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Muhammad F, Weber KA, Bédard S, Haynes G, Smith L, Khan AF, Hameed S, Gray K, McGovern K, Rohan M, Ding L, Van Hal M, Dickson D, Tamimi MA, Parrish T, Dhaher Y, Smith ZA. Cervical spinal cord morphometrics in degenerative cervical myelopathy: quantification using semi-automated normalized technique and correlation with neurological dysfunctions. Spine J 2024:S1529-9430(24)00886-6. [PMID: 39038658 DOI: 10.1016/j.spinee.2024.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/27/2024] [Accepted: 07/07/2024] [Indexed: 07/24/2024]
Abstract
BACKGROUND CONTEXT Degenerative cervical myelopathy (DCM) is characterized by spinal cord atrophy. Accurate estimation of spinal cord atrophy is key to the understanding of neurological diseases, including DCM. However, its clinical application is hampered by difficulties in its precise and consistent estimation due to significant variability in spinal cord morphometry along the cervical spine, both within and between individuals. PURPOSE To characterize morphometrics of the compressed spinal cord in DCM patients. We employed our semiautomated analysis framework that incorporates the Spinal Cord Toolbox (SCT) and a normalization approach to effectively address the challenges posed by cord compression in these patients. Additionally, we examined the clinical relevance of these morphometric measures to enhance our understanding of DCM pathophysiology. STUDY DESIGN Prospective study. PATIENT SAMPLE This study investigated 36 DCM patients and 31 healthy controls (HCs). OUTCOME MEASURES Clinical scores including 9-hole peg test for hand dexterity, hand grip strength, balance, gait speed, modified Japanese Orthopaedic Association (mJOA) score, and imaging-based spinal cord morphometrics. METHOD Using the generic spine acquisition protocol and our semiautomated analysis pipeline, spinal cord morphometrics, including cross-sectional area (CSA), anterior-posterior (AP) and transverse (RL) diameters, eccentricity, and solidity, were estimated from sagittal T2w magnetic resonance imaging (MRI) images using the Spinal Cord Toolbox (SCT). Normalized metrics were extracted from the C1 to C7 vertebral levels and compared between DCM patients and HC. Morphometric data at regions of maximum spinal cord compression (MSCC) were correlated with the clinical scores. A subset of participants underwent follow-up scans at 6 months to monitor longitudinal changes in spinal cord atrophy. RESULTS Spinal cord morphometric data were normalized against the healthy population morphometry (PAM50 database) and extracted for all participants. DCM patients showed a notable reduction in CSA, AP, and RL diameter across all vertebral levels compared to HC. MSCC metrics correlated significantly with clinical scores like dexterity, grip strength, and mJOA scores. Longitudinal analysis indicated a decrease in CSA and worsening clinical scores in DCM patients. CONCLUSION Our processing pipeline offers a reliable method for assessing spinal cord compression in DCM patients. Normalized spinal cord morphometrics, particularly the CSA could have potential for monitoring DCM disease severity and progression, guiding treatment decisions. Furthermore, to our knowledge our study is the first to apply the generic spinal cord acquisition protocol, ensuring consistent imaging across different MRI scanners and settings. Coupled with our semiautomated analysis pipeline, this protocol is key for the detailed morphometric characterization of compressed spinal cords in patients with DCM, a disease that is both complex and heterogenous. This study was funded by the National Institute of Neurological Disorders and Stroke (NINDS) (K23:NS091430) and (R01: NS129852-01A1).
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Affiliation(s)
- Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | - Kenneth A Weber
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, Palo Alto, CA, USA
| | - Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Lonnie Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Sanaa Hameed
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Kathyrn Gray
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Kathleen McGovern
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Michael Rohan
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Lei Ding
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Michael Van Hal
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Douglas Dickson
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mazin Al Tamimi
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Todd Parrish
- Department of Radiology, Fienberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Yasin Dhaher
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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2
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Cook SR, Vasamreddy K, Combes A, Vandekar S, Visagie M, Houston D, Wald L, Kumar A, McGrath M, McKnight CD, Bagnato F, Smith SA, O’Grady KP. Biological variation in cervical spinal cord MRI morphometry in healthy individuals and people with multiple sclerosis. J Neuroimaging 2024; 34:466-474. [PMID: 38858847 PMCID: PMC11236499 DOI: 10.1111/jon.13219] [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: 02/06/2024] [Revised: 05/06/2024] [Accepted: 05/24/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND AND PURPOSE Conclusions from prior literature regarding the impact of sex, age, and height on spinal cord (SC) MRI morphometrics are conflicting, while the effect of body weight on SC morphometrics has been found to be nonsignificant. The purpose of this case-control study is to assess the associations between cervical SC MRI morphometric parameters and age, sex, height, and weight to establish their potential role as confounding variables in a clinical study of people with multiple sclerosis (MS) compared to a cohort of healthy volunteers. METHODS Sixty-nine healthy volunteers and 31 people with MS underwent cervical SC MRI at 3 Tesla field strength. Images were centered at the C3/C4 intervertebral disc and processed using Spinal Cord Toolbox v.4.0.2. Mixed-effects linear regression models were used to evaluate the effects of biological variables and disease status on morphometric parameters. RESULTS Sex, age, and height had significant effects on cord and gray matter (GM) cross-sectional area (CSA) as well as the GM:cord CSA ratio. There were no significant effects of body weight on morphometric parameters. The effect of MS disease duration on cord CSA in the C4 level was significant when controlling for all other variables. CONCLUSIONS Studies of disease-related changes in SC morphometry should control for sex, age, and height to account for physiological variation.
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Affiliation(s)
- Sarah R. Cook
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Yale University, New Haven, CT, United States
| | - Kritin Vasamreddy
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Anna Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mereze Visagie
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Delaney Houston
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lily Wald
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Ashwin Kumar
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Megan McGrath
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Colin D. McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Neurology, VA Hospital, TN Valley Healthcare Center, Nashville, TN, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Kristin P. O’Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
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3
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Wendebourg MJ, Weigel M, Weidensteiner C, Sander L, Kesenheimer E, Naumann N, Haas T, Madoerin P, Braun N, Neuwirth C, Weber M, Jahn K, Kappos L, Granziera C, Schweikert K, Sinnreich M, Bieri O, Schlaeger R. Cervical and thoracic spinal cord gray matter atrophy is associated with disability in patients with amyotrophic lateral sclerosis. Eur J Neurol 2024; 31:e16268. [PMID: 38465478 PMCID: PMC11235652 DOI: 10.1111/ene.16268] [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: 09/12/2023] [Revised: 01/24/2024] [Accepted: 02/14/2024] [Indexed: 03/12/2024]
Abstract
BACKGROUND AND PURPOSE In amyotrophic lateral sclerosis (ALS), there is an unmet need for more precise patient characterization through quantitative, ideally operator-independent, assessments of disease extent and severity. Radially sampled averaged magnetization inversion recovery acquisitions (rAMIRA) magnetic resonance imaging enables gray matter (GM) and white matter (WM) area quantitation in the cervical and thoracic spinal cord (SC) with optimized contrast. We aimed to investigate rAMIRA-derived SC GM and SC WM areas and their association with clinical phenotype and disability in ALS. METHODS A total of 36 patients with ALS (mean [SD] age 61.7 [12.6] years, 14 women) and 36 healthy, age- and sex-matched controls (HCs; mean [SD] age 63.1 [12.1] years, 14 women) underwent two-dimensional axial rAMIRA imaging at the inter-vertebral disc levels C2/3-C5/C6 and the lumbar enlargement level Tmax. ALS Functional Rating Scale-revised (ALSFRS-R) score, muscle strength, and sniff nasal inspiratory pressure (SNIP) were assessed. RESULTS Compared to HCs, GM and WM areas were reduced in patients at all cervical levels (p < 0.0001). GM area (p = 0.0001), but not WM area, was reduced at Tmax. Patients with King's Stage 3 showed significant GM atrophy at all levels, while patients with King's Stage 1 showed significant GM atrophy selectively at Tmax. SC GM area was significantly associated with muscle force at corresponding myotomes. GM area at C3/C4 was associated with ALSFRS-R (p < 0.001) and SNIP (p = 0.0016). CONCLUSION Patients with ALS assessed by rAMIRA imaging show significant cervical and thoracic SC GM and SC WM atrophy. SC GM area correlates with muscle strength and clinical disability. GM area reduction at Tmax may be an early disease sign. Longitudinal studies are warranted.
