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Valošek J, Cohen-Adad J. Reproducible Spinal Cord Quantitative MRI Analysis with the Spinal Cord Toolbox. Magn Reson Med Sci 2024; 23:307-315. [PMID: 38479843 PMCID: PMC11234946 DOI: 10.2463/mrms.rev.2023-0159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024] Open
Abstract
The spinal cord plays a pivotal role in the central nervous system, providing communication between the brain and the body and containing critical motor and sensory networks. Recent advancements in spinal cord MRI data acquisition and image analysis have shown a potential to improve the diagnostics, prognosis, and management of a variety of pathological conditions. In this review, we first discuss the significance of standardized spinal cord MRI acquisition protocol in multi-center and multi-manufacturer studies. Then, we cover open-access spinal cord MRI datasets, which are important for reproducible science and validation of new methods. Finally, we elaborate on the recent advances in spinal cord MRI data analysis techniques implemented in the open-source software package Spinal Cord Toolbox (SCT).
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Affiliation(s)
- 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, Czechia
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
- Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
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2
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Al-Shaari H, Heales CJ, Fulford J. Within-participants reliability and measurement error of magnetization transfer imaging determinations within the healthy cervical spinal cord. Radiography (Lond) 2024; 30:1085-1092. [PMID: 38772065 DOI: 10.1016/j.radi.2024.04.027] [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: 02/03/2024] [Revised: 04/15/2024] [Accepted: 04/28/2024] [Indexed: 05/23/2024]
Abstract
PURPOSE To assess the within-participant reliability and measurement error in the determination of MTR in the healthy human cervical spinal cord. METHODS AND MATERIALS A total of twenty healthy controls (10 male, mean ± sd age: 33.9 ± 3.5 years, 10 females, mean ± sd age: 47.5 ± 14.4 years), with no family history of any neurological disorders or a contraindication to MRI scanning were recruited over a period of two months. Each participant was scanned twice with a 3T MRI scanner using standard MTI sequences. Spinal Cord Toolbox (v5.4) was used for image post-processing. Data were first segmented and then registered to a template and then MTR was computed. The within-participant coefficients of variation (CV%), single and average within-participants intraclass correlation coefficients (ICC) and Bland-Altman plots were determined for MT values over the volume between the 2nd and 5th cervical vertebrae for the total WM and for specific WM regions: dorsal column (DC), ventral column (VC) and lateral column (LC). RESULTS MTR showed poor to excellent within-participant reliability for the total WM, DC, VC and LC with single/average ICC values of 0.03/0.06, 0.10/0.18, 0.39/0.75, and 0.001/0.002, respectively, and the CV% reported an acceptable variation with values less than 10%. The Bland-Altman plots showed good within-participant agreement between the scan-rescan values. CONCLUSION This study demonstrates that clinical trials using MTI technique are feasible and shows that quantitative MTI can monitor tissue changes in degenerative WM patients. IMPLICATIONS FOR PRACTICE MTI with its MTR index provide broad assessment of the integrity of white matter tissue and are being studied widely in brain as a diagnostic tool for the assessment of different neurological diseases.
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Affiliation(s)
- H Al-Shaari
- Faculty of Health and Life Sciences, Medical Imaging Department, University of Exeter, Exeter, UK; College of Applied Medical Sciences, Radiological Sciences Department, Najran University, Najran, 61441, Kingdom of Saudi Arabia.
| | - C J Heales
- Faculty of Health and Life Sciences, Medical Imaging Department, University of Exeter, Exeter, UK.
| | - J Fulford
- Faculty of Health and Life Sciences, Medical Imaging Department, University of Exeter, Exeter, UK.
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Al-Shaari H, Fulford J, Heales CJ. Diffusion tensor imaging within the healthy cervical spinal cord: Within- participants reliability and measurement error. Magn Reson Imaging 2024; 109:56-66. [PMID: 38458552 DOI: 10.1016/j.mri.2024.03.005] [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: 05/06/2023] [Revised: 03/05/2024] [Accepted: 03/05/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Diffusion tensor imaging (DTI) is a promising technique for the visualization of the cervical spinal cord (CSC) in vivo. It provides information about the tissue structure of axonal white matter, and it is thought to be more sensitive than other MR imaging techniques for the evaluation of damage to tracts in the spinal cord. AIM The purpose of this study was to determine the within-participants reliability and error magnitude of measurements of DTI metrics in healthy human CSC. METHODS A total of twenty healthy controls (10 male, mean age: 33.9 ± 3.5 years, 10 females, mean age: 47.5 ± 14.4 years), with no family history of any neurological disorders or a contraindication to MRI scanning were recruited over a period of two months. Each participant was scanned twice with an MRI 3 T scanner using standard DTI sequences. Spinal Cord Toolbox (SCT) software was used for image post-processing. Data were first corrected for motion artefact, then segmented, registered to a template, and then the DTI metrics were computed. The within-participants coefficients of variation (CV%), the single and average within-participants intraclass correlation coefficients (ICC) and Bland-Altman plots for WM, VC, DC and LC fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were determined for the cervical spinal cord (between the 2nd and 5th cervical vertebrae). RESULTS DTI metrics showed poor to excellent within-participants reliability for both single and average ICC and moderate to high reproducibility for CV%, all variation dependent on the location of the ROI. The BA plots showed good within-participants agreement between the scan-rescan values. CONCLUSION Results from this reliability study demonstrate that clinical trials using the DTI technique are feasible and that DTI, in particular regions of the cord is suitable for use for the monitoring of degenerative WM changes.
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Affiliation(s)
- Hussein Al-Shaari
- Diagnostic Radiology Department, College of Applied Medical Sciences, Najran University, Najran 61441, Saudi Arabia; Department of Medical Imaging, Faculty of Health and Life Sciences, The University of Exeter, South Cloisters, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, UK.
| | - Jon Fulford
- Department of Medical Imaging, Faculty of Health and Life Sciences, The University of Exeter, South Cloisters, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, UK.
| | - C J Heales
- Department of Medical Imaging, Faculty of Health and Life Sciences, The University of Exeter, South Cloisters, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, UK.
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Sengupta A, Mishra A, Wang F, Chen LM, Gore JC. Characteristic BOLD signals are detectable in white matter of the spinal cord at rest and after a stimulus. Proc Natl Acad Sci U S A 2024; 121:e2316117121. [PMID: 38776372 PMCID: PMC11145258 DOI: 10.1073/pnas.2316117121] [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: 09/26/2023] [Accepted: 02/16/2024] [Indexed: 05/25/2024] Open
Abstract
We report the reliable detection of reproducible patterns of blood-oxygenation-level-dependent (BOLD) MRI signals within the white matter (WM) of the spinal cord during a task and in a resting state. Previous functional MRI studies have shown that BOLD signals are robustly detectable not only in gray matter (GM) in the brain but also in cerebral WM as well as the GM within the spinal cord, but similar signals in WM of the spinal cord have been overlooked. In this study, we detected BOLD signals in the WM of the spinal cord in squirrel monkeys and studied their relationships with the locations and functions of ascending and descending WM tracts. Tactile sensory stimulus -evoked BOLD signal changes were detected in the ascending tracts of the spinal cord using a general-linear model. Power spectral analysis confirmed that the amplitude at the fundamental frequency of the response to a periodic stimulus was significantly higher in the ascending tracts than the descending ones. Independent component analysis of resting-state signals identified coherent fluctuations from eight WM hubs which correspond closely to the known anatomical locations of the major WM tracts. Resting-state analyses showed that the WM hubs exhibited correlated signal fluctuations across spinal cord segments in reproducible patterns that correspond well with the known neurobiological functions of WM tracts in the spinal cord. Overall, these findings provide evidence of a functional organization of intraspinal WM tracts and confirm that they produce hemodynamic responses similar to GM both at baseline and under stimulus conditions.
