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Banerjee R, Kaptan M, Tinnermann A, Khatibi A, Dabbagh A, Büchel C, Kündig CW, Law CSW, Pfyffer D, Lythgoe DJ, Tsivaka D, Van De Ville D, Eippert F, Muhammad F, Glover GH, David G, Haynes G, Haaker J, Brooks JCW, Finsterbusch J, Martucci KT, Hemmerling KJ, Mobarak-Abadi M, Hoggarth MA, Howard MA, Bright MG, Kinany N, Kowalczyk OS, Freund P, Barry RL, Mackey S, Vahdat S, Schading S, McMahon SB, Parish T, Marchand-Pauvert V, Chen Y, Smith ZA, Weber KA, De Leener B, Cohen-Adad J. EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.07.631402. [PMID: 39829895 PMCID: PMC11741348 DOI: 10.1101/2025.01.07.631402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.0, and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared to other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.
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Affiliation(s)
- Rohan Banerjee
- Department of Computer Science, Polytechnique Montreal, Montreal, Quebec, Canada
- Mila - Quebec AI Institute, Montreal, Quebec, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Merve Kaptan
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Alexandra Tinnermann
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ali Khatibi
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), University of Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, UK
| | - Alice Dabbagh
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian W Kündig
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Christine S W Law
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Dario Pfyffer
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Dimitra Tsivaka
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
- Medical Physics Department, Medical School, University of Thessaly, Larisa, Greece
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, OK, USA
| | - Gary H Glover
- Radiological Sciences Laboratory, Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Gergely David
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Grace Haynes
- Stephenson School of Biomedical Engineering at the University of Oklahoma in Norman, OK, USA
| | - Jan Haaker
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonathan C W Brooks
- Department of Psychology, University of Liverpool, Liverpool, United Kingdom
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katherine T Martucci
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Kimberly J Hemmerling
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Mahdi Mobarak-Abadi
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
| | - Mark A Hoggarth
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Department of Physical Therapy, North Central College, Naperville, Illinois, USA
| | - Matthew A Howard
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Molly G Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Nawal Kinany
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Olivia S Kowalczyk
- Functional Imaging Laboratory, Department of Imaging Neuroscience, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Functional Imaging Laboratory, Department of Imaging Neuroscience, Queen Square Institute of Neurology, University College London, London, UK
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Shahabeddin Vahdat
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Simon Schading
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Stephen B McMahon
- Wolfson Centre for Age Related Diseases, King's College London, London UK
| | - Todd Parish
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | | | - Yufen Chen
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, OK, USA
| | - Kenneth A Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Benjamin De Leener
- Department of Computer Science, Polytechnique Montreal, Montreal, Quebec, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Research Center, Ste-Justine Hospital University Centre, Montreal, Quebec, Canada
| | - Julien Cohen-Adad
- Mila - Quebec AI Institute, Montreal, Quebec, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada
- Research Center, Ste-Justine Hospital University Centre, Montreal, Quebec, Canada
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Gaubert M, Combès B, Bannier E, Masson A, Caron V, Baudron G, Ferré JC, Michel L, Le Page E, Stankoff B, Edan G, Bodini B, Kerbrat A. Microstructural Damage and Repair in the Spinal Cord of Patients With Early Multiple Sclerosis and Association With Disability at 5 Years. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2025; 12:e200333. [PMID: 39571137 PMCID: PMC11587990 DOI: 10.1212/nxi.0000000000200333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 10/01/2024] [Indexed: 11/27/2024]
Abstract