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Affiliation(s)
- Maria Janina Wendebourg
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
| | - Matthias Weigel
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Claudia Weidensteiner
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Laura Sander
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
| | - Eva Kesenheimer
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
| | - Nicole Naumann
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
| | - Tanja Haas
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
| | - Philipp Madoerin
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
| | - Nathalie Braun
- Neuromuscular Diseases Unit/ALS ClinicKantonsspital Sankt GallenSt. GallenSwitzerland
| | - Christoph Neuwirth
- Neuromuscular Diseases Unit/ALS ClinicKantonsspital Sankt GallenSt. GallenSwitzerland
| | - Markus Weber
- Neuromuscular Diseases Unit/ALS ClinicKantonsspital Sankt GallenSt. GallenSwitzerland
| | - Kathleen Jahn
- Clinics of Respiratory MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
| | - Ludwig Kappos
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
| | - Cristina Granziera
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
| | - Kathi Schweikert
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
| | - Michael Sinnreich
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Biomedicine (DBE)University of BaselBaselSwitzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Regina Schlaeger
- Department of NeurologyUniversity Hospital Basel and University of BaselBaselSwitzerland
- Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
- Department of Biomedical Engineering, Translational Imaging in Neurology (ThINk)University of BaselBaselSwitzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University of BaselBaselSwitzerland
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4
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Labounek R, Bondy MT, Paulson AL, Bédard S, Abramovic M, Alonso-Ortiz E, Atcheson NT, Barlow LR, Barry RL, Barth M, Battiston M, Büchel C, Budde MD, Callot V, Combes A, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak AV, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Gandini Wheeler-Kingshott CAM, Germani G, Gilbert G, Giove F, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers JM, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler H, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Laganà MM, Laule C, Law CSW, Leutritz T, Liu Y, Llufriu S, Mackey S, Martin AR, Martinez-Heras E, Mattera L, O’Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley GW, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber KA, Weiskopf N, Wise RG, Wyss PO, Xu J, Cohen-Adad J, Lenglet C, Nestrašil I. Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591421. [PMID: 38746371 PMCID: PMC11092490 DOI: 10.1101/2024.04.29.591421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.
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Affiliation(s)
- René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Monica T. Bondy
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Amy L. Paulson
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
| | - Nicole T Atcheson
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | - Laura R. Barlow
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, Massachusetts, USA
| | - Markus Barth
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Christian Büchel
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew D. Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
- Clement J. Zablocki Veteran’s Affairs Medical Center, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna Combes
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | | | - Marek Dostál
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Adam V. Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Jürgen Finsterbusch
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Claudia A. M. Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - GianCarlo Germani
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Francesco Grussu
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
- Department of Neurology, University Hospital Brno, Brno, Czech Republic
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James M. Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Haleh Karbasforoushan
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
| | - Ali Khatibi
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), University of Birmingham, Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Joo-won Kim
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Nawal Kinany
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Hagen Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Science, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Petr Kudlička
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
- First Department of Neurology, St. Anne’s University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Nyoman D. Kurniawan
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | | | | | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, Canada
| | | | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, China
| | - Sara Llufriu
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Allan R. Martin
- Department of Neurological Surgery, University of California, Davis, CA, USA
| | - Eloy Martinez-Heras
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Geneva, Genève, Switzerland
| | - Kristin P. O’Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nico Papinutto
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Todd B. Parrish
- Department of Radiology, Northwestern University, Chicago, IL 60611, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
- Centre for Medical Image Computing, University College London, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Marc J. Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, Australia
| | - Rebecca S. Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Giovanni Savini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20072, Pieve Emanuele (MI), Italy
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089, Rozzano (MI), Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Alan C. Seifert
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alex K. Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN USA
| | - Zachary A. Smith
- Department of Neurosurgery, University of Oklahoma, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Yuichi Suzuki
- The University of Tokyo Hospital, Radiology Center, Tokyo, Japan
| | - George W Tackley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
| | - Alexandra Tinnermann
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Valošek
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Department of Neurosurgery, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Marios C. Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Kenneth A. Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
| | - Richard G. Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
- Department of Neurosciences, Imaging, and Clinical Sciences, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
| | - Patrik O. Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Igor Nestrašil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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Büeler S, Freund P, Kessler TM, Liechti MD, David G. Improved inter-subject alignment of the lumbosacral cord for group-level in vivo gray and white matter assessments: A scan-rescan MRI study at 3T. PLoS One 2024; 19:e0301449. [PMID: 38626171 PMCID: PMC11020367 DOI: 10.1371/journal.pone.0301449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 03/15/2024] [Indexed: 04/18/2024] Open
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) enables the investigation of pathological changes in gray and white matter at the lumbosacral enlargement (LSE) and conus medullaris (CM). However, conducting group-level analyses of MRI metrics in the lumbosacral spinal cord is challenging due to variability in CM length, lack of established image-based landmarks, and unknown scan-rescan reliability. This study aimed to improve inter-subject alignment of the lumbosacral cord to facilitate group-level analyses of MRI metrics. Additionally, we evaluated the scan-rescan reliability of MRI-based cross-sectional area (CSA) measurements and diffusion tensor imaging (DTI) metrics. METHODS Fifteen participants (10 healthy volunteers and 5 patients with spinal cord injury) underwent axial T2*-weighted and diffusion MRI at 3T. We assessed the reliability of spinal cord and gray matter-based landmarks for inter-subject alignment of the lumbosacral cord, the inter-subject variability of MRI metrics before and after adjusting for the CM length, the intra- and inter-rater reliability of CSA measurements, and the scan-rescan reliability of CSA measurements and DTI metrics. RESULTS The slice with the largest gray matter CSA as an LSE landmark exhibited the highest reliability, both within and across raters. Adjusting for the CM length greatly reduced the inter-subject variability of MRI metrics. The intra-rater, inter-rater, and scan-rescan reliability of MRI metrics were the highest at and around the LSE (scan-rescan coefficient of variation <3% for CSA measurements and <7% for DTI metrics within the white matter) and decreased considerably caudal to it. CONCLUSIONS To facilitate group-level analyses, we recommend using the slice with the largest gray matter CSA as a reliable LSE landmark, along with an adjustment for the CM length. We also stress the significance of the anatomical location within the lumbosacral cord in relation to the reliability of MRI metrics. The scan-rescan reliability values serve as valuable guides for power and sample size calculations in future longitudinal studies.
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Affiliation(s)
- Silvan Büeler
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- UCL Queen Square Institute of Neurology, Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Thomas M. Kessler
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Martina D. Liechti
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Gergely David
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
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6
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Bédard S, Bouthillier M, Cohen-Adad J. Pontomedullary junction as a reference for spinal cord cross-sectional area: validation across neck positions. Sci Rep 2023; 13:13527. [PMID: 37598229 PMCID: PMC10439961 DOI: 10.1038/s41598-023-40731-3] [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: 04/18/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023] Open
Abstract
Spinal cord cross-sectional area (CSA) is an important MRI biomarker to assess spinal cord atrophy in various neurodegenerative and traumatic spinal cord diseases. However, the conventional method of computing CSA based on vertebral levels is inherently flawed, as the prediction of spinal levels from vertebral levels lacks reliability, leading to considerable variability in CSA measurements. Computing CSA from an intrinsic neuroanatomical reference, the pontomedullary junction (PMJ), has been proposed in previous work to overcome limitations associated with using a vertebral reference. However, the validation of this alternative approach, along with its variability across and within participants under variable neck extensions, remains unexplored. The goal of this study was to determine if the variability of CSA across neck flexions/extensions is reduced when using the PMJ, compared to vertebral levels. Ten participants underwent a 3T MRI T2w isotropic scan at 0.6 mm3 for 3 neck positions: extension, neutral and flexion. Spinal cord segmentation, vertebral labeling, PMJ labeling, and CSA were computed automatically while spinal segments were labeled manually. Mean coefficient of variation for CSA across neck positions was 3.99 ± 2.96% for the PMJ method vs. 4.02 ± 3.01% for manual spinal segment method vs. 4.46 ± 3.10% for the disc method. These differences were not statistically significant. The PMJ method was slightly more reliable than the disc-based method to compute CSA at specific spinal segments, although the difference was not statistically significant. This suggests that the PMJ can serve as a valuable alternative and reliable method for estimating CSA when a disc-based approach is challenging or not feasible, such as in cases involving fused discs in individuals with spinal cord injuries.
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Affiliation(s)
- Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.
| | - Maxime Bouthillier
- Centre Hospitalier de l'Université de Montréal, University of Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada
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7
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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: 2.0] [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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8
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Block VJ, Cheng S, Juwono J, Cuneo R, Kirkish G, Alexander AM, Khan M, Akula A, Caverzasi E, Papinutto N, Stern WA, Pletcher MJ, Marcus GM, Olgin JE, Hauser SL, Gelfand JM, Bove R, Cree BAC, Henry RG. Association of daily physical activity with brain volumes and cervical spinal cord areas in multiple sclerosis. Mult Scler 2023; 29:363-373. [PMID: 36573559 PMCID: PMC9972237 DOI: 10.1177/13524585221143726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Remote activity monitoring has the potential to evaluate real-world, motor function, and disability at home. The relationships of daily physical activity with spinal cord white matter and gray matter (GM) areas, multiple sclerosis (MS) disability and leg function, are unknown. OBJECTIVE Evaluate the association of structural central nervous system pathology with ambulatory disability. METHODS Fifty adults with progressive or relapsing MS with motor disability who could walk >2 minutes were assessed using clinician-evaluated, patient-reported outcomes, and quantitative brain and spinal cord magnetic resonance imaging (MRI) measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 days. Univariate and multivariate analyses were performed to assess correlations between physical activity and other disability metrics. RESULTS Mean age was 53.3 years and median Expanded Disability Status Scale (EDSS) was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures. Greater STEPS were significantly correlated with greater C2-C3 spinal cord GM areas (ρ = 0.39, p = 0.04), total cord area (TCA; ρ = 0.35, p = 0.04), and cortical GM volume (ρ = 0.32, p = 0.04). CONCLUSION These results provide preliminary evidence that spinal cord GM area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology.