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Affiliation(s)
- Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
| | - Li Min Chen
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
| | - John C. Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN37235
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5
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Filimonova E, Abdaev M, Vasilenko I, Kubetskij Y, Prokhorov O, Rzaev J. Evaluation of the structural integrity of different spinal cord tracts with magnetization transfer ratio in degenerative cervical myelopathy. Neuroradiology 2024; 66:839-846. [PMID: 38441573 DOI: 10.1007/s00234-024-03327-w] [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: 01/17/2024] [Accepted: 02/27/2024] [Indexed: 04/21/2024]
Abstract
PURPOSE Degenerative cervical myelopathy (DCM) is a common cause of spinal cord dysfunction. In this study, we explored the potential of magnetization transfer ratio (MTR) for evaluating the structural integrity of spinal cord tracts in patients with clinically significant DCM. METHODS Fifty-three patients with DCM and 41 patients with cervical radiculopathy were evaluated using high-resolution cervical spinal cord magnetic resonance imaging (MRI), which included the magnetization transfer technique. MRI data were analyzed with the Spinal Cord Toolbox (v5.5); MTR values in each spinal tract were calculated and compared between groups after correction for patient age and sex. Correlations between MTR values and patients' clinical disability rate were also evaluated. RESULTS A statistically significant reduction in the average MTR of the spinal cord white matter, as well as the MTR of the ventral columns and lateral funiculi, was revealed in the DCM group (adjusted p < 0.01 for all comparisons). Furthermore, reductions in MTR values in the fasciculus cuneatus, spinocerebellar, rubrospinal, and reticulospinal tracts were found in patients with DCM (adjusted p < 0.01 for all comparisons). Positive correlations between the JOA score and the MTR within the ventral columns of the spinal cord (R = 0.38, adjusted p < 0.05) and the ventral spinocerebellar tract (R = 0.41, adjusted p < 0.05) were revealed. CONCLUSION The findings of our study indicate that demyelination in patients with DCM primarily affects the spinal tracts of the extrapyramidal system, and the extent of these changes is related to the severity of the condition.
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Affiliation(s)
- Elena Filimonova
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia.
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia.
| | - Mars Abdaev
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia
| | - Ivan Vasilenko
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia
| | | | | | - Jamil Rzaev
- FSBI "Federal Center of Neurosurgery", Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
- Novosibirsk State University, Novosibirsk, Russia
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6
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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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7
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Oquita R, Cuello V, Uppati S, Mannuru S, Salinas D, Dobbs M, Potter-Baker KA. Moving toward elucidating alternative motor pathway structures post-stroke: the value of spinal cord neuroimaging. Front Neurol 2024; 15:1282685. [PMID: 38419695 PMCID: PMC10899520 DOI: 10.3389/fneur.2024.1282685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024] Open
Abstract
Stroke results in varying levels of motor and sensory disability that have been linked to the neurodegeneration and neuroinflammation that occur in the infarct and peri-infarct regions within the brain. Specifically, previous research has identified a key role of the corticospinal tract in motor dysfunction and motor recovery post-stroke. Of note, neuroimaging studies have utilized magnetic resonance imaging (MRI) of the brain to describe the timeline of neurodegeneration of the corticospinal tract in tandem with motor function following a stroke. However, research has suggested that alternate motor pathways may also underlie disease progression and the degree of functional recovery post-stroke. Here, we assert that expanding neuroimaging techniques beyond the brain could expand our knowledge of alternate motor pathway structure post-stroke. In the present work, we will highlight findings that suggest that alternate motor pathways contribute to post-stroke motor dysfunction and recovery, such as the reticulospinal and rubrospinal tract. Then we review imaging and electrophysiological techniques that evaluate alternate motor pathways in populations of stroke and other neurodegenerative disorders. We will then outline and describe spinal cord neuroimaging techniques being used in other neurodegenerative disorders that may provide insight into alternate motor pathways post-stroke.
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Affiliation(s)
- Ramiro Oquita
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Victoria Cuello
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Sarvani Uppati
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Sravani Mannuru
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Daniel Salinas
- Department of Neuroscience, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Michael Dobbs
- Department of Clinical Neurosciences, College of Medicine, Florida Atlantic University, Boca Raton, FL, United States
| | - Kelsey A. Potter-Baker
- Department of Neuroscience, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
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8
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Lebret A, Lévy S, Pfender N, Farshad M, Altorfer FCS, Callot V, Curt A, Freund P, Seif M. Investigation of perfusion impairment in degenerative cervical myelopathy beyond the site of cord compression. Sci Rep 2023; 13:22660. [PMID: 38114733 PMCID: PMC10730822 DOI: 10.1038/s41598-023-49896-3] [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: 08/09/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023] Open
Abstract
The aim of this study was to determine tissue-specific blood perfusion impairment of the cervical cord above the compression site in patients with degenerative cervical myelopathy (DCM) using intravoxel incoherent motion (IVIM) imaging. A quantitative MRI protocol, including structural and IVIM imaging, was conducted in healthy controls and patients. In patients, T2-weighted scans were acquired to quantify intramedullary signal changes, the maximal canal compromise, and the maximal cord compression. T2*-weighted MRI and IVIM were applied in all participants in the cervical cord (covering C1-C3 levels) to determine white matter (WM) and grey matter (GM) cross-sectional areas (as a marker of atrophy), and tissue-specific perfusion indices, respectively. IVIM imaging resulted in microvascular volume fraction ([Formula: see text]), blood velocity ([Formula: see text]), and blood flow ([Formula: see text]) indices. DCM patients additionally underwent a standard neurological clinical assessment. Regression analysis assessed associations between perfusion parameters, clinical outcome measures, and remote spinal cord atrophy. Twenty-nine DCM patients and 30 healthy controls were enrolled in the study. At the level of stenosis, 11 patients showed focal radiological evidence of cervical myelopathy. Above the stenosis level, cord atrophy was observed in the WM (- 9.3%; p = 0.005) and GM (- 6.3%; p = 0.008) in patients compared to healthy controls. Blood velocity (BV) and blood flow (BF) indices were decreased in the ventral horns of the GM (BV: - 20.1%, p = 0.0009; BF: - 28.2%, p = 0.0008), in the ventral funiculi (BV: - 18.2%, p = 0.01; BF: - 21.5%, p = 0.04) and lateral funiculi (BV: - 8.5%, p = 0.03; BF: - 16.5%, p = 0.03) of the WM, across C1-C3 levels. A decrease in microvascular volume fraction was associated with GM atrophy (R = 0.46, p = 0.02). This study demonstrates tissue-specific cervical perfusion impairment rostral to the compression site in DCM patients. IVIM indices are sensitive to remote perfusion changes in the cervical cord in DCM and may serve as neuroimaging biomarkers of hemodynamic impairment in future studies. The association between perfusion impairment and cervical cord atrophy indicates that changes in hemodynamics caused by compression may contribute to the neurodegenerative processes in DCM.
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Affiliation(s)
- Anna Lebret
- Spinal Cord Injury Center, Balgrist University Hospital, Zürich, Switzerland
| | - Simon Lévy
- CNRS, CRMBM, Aix-Marseille University, Marseille, France
- APHM, CEMEREM, Hôpital Universitaire Timone, Marseille, France
- MR Research Collaborations, Siemens Healthcare Pty Ltd, Melbourne, Australia
| | - Nikolai Pfender
- Spinal Cord Injury Center, Balgrist University Hospital, Zürich, Switzerland
| | - Mazda Farshad
- Department of Orthopedic Surgery, Balgrist University Hospital, Zürich, Switzerland
| | | | - Virginie Callot
- CNRS, CRMBM, Aix-Marseille University, Marseille, France
- APHM, CEMEREM, Hôpital Universitaire Timone, Marseille, France
| | - Armin Curt
- Spinal Cord Injury Center, Balgrist University Hospital, Zürich, Switzerland
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, Zürich, Switzerland
- Department of Brain Repair and Rehabilitation, Wellcome Trust Center for Neuroimaging, Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Maryam Seif
- Spinal Cord Injury Center, Balgrist University Hospital, Zürich, Switzerland.