BACKGROUND AND OBJECTIVES The dynamics of microstructural spinal cord (SC) damage and repair in people with multiple sclerosis (pwMS) and their clinical relevance have yet to be explored. We set out to describe patient-specific profiles of microstructural SC damage and change during the first year after MS diagnosis and to investigate their associations with disability and SC atrophy at 5 years. METHODS We performed a longitudinal monocentric cohort study among patients with relapsing-remitting MS: first relapse <1 year, no relapse <1 month, and high initial severity on MRI (>9 T2 lesions on brain MRI and/or initial myelitis). pwMS and age-matched healthy controls (HCs) underwent cervical SC magnetization transfer (MT) imaging at baseline and at 1 year for pwMS. Based on HC data, SC MT ratio z-score maps were computed for each person with MS. An index of microstructural damage was calculated as the proportion of voxels classified as normal at baseline and identified as damaged after 1 year. Similarly, an index of repair was also calculated (voxels classified as damaged at baseline and as normal after 1 year). Linear models including these indices and disability or SC cross-sectional area (CSA) change between baseline and 5 years were implemented. RESULTS Thirty-seven patients and 19 HCs were included. We observed considerable variability in the extent of microstructural SC damage at baseline (0%-58% of SC voxels). We also observed considerable variability in damage and repair indices over 1 year (0%-31% and 0%-20%), with 18 patients showing predominance of damage and 18 predominance of repair. The index of microstructural damage was associated positively with the Expanded Disability Status Scale score (r = 0.504, p = 0.002) and negatively with CSA change (r = -0.416, p = 0.02) at 5 years, independent of baseline SC lesion volume. DISCUSSION People with early relapsing-remitting MS exhibited heterogeneous profiles of microstructural SC damage and repair. Progression of microstructural damage was associated with disability progression and SC atrophy 5 years later. These results indicate a potential for microstructural repair in the SC to prevent disability progression in pwMS.
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Affiliation(s)
- Malo Gaubert
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Benoit Combès
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Elise Bannier
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Arthur Masson
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Vivien Caron
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Gaëlle Baudron
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Jean-Christophe Ferré
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Laure Michel
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Emmanuelle Le Page
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Bruno Stankoff
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Gilles Edan
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Benedetta Bodini
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Anne Kerbrat
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
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Luchetti L, Prados F, Cortese R, Gentile G, Calabrese M, Mortilla M, De Stefano N, Battaglini M. Evaluation of cervical spinal cord atrophy using a modified SIENA approach. Neuroimage 2024; 298:120775. [PMID: 39106936 DOI: 10.1016/j.neuroimage.2024.120775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 07/12/2024] [Accepted: 08/02/2024] [Indexed: 08/09/2024] Open
Abstract
Spinal cord (SC) atrophy obtained from structural magnetic resonance imaging has gained relevance as an indicator of neurodegeneration in various neurological disorders. The common method to assess SC atrophy is by comparing numerical differences of the cross-sectional spinal cord area (CSA) between time points. However, this indirect approach leads to considerable variability in the obtained results. Studies showed that this limitation can be overcome by using a registration-based technique. The present study introduces the Structural Image Evaluation using Normalization of Atrophy on the Spinal Cord (SIENA-SC), which is an adapted version of the original SIENA method, designed to directly calculate the percentage of SC volume change over time from clinical brain MRI acquired with an extended field of view to cover the superior part of the cervical SC. In this work, we compared SIENA-SC with the Generalized Boundary Shift Integral (GBSI) and the CSA change. On a scan-rescan dataset, SIENA-SC was shown to have the lowest measurement error than the other two methods. When comparing a group of 190 Healthy Controls with a group of 65 Multiple Sclerosis patients, SIENA-SC provided significantly higher yearly rates of atrophy in patients than in controls and a lower sample size when measured for treatment effect sizes of 50%, 30% and 10%. Our findings indicate that SIENA-SC is a robust, reproducible, and sensitive approach for assessing longitudinal changes in spinal cord volume, providing neuroscientists with an accessible and automated tool able to reduce the need for manual intervention and minimize variability in measurements.
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Affiliation(s)
- Ludovico Luchetti
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy; Siena Imaging S.r.l., Siena, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering Department, University College London, London, United Kingdom; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | | | - Massimilano Calabrese
- Department of Neuroscience, Biomedicine and Movements, The Multiple Sclerosis Center of the University Hospital of Verona, Verona, Italy
| | - Marzia Mortilla
- Anna Meyer Children's University Hospital-IRCCS, Florence, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy; Siena Imaging S.r.l., Siena, Italy.