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Affiliation(s)
- Valerie J Block
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA/Department of Physical Therapy and Rehabilitation
Science, University of California San Francisco, San Francisco, CA,
USA
| | - Shuiting Cheng
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Jeremy Juwono
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Richard Cuneo
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Gina Kirkish
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Amber M Alexander
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Mahir Khan
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Amit Akula
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Eduardo Caverzasi
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA/Department of Brain and Behavioral Sciences, University
of Pavia, Pavia, Italy
| | - Nico Papinutto
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | | | - Mark J Pletcher
- Department of Epidemiology and Biostatistics,
University of California San Francisco, San Francisco, CA, USA/Department of
Medicine, University of California San Francisco, San Francisco, CA,
USA
| | - Gregory M Marcus
- Department of Epidemiology and Biostatistics,
University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey E Olgin
- Department of Epidemiology and Biostatistics,
University of California San Francisco, San Francisco, CA, USA
| | - Stephen L Hauser
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Jeffrey M Gelfand
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Riley Bove
- UCSF Weill Institute for Neurosciences,
Department of Neurology, University of California San Francisco, San
Francisco, CA, USA
| | - Bruce AC Cree
- BAC Cree UCSF Weill Institute for
Neurosciences, Department of Neurology, University of California, 1651 4th St
Suite 252, San Francisco, San Francisco, CA 94158, USA.
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9
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Association of volumetric MRI measures and disability in MS patients of the same age: Descriptions from a birth year cohort. Mult Scler Relat Disord 2023; 71:104568. [PMID: 36805177 DOI: 10.1016/j.msard.2023.104568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 01/20/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023]
Abstract
BACKGROUND AND OBJECTIVES Although MRI-based markers of neuroinflammation have proven crucial for the diagnosis of multiple sclerosis (MS), predicting clinical progression with inflammation remains difficult. Neurodegenerative markers such as brain volume loss show stronger clinical (predictive) correlations, but also harbor age-related variation that must be disentangled from disease duration. In this study we investigated how clinical disability is related to volumetric MRI measures in a cohort of MS patients and healthy controls (HC) of the same age: Project Y. METHODS This study included 234 MS patients born in 1966 and 112 HC born between 1965 and 1967 in the Netherlands. Disability was quantified using the expanded disability status scale (EDSS), nine hole peg test (9HPT), and timed 25 foot walking test (T25FWT). Volumes were quantified on 3T MRI as normalized whole brain (NBV) and regional gray matter (GM) volumes using the same scanner and MRI protocol: cortical (normalized cortical gray matter volume; NCGMV), deep (NDGMV), thalamic (NThalV), and cerebellar (NCbV) GM volumes. In addition, mean upper cervical cord area (MUCCA), white matter lesion volume (LV), and spinal cord lesions were assessed. These measures were compared between patients and HC, and related to disability measures using linear regression. RESULTS Mean age of people with MS (PwMS) was 52.8 years (SD 0.9) and median disease duration 15.8 years (IQR 8.7-24.8). All global and regional brain measures were lower in MS patients compared to HC. Univariate regression models showed that NDGMV (β = -0.20) and MUCCA (β = -0.38) were most strongly related to the EDSS in all PwMS. After subtype stratification, MUCCA was most strongly related to the EDSS (β = -0.60) and 9HPT (β = -0.55) in secondary progressive PwMS. Multivariate regression models demonstrated that in all PwMS, the EDSS was best explained by lower MUCCA, longer disease durations and a progressive disease course (adjusted-R (Sastre-Garriga et al., 2017) = 0.26, p < 0.001). MUCCA was a consistent correlate in separate models of the EDSS for all PwMS, relapsing and progressive onset PwMS. The 9HPT (adjusted-R (Sastre-Garriga et al., 2017) = 0.20, p < 0.001) was best explained by lower MUCCA, higher LV and pack years, while lower limb disability (adjusted-R (Sastre-Garriga et al., 2017) = 0.11, p < 0.001) was best explained by lower MUCCA, progressive onset MS and female sex. DISCUSSION Our results indicate that in a cohort unbiased by age differences, spinal cord and deep gray matter volumes best related to physical disability. Our results support the use of these measures in clinical practice and trials.
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10
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Longitudinal assessment of cervical spinal cord compartments in multiple sclerosis. Mult Scler Relat Disord 2023; 71:104545. [PMID: 36758461 DOI: 10.1016/j.msard.2023.104545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/21/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023]
Abstract
BACKGROUND Although cervical spinal cord (cSC) area is an established biomarker in MS, there is currently a lack of longitudinal assessments of cSC gray and white matter areas. OBJECTIVE We conducted an explorative analysis of longitudinal changes of cSC gray and white matter areas in MS patients. METHODS 65 MS patients (33 relapsing-remitting; 20 secondary progressive and 12 primary progressive) and 20 healthy controls (HC) received clinical and upper cSC MRI assessments over 1.10±0.28 years. cSC compartments were quantified on MRI using the novel averaged magnetization inversion recovery acquisitions sequence (in-plane resolution=0.67 × 0.67mm2), and in-house developed post-processing methods. Patients were stratified regarding clinical progression. RESULTS Patients with clinical progression showed faster reduction of cSC areas over time at the level of cSC enlargement (approximate vertebral level C4-C5) compared to stable patients (p<0.05). In addition, when compared to the rostral-cSC (approximate vertebral level C2-C3), a preferential reduction of cSC and white matter areas over time at the level of cSC enlargement (p<0.05 and p<0.01, respectively) was demonstrated only in patients with clinical progression, but not in stable MS patients and HC. Compared to HC, MS patients showed comparable changes over time in all cSC compartments. CONCLUSIONS MS patients with clinical disease progression demonstrate subtle signs of a more pronounced tissue loss at the level of cSC enlargement. Future studies should consider larger sample sizes and more extended observation periods.
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11
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Tsagkas C, Horvath-Huck A, Haas T, Amann M, Todea A, Altermatt A, Müller J, Cagol A, Leimbacher M, Barakovic M, Weigel M, Pezold S, Sprenger T, Kappos L, Bieri O, Granziera C, Cattin P, Parmar K. Fully Automatic Method for Reliable Spinal Cord Compartment Segmentation in Multiple Sclerosis. AJNR Am J Neuroradiol 2023; 44:218-227. [PMID: 36702504 PMCID: PMC9891337 DOI: 10.3174/ajnr.a7756] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 12/05/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE Fully automatic quantification methods of spinal cord compartments are needed to study pathologic changes of the spinal cord GM and WM in MS in vivo. We propose a novel method for automatic spinal cord compartment segmentation (SCORE) in patients with MS. MATERIALS AND METHODS The cervical spinal cords of 24 patients with MS and 24 sex- and age-matched healthy controls were scanned on a 3T MR imaging system, including an averaged magnetization inversion recovery acquisition sequence. Three experienced raters manually segmented the spinal cord GM and WM, anterior and posterior horns, gray commissure, and MS lesions. Subsequently, manual segmentations were used to train neural segmentation networks of spinal cord compartments with multidimensional gated recurrent units in a 3-fold cross-validation fashion. Total intracranial volumes were quantified using FreeSurfer. RESULTS The intra- and intersession reproducibility of SCORE was high in all spinal cord compartments (eg, mean relative SD of GM and WM: ≤ 3.50% and ≤1.47%, respectively) and was better than manual segmentations (all P < .001). The accuracy of SCORE compared with manual segmentations was excellent, both in healthy controls and in patients with MS (Dice similarity coefficients of GM and WM: ≥ 0.84 and ≥0.92, respectively). Patients with MS had lower total WM areas (P < .05), and total anterior horn areas (P < .01 respectively), as measured with SCORE. CONCLUSIONS We demonstrate a novel, reliable quantification method for spinal cord tissue segmentation in healthy controls and patients with MS and other neurologic disorders affecting the spinal cord. Patients with MS have reduced areas in specific spinal cord tissue compartments, which may be used as MS biomarkers.