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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9
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Haynes G, Muhammad F, Khan AF, Mohammadi E, Smith ZA, Ding L. The current state of spinal cord functional magnetic resonance imaging and its application in clinical research. J Neuroimaging 2023; 33:877-888. [PMID: 37740582 DOI: 10.1111/jon.13158] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/11/2023] [Indexed: 09/24/2023] Open
Abstract
Since its development, spinal cord functional magnetic resonance imaging (fMRI) has utilized various methodologies and stimulation protocols to develop a deeper understanding of a healthy human spinal cord that lays a foundation for its use in clinical research and practice. In this review, we conducted a comprehensive literature search on spinal cord fMRI studies and summarized the recent advancements and resulting scientific achievements of spinal cord fMRI in the following three aspects: the current state of spinal cord fMRI methodologies and stimulation protocols, knowledge about the healthy spinal cord's functions obtained via spinal cord fMRI, and fMRI's exemplary usage in spinal cord diseases and injuries. We conclude with a discussion that, while technical challenges exist, novel fMRI technologies for and new knowledge about the healthy human spinal cord have been established. Empowered by these developments, investigations of pathological and injury states within the spinal cord have become the next important direction of spinal cord fMRI. Recent clinical investigations into spinal cord pathologies, for example, fibromyalgia, multiple sclerosis, spinal cord injury, and cervical spondylotic myelopathy, have already provided deep insights into spinal cord impairments and the time course of impairment-caused changes. We expect that future spinal cord fMRI advancement and research development will further enhance our understanding of various spinal cord diseases and provide the foundation for evaluating existing and developing new treatment plans.
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Affiliation(s)
- Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Esmaeil Mohammadi
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, Oklahoma, USA
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10
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Snoussi H, Cohen‐Adad J, Combès B, Bannier É, Tounekti S, Kerbrat A, Barillot C, Caruyer E. Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord. Brain Behav 2023; 13:e3159. [PMID: 37775975 PMCID: PMC10636413 DOI: 10.1002/brb3.3159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 07/03/2023] [Accepted: 07/06/2023] [Indexed: 10/01/2023] Open
Abstract
INTRODUCTION Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. Although conventional magnetic resonance imaging (MRI) is widely used for MS diagnosis and clinical follow-up, quantitative MRI has the potential to provide valuable intrinsic values of tissue properties that can enhance accuracy. In this study, we investigate the efficacy of diffusion MRI in distinguishing MS lesions within the cervical spinal cord, using a combination of metrics extracted from diffusion tensor imaging and Ball-and-Stick models. METHODS We analyzed spinal cord data acquired from multiple hospitals and extracted average diffusion MRI metrics per vertebral level using a collection of image processing methods and an atlas-based approach. We then performed a statistical analysis to evaluate the feasibility of these metrics for detecting lesions, exploring the usefulness of combining different metrics to improve accuracy. RESULTS Our study demonstrates the sensitivity of each metric to underlying microstructure changes in MS patients. We show that selecting a specific subset of metrics, which provide complementary information, significantly improves the prediction score of lesion presence in the cervical spinal cord. Furthermore, the Ball-and-Stick model has the potential to provide novel information about the microstructure of damaged tissue. CONCLUSION Our results suggest that diffusion measures, particularly combined measures, are sensitive in discriminating abnormal from healthy cervical vertebral levels in patients. This information could aid in improving MS diagnosis and clinical follow-up. Our study highlights the potential of the Ball-and-Stick model in providing additional insights into the microstructure of the damaged tissue.
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Affiliation(s)
- Haykel Snoussi
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, FranceUniversité de Rennes, CNRS, Inria, Inserm, IRISA UMR 6074RennesFrance
- Department of RadiologyBoston Children's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Julien Cohen‐Adad
- NeuroPoly LabInstitute of Biomedical Engineering, Polytechnique MontrealMontrealQuebecCanada
- Functional Neuroimaging UnitCRIUGM, Université de MontréalMontréalQuebecCanada
- Mila – Quebec AI InstituteMontréalQuebecCanada
| | - Benoît Combès
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, FranceUniversité de Rennes, CNRS, Inria, Inserm, IRISA UMR 6074RennesFrance
| | - Élise Bannier
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, FranceUniversité de Rennes, CNRS, Inria, Inserm, IRISA UMR 6074RennesFrance
- Department of RadiologyRennes University HospitalRennesFrance
| | - Slimane Tounekti
- Department of RadiologyThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
| | - Anne Kerbrat
- Departement of NeurologyRennes University HospitalRennesFrance
| | - Christian Barillot
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, FranceUniversité de Rennes, CNRS, Inria, Inserm, IRISA UMR 6074RennesFrance
| | - Emmanuel Caruyer
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, FranceUniversité de Rennes, CNRS, Inria, Inserm, IRISA UMR 6074RennesFrance
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11
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Khamaysa M, Lefort M, Pélégrini-Issac M, Lackmy-Vallée A, Preuilh A, Devos D, Rolland AS, Desnuelle C, Chupin M, Marchand-Pauvert V, Querin G, Pradat PF. Comparison of spinal magnetic resonance imaging and classical clinical factors in predicting motor capacity in amyotrophic lateral sclerosis. J Neurol 2023:10.1007/s00415-023-11727-w. [PMID: 37103756 DOI: 10.1007/s00415-023-11727-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/10/2023] [Accepted: 04/12/2023] [Indexed: 04/28/2023]
Abstract
BACKGROUND Motor capacity is crucial in amyotrophic lateral sclerosis (ALS) clinical trial design and patient care. However, few studies have explored the potential of multimodal MRI to predict motor capacity in ALS. This study aims to evaluate the predictive value of cervical spinal cord MRI parameters for motor capacity in ALS compared to clinical prognostic factors. METHODS Spinal multimodal MRI was performed shortly after diagnosis in 41 ALS patients and 12 healthy participants as part of a prospective multicenter cohort study, the PULSE study (NCT00002013-A00969-36). Motor capacity was assessed using ALSFRS-R scores. Multiple stepwise linear regression models were constructed to predict motor capacity at 3 and 6 months from diagnosis, based on clinical variables, structural MRI measurements, including spinal cord cross-sectional area (CSA), anterior-posterior, and left-to-right cross-section diameters at vertebral levels from C1 to T4, and diffusion parameters in the lateral corticospinal tracts (LCSTs) and dorsal columns. RESULTS Structural MRI measurements were significantly correlated with the ALSFRS-R score and its sub-scores. And as early as 3 months from diagnosis, structural MRI measurements fit the best multiple linear regression model to predict the total ALSFRS-R (R2 = 0.70, p value = 0.0001) and arm sub-score (R2 = 0.69, p value = 0.0002), and combined with DTI metric in the LCST and clinical factors fit the best multiple linear regression model to predict leg sub-score (R2 = 0.73, p value = 0.0002). CONCLUSIONS Spinal multimodal MRI could be promising as a tool to enhance prognostic accuracy and serve as a motor function proxy in ALS.
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Affiliation(s)
- M Khamaysa
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - M Lefort
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - M Pélégrini-Issac
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - A Lackmy-Vallée
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - A Preuilh
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - D Devos
- Département de Neurology, Centre Référent SLA, CHU de Lille, Centre LICEND COEN, Lille, France
- Départment de Pharmacologie Médicale, Université de Lille, INSERM UMRS_1172 LilNCog, CHU de Lille, Centre LICEND COEN, Lille, France
| | - A-S Rolland
- Départment de Pharmacologie Médicale, Université de Lille, INSERM UMRS_1172 LilNCog, CHU de Lille, Centre LICEND COEN, Lille, France
| | - C Desnuelle
- Faculté Médecine de Nice, Département de Neurologie, Université Cote d'Azur, Nice, France
| | - M Chupin
- CATI Multicenter Neuroimaging Platform, Paris, France
| | - V Marchand-Pauvert
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - G Querin
- APHP, Service de Neuromyologie, Hôpital Pitié-Salpêtrière, Centre Référent Maladies Neuromusculaires Rares, Paris, France
- Institut de Myologie, I-Motion Clinical Trials Platform, Hôpital Pitié-Salpêtrière, Paris, France
| | - Pierre-François Pradat
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France.
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France.
- Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute Ulster University, C-TRIC, Altnagelvin Hospital, Derry/Londonderry, UK.