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Freund P, Boller V, Emmenegger TM, Akbar M, Hupp M, Pfender N, Wheeler‐Kingshott CAMG, Cohen‐Adad J, Fehlings MG, Curt A, Seif M. Quantifying neurodegeneration of the cervical cord and brain in degenerative cervical myelopathy: A multicentre study using quantitative magnetic resonance imaging. Eur J Neurol 2024; 31:e16297. [PMID: 38713645 PMCID: PMC11235710 DOI: 10.1111/ene.16297] [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: 12/22/2023] [Revised: 03/06/2024] [Accepted: 03/21/2024] [Indexed: 05/09/2024]
Abstract
BACKGROUND AND PURPOSE Simultaneous assessment of neurodegeneration in both the cervical cord and brain across multiple centres can enhance the effectiveness of clinical trials. Thus, this study aims to simultaneously assess microstructural changes in the cervical cord and brain above the stenosis in degenerative cervical myelopathy (DCM) using quantitative magnetic resonance imaging (MRI) in a multicentre study. METHODS We applied voxelwise analysis with a probabilistic brain/spinal cord template embedded in statistical parametric mappin (SPM-BSC) to process multi parametric mapping (MPM) including effective transverse relaxation rate (R2*), longitudinal relaxation rate (R1), and magnetization transfer (MT), which are indirectly sensitive to iron and myelin content. Regression analysis was conducted to establish associations between neurodegeneration and clinical impairment. Thirty-eight DCM patients (mean age ± SD = 58.45 ± 11.47 years) and 38 healthy controls (mean age ± SD = 41.18 ± 12.75 years) were recruited at University Hospital Balgrist, Switzerland and Toronto Western Hospital, Canada. RESULTS Remote atrophy was observed in the cervical cord (p = 0.002) and in the left thalamus (0.026) of the DCM group. R1 was decreased in the periaqueductal grey matter (p = 0.014), thalamus (p = 0.001), corpus callosum (p = 0.0001), and cranial corticospinal tract (p = 0.03). R2* was increased in the primary somatosensory cortices (p = 0.008). Sensory impairments were associated with increased iron-sensitive R2* in the thalamus and periaqueductal grey matter in DCM. CONCLUSIONS Simultaneous assessment of the spinal cord and brain revealed DCM-induced demyelination, iron deposition, and atrophy. The extent of remote neurodegeneration was associated with sensory impairment, highlighting the intricate and expansive nature of microstructural neurodegeneration in DCM, reaching beyond the stenosis level.
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Affiliation(s)
- Patrick Freund
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Viveka Boller
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Tim M. Emmenegger
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Muhammad Akbar
- Spine Program Division of NeurosurgeryUniversity of Toronto and Toronto Western HospitalTorontoOntarioCanada
| | - Markus Hupp
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Nikolai Pfender
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Claudia Angela Michela Gandini Wheeler‐Kingshott
- NMR Research Unit, Queen Square MS CentreUniversity College London (UCL) Queen Square Institute of Neurology, Faculty of Brain SciencesLondonUK
- Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
- Digital Neuroscience Research UnitIRCCS Mondino FoundationPaviaItaly
| | - Julien Cohen‐Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique MontrealMontrealQuebecCanada
- Functional Neuroimaging Unit, CRIUGMUniversity of MontrealMontrealQuebecCanada
| | - Michael G. Fehlings
- Spine Program Division of NeurosurgeryUniversity of Toronto and Toronto Western HospitalTorontoOntarioCanada
| | - Armin Curt
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Maryam Seif
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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Pareto D, Corral JF, Garcia-Vidal A, Alberich M, Auger C, Rio J, Mongay N, Sastre-Garriga J, Rovira À. Assessing the Equivalence of Brain-Derived Measures from Two 3D T1-Weighted Acquisitions: One Covering the Brain and One Covering the Brain and Spinal Cord. AJNR Am J Neuroradiol 2023; 44:569-573. [PMID: 37080719 PMCID: PMC10171373 DOI: 10.3174/ajnr.a7843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 02/01/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND AND PURPOSE In MS, it is common to acquire brain and spinal cord MR imaging sequences separately to assess the extent of the disease. The goal of this study was to see how replacing the traditional brain T1-weighted images (brain-T1) with an acquisition that included both the brain and the cervical spinal cord (cns-T1) affected brain- and spinal cord-derived measures. MATERIALS AND METHODS Thirty-six healthy controls (HC) and 42 patients with MS were included. Of those, 18 HC and 35 patients with MS had baseline and follow-up at 1 year acquired on a 3T magnet. Two 3D T1-weighted images (brain-T1 and cns-T1) were acquired at each time point. Regional cortical thickness and volumes were determined with FastSurfer, and the percentage brain volume change per year was obtained with SIENA. The spinal cord area was estimated with the Spinal Cord Toolbox. Intraclass correlation coefficients (ICC) were calculated to check for consistency of measures obtained from brain-T1 and cns-T1. RESULTS Cortical thickness measures showed an ICC >0.75 in 94% of regions in healthy controls and 80% in patients with MS. Estimated regional volumes had an ICC >0.88, and the percentage brain volume change had an ICC >0.79 for both groups. The spinal cord area measures had an ICC of 0.68 in healthy controls and 0.92 in patients with MS. CONCLUSIONS Brain measurements obtained from 3D cns-T1 are highly equivalent to those obtained from a brain-T1, suggesting that it could be feasible to replace the brain-T1 with cns-T1.