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Affiliation(s)
- C Tsagkas
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
| | - A Horvath-Huck
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - T Haas
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
| | - M Amann
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
- Medical Image Analysis Center AG (M.A., A.A.), Basel, Switzerland
| | - A Todea
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Radiology; Department of Neuroradiology (A.T.), Clinic for Radiology & Nuclear Medicine; and Research Center for Clinical Neuroimmunology
| | - A Altermatt
- Medical Image Analysis Center AG (M.A., A.A.), Basel, Switzerland
| | - J Müller
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
| | - A Cagol
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - M Leimbacher
- Medical Faculty (M.L., P.C.), University of Basel, Basel, Switzerland
| | - M Barakovic
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - M Weigel
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - S Pezold
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - T Sprenger
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Department of Neurology (T.S.), DKD Helios Klinik Wiesbaden, Wiesbaden, Germany
| | - L Kappos
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Neuroscience Basel (RC2NB) (L.K.), Departments of Medicine, Clinical Research, and Biomedical Imaging, University Hospital Basel and University of Basel, Basel, Switzerland
| | - O Bieri
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - C Granziera
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - P Cattin
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
- Medical Faculty (M.L., P.C.), University of Basel, Basel, Switzerland
| | - K Parmar
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Reha Rheinfelden (K.P.), Rheinfelden, Switzerland
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12
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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: 3] [Impact Index Per Article: 3.0] [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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13
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Nigri A, Dalla Bella E, Ferraro S, Medina Carrion JP, Demichelis G, Bersano E, Consonni M, Bischof A, Stanziano M, Palermo S, Lauria G, Bruzzone MG, Papinutto N. Cervical spinal cord atrophy in amyotrophic lateral sclerosis across disease stages. Ann Clin Transl Neurol 2023; 10:213-224. [PMID: 36599092 PMCID: PMC9930423 DOI: 10.1002/acn3.51712] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/11/2022] [Accepted: 11/21/2022] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE Spinal cord degeneration is a hallmark of amyotrophic lateral sclerosis. The assessment of gray matter and white matter cervical spinal cord atrophy across clinical stages defined using the King's staging system could advance the understanding of amyotrophic lateral sclerosis progression. METHODS We assessed the in vivo spatial pattern of gray and white matter atrophy along cervical spinal cord (C2 to C6 segments) using 2D phase-sensitive inversion recovery imaging in a cohort of 44 amyotrophic lateral sclerosis patients, evaluating its change across the King's stages and the correlation with disability scored by the amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) and disease duration. A mathematical model inferring the potential onset of cervical gray matter atrophy was developed. RESULTS In amyotrophic lateral sclerosis patients at King's stage 1, significant cervical spinal cord alterations were mainly identified in gray matter, whereas they involved both gray and white matter in patients at King's stage ≥ 2. Gray and white matter areas correlated with clinical disability at all cervical segments. C3-C4 level was the segment showing early gray matter atrophy starting about 7 to 20 months before symptom onset according to our model. INTERPRETATION Our findings suggest that cervical spinal cord atrophy spreads from gray to white matter across King's stages in amyotrophic lateral sclerosis, making spinal cord magnetic resonance imaging an in vivo assessment tool to measure the progression of the disease.
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Affiliation(s)
- Anna Nigri
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Eleonora Dalla Bella
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Stefania Ferraro
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,School of Life Science and Technology, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | | | - Greta Demichelis
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Enrica Bersano
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,Department of Medical Biotechnology and Translational MedicineUniversity of MilanMilanItaly
| | - Monica Consonni
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Antje Bischof
- Weill Institute for Neurosciences, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA,Department of Neurology with Institute for Translational NeurologyUniversity Hospital MünsterMünsterGermany
| | - Mario Stanziano
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
| | - Sara Palermo
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Giuseppe Lauria
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,Department of Medical Biotechnology and Translational MedicineUniversity of MilanMilanItaly
| | | | - Nico Papinutto
- Weill Institute for Neurosciences, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
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14
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Schading S, David G, Max Emmenegger T, Achim C, Thompson A, Weiskopf N, Curt A, Freund P. Dynamics of progressive degeneration of major spinal pathways following spinal cord injury: A longitudinal study. Neuroimage Clin 2023; 37:103339. [PMID: 36758456 PMCID: PMC9939725 DOI: 10.1016/j.nicl.2023.103339] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/23/2022] [Accepted: 01/26/2023] [Indexed: 02/04/2023]
Abstract
BACKGROUND Following spinal cord injury (SCI), disease processes spread gradually along the spinal cord forming a spatial gradient with most pronounced changes located at the lesion site. However, the dynamics of this gradient in SCI patients is not established. OBJECTIVE This study tracks the spatiotemporal dynamics of remote anterograde and retrograde spinal tract degeneration in the upper cervical cord following SCI over two years utilizing quantitative MRI. METHODS Twenty-three acute SCI patients (11 paraplegics, 12 tetraplegics) and 21 healthy controls were scanned with a T1-weighted sequence for volumetry and a FLASH sequence for myelin-sensitive magnetization transfer saturation (MTsat) of the upper cervical cord. We estimated myelin content from MTsat maps within the corticospinal tracts (CST) and dorsal columns (DC) and measured spinal cord atrophy by means of left-right width (LRW) and anterior-posterior width (APW) on the T1-weighted images across cervical levels C1-C3. MTsat in the CST and LRW were considered proxies for retrograde degeneration, while MTsat in the DC and APW provided evidence for anterograde degeneration, respectively. Using regression models, we compared the temporal and spatial trajectories of these MRI readouts between tetraplegics, paraplegics, and controls over a 2-year period and assessed their associations with clinical improvement. RESULTS Linear rates and absolute differences in myelin-sensitive MTsat indicated retrograde and anterograde neurodegeneration in the CST and DC, respectively. Changes in MTsat within the CST and in LRW progressively developed over time forming a gradient towards lower cervical levels by 2 years after injury, especially in tetraplegics (change per cervical level in MTsat: -0.247 p.u./level, p = 0.034; in LRW: -0.323 mm/level, p = 0.024). MTsat within the DC was already decreased at cervical levels C1-C3 at baseline (1.5 months after injury) in both tetra- and paraplegics, while linear decreases in APW over time were similar across C1-C3, preserving the spatial gradient. The relative improvement in light touch score was associated with MTsat within the DC at baseline (rs = 0.575, p = 0.014). CONCLUSION Rostral and remote to the injury, the CST and DC show ongoing structural changes, indicative of myelin reductions and atrophy within 2 years after SCI. While anterograde degeneration in the DC was already detectable uniformly at C1-C3 early following SCI, retrograde degeneration in the CST developed over time revealing specific spatial and temporal neurodegenerative gradients. Disentangling and quantifying such dynamic pathological processes may provide biomarkers for regenerative and remyelinating therapies along entire spinal pathways.