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12
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Sengupta A, Mishra A, Wang F, Chen L, Gore J. Identification of synchronous BOLD signal patterns in white matter of primate spinal cord. RESEARCH SQUARE 2023:rs.3.rs-2389151. [PMID: 36993492 PMCID: PMC10055542 DOI: 10.21203/rs.3.rs-2389151/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2023]
Abstract
Functional MRI studies of the brain have shown that blood-oxygenation-level-dependent (BOLD) signals are robustly detectable not only in gray matter (GM) but also in white matter (WM). Here, we report the detection and characteristics of BOLD signals in WM of spinal cord (SC) of squirrel monkeys. Tactile stimulus-evoked BOLD signal changes were detected in the ascending sensory tracts of SC using a General-Linear Model (GLM) as well as Independent Component Analysis (ICA). ICA of resting state signals identified coherent fluctuations from eight WM hubs which correspond closely with known anatomical locations of SC WM tracts. Resting state analyses showed that the WM hubs exhibited correlated signal fluctuations within and between SC segments in specific patterns that correspond well with the known neurobiological functions of WM tracts in SC. Overall, these findings suggest WM BOLD signals in SC show similar features as GM both at baseline and under stimulus conditions.
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Affiliation(s)
| | | | - Feng Wang
- Vanderbilt University Medical Center
| | - Li Chen
- Vanderbilt University Medical Center
| | - John Gore
- Vanderbilt University Medical Center
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13
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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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14
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Yang HE, Kim WT, Kim DH, Kim SW, Yoo WK. Utility of Diffusion and Magnetization Transfer MRI in Cervical Spondylotic Myelopathy: A Pilot Study. Diagnostics (Basel) 2022; 12:diagnostics12092090. [PMID: 36140491 PMCID: PMC9497906 DOI: 10.3390/diagnostics12092090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/26/2022] [Accepted: 08/28/2022] [Indexed: 11/16/2022] Open
Abstract
Diffusion tensor imaging (DTI) and magnetization transfer (MT) magnetic resonance imaging (MRI) can help detect spinal cord pathology, and tract-specific analysis of their parameters, such as fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD), radial diffusivity (RD) and MT ratio (MTR), can give microstructural information. We performed the tract-based acquisition of MR parameters of three major motor tracts: the lateral corticospinal (CS), rubrospinal (RuS) tract, and lateral reticulospinal (RS) tract as well as two major sensory tracts, i.e., the fasciculus cuneatus (FC) and spinal lemniscus, to detect pathologic change and find correlations with clinical items. MR parameters were extracted for each tract at three levels: the most compressed lesion level and above and below the lesion. We compared the MR parameters of eight cervical spondylotic myelopathy patients and 12 normal controls and analyzed the correlation between clinical evaluation items and MR parameters in patients. RuS and lateral RS showed worse DTI parameters at the lesion level in patients compared to the controls. Worse DTI parameters in those tracts were correlated with weaker power grasp at the lesion level. FC and lateral CS showed a correlation between higher RD and lower FA and MTR with a weaker lateral pinch below the lesion level.
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Affiliation(s)
- Hea-Eun Yang
- Department of Rehabilitation Medicine, VHS Medical Center, Seoul 05368, Korea
| | - Wan-Tae Kim
- Department of Radiology, VHS Medical Center, Seoul 05368, Korea
| | - Dae-Hyun Kim
- Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul 03722, Korea
| | - Seok-Woo Kim
- Department of Orthopaedic Surgery, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Woo-Kyoung Yoo
- Department of Physical Medicine and Rehabilitation, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
- Correspondence:
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15
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Rezende TJR, Schmitt GS, de Lima FD, de Brito MR, Matos PCAAP, Bonadia LC, Martinez ARM, Cendes F, Pedroso JL, Barsottini OGP, Marques W, França MC. RFC1-Related Disorder: In Vivo Evaluation of Spinal Cord Damage. Mov Disord 2022; 37:2122-2128. [PMID: 35877029 DOI: 10.1002/mds.29169] [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: 04/04/2022] [Revised: 06/10/2022] [Accepted: 07/05/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND RFC1-related disorder is a novel heredodegenerative condition with a broad phenotypic spectrum. Its neuropathological bases are not yet fully understood, particularly regarding the pattern, extent, and clinical relevance of spinal cord (SC) damage. OBJECTIVES The objectives were to determine the SC structural signature in RFC1-related disorder in vivo and to identify potential clinical correlates for these imaging abnormalities. METHODS We enrolled 17 subjects with biallelic RFC1 (AAGGG)n expansions and 11 age- and sex-matched healthy controls that underwent multimodal magnetic resonance imaging SC acquisitions in a 3T Philips Achieva scanner. Both global morphometry and tract-specific analyses were then performed across all cervical levels. Between-group comparisons were assessed using nonparametric tests. RESULTS In the patient group, mean age and disease duration were 62.9 ± 9.3 and 9.3 ± 4.0, respectively. Compared to controls, patients had remarkable SC cross-sectional area reduction along all cervical levels but anteroposterior flattening only in the lower cervical levels. There was also prominent SC gray matter atrophy. Diffusivity abnormalities were identified in the dorsal columns but not in the lateral corticospinal tracts. Disease severity did not correlate with these imaging parameters. CONCLUSION SC damage is a hallmark of RFC1-related disorder and characterized by gray as well as white matter involvement. In particular, dorsal columns are severely and diffusely affected. The clinical correlates of these imaging abnormalities still deserve additional investigations. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Thiago J R Rezende
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Gabriel S Schmitt
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Fabricio D de Lima
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Mariana Rabelo de Brito
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Paula Camila A A P Matos
- Ataxia Unit, Department of Neurology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Luciana Cardoso Bonadia
- Department of Medical Genetics, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Alberto R M Martinez
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Fernando Cendes
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - José Luiz Pedroso
- Ataxia Unit, Department of Neurology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Orlando G P Barsottini
- Ataxia Unit, Department of Neurology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Wilson Marques
- Department of Neuroscience and Behavioral Science, School of Medicine-University of São Paulo (USP) of Ribeirão Preto, Ribeirão Preto, Brazil
| | - Marcondes Cavalcante França
- Department of Neurology, School of Medical Sciences-University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
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16
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Trò R, Roascio M, Tortora D, Severino M, Rossi A, Cohen-Adad J, Fato MM, Arnulfo G. Diffusion Kurtosis Imaging of Neonatal Spinal Cord in Clinical Routine. FRONTIERS IN RADIOLOGY 2022; 2:794981. [PMID: 37492682 PMCID: PMC10365122 DOI: 10.3389/fradi.2022.794981] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 01/20/2022] [Indexed: 07/27/2023]
Abstract
Diffusion kurtosis imaging (DKI) has undisputed advantages over the more classical diffusion magnetic resonance imaging (dMRI) as witnessed by the fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized, in particular in spinal cord (SC) imaging, because of its inherently demanding technological requirements. Due to its extreme sensitivity to non-Gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, which are not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between the SC region and the brain above, managing to apply such a method to the neonatal cohort becomes of utmost importance. This study will (i) mention current methodological challenges associated with the application of advanced dMRI methods, like DKI, in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox for handling the DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present results of its application in a pilot clinical case study. With the proposed pipeline, we preliminarily show that DKI is more sensitive than DTI-related measures to alterations caused by brain white matter injuries in the underlying cervical SC.
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Affiliation(s)
- Rosella Trò
- Departments of Informatics, Bioengineering, Robotics, and System Engineering, University of Genoa, Genoa, Italy
| | - Monica Roascio
- Departments of Informatics, Bioengineering, Robotics, and System Engineering, University of Genoa, Genoa, Italy
| | | | | | - Andrea Rossi
- Neuroradiology Unit, Istituto Giannina Gaslini, Genoa, Italy
- Department of Health Sciences, University of Genoa, Genoa, Italy
| | - 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
| | - Marco Massimo Fato
- Departments of Informatics, Bioengineering, Robotics, and System Engineering, University of Genoa, Genoa, Italy
| | - Gabriele Arnulfo
- Departments of Informatics, Bioengineering, Robotics, and System Engineering, University of Genoa, Genoa, Italy
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
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17
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Valošek J, Bednařík P, Keřkovský M, Hluštík P, Bednařík J, Svatkova A. Quantitative MR Markers in Non-Myelopathic Spinal Cord Compression: A Narrative Review. J Clin Med 2022; 11:2301. [PMID: 35566426 PMCID: PMC9105390 DOI: 10.3390/jcm11092301] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 02/01/2023] Open
Abstract
Degenerative spinal cord compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical spinal cord compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, and magnetic resonance spectroscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients consistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels, caused by demyelination and axonal injury, MT and 1H-MRS, along with advanced and tract-specific diffusion MRI, recently revealed microstructural alterations, also rostrally pointing to Wallerian degeneration. Recent studies also disclosed a significant relationship between microstructural damage and functional deficits, as assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI, in combination with electrophysiology, critically extends our understanding of the underlying pathophysiology of degenerative spinal cord compression and may provide predictive markers of DCM development for accurate patient management. However, the prognostic value must be validated in longitudinal studies.