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Affiliation(s)
- D Pareto
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - J F Corral
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - A Garcia-Vidal
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
| | - M Alberich
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - C Auger
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
| | - J Rio
- Department of Neurology and Neuroimmunology (J.R., N.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - N Mongay
- Department of Neurology and Neuroimmunology (J.R., N.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - J Sastre-Garriga
- Department of Neurology and Neuroimmunology (J.R., N.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - À Rovira
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
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6
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Schading S, Seif M, Leutritz T, Hupp M, Curt A, Weiskopf N, Freund P. Reliability of spinal cord measures based on synthetic T 1-weighted MRI derived from multiparametric mapping (MPM). Neuroimage 2023; 271:120046. [PMID: 36948280 DOI: 10.1016/j.neuroimage.2023.120046] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/14/2023] [Accepted: 03/18/2023] [Indexed: 03/24/2023] Open
Abstract
Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T1-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T1-w MRI (synT1-w) estimated from the MPM, in order to measure CSA. SynT1-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R1) and effective transverse (R2*) relaxation rates. The reliability of CSA measurements from synT1-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT1-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT1-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm2 compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT1-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT1-w images, thereby reducing scan time significantly.
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Affiliation(s)
- Simon Schading
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Maryam Seif
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Markus Hupp
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Armin Curt
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
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7
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Matusche B, Litvin L, Schneider R, Bellenberg B, Mühlau M, Pongratz V, Berthele A, Groppa S, Muthuraman M, Zipp F, Paul F, Wiendl H, Meuth SG, Sämann P, Weber F, Linker RA, Kümpfel T, Gold R, Lukas C. Early spinal cord pseudoatrophy in interferon-beta-treated multiple sclerosis. Eur J Neurol 2023; 30:453-462. [PMID: 36318271 DOI: 10.1111/ene.15620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 10/26/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Brain pseudoatrophy has been shown to play a pivotal role in the interpretation of brain atrophy measures during the first year of disease-modifying therapy in multiple sclerosis. Whether pseudoatrophy also affects the spinal cord remains unclear. The aim of this study was to analyze the extent of pseudoatrophy in the upper spinal cord during the first 2 years after therapy initiation and compare this to the brain. METHODS A total of 129 patients from a prospective longitudinal multicentric national cohort study for whom magnetic resonance imaging scans at baseline, 12 months, and 24 months were available were selected for brain and spinal cord volume quantification. Annual percentage brain volume and cord area change were calculated using SIENA (Structural Image Evaluation of Normalized Atrophy) and NeuroQLab, respectively. Linear mixed model analyses were performed to compare patients on interferon-beta therapy (n = 84) and untreated patients (n = 45). RESULTS Patients treated with interferon-beta demonstrated accelerated annual percentage brain volume and cervical cord area change in the first year after treatment initiation, whereas atrophy rates stabilized to a similar and not significantly different level compared to untreated patients during the second year. CONCLUSIONS These results suggest that pseudoatrophy occurs not only in the brain, but also in the spinal cord during the first year of interferon-beta treatment.