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Affiliation(s)
- Simon Schading
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Gergely David
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Tim Max Emmenegger
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Cristian Achim
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Alan Thompson
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - 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
| | - Armin Curt
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - 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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15
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Rezende TJR, Adanyeguh IM, Arrigoni F, Bender B, Cendes F, Corben LA, Deistung A, Delatycki M, Dogan I, Egan GF, Göricke SL, Georgiou-Karistianis N, Henry PG, Hutter D, Jahanshad N, Joers JM, Lenglet C, Lindig T, Martinez ARM, Martinuzzi A, Paparella G, Peruzzo D, Reetz K, Romanzetti S, Schöls L, Schulz JB, Synofzik M, Thomopoulos SI, Thompson PM, Timmann D, Harding IH, França MC. Progressive Spinal Cord Degeneration in Friedreich's Ataxia: Results from ENIGMA-Ataxia. Mov Disord 2023; 38:45-56. [PMID: 36308733 PMCID: PMC9852007 DOI: 10.1002/mds.29261] [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: 06/09/2022] [Revised: 08/23/2022] [Accepted: 10/04/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Spinal cord damage is a hallmark of Friedreich's ataxia (FRDA), but its progression and clinical correlates remain unclear. OBJECTIVE The objective of this study was to perform a characterization of cervical spinal cord structural damage in a large multisite FRDA cohort. METHODS We performed a cross-sectional analysis of cervical spinal cord (C1-C4) cross-sectional area (CSA) and eccentricity using magnetic resonance imaging data from eight sites within the ENIGMA-Ataxia initiative, including 256 individuals with FRDA and 223 age- and sex-matched control subjects. Correlations and subgroup analyses within the FRDA cohort were undertaken based on disease duration, ataxia severity, and onset age. RESULTS Individuals with FRDA, relative to control subjects, had significantly reduced CSA at all examined levels, with large effect sizes (d > 2.1) and significant correlations with disease severity (r < -0.4). Similarly, we found significantly increased eccentricity (d > 1.2), but without significant clinical correlations. Subgroup analyses showed that CSA and eccentricity are abnormal at all disease stages. However, although CSA appears to decrease progressively, eccentricity remains stable over time. CONCLUSIONS Previous research has shown that increased eccentricity reflects dorsal column (DC) damage, while decreased CSA reflects either DC or corticospinal tract (CST) damage, or both. Hence our data support the hypothesis that damage to the DC and damage to CST follow distinct courses in FRDA: developmental abnormalities likely define the DC, while CST alterations may be both developmental and degenerative. These results provide new insights about FRDA pathogenesis and indicate that CSA of the cervical spinal cord should be investigated further as a potential biomarker of disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Thiago JR Rezende
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Isaac M Adanyeguh
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Filippo Arrigoni
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Fernando Cendes
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Louise A Corben
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
- Bruce Lefroy Centre, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Halle (Saale), Germany
- Department of Neurology and Center for Translational and Behavioral Neuroscience “(C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Martin Delatycki
- Bruce Lefroy Centre, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Gary F Egan
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
- Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
| | - Sophia L Göricke
- Institute of Diagnostic and Interventional Radiology and Neuroradiology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Nellie Georgiou-Karistianis
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Diane Hutter
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - James M Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tobias Lindig
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Alberto RM Martinez
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Andrea Martinuzzi
- Scientific Institute, IRCCS Eugenio Medea, Conegliano-Pieve di Soligo Research Centre, Conegliano, Italy
| | - Gabriella Paparella
- Scientific Institute, IRCCS Eugenio Medea, Conegliano-Pieve di Soligo Research Centre, Conegliano, Italy
| | - Denis Peruzzo
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Sandro Romanzetti
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Ludger Schöls
- Department of Neurodegenerative Diseases, Center of Neurology and Hertie Institute for Clinical Brain Research,University Tuübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Jörg B Schulz
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Center of Neurology and Hertie Institute for Clinical Brain Research,University Tuübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dagmar Timmann
- Department of Neurology and Center for Translational and Behavioral Neuroscience “(C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Ian H Harding
- Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Marcondes C. França
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
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16
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Tsagkas C, Huck-Horvath A, Cagol A, Haas T, Barakovic M, Amann M, Ruberte E, Melie-Garcia L, Weigel M, Pezold S, Schlaeger R, Kuhle J, Sprenger T, Kappos L, Bieri O, Cattin P, Granziera C, Parmar K. Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis. Mult Scler 2022; 29:702-718. [PMID: 36550626 DOI: 10.1177/13524585221139152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Spinal cord (SC) gray and white matter pathology plays a central role in multiple sclerosis (MS). OBJECTIVE We aimed to investigate the extent, pattern, and clinical relevance of SC gray and white matter atrophy in vivo. METHODS 39 relapsing-remitting patients (RRMS), 40 progressive MS patients (PMS), and 24 healthy controls (HC) were imaged at 3T using the averaged magnetization inversion recovery acquisitions sequence. Total and lesional cervical gray and white matter, and posterior (SCPH) and anterior horn (SCAH) areas were automatically quantified. Clinical assessment included the expanded disability status scale, timed 25-foot walk test, nine-hole peg test, and the 12-item MS walking scale. RESULTS PMS patients had significantly reduced cervical SCAH - but not SCPH - areas compared with HC and RRMS (both p < 0.001). In RRMS and PMS, the cervical SCAH areas increased significantly less in the region of cervical SC enlargement compared with HC (all p < 0.001). This reduction was more pronounced in PMS compared with RRMS (both p < 0.001). In PMS, a lower cervical SCAH area was the most important magnetic resonance imaging (MRI)-variable for higher disability scores. CONCLUSION MS patients show clinically relevant cervical SCAH atrophy, which is more pronounced in PMS and at the level of cervical SC enlargement.
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Affiliation(s)
- Charidimos Tsagkas
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Antal Huck-Horvath
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Tanja Haas
- Division of Radiological Physics, Department of Radiology, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Michael Amann
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Department of Biomedical Engineering, University of Basel, Basel, Switzerland; Medical Image Analysis Center AG, Basel, Switzerland
| | - Esther Ruberte
- Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Medical Image Analysis Center AG, Basel, Switzerland
| | - Lester Melie-Garcia
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Department of Biomedical Engineering, University of Basel, Basel, Switzerland/Division of Radiological Physics, Department of Radiology, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Simon Pezold
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Regina Schlaeger
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Till Sprenger
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Department of Neurology, DKD HELIOS Klinik Wiesbaden, Wiesbaden, Germany
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Oliver Bieri
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland/Division of Radiological Physics, Department of Radiology, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Philippe Cattin
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Katrin Parmar
- Neurologic Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland/Translational Imaging in Neurology (ThINk) Basel, Departments of Head, Spine and Neuromedicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Reha Rheinfelden, Rheinfelden, Switzerland
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17
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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: 0] [Impact Index Per Article: 0] [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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18
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Shinn R, Riffe A, Edwards M, Rossmeisl J. MRI diffusion tensor imaging scalar values in dogs with intervertebral disc herniation: A comparison between manual and semiautomated region of interest methods. Vet Radiol Ultrasound 2022; 63:753-762. [PMID: 35789512 DOI: 10.1111/vru.13126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 04/13/2022] [Accepted: 04/14/2022] [Indexed: 11/29/2022] Open
Abstract
Magnetic resonance imaging (MRI) diffusion tensor imaging (DTI) measures have been described as methods for quantifying spinal cord injury and predicting outcome in dogs with intervertebral disc herniation (IVDH); however, studies comparing methods for selecting regions of interest (ROIs) are currently lacking. The aims of this retrospective, methods comparison, observational study were to compare DTI measurements acquired using manual (mROI) versus semiautomated ROI (sROI) methods and to compare DTI measurements with patient outcomes. Magnetic resonance imaging scans that included DTI pulse sequences were retrieved for 65 dogs with confirmed IVDH. Regions of interest were placed at one vertebral length cranial and caudal to the region of spinal cord compression (RSCC) using the mROI and sROI methods. Scalar values based on the mROI and sROI methods were compared. There was a significant difference for all DTI measures (P < 0.0001), where fractional anisotropy was higher (95% confidence interval [CI]: 0.15, 0.19) and mean diffusivity (MD; CI: -0.41, -0.35), axial diffusivity (AD; CI: -0.47, -0.36) and radial diffusivity (RD; CI: -0.36, -0.27) were lower for the mROI than for the sROI. For both the mROI and sROI, MD, AD, and RD were significantly lower (p < 0.05) at the RSCC in paraplegic dogs that did not regain motor function. The findings indicated that DTI methods for quantifying SCI using open source software and ROI were feasible for use in dogs with IVDH; however, values based on sROI methods differed from values based on mROI methods. Some DTI measures based on both the mROI and sROI methods were predictive of poor patient outcome.
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Affiliation(s)
- Richard Shinn
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Ashley Riffe
- VCA Alameda East Veterinary Hospital, Denver, Colorado, USA
| | - Michael Edwards
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - John Rossmeisl
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
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19
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Simultaneous assessment of regional distributions of atrophy across the neuraxis in MS patients. Neuroimage Clin 2022; 34:102985. [PMID: 35316667 PMCID: PMC8938332 DOI: 10.1016/j.nicl.2022.102985] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND The ability to assess brain and cord atrophy simultaneously would improve the efficiency of MRI to track disease evolution. OBJECTIVE To test a promising tool to simultaneously map the regional distribution of atrophy in multiple sclerosis (MS) patients across the brain and cord. METHODS Voxel-based morphometry combined with a statistical parametric mapping probabilistic brain-spinal cord (SPM-BSC) template was applied to standard T1-weighted magnetic resonance imaging (MRI) scans covering the brain and cervical cord from 37 MS patients and 20 healthy controls (HC). We also measured the cord area at C2-C3 with a semi-automatic segmentation method using (i) the same T1-weighted acquisitions used for the new voxel-based analysis and (ii) dedicated spinal cord phase sensitive inversion recovery (PSIR) acquisitions. Cervical cord findings derived from the three approaches were compared to each other and the goodness to fit to clinical scores was assessed by regression analyses. RESULTS The SPM-BSC approach revealed a severity-dependent pattern of atrophy across the cervical cord and thalamus in MS patients when compared to HCs. The magnitude of cord atrophy was confirmed by the semi-automatic extraction approach at C2-C3 using both standard brain T1-weighted and advanced cord dedicated acquisitions. Associations between atrophy of cord and thalamus with disability and cognition were demonstrated. CONCLUSION Atrophy in the brain and cervical cord of MS patients can be identified simultaneously and rapidly at the voxel-level. The SPM-BSC approach yields similar results as available standard processing tools with the added advantage of performing the analysis simultaneously and faster.