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Affiliation(s)
- Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic; (J.V.); (P.H.)
- Department of Radiology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
- Department of Biomedical Engineering, University Hospital Olomouc, 779 00 Olomouc, Czech Republic
| | - Petr Bednařík
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark;
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark
| | - Miloš Keřkovský
- Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic; (M.K.); (J.B.)
- Department of Radiology and Nuclear Medicine, University Hospital Brno, 625 00 Brno, Czech Republic
| | - Petr Hluštík
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic; (J.V.); (P.H.)
- Department of Neurology, University Hospital Olomouc, 779 00 Olomouc, Czech Republic
| | - Josef Bednařík
- Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic; (M.K.); (J.B.)
- Department of Neurology, University Hospital Brno, 625 00 Brno, Czech Republic
- Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic
| | - Alena Svatkova
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark;
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark
- Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, 1090 Vienna, Austria
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18
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Cohen‐Adad J, Alonso‐Ortiz E, Alley S, Lagana MM, Baglio F, Vannesjo SJ, Karbasforoushan H, Seif M, Seifert AC, Xu J, Kim J, Labounek R, Vojtíšek L, Dostál M, Valošek J, Samson RS, Grussu F, Battiston M, Gandini Wheeler‐Kingshott CAM, Yiannakas MC, Gilbert G, Schneider T, Johnson B, Prados F. Comparison of multicenter
MRI
protocols for visualizing the spinal cord gray matter. Magn Reson Med 2022; 88:849-859. [DOI: 10.1002/mrm.29249] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 12/28/2022]
Affiliation(s)
- Julien Cohen‐Adad
- NeuroPoly Lab Institute of Biomedical Engineering, Polytechnique Montreal Montreal Canada
- Functional Neuroimaging Unit, CRIUGM University of Montreal Montreal Canada
- Mila ‐ Quebec AI Institute Montreal Canada
| | - Eva Alonso‐Ortiz
- NeuroPoly Lab Institute of Biomedical Engineering, Polytechnique Montreal Montreal Canada
| | - Stephanie Alley
- NeuroPoly Lab Institute of Biomedical Engineering, Polytechnique Montreal Montreal Canada
| | | | | | - Signe Johanna Vannesjo
- Wellcome Center for Integrative Neuroimaging, FMRIB University of Oxford, John Radcliffe Hospital Oxford UK
- Department of Physics Norwegian University of Science and Technology Trondheim Norway
| | - Haleh Karbasforoushan
- Interdepartmental Neuroscience Program Northwestern University School of Medicine Chicago IL USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine Stanford University Stanford CA USA
| | - 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
| | - 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 NY USA
| | - Junqian Xu
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences Icahn School of Medicine at Mount Sinai New York NY USA
| | - 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 NY USA
| | - René Labounek
- Departments of Neurology and Biomedical Engineering University Hospital Olomouc Olomouc Czech Republic
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics Masonic Institute for the Developing Brain, University of Minnesota Minneapolis MN USA
| | - Lubomír Vojtíšek
- Central European Institute of Technology Masaryk University Brno Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine University Hospital Brno Brno Czech Republic
| | - Jan Valošek
- Departments of Neurology and Biomedical Engineering University Hospital Olomouc Olomouc Czech Republic
| | - Rebecca S. Samson
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
| | - Francesco Grussu
- Queen Square MS Centre, UCL 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
| | - Marco Battiston
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
| | - Claudia A. M. Gandini Wheeler‐Kingshott
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
- Department of Brain and Behavioral Sciences University of Pavia Pavia Italy
- Brain MRI 3T Research Center C. Mondino National Neurological Institute Pavia Italy
| | - Marios C. Yiannakas
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
| | | | | | - Brian Johnson
- MR Clinical Development, Philips North America Gainesville FL USA
| | - Ferran Prados
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
- e‐Health Center, Universitat Oberta de Catalunya Barcelona Spain
- Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, University College London London UK
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19
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Towards reliable spinal cord fMRI: assessment of common imaging protocols. Neuroimage 2022; 250:118964. [DOI: 10.1016/j.neuroimage.2022.118964] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/07/2022] [Accepted: 02/01/2022] [Indexed: 01/29/2023] Open
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20
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Navas-Sánchez FJ, Marcos-Vidal L, de Blas DM, Fernández-Pena A, Alemán-Gómez Y, Guzmán-de-Villoria JA, Romero J, Catalina I, Lillo L, Muñoz-Blanco JL, Ordoñez-Ugalde A, Quintáns B, Sobrido MJ, Carmona S, Grandas F, Desco M. Tract-specific damage at spinal cord level in pure hereditary spastic paraplegia type 4: a diffusion tensor imaging study. J Neurol 2022; 269:3189-3203. [PMID: 34999956 DOI: 10.1007/s00415-021-10933-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 12/03/2021] [Accepted: 12/03/2021] [Indexed: 01/15/2023]
Abstract
BACKGROUND SPG4 is a subtype of hereditary spastic paraplegia (HSP), an upper motor neuron disorder characterized by axonal degeneration of the corticospinal tracts and the fasciculus gracilis. The few neuroimaging studies that have focused on the spinal cord in HSP are based mainly on the analysis of structural characteristics. METHODS We assessed diffusion-related characteristics of the spinal cord using diffusion tensor imaging (DTI), as well as structural and shape-related properties in 12 SPG4 patients and 14 controls. We used linear mixed effects models up to T3 in order to analyze the global effects of 'group' and 'clinical data' on structural and diffusion data. For DTI, we carried out a region of interest (ROI) analysis in native space for the whole spinal cord, the anterior and lateral funiculi, and the dorsal columns. We also performed a voxelwise analysis of the spinal cord to study local diffusion-related changes. RESULTS A reduced cross-sectional area was observed in the cervical region of SPG4 patients, with significant anteroposterior flattening. DTI analyses revealed significantly decreased fractional anisotropy (FA) and increased radial diffusivity at all the cervical and thoracic levels, particularly in the lateral funiculi and dorsal columns. The FA changes in SPG4 patients were significantly related to disease severity, measured as the Spastic Paraplegia Rating Scale score. CONCLUSIONS Our results in SPG4 indicate tract-specific axonal damage at the level of the cervical and thoracic spinal cord. This finding is correlated with the degree of motor disability.
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Affiliation(s)
- Francisco J Navas-Sánchez
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain. .,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.