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Affiliation(s)
- Britta Matusche
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Ludmila Litvin
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Ruth Schneider
- Department of Neurology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Barbara Bellenberg
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Mark Mühlau
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Viola Pongratz
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine-Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine-Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine-Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Heinz Wiendl
- Department of Neurology, Institute of Translational Neurology, University of Münster, Münster, Germany
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Frank Weber
- Neurological Clinic, Sana Clinic Cham, Cham, Germany
| | - Ralf A Linker
- Department of Neurology, University of Regensburg, Regensburg, Germany
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, Biomedical Center and University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Ralf Gold
- Department of Neurology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Carsten Lukas
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
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8
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Sastre-Garriga J, Rovira A, García-Vidal A, Carbonell-Mirabent P, Alberich M, Vidal-Jordana A, Auger C, Tintore M, Montalban X, Pareto D. Spinal cord reserve in multiple sclerosis. J Neurol Neurosurg Psychiatry 2023:jnnp-2022-330613. [PMID: 36690430 DOI: 10.1136/jnnp-2022-330613] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/10/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND The spinal cord (SC) is a preferential target of multiple sclerosis (MS) damage highly relevant towards disability. Differential impact of such damage could be due to the initial amount of SC tissue, as described for the brain parenchyma (brain reserve concept). We aimed to test the existence of SC reserve by using spinal canal area (SCaA) as a proxy. METHODS Brain sagittal three-dimensional T1-weighted scans covering down to C5 level were acquired in 2930 people with MS and 43 healthy controls (HCs) in a cross-sectional, multicentre study. SC area (SCA) and SCaA were obtained with the Spinal Cord Toolbox. Demographical data and patient-derived disability scores were obtained. SC parameters were compared between groups with age-adjusted and sex-adjusted linear regression models. The main outcome of the study, the existence of an association between SCaA and Patient Determined Disease Steps, was tested with scaled linear models. RESULTS 1747 persons with MS (mean age: 46.35 years; 73.2% female) and 42 HCs (mean age: 45.56 years; 78.6% female) were analysed after exclusion of post-processing errors and application of quality criteria. SCA (60.41 mm2 vs 65.02 mm2, p<0.001) was lower in people with MS compared with HC; no differences in SCaA were observed (213.24 mm2 vs 212.61 mm2, p=0.125). Adjusted scaled linear models showed that a larger SCaA was significantly associated with lower scores on Patient Determined Disease Steps (beta coefficient: -0.12, p=0.0124) independently of spinal cord atrophy, brain T2 lesion volume, age and sex. CONCLUSIONS A larger SCaA may be protective against disability in MS, possibly supporting the existence of SC reserve.
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Affiliation(s)
- Jaume Sastre-Garriga
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Alex Rovira
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Aran García-Vidal
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Pere Carbonell-Mirabent
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Manel Alberich
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Angela Vidal-Jordana
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Cristina Auger
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Mar Tintore
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Xavier Montalban
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Deborah Pareto
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
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9
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Seif M, Leutritz T, Schading S, Emmengger T, Curt A, Weiskopf N, Freund P. Reliability of multi-parameter mapping (MPM) in the cervical cord: A multi-center multi-vendor quantitative MRI study. Neuroimage 2022; 264:119751. [PMID: 36384206 DOI: 10.1016/j.neuroimage.2022.119751] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 11/07/2022] [Accepted: 11/12/2022] [Indexed: 11/14/2022] Open
Abstract
MRI based multicenter studies which target neurological pathologies affecting the spinal cord and brain - including spinal cord injury (SCI) - require standardized acquisition protocols and image processing methods. We have optimized and applied a multi-parameter mapping (MPM) protocol that simultaneously covers the brain and the cervical cord within a traveling heads study across six clinical centers (Leutritz et al., 2020). The MPM protocol includes quantitative maps (magnetization transfer saturation (MT), proton density (PD), longitudinal (R1), and effective transverse (R2*) relaxation rates) sensitive to myelination, water content, iron concentration, and morphometric measures, such as cross-sectional cord area. Previously, we assessed the repeatability and reproducibility of the brain MPM data acquired in the five healthy participants who underwent two scan-rescans (Leutritz et al., 2020). This study focuses on the cervical cord MPM data derived from the same acquisitions to determine its repeatability and reproducibility in the cervical cord. MPM matrices of the cervical cord were generated and processed using the hMRI and the spinal cord toolbox. To determine reliability of the cervical MPM data, the intra-site (i.e., scan-rescan) coefficient of variation (CoV), inter-site CoV, and bias within region of interests (C1, C2 and C3 levels) were determined. The range of the mean intra- and inter-site CoV of MT, R1 and PD was between 2.5% and 12%, and between 1.1% and 4.0% for the morphometric measures. In conclusion, the cervical MPM data showed a high repeatability and reproducibility for key imaging biomarkers and hence can be employed as a standardized tool in multi-center studies, including clinical trials.