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20
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Davies BM, Mowforth O, Gharooni AA, Tetreault L, Nouri A, Dhillon RS, Bednarik J, Martin AR, Young A, Takahashi H, Boerger TF, Newcombe VFJ, Zipser CM, Freund P, Koljonen PA, Rodrigues-Pinto R, Rahimi-Movaghar V, Wilson JR, Kurpad SN, Fehlings MG, Kwon BK, Harrop JS, Guest JD, Curt A, Kotter MRN. A New Framework for Investigating the Biological Basis of Degenerative Cervical Myelopathy [AO Spine RECODE-DCM Research Priority Number 5]: Mechanical Stress, Vulnerability and Time. Global Spine J 2022; 12:78S-96S. [PMID: 35174728 PMCID: PMC8859710 DOI: 10.1177/21925682211057546] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
STUDY DESIGN Literature Review (Narrative). OBJECTIVE To propose a new framework, to support the investigation and understanding of the pathobiology of DCM, AO Spine RECODE-DCM research priority number 5. METHODS Degenerative cervical myelopathy is a common and disabling spinal cord disorder. In this perspective, we review key knowledge gaps between the clinical phenotype and our biological models. We then propose a reappraisal of the key driving forces behind DCM and an individual's susceptibility, including the proposal of a new framework. RESULTS Present pathobiological and mechanistic knowledge does not adequately explain the disease phenotype; why only a subset of patients with visualized cord compression show clinical myelopathy, and the amount of cord compression only weakly correlates with disability. We propose that DCM is better represented as a function of several interacting mechanical forces, such as shear, tension and compression, alongside an individual's vulnerability to spinal cord injury, influenced by factors such as age, genetics, their cardiovascular, gastrointestinal and nervous system status, and time. CONCLUSION Understanding the disease pathobiology is a fundamental research priority. We believe a framework of mechanical stress, vulnerability, and time may better represent the disease as a whole. Whilst this remains theoretical, we hope that at the very least it will inspire new avenues of research that better encapsulate the full spectrum of disease.
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Affiliation(s)
| | - Oliver Mowforth
- Department of Neurosurgery, University of Cambridge, Cambridge, UK
| | | | - Lindsay Tetreault
- New York University, Langone Health, Graduate Medical Education, Department of Neurology, New York, NY, USA
| | - Aria Nouri
- Division of Neurosurgery, Geneva University Hospitals, University of Geneva, Genève, Switzerland
| | - Rana S. Dhillon
- Department of Neurosurgery, St Vincent’s Hospital Melbourne, Fitzroy, VIC, Australia
| | - Josef Bednarik
- Department of Neurology, University Hospital Brno and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Allan R. Martin
- Department of Neurosurgery, University of California Davis, Sacramento, CA, USA
| | - Adam Young
- Department of Neurosurgery, University of Cambridge, Cambridge, UK
| | - Hitoshi Takahashi
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Timothy F. Boerger
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI, USA
| | - Virginia FJ Newcombe
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Carl Moritz Zipser
- University Spine Center, Balgrist University Hospital, Zurich, Switzerland
| | - Patrick Freund
- University Spine Center, Balgrist University Hospital, Zurich, Switzerland
| | - Paul Aarne Koljonen
- Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ricardo Rodrigues-Pinto
- Spinal Unit (UVM), Department of Orthopaedics, Centro Hospitalar Universitário do Porto - Hospital de Santo António, Porto, Portugal
- Instituto de Ciências Biomédicas Abel Salazar, Porto, Portugal
| | - Vafa Rahimi-Movaghar
- Department of Neurosurgery, Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Jefferson R. Wilson
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Shekar N Kurpad
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI, USA
| | - Michael G. Fehlings
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Brian K. Kwon
- Vancouver Spine Surgery Institute, Department of Orthopedics, The University of British Columbia, Vancouver, BC, Canada
| | - James S. Harrop
- Department of Neurological Surgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - James D. Guest
- Department of Neurosurgery and the Miami Project to Cure Paralysis, The Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Armin Curt
- University Spine Center, Balgrist University Hospital, Zurich, Switzerland
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21
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David G, Vallotton K, Hupp M, Curt A, Freund P, Seif M. Extent of cord pathology in the lumbosacral enlargement in non-traumatic versus traumatic spinal cord injury. J Neurotrauma 2022; 39:639-650. [PMID: 35018824 DOI: 10.1089/neu.2021.0389] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
This study compares remote neurodegenerative changes caudal to a cervical injury in degenerative cervical myelopathy (DCM) (i.e., non-traumatic) and incomplete traumatic spinal cord injury (tSCI) patients, using MRI-based tissue area measurements and diffusion tensor imaging (DTI). Eighteen mild to moderate DCM patients with sensory impairments (mJOA score: 16.2±1.9), 14 incomplete tetraplegic tSCI patients (AIS C&D), and 20 healthy controls were recruited. All participants received DTI and T2*-weighted scans in the lumbosacral enlargement (caudal to injury) and at C2/C3 (rostral to injury). MRI readouts included DTI metrics in the white matter (WM) columns and cross-sectional WM and gray matter area. One-way ANOVA with Tukey's post-hoc comparison (p<0.05) was used to assess group differences. In the lumbosacral enlargement, compared to DCM, tSCI patients exhibited decreased fractional anisotropy in the lateral (tSCI vs. DCM, -11.9%, p=0.007) and ventral WM column (-8.0%, p=0.021), and showed trend toward lower values in the dorsal column (-8.9%, p=0.068). At C2/C3, compared to controls, fractional anisotropy was lower in both groups in the dorsal (DCM vs. controls, -7.9%, p=0.024; tSCI vs. controls, -10.0%, p=0.007) and in the lateral column (DCM: -6.2%, p=0.039; tSCI: -13.3%, p<0.001), while tSCI patients had lower fractional anisotropy than DCM patients in the lateral column (-7.6%, p=0.029). WM areas were not different between patient groups but were lower compared to controls in the lumbosacral enlargement (DCM: -16.9%, p<0.001; tSCI, -10.5%, p=0.043) and at C2/C3 (DCM: -16.0%, p<0.001; tSCI: -18.1%, p<0.001). In conclusion, mild to moderate DCM and incomplete tSCI lead to similar degree of degeneration of the dorsal and lateral columns at C2/C3, but tSCI results in more widespread white matter damage in the lumbosacral enlargement. These remote changes are likely to contribute to the patients' impairment and recovery. DTI is a sensitive tool to assess remote pathological changes in DCM and tSCI patients.
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Affiliation(s)
- Gergely David
- University of Zurich, Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland.,University Medical Center Hamburg-Eppendorf, 37734, Department of Systems Neuroscience, Hamburg, Germany;
| | - Kevin Vallotton
- University of Zurich, Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland;
| | - Markus Hupp
- University of Zurich, 27217, Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland;
| | - Armin Curt
- University of Zurich, 27217, Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland;
| | - Patrick Freund
- University of Zurich, 27217, Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland.,UCL Institute of Neurology, 61554, Department of Brain Repair and Rehabilitation, London, United Kingdom of Great Britain and Northern Ireland.,UCL Institute of Neurology, 61554, Wellcome Trust Centre for Neuroimaging, London, United Kingdom of Great Britain and Northern Ireland.,Max Planck Institute for Human Cognitive and Brain Sciences, 27184, Department of Neurophysics, Leipzig, Germany;
| | - Maryam Seif
- University of Zurich, 27217, Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland.,Max Planck Institute for Human Cognitive and Brain Sciences, 27184, Leipzig, Department of Neurophysics, Germany;
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22
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Bischof A, Papinutto N, Keshavan A, Rajesh A, Kirkish G, Zhang X, Mallott JM, Asteggiano C, Sacco S, Gundel TJ, Zhao C, Stern WA, Caverzasi E, Zhou Y, Gomez R, Ragan NR, Santaniello A, Zhu AH, Juwono J, Bevan CJ, Bove RM, Crabtree E, Gelfand JM, Goodin DS, Graves JS, Green AJ, Oksenberg JR, Waubant E, Wilson MR, Zamvil SS, Cree BA, Hauser SL, Henry RG. Spinal cord atrophy predicts progressive disease in relapsing multiple sclerosis. Ann Neurol 2021; 91:268-281. [PMID: 34878197 PMCID: PMC8916838 DOI: 10.1002/ana.26281] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 12/04/2021] [Accepted: 12/06/2021] [Indexed: 11/06/2022]
Abstract
Objective A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS). Methods From a single‐center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12‐year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion. Results Patients who developed SPMS showed faster cord atrophy rates (−2.19%/yr) at least 4 years before conversion compared to their RRMS matches (−0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (−1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (−1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively. Interpretation Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 2022;91:268–281
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Affiliation(s)
- Antje Bischof
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Nico Papinutto
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Anisha Keshavan
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Anand Rajesh
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Gina Kirkish
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Xinheng Zhang
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Jacob M Mallott
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Carlo Asteggiano
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Simone Sacco
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Tristan J Gundel
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Chao Zhao
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - William A Stern
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Eduardo Caverzasi
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Yifan Zhou
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Refujia Gomez
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Nicholas R Ragan
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Adam Santaniello
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Alyssa H Zhu
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Jeremy Juwono
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Carolyn J Bevan
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Riley M Bove
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Elizabeth Crabtree
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Jeffrey M Gelfand
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Douglas S Goodin
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Jennifer S Graves
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Ari J Green
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Jorge R Oksenberg
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Emmanuelle Waubant
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Michael R Wilson
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Scott S Zamvil
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
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- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Bruce A Cree
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Stephen L Hauser
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
| | - Roland G Henry
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, 675, Nelson Rising Lane, 94158, San Francisco, California, USA
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23
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Cohen-Adad J, Alonso-Ortiz E, Abramovic M, Arneitz C, Atcheson N, Barlow L, Barry RL, Barth M, Battiston M, Büchel C, Budde M, Callot V, Combes AJE, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak A, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Gandini Wheeler-Kingshott CAM, Germani G, Gilbert G, Giove F, Gros C, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers J, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler HH, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Labounek R, Laganà MM, Laule C, Law CS, Lenglet C, Leutritz T, Liu Y, Llufriu S, Mackey S, Martinez-Heras E, Mattera L, Nestrasil I, O'Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley G, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber Ii KA, Weiskopf N, Wise RG, Wyss PO, Xu J. Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Sci Data 2021; 8:219. [PMID: 34400655 PMCID: PMC8368310 DOI: 10.1038/s41597-021-00941-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 03/26/2021] [Indexed: 12/21/2022] Open
Abstract
In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.