| | - Luis Marcos-Vidal
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Departamento de Bioingeniería E Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain
| | - Daniel Martín de Blas
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Departamento de Bioingeniería E Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain
| | - Alberto Fernández-Pena
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Departamento de Bioingeniería E Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain
| | - Yasser Alemán-Gómez
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, Prilly, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Lausanne, Switzerland
| | - Juan A Guzmán-de-Villoria
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Servicio de Radiodiagnóstico, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Julia Romero
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Servicio de Radiodiagnóstico, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Irene Catalina
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Servicio de Neurología, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Laura Lillo
- Servicio de Neurología, Hospital Ruber Internacional, Madrid, Spain
| | - José L Muñoz-Blanco
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Servicio de Neurología, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Andrés Ordoñez-Ugalde
- Instituto de Investigación Sanitaria, Hospital Clínico Universitario, Santiago de Compostela, Spain.,Laboratorio Biomolecular, Cuenca, Ecuador.,Unidad de Genética y Molecular, Hospital de Especialidades José Carrasco Arteaga, Cuenca, Ecuador
| | - Beatriz Quintáns
- Instituto de Investigación Sanitaria, Hospital Clínico Universitario, Santiago de Compostela, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-U711), Madrid, Spain.,Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain
| | - María-Jesús Sobrido
- Instituto de Investigación Sanitaria, Hospital Clínico Universitario, Santiago de Compostela, Spain.,Instituto de Investigación Biomédica, Hospital Clínico Universitario de A Coruña, SERGAS, A Coruña, Spain
| | - Susanna Carmona
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Francisco Grandas
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Servicio de Neurología, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Manuel Desco
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Dr Esquerdo 46, 28007, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Departamento de Bioingeniería E Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Madrid, Spain.,Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
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21
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David G, Pfyffer D, Vallotton K, Pfender N, Thompson A, Weiskopf N, Mohammadi S, Curt A, Freund P. Longitudinal changes of spinal cord grey and white matter following spinal cord injury. J Neurol Neurosurg Psychiatry 2021; 92:1222-1230. [PMID: 34341143 PMCID: PMC8522459 DOI: 10.1136/jnnp-2021-326337] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 06/09/2021] [Indexed: 11/21/2022]
Abstract
OBJECTIVES Traumatic and non-traumatic spinal cord injury produce neurodegeneration across the entire neuraxis. However, the spatiotemporal dynamics of spinal cord grey and white matter neurodegeneration above and below the injury is understudied. METHODS We acquired longitudinal data from 13 traumatic and 3 non-traumatic spinal cord injury patients (8-8 cervical and thoracic cord injuries) within 1.5 years after injury and 10 healthy controls over the same period. The protocol encompassed structural and diffusion-weighted MRI rostral (C2/C3) and caudal (lumbar enlargement) to the injury level to track tissue-specific neurodegeneration. Regression models assessed group differences in the temporal evolution of tissue-specific changes and associations with clinical outcomes. RESULTS At 2 months post-injury, white matter area was decreased by 8.5% and grey matter by 15.9% in the lumbar enlargement, while at C2/C3 only white matter was decreased (-9.7%). Patients had decreased cervical fractional anisotropy (FA: -11.3%) and increased radial diffusivity (+20.5%) in the dorsal column, while FA was lower in the lateral (-10.3%) and ventral columns (-9.7%) of the lumbar enlargement. White matter decreased by 0.34% and 0.35% per month at C2/C3 and lumbar enlargement, respectively, and grey matter decreased at C2/C3 by 0.70% per month. CONCLUSIONS This study describes the spatiotemporal dynamics of tissue-specific spinal cord neurodegeneration above and below a spinal cord injury. While above the injury, grey matter atrophy lagged initially behind white matter neurodegeneration, in the lumbar enlargement these processes progressed in parallel. Tracking trajectories of tissue-specific neurodegeneration provides valuable assessment tools for monitoring recovery and treatment effects.
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Affiliation(s)
- Gergely David
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Dario Pfyffer
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Kevin Vallotton
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Nikolai Pfender
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Alan Thompson
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, 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
| | - Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, 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 Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK
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22
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Landelle C, Lungu O, Vahdat S, Kavounoudias A, Marchand-Pauvert V, De Leener B, Doyon J. Investigating the human spinal sensorimotor pathways through functional magnetic resonance imaging. Neuroimage 2021; 245:118684. [PMID: 34732324 DOI: 10.1016/j.neuroimage.2021.118684] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 01/29/2023] Open
Abstract
Most of our knowledge about the human spinal ascending (sensory) and descending (motor) pathways comes from non-invasive electrophysiological investigations. However, recent methodological advances in acquisition and analyses of functional magnetic resonance imaging (fMRI) data from the spinal cord, either alone or in combination with the brain, have allowed us to gain further insights into the organization of this structure. In the current review, we conducted a systematic search to produced somatotopic maps of the spinal fMRI activity observed through different somatosensory, motor and resting-state paradigms. By cross-referencing these human neuroimaging findings with knowledge acquired through neurophysiological recordings, our review demonstrates that spinal fMRI is a powerful tool for exploring, in vivo, the human spinal cord pathways. We report strong cross-validation between task-related and resting-state fMRI in accordance with well-known hemicord, postero-anterior and rostro-caudal organization of these pathways. We also highlight the specific advantages of using spinal fMRI in clinical settings to characterize better spinal-related impairments, predict disease progression, and guide the implementation of therapeutic interventions.
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Affiliation(s)
- Caroline Landelle
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
| | - Ovidiu Lungu
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Anne Kavounoudias
- CNRS, UMR7291, Laboratory of Cognitive Neurosciences, Aix-Marseille University, Marseille, France
| | | | - Benjamin De Leener
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada; CHU Sainte-Justine Research Centre, Montreal, QC, Canada
| | - Julien Doyon
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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23
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Hernandez ALCC, Rezende TJR, Martinez ARM, de Brito MR, França MC. Tract-Specific Spinal Cord Diffusion Tensor Imaging in Friedreich's Ataxia. Mov Disord 2021; 37:354-364. [PMID: 34713932 DOI: 10.1002/mds.28841] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/30/2021] [Accepted: 10/02/2021] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Spinal cord (SC) damage is a hallmark in Friedreich's ataxia (FRDA). Neuroimaging has been able to capture some SC macroscopic changes, but no study has evaluated microstructural SC white matter (WM) damage in vivo. OBJECTIVES We designed a cross-sectional study to evaluate microstructural integrity in SC WM tracts of FRDA patients using diffusion tensor imaging (DTI) with an automated analysis pipeline. METHODS Thirty patients and 30 matched healthy controls underwent 3 Tesla (T) magnetic resonance imaging (MRI). We obtained cervical SC T2 and diffusion-weighted imaging (DWI) acquisitions. Images were processed using the Spinal Cord Toolbox v.4.3.0. For levels C2-C5, we measured cross-sectional area (CSA) and WM DTI parameters (axial diffusivity [AD], fractional anisotropy [FA], radial diffusivity [RD], and mean diffusivity [MD]). Age, duration, and FARS scores were also obtained. RESULTS Mean age and disease duration of patients were 31 ± 10 and 11 ± 9 years, respectively. There was CSA reduction in FRDA amongst all levels. Between-group differences in FA, MD, and RD in total white matter (TWM), dorsal columns (DC), fasciculus gracilis (FG), fasciculus cuneatus (FC), and corticospinal tracts (CST) were present in all levels. FA and RD from TWM, DC, FC, and CST correlated with FARS scores, and in CST they also correlated with disease duration. CONCLUSION DTI uncovered abnormalities in SC WM tracts, which correlated with clinical features in FRDA. CSA and CST FA in C2 correlated best with disease severity, whereas DC FA showed the largest effect size to differentiate patients and healthy controls. SC WM microstructure is a potential neuroimaging biomarker to be explored in the disease. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Ana Luisa C C Hernandez
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Thiago J R Rezende
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Alberto R M Martinez
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Mariana R de Brito
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Marcondes C França
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
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Scheuren PS, David G, Kramer JLK, Jutzeler CR, Hupp M, Freund P, Curt A, Hubli M, Rosner J. Combined Neurophysiologic and Neuroimaging Approach to Reveal the Structure-Function Paradox in Cervical Myelopathy. Neurology 2021; 97:e1512-e1522. [PMID: 34380751 DOI: 10.1212/wnl.0000000000012643] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 07/16/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To explore the so-called structure-function paradox in individuals with focal spinal lesions by means of tract-specific MRI coupled with multimodal evoked potentials and quantitative sensory testing. METHODS Individuals with signs and symptoms attributable to cervical myelopathy (i.e., no evidence of competing neurologic diagnoses) were recruited at the Balgrist University Hospital, Zurich, Switzerland, between February 2018 and March 2019. We evaluated the relationship between the extent of structural damage within spinal nociceptive pathways (i.e., dorsal horn, spinothalamic tract, anterior commissure) assessed with atlas-based MRI and (1) the functional integrity of spinal nociceptive pathways measured with contact heat-, cold-, and pinprick-evoked potentials and (2) clinical somatosensory phenotypes assessed with quantitative sensory testing. RESULTS Sixteen individuals (mean age 61 years) with either degenerative (n = 13) or posttraumatic (n = 3) cervical myelopathy participated in the study. Most individuals presented with mild myelopathy (modified Japanese Orthopaedic Association score >15; n = 13). A total of 71% of individuals presented with structural damage within spinal nociceptive pathways on MRI. However, 50% of these individuals presented with complete functional sparing (i.e., normal contact heat-, cold-, and pinprick-evoked potentials). The extent of structural damage within spinal nociceptive pathways was not associated with functional integrity of thermal (heat: p = 0.57; cold: p = 0.49) and mechano-nociceptive pathways (p = 0.83) or with the clinical somatosensory phenotype (heat: p = 0.16; cold: p = 0.37; mechanical: p = 0.73). The amount of structural damage to the spinothalamic tract did not correlate with spinothalamic conduction velocity (p > 0.05; ρ = -0.11). DISCUSSION Our findings provide neurophysiologic evidence to substantiate that structural damage in the spinal cord does not equate to functional somatosensory deficits. This study recognizes the pronounced structure-function paradox in cervical myelopathies and underlines the inevitable need for a multimodal phenotyping approach to reveal the eloquence of lesions within somatosensory pathways.