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Affiliation(s)
- Maryam Seif
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Simon Schading
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland
| | - Tim Emmengger
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland
| | - Armin Curt
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Faculty of Physics and Earth Sciences, Felix Bloch Institute for Solid State Physics, Leipzig University, Leipzig, Germany
| | - Patrick Freund
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
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10
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Bédard S, Cohen-Adad J. Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction. FRONTIERS IN NEUROIMAGING 2022; 1:1031253. [PMID: 37555172 PMCID: PMC10406309 DOI: 10.3389/fnimg.2022.1031253] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 10/04/2022] [Indexed: 08/10/2023]
Abstract
Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models required manual intervention and used vertebral levels as a reference, which is an imprecise prediction of the spinal levels. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated factors to explain variability, and developed normalization strategies on a large cohort (N = 804). Following automatic spinal cord segmentation, vertebral labeling and PMJ labeling, the spinal cord CSA was computed on T1w MRI scans from the UK Biobank database. The CSA was computed using two methods. For the first method, the CSA was computed at the level of the C2-C3 intervertebral disc. For the second method, the CSA was computed at 64 mm caudally from the PMJ, this distance corresponding to the average distance between the PMJ and the C2-C3 disc across all participants. The effect of various demographic and anatomical factors was explored, and a stepwise regression found significant predictors; the coefficients of the best fit model were used to normalize CSA. CSA measured at C2-C3 disc and using the PMJ differed significantly (paired t-test, p-value = 0.0002). The best normalization model included thalamus, brain volume, sex and the interaction between brain volume and sex. The coefficient of variation went down for PMJ CSA from 10.09 (without normalization) to 8.59%, a reduction of 14.85%. For CSA at C2-C3, it went down from 9.96 to 8.42%, a reduction of 15.13 %. This study introduces an end-to-end automatic pipeline to measure and normalize cord CSA from a neurological reference. This approach requires further validation to assess atrophy in longitudinal studies. The inter-subject variability of CSA can be partly accounted for by demographics and anatomical factors.
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Affiliation(s)
- Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, Centre de recherche de l'Institut universitaire de gériatrie de Montréal (CRIUGM), University of Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
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11
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Combes AJE, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States.
| | - Margareta A Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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12
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De Stefano N, Battaglini M, Pareto D, Cortese R, Zhang J, Oesingmann N, Prados F, Rocca MA, Valsasina P, Vrenken H, Gandini Wheeler-Kingshott CAM, Filippi M, Barkhof F, Rovira À. MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies. Neuroimage Clin 2022; 34:102972. [PMID: 35245791 PMCID: PMC8892169 DOI: 10.1016/j.nicl.2022.102972] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 11/24/2022]
Abstract
Sharing data from cooperative studies is essential to develop new biomarkers in MS. Differences in MRI acquisition, analysis, storage represent a substantial constraint. We review the state of the art and developments in the harmonization of MRI. We provide recommendations to harmonize large MRI datasets in the MS field.
There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.
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Affiliation(s)
- Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Jian Zhang
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | | | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, UCL, London, WC1V 6LJ, United Kingdom; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Hugo Vrenken
- Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Brain MRI 3T Research Center, C. Mondino National Neurological Institute, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy; Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, UCL, London, WC1V 6LJ, United Kingdom; Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
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