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Affiliation(s)
- Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada.
- Mila - Quebec AI Institute, Montreal, QC, Canada.
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Carina Arneitz
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Nicole Atcheson
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Laura Barlow
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Markus Barth
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Christian Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin De Leener
- Department of Computer and Software Engineering, Polytechnique Montreal, Montreal, Canada
- CHU Sainte-Justine Research Centre, Montreal, QC, Canada
| | - Maxime Descoteaux
- Centre de Recherche CHUS, CIMS, Sherbrooke, Canada
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, Canada
| | | | - Marek Dostál
- UHB - University Hospital Brno and Masaryk University, Department of Radiology and Nuclear Medicine, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Adam Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Falk Eippert
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Karla R Epperson
- Richard M. Lucas Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Kevin S Epperson
- Richard M. Lucas Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University of Zurich, Zurich, Switzerland
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Giancarlo Germani
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Francesco Grussu
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Multimodal and functional imaging laboratory, Central European Institute of Technology (CEITEC), Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, the University of Tokyo, Tokyo, Japan
| | - Haleh Karbasforoushan
- Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA
| | - Miloš Keřkovský
- UHB - University Hospital Brno and Masaryk University, Department of Radiology and Nuclear Medicine, Brno, Czech Republic
| | - Ali Khatibi
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
| | - Joo-Won Kim
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nawal Kinany
- Institute of Bioengineering/Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Hagen H Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department Of Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Petr Kudlička
- Multimodal and functional imaging laboratory, Central European Institute of Technology (CEITEC), Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Nyoman D Kurniawan
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Slawomir Kusmia
- CUBRIC, Cardiff University, Wales, UK
- Centre for Medical Image Computing (CMIC), Medical Physics and Biomedical Engineering Department, University College London, London, UK
- Epilepsy Society MRI Unit, Chalfont St Peter, UK
| | - René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Departments of Neurology and Biomedical Engineering, University Hospital Olomouc, Olomouc, Czech Republic
| | | | - Cornelia Laule
- Departments of Radiology, Pathology & Laboratory Medicine, Physics & Astronomy; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
| | - Christine S Law
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Sara Llufriu
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eloy Martinez-Heras
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Genève, 1202, Geneva, Switzerland
| | - Igor Nestrasil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nico Papinutto
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Neuroradiology Section, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Todd B Parrish
- Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Medical Physics and Biomedical Engineering Department, University College London, London, UK
- E-health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Àlex Rovira
- Neuroradiology Section, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Marc J Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Rebecca S Samson
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Giovanni Savini
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alan C Seifert
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alex K Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zachary A Smith
- University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Y Suzuki
- Department of Radiology, the University of Tokyo, Tokyo, Japan
| | | | - Alexandra Tinnermann
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University and University Hospital Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Institute of Bioengineering/Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Kenneth A Weber Ii
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - 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
| | - Richard G Wise
- CUBRIC, Cardiff University, Wales, UK
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio University" of Chieti-Pescara, Chieti-Pescara, Italy
| | - Patrik O Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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24
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Kesenheimer EM, Wendebourg MJ, Weigel M, Weidensteiner C, Haas T, Richter L, Sander L, Horvath A, Barakovic M, Cattin P, Granziera C, Bieri O, Schlaeger R. Normalization of Spinal Cord Total Cross-Sectional and Gray Matter Areas as Quantified With Radially Sampled Averaged Magnetization Inversion Recovery Acquisitions. Front Neurol 2021; 12:637198. [PMID: 33841307 PMCID: PMC8027254 DOI: 10.3389/fneur.2021.637198] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 02/05/2021] [Indexed: 11/19/2022] Open
Abstract
Background: MR imaging of the spinal cord (SC) gray matter (GM) at the cervical and lumbar enlargements' level may be particularly informative in lower motor neuron disorders, e. g., spinal muscular atrophy, but also in other neurodegenerative or autoimmune diseases affecting the SC. Radially sampled averaged magnetization inversion recovery acquisition (rAMIRA) is a novel approach to perform SC imaging in clinical settings with favorable contrast and is well-suited for SC GM quantitation. However, before applying rAMIRA in clinical studies, it is important to understand (i) the sources of inter-subject variability of total SC cross-sectional areas (TCA) and GM area (GMA) measurements in healthy subjects and (ii) their relation to age and sex to facilitate the detection of pathology-associated changes. In this study, we aimed to develop normalization strategies for rAMIRA-derived SC metrics using skull and spine-based metrics to reduce anatomical variability. Methods: Sixty-one healthy subjects (age range 11–93 years, 37.7% women) were investigated with axial two-dimensional rAMIRA imaging at 3T MRI. Cervical and thoracic levels including the level of the cervical (C4/C5) and lumbar enlargements (Tmax) were examined. SC T2-weighted sagittal images and high-resolution 3D whole-brain T1-weighted images were acquired. TCA and GMAs were quantified. Anatomical variables with associations of |r| > 0.30 in univariate association with SC areas, and age and sex were used to construct normalization models using backward selection with TCAC4/C5 as outcome. The effect of the normalization was assessed by % relative standard deviation (RSD) reductions. Results: Mean inter-individual variability and the SD of the SC area metrics were considerable: TCAC4/5: 8.1%/9.0; TCATmax: 8.9%/6.5; GMAC4/C5: 8.6%/2.2; GMATmax: 12.2%/3.8. Normalization based on sex, brain WM volume, and spinal canal area resulted in RSD reductions of 23.7% for TCAs and 12.0% for GM areas at C4/C5. Normalizations based on the area of spinal canal alone resulted in RSD reductions of 10.2% for TCAs and 9.6% for GM areas at C4/C5, respectively. Discussion: Anatomic inter-individual variability of SC areas is substantial. This study identified effective normalization models for inter-subject variability reduction in TCA and SC GMA in healthy subjects based on rAMIRA imaging.
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Affiliation(s)
- Eva M Kesenheimer
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Department of Clinical Research, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Maria Janina Wendebourg
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Department of Clinical Research, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Claudia Weidensteiner
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Tanja Haas
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Laura Richter
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Department of Clinical Research, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Laura Sander
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Department of Clinical Research, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Antal Horvath
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Philippe Cattin
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Cristina Granziera
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Regina Schlaeger
- Neurologic Clinic and Policlinic, University Hospital Basel, Basel, Switzerland.,Department of Clinical Research, University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Medicine and Biomedical Engineering, Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
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25
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Sander L, Horvath A, Pezold S, Andermatt S, Amann M, Sinnecker T, Wendebourg MJ, Kesenheimer E, Yaldizli Ö, Kappos L, Granziera C, Wuerfel J, Cattin P, Schlaeger R. Improving Accuracy of Brainstem MRI Volumetry: Effects of Age and Sex, and Normalization Strategies. Front Neurosci 2021; 14:609422. [PMID: 33424541 PMCID: PMC7785816 DOI: 10.3389/fnins.2020.609422] [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: 09/23/2020] [Accepted: 11/30/2020] [Indexed: 12/04/2022] Open
Abstract
Background: Brainstem-mediated functions are impaired in neurodegenerative diseases and aging. Atrophy can be visualized by MRI. This study investigates extrinsic sources of brainstem volume variability, intrinsic sources of anatomical variability, and the influence of age and sex on the brainstem volumes in healthy subjects. We aimed to develop efficient normalization strategies to reduce the effects of intrinsic anatomic variability on brainstem volumetry. Methods: Brainstem segmentation was performed from MPRAGE data using our deep-learning-based brainstem segmentation algorithm MD-GRU. The extrinsic variability of brainstem volume assessments across scanners and protocols was investigated in two groups comprising 11 (median age 33.3 years, 7 women) and 22 healthy subjects (median age 27.6 years, 50% women) scanned twice and compared using Dice scores. Intrinsic anatomical inter-individual variability and age and sex effects on brainstem volumes were assessed in segmentations of 110 healthy subjects (median age 30.9 years, range 18–72 years, 53.6% women) acquired on 1.5T (45%) and 3T (55%) scanners. The association between brainstem volumes and predefined anatomical covariates was studied using Pearson correlations. Anatomical variables with associations of |r| > 0.30 as well as the variables age and sex were used to construct normalization models using backward selection. The effect of the resulting normalization models was assessed by % relative standard deviation reduction and by comparing the inter-individual variability of the normalized brainstem volumes to the non-normalized values using paired t- tests with Bonferroni correction. Results: The extrinsic variability of brainstem volumetry across different field strengths and imaging protocols was low (Dice scores > 0.94). Mean inter-individual variability/SD of total brainstem volumes was 9.8%/7.36. A normalization based on either total intracranial volume (TICV), TICV and age, or v-scale significantly reduced the inter-individual variability of total brainstem volumes compared to non-normalized volumes and similarly reduced the relative standard deviation by about 35%. Conclusion: The extrinsic variability of the novel brainstem segmentation method MD-GRU across different scanners and imaging protocols is very low. Anatomic inter-individual variability of brainstem volumes is substantial. This study presents efficient normalization models for variability reduction in brainstem volumetry in healthy subjects.