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Affiliation(s)
- Paulina Simonne Scheuren
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Gergely David
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - John Lawrence Kipling Kramer
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Catherine Ruth Jutzeler
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Markus Hupp
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Patrick Freund
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Armin Curt
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Michèle Hubli
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland
| | - Jan Rosner
- From the Spinal Cord Injury Center (P.S.S., G.D., M. Hupp, P.F., A.C., M. Hubli, J.R.), Balgrist University Hospital, University of Zurich, Switzerland; International Collaboration on Repair Discoveries (ICORD) (J.L.K.K.), Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine (J.L.K.K.), University of British Columbia, Vancouver, Canada; Department of Biosystems Science and Technology (C.R.J.), Swiss Federal Institute of Technology Zurich, Switzerland; Wellcome Centre for Human Neuroimaging (P.F.), UCL Institute of Neurology, UCL, London, UK; Department of Neurophysics (P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; and Department of Neurology (J.R.), University Hospital Bern, Inselspital, University of Bern, Switzerland.
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25
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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, Wheeler-Kingshott CAMG, 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 H, 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 KA, Weiskopf N, Wise RG, Wyss PO, Xu J. Generic acquisition protocol for quantitative MRI of the spinal cord. Nat Protoc 2021; 16:4611-4632. [PMID: 34400839 PMCID: PMC8811488 DOI: 10.1038/s41596-021-00588-0] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 06/10/2021] [Indexed: 02/08/2023]
Abstract
Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.
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Affiliation(s)
- Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada.
- Mila-Quebec AI Institute, Montreal, Quebec, Canada.
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, 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, Queensland, Australia
| | - Laura Barlow
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, 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, Queensland, 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, Quebec, Canada
- CHU Sainte-Justine Research Centre, Montreal, Quebec, Canada
| | - Maxime Descoteaux
- Centre de Recherche CHUS, CIMS, Sherbrooke, Quebec, Canada
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, Quebec, 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, Quebec, Canada
| | - Adam Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, 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, Quebec, 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, Quebec, Canada
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, 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, Quebec, 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 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, British Columbia, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, 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, Queensland, 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, British Columbia, 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, 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, Quebec, 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, Queensland, 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
| | - Yuichi 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
- 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, 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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26
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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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27
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Shahrampour S, De Leener B, Alizadeh M, Middleton D, Krisa L, Flanders AE, Faro SH, Cohen-Adad J, Mohamed FB. Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord. AJNR Am J Neuroradiol 2021; 42:1727-1734. [PMID: 34326104 DOI: 10.3174/ajnr.a7221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/19/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Multi-parametric MRI, provides a variety of biomarkers sensitive to white matter integrity, However, spinal cord MRI data in pediatrics is rare compared to adults. The purpose of this work was 3-fold: 1) to develop a processing pipeline for atlas-based generation of the typically developing pediatric spinal cord WM tracts, 2) to derive atlas-based normative values of the DTI indices for various WM pathways, and 3) to investigate age-related changes in the obtained normative DTI indices along the extracted tracts. MATERIALS AND METHODS DTI scans of 30 typically developing subjects (age range, 6-16 years) were acquired on a 3T MR imaging scanner. The data were registered to the PAM50 template in the Spinal Cord Toolbox. Next, the DTI indices for various WM regions were extracted at a single section centered at the C3 vertebral body in all the 30 subjects. Finally, an ANOVA test was performed to examine the effects of the following: 1) laterality, 2) functionality, and 3) age, with DTI-derived indices in 34 extracted WM regions. RESULTS A postprocessing pipeline was developed and validated to delineate pediatric spinal cord WM tracts. The results of ANOVA on fractional anisotropy values showed no effect for laterality (P = .72) but an effect for functionality (P < .001) when comparing the 30 primary WM labels. There was a significant (P < .05) effect of age and maturity of the left spinothalamic tract on mean diffusivity, radial diffusivity, and axial diffusivity values. CONCLUSIONS The proposed automated pipeline in this study incorporates unique postprocessing steps followed by template registration and quantification of DTI metrics using atlas-based regions. This method eliminates the need for manual ROI analysis of WM tracts and, therefore, increases the accuracy and speed of the measurements.
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Affiliation(s)
- S Shahrampour
- From the Departments of Radiology (S.S., M.A., D.M., F.B.M.)
| | - B De Leener
- Department of Computer Engineering and Software Engineering (B.D.L.)
| | - M Alizadeh
- From the Departments of Radiology (S.S., M.A., D.M., F.B.M.)
| | - D Middleton
- From the Departments of Radiology (S.S., M.A., D.M., F.B.M.)
| | | | - A E Flanders
- Radiology (A.E.F., S.H.F.), Thomas Jefferson University, Philadelphia, Pennsylvania
| | - S H Faro
- Radiology (A.E.F., S.H.F.), Thomas Jefferson University, Philadelphia, Pennsylvania
| | - J Cohen-Adad
- NeuroPoly Lab (J.C.-A.), Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,Functional Neuroimaging Unit (J.C.-A.), Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Université de Montréal, Montreal, Quebec, Canada
| | - F B Mohamed
- From the Departments of Radiology (S.S., M.A., D.M., F.B.M.)
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28
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Lemay A, Gros C, Zhuo Z, Zhang J, Duan Y, Cohen-Adad J, Liu Y. Automatic multiclass intramedullary spinal cord tumor segmentation on MRI with deep learning. NEUROIMAGE-CLINICAL 2021; 31:102766. [PMID: 34352654 PMCID: PMC8350366 DOI: 10.1016/j.nicl.2021.102766] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/22/2021] [Accepted: 07/17/2021] [Indexed: 11/25/2022]
Abstract
Automatic spinal cord tumor segmentation with deep learning. Multi-class model for tumor, edema, and cavity. Model trained to recognize astrocytoma, ependymoma, and hemangioblastoma. Multi-contrast input for more robustness: Gd-T1w and T2w. Method and model are available in open-source Spinal Cord Toolbox (SCT).
Spinal cord tumors lead to neurological morbidity and mortality. Being able to obtain morphometric quantification (size, location, growth rate) of the tumor, edema, and cavity can result in improved monitoring and treatment planning. Such quantification requires the segmentation of these structures into three separate classes. However, manual segmentation of three-dimensional structures is time consuming, tedious and prone to intra- and inter-rater variability, motivating the development of automated methods. Here, we tailor a model adapted to the spinal cord tumor segmentation task. Data were obtained from 343 patients using gadolinium-enhanced T1-weighted and T2-weighted MRI scans with cervical, thoracic, and/or lumbar coverage. The dataset includes the three most common intramedullary spinal cord tumor types: astrocytomas, ependymomas, and hemangioblastomas. The proposed approach is a cascaded architecture with U-Net-based models that segments tumors in a two-stage process: locate and label. The model first finds the spinal cord and generates bounding box coordinates. The images are cropped according to this output, leading to a reduced field of view, which mitigates class imbalance. The tumor is then segmented. The segmentation of the tumor, cavity, and edema (as a single class) reached 76.7 ± 1.5% of Dice score and the segmentation of tumors alone reached 61.8 ± 4.0% Dice score. The true positive detection rate was above 87% for tumor, edema, and cavity. To the best of our knowledge, this is the first fully automatic deep learning model for spinal cord tumor segmentation. The multiclass segmentation pipeline is available in the Spinal Cord Toolbox (https://spinalcordtoolbox.com/). It can be run with custom data on a regular computer within seconds.
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Affiliation(s)
- Andreanne Lemay
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Mila, Quebec AI Institute, Canada
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Mila, Quebec AI Institute, Canada
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jie Zhang
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Mila, Quebec AI Institute, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada.
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
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29
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Valošek J, Labounek R, Horák T, Horáková M, Bednařík P, Keřkovský M, Kočica J, Rohan T, Lenglet C, Cohen-Adad J, Hluštík P, Vlčková E, Kadaňka Z, Bednařík J, Svatkova A. Diffusion magnetic resonance imaging reveals tract-specific microstructural correlates of electrophysiological impairments in non-myelopathic and myelopathic spinal cord compression. Eur J Neurol 2021; 28:3784-3797. [PMID: 34288268 PMCID: PMC8530898 DOI: 10.1111/ene.15027] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 07/16/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND AND PURPOSE Non-myelopathic degenerative cervical spinal cord compression (NMDC) frequently occurs throughout aging and may progress to potentially irreversible degenerative cervical myelopathy (DCM). Whereas standard clinical magnetic resonance imaging (MRI) and electrophysiological measures assess compression severity and neurological dysfunction, respectively, underlying microstructural deficits still have to be established in NMDC and DCM patients. The study aims to establish tract-specific diffusion MRI markers of electrophysiological deficits to predict the progression of asymptomatic NMDC to symptomatic DCM. METHODS High-resolution 3 T diffusion MRI was acquired for 103 NMDC and 21 DCM patients compared to 60 healthy controls to reveal diffusion alterations and relationships between tract-specific diffusion metrics and corresponding electrophysiological measures and compression severity. Relationship between the degree of DCM disability, assessed by the modified Japanese Orthopaedic Association scale, and tract-specific microstructural changes in DCM patients was also explored. RESULTS The study identified diffusion-derived abnormalities in the gray matter, dorsal and lateral tracts congruent with trans-synaptic degeneration and demyelination in chronic degenerative spinal cord compression with more profound alterations in DCM than NMDC. Diffusion metrics were affected in the C3-6 area as well as above the compression level at C3 with more profound rostral deficits in DCM than NMDC. Alterations in lateral motor and dorsal sensory tracts correlated with motor and sensory evoked potentials, respectively, whereas electromyography outcomes corresponded with gray matter microstructure. DCM disability corresponded with microstructure alteration in lateral columns. CONCLUSIONS Outcomes imply the necessity of high-resolution tract-specific diffusion MRI for monitoring degenerative spinal pathology in longitudinal studies.
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Affiliation(s)
- Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czechia.,Department of Biomedical Engineering, University Hospital, Olomouc, Czechia
| | - René Labounek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czechia.,Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Tomáš Horák
- Central European Institute of Technology, Masaryk University, Brno, Czechia.,Department of Neurology, University Hospital Brno, Brno, Czechia.,Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Magda Horáková
- Department of Neurology, University Hospital Brno, Brno, Czechia.,Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Petr Bednařík
- Central European Institute of Technology, Masaryk University, Brno, Czechia.,High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Miloš Keřkovský
- Faculty of Medicine, Masaryk University, Brno, Czechia.,Department of Radiology and Nuclear Medicine, University Hospital Brno, Brno, Czechia
| | - Jan Kočica
- Department of Neurology, University Hospital Brno, Brno, Czechia.,Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Tomáš Rohan
- Faculty of Medicine, Masaryk University, Brno, Czechia.,Department of Radiology and Nuclear Medicine, University Hospital Brno, Brno, Czechia
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada.,Mila - Quebec AI Institute, Montreal, Quebec, Canada
| | - Petr Hluštík
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czechia
| | - Eva Vlčková
- Department of Neurology, University Hospital Brno, Brno, Czechia.,Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Zdeněk Kadaňka
- Department of Neurology, University Hospital Brno, Brno, Czechia.,Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Josef Bednařík
- Central European Institute of Technology, Masaryk University, Brno, Czechia.,Department of Neurology, University Hospital Brno, Brno, Czechia.,Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Alena Svatkova
- Central European Institute of Technology, Masaryk University, Brno, Czechia.,Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
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Johnson B, Walter AE, Wilkes JR, Papa L, Slobounov SM. Changes in White Matter of the Cervical Spinal Cord after a Single Season of Collegiate Football. Neurotrauma Rep 2021; 2:84-93. [PMID: 34223548 PMCID: PMC8240824 DOI: 10.1089/neur.2020.0035] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The involvement of the central nervous system (CNS), specifically the white matter tracts in the cervical spinal cord, was examined with diffusion tensor imaging (DTI) following exposure to repetitive head acceleration events (HAEs) after a single season of collegiate football. Fifteen National Collegiate Athletic Association (NCAA) Division 1 football players underwent DTI of the cervical spinal cord (vertebral level C1–4) at pre-season (before any contact practices began) and post-season (within 1 week of the last regular season game) intervals. Helmet accelerometer data were also collected in parallel throughout the season. From pre-season to post-season, a significant decrease (p < 0.05) of axial diffusivity was seen within the right spino-olivary tract. In addition, a significant decrease (p < 0.05) in global white matter fractional anisotropy (FA) along with increases (p < 0.05) in global white matter mean diffusivity (MD) and radial diffusivity (RD) were found. These changes in FA from pre-season to post-season were significantly moderated by previous concussion history (p < 0.05) and number of HAEs over 80 g (p < 0.05). Despite the absence of sports-related concussion (SRC), we present measurable changes in the white matter integrity of the cervical spinal cord suggesting injury from repetitive HAEs, or SRC, may include the entirety of the CNS, not just the brain.
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Affiliation(s)
- Brian Johnson
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Alexa E Walter
- Department of Kinesiology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - James R Wilkes
- Department of Kinesiology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Linda Papa
- Department of Emergency Medicine, Orlando Regional Medical Center, Orlando, Florida, USA.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Semyon M Slobounov
- Department of Kinesiology, The Pennsylvania State University, University Park, Pennsylvania, USA
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Gros C, Lemay A, Cohen-Adad J. SoftSeg: Advantages of soft versus binary training for image segmentation. Med Image Anal 2021; 71:102038. [PMID: 33784599 DOI: 10.1016/j.media.2021.102038] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/07/2021] [Accepted: 03/11/2021] [Indexed: 12/28/2022]
Abstract
Most image segmentation algorithms are trained on binary masks formulated as a classification task per pixel. However, in applications such as medical imaging, this "black-and-white" approach is too constraining because the contrast between two tissues is often ill-defined, i.e., the voxels located on objects' edges contain a mixture of tissues (a partial volume effect). Consequently, assigning a single "hard" label can result in a detrimental approximation. Instead, a soft prediction containing non-binary values would overcome that limitation. In this study, we introduce SoftSeg, a deep learning training approach that takes advantage of soft ground truth labels, and is not bound to binary predictions. SoftSeg aims at solving a regression instead of a classification problem. This is achieved by using (i) no binarization after preprocessing and data augmentation, (ii) a normalized ReLU final activation layer (instead of sigmoid), and (iii) a regression loss function (instead of the traditional Dice loss). We assess the impact of these three features on three open-source MRI segmentation datasets from the spinal cord gray matter, the multiple sclerosis brain lesion, and the multimodal brain tumor segmentation challenges. Across multiple random dataset splittings, SoftSeg outperformed the conventional approach, leading to an increase in Dice score of 2.0% on the gray matter dataset (p=0.001), 3.3% for the brain lesions, and 6.5% for the brain tumors. SoftSeg produces consistent soft predictions at tissues' interfaces and shows an increased sensitivity for small objects (e.g., multiple sclerosis lesions). The richness of soft labels could represent the inter-expert variability, the partial volume effect, and complement the model uncertainty estimation, which is typically unclear with binary predictions. The developed training pipeline can easily be incorporated into most of the existing deep learning architectures. SoftSeg is implemented in the freely-available deep learning toolbox ivadomed (https://ivadomed.org).
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Affiliation(s)
- Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada
| | - Andreanne Lemay
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada.
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Irimia A, Van Horn JD. Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system. Neuroimage 2021; 225:117478. [PMID: 33160086 PMCID: PMC8485987 DOI: 10.1016/j.neuroimage.2020.117478] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 09/15/2020] [Accepted: 10/13/2020] [Indexed: 12/13/2022] Open
Abstract
The emergence of diffusion, structural, and functional