus
- Deutsches Institut für Medizinische Dokumentation und Information, Waisenhausgasse 36-38a, Köln 50676, Germany.
| | - Jochen Hirsch
- Fraunhofer MEVIS, Institut für Bildgestützte Medizin, Universitätsallee 29, Bremen 28359, Germany.
| | - Philipp Eisele
- Universitätsmedizin Mannheim, Department of Neurology, Theodor-Kutzer-Ufer 1-3, Mannheim 68167, Germany.
| | - Kristina Szabo
- Universitätsmedizin Mannheim, Department of Neurology, Theodor-Kutzer-Ufer 1-3, Mannheim 68167, Germany.
| | - Christel Weiss
- Department of Biometry and Statistics, Medical Faculty Mannheim, Ruprecht-Karls University Heidelberg, Mannheim 68167, Germany.
| | - Michael Amann
- MIAC, Basel, Universitätsspital Basel, Mittlere Strasse 83, Basel 4056, Switzerland.
| | - Katrin Weier
- Neurology, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel, Petersgraben 4, Basel 4052, Switzerland.
| | - Yvonne Naegelin
- Neurology, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel, Petersgraben 4, Basel 4052, Switzerland.
| | - Ludwig Kappos
- Neurology, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel, Petersgraben 4, Basel 4052, Switzerland.
| | - Achim Gass
- Universitätsmedizin Mannheim, Department of Neurology, Theodor-Kutzer-Ufer 1-3, Mannheim 68167, Germany.
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