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Affiliation(s)
- Laura Sander
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Antal Horvath
- Department of Biomedical Engineering, Center for Medical Image Analysis & Navigation (CIAN), University of Basel, Allschwil, Switzerland
| | - Simon Pezold
- Department of Biomedical Engineering, Center for Medical Image Analysis & Navigation (CIAN), University of Basel, Allschwil, Switzerland
| | - Simon Andermatt
- Department of Biomedical Engineering, Center for Medical Image Analysis & Navigation (CIAN), University of Basel, Allschwil, Switzerland
| | - Michael Amann
- Department of Biomedical Engineering, Medical Image Analysis Center (MIAC AG) and qbig, University of Basel, Basel, Switzerland
| | - Tim Sinnecker
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Department of Biomedical Engineering, Medical Image Analysis Center (MIAC AG) and qbig, University of Basel, Basel, Switzerland
| | - Maria J Wendebourg
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Eva Kesenheimer
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Özgür Yaldizli
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Department of Biomedical Engineering, Medical Image Analysis Center (MIAC AG) and qbig, University of Basel, Basel, Switzerland
| | - Philippe Cattin
- Department of Biomedical Engineering, Center for Medical Image Analysis & Navigation (CIAN), University of Basel, Allschwil, Switzerland
| | - Regina Schlaeger
- Neurologic Clinic and Policlinic, Departments of Medicine and Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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Bautin P, Cohen-Adad J. Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants. NEUROIMAGE: CLINICAL 2021; 32:102849. [PMID: 34624638 PMCID: PMC8503570 DOI: 10.1016/j.nicl.2021.102849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/07/2021] [Accepted: 09/28/2021] [Indexed: 11/20/2022] Open
Abstract
Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy. Simulate spinal cord atrophy and scan-rescan variability. Fully automated analysis method available on an open access database. Evaluation of sample size and inter/intra-subject variability for T1w and T2w images.
Spinal cord atrophy is a well-known biomarker in multiple sclerosis (MS) and other diseases. It is measured by segmenting the spinal cord on an MRI image and computing the average cross-sectional area (CSA) over a few slices. Introduced about 25 years ago, this procedure is highly sensitive to the quality of the segmentation and is prone to rater-bias. Recently, fully-automated spinal cord segmentation methods, which remove the rater-bias and enable the automated analysis of large populations, have been introduced. A lingering question related to these automated methods is: How reliable are they at detecting atrophy? In this study, we evaluated the precision and accuracy of automated atrophy measurements by simulating scan-rescan experiments. Spinal cord MRI data from the open-access spine-generic project were used. The dataset aggregates 42 sites worldwide and consists of 260 healthy subjects and includes T1w and T2w contrasts. To simulate atrophy, each volume was globally rescaled at various scaling factors. Moreover, to simulate patient repositioning, random rigid transformations were applied. Using the DeepSeg algorithm from the Spinal Cord Toolbox, the spinal cord was segmented and vertebral levels were identified. Then, the average CSA between C3-C5 vertebral levels was computed for each Monte Carlo sample, allowing us to derive measures of atrophy, intra/inter-subject variability, and sample-size calculations. The minimum sample size required to detect an atrophy of 2% between unpaired study arms, commonly seen in MS studies, was 467 +/− 13.9 using T1w and 467 +/− 3.2 using T2w images. The minimum sample size to detect a longitudinal atrophy (between paired study arms) of 0.8% was 60 +/− 25.1 using T1w and 10 +/− 1.2 using T2w images. At the intra-subject level, the estimated CSA, observed in this study, showed good precision compared to other studies with COVs (across Monte Carlo transformations) of 0.8% for T1w and 0.6% for T2w images. While these sample sizes seem small, we would like to stress that these results correspond to a “best case” scenario, in that the dataset used here was of particularly good quality and the model for simulating atrophy does not encompass all the variability met in real-life datasets. The simulated atrophy and scan-rescan variability may over-simplify the biological reality. The proposed framework is open-source and available at https://csa-atrophy.readthedocs.io/.
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Affiliation(s)
- Paul Bautin
- 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, CRIUGM, Université de Montréal, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada.
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Azzarito M, Kyathanahally SP, Balbastre Y, Seif M, Blaiotta C, Callaghan MF, Ashburner J, Freund P. Simultaneous voxel-wise analysis of brain and spinal cord morphometry and microstructure within the SPM framework. Hum Brain Mapp 2020; 42:220-232. [PMID: 32991031 PMCID: PMC7721239 DOI: 10.1002/hbm.25218] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 08/05/2020] [Accepted: 09/09/2020] [Indexed: 12/12/2022] Open
Abstract
To validate a simultaneous analysis tool for the brain and cervical cord embedded in the statistical parametric mapping (SPM) framework, we compared trauma-induced macro- and microstructural changes in spinal cord injury (SCI) patients to controls. The findings were compared with results obtained from existing processing tools that assess the brain and spinal cord separately. A probabilistic brain-spinal cord template (BSC) was generated using a generative semi-supervised modelling approach. The template was incorporated into the pre-processing pipeline of voxel-based morphometry and voxel-based quantification analyses in SPM. This approach was validated on T1-weighted scans and multiparameter maps, by assessing trauma-induced changes in SCI patients relative to controls and comparing the findings with the outcome from existing analytical tools. Consistency of the MRI measures was assessed using intraclass correlation coefficients (ICC). The SPM approach using the BSC template revealed trauma-induced changes across the sensorimotor system in the cord and brain in SCI patients. These changes were confirmed with established approaches covering brain or cord, separately. The ICC in the brain was high within regions of interest, such as the sensorimotor cortices, corticospinal tracts and thalamus. The simultaneous voxel-wise analysis of brain and cervical spinal cord was performed in a unique SPM-based framework incorporating pre-processing and statistical analysis in the same environment. Validation based on a SCI cohort demonstrated that the new processing approach based on the brain and cord is comparable to available processing tools, while offering the advantage of performing the analysis simultaneously across the neuraxis.
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Affiliation(s)
- Michela Azzarito
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sreenath P Kyathanahally
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Yaël Balbastre
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Claudia Blaiotta
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - John Ashburner
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, UK
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Papinutto N, Cordano C, Asteggiano C, Caverzasi E, Mandelli ML, Lauricella M, Yabut N, Neylan M, Kirkish G, Gorno-Tempini ML, Henry RG. MRI Measurement of Upper Cervical Spinal Cord Cross-Sectional Area in Children. J Neuroimaging 2020; 30:598-602. [PMID: 32639671 DOI: 10.1111/jon.12758] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 06/24/2020] [Accepted: 06/26/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND AND PURPOSE Neurological and neurodegenerative diseases can affect the spinal cord (SC) of pediatric patients. Magnetic resonance imaging (MRI) allows for in vivo quantification of SC atrophy via cross-sectional area (CSA). The study of CSA values in the general population is important to disentangle disease-related changes from intersubject variability. This study aimed at providing normative values for cervical CSA in children, extending our previous work performed with adults. METHODS Seventy-eight children (age 7-17 years) were selected from a Developmental Dyslexia study. All subjects underwent a 3T brain MRI session and any incidental findings were reported on the scans. A sagittal 1 mm3 3-dimensional T1 -weighted brain acquisition extended to the upper cervical cord was used to measure CSA at C2-C3, as well as spinal canal area and skull volume (V-scale). These three metrics were linearly fitted as a function of age to extract trends and percentage annual changes. Sex differences of CSA were assessed using least squares regression analyses, adjusting for age. We tested normalization strategies proven to be effective in reducing the intersubject variability of adults' CSA. RESULTS CSA changed as a function of age at a faster rate when compared with skull volume (CSA: 1.82% increase, V-scale: .60% reduction). Sex had a statistically significant effect on CSA. Normalization methods based on canal area and skull volume reduced the CSA intersubject variability up to 16.84%. CONCLUSIONS We present CSA normative values in a large cohort of children, reporting on sources of intersubject variability and how to reduce them applying normalization methods previously developed.
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Affiliation(s)
- Nico Papinutto
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Christian Cordano
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Carlo Asteggiano
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Eduardo Caverzasi
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Maria Luisa Mandelli
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Michael Lauricella
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Nicole Yabut
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Matthew Neylan
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Gina Kirkish
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Maria Luisa Gorno-Tempini
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
| | - Roland G Henry
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, CA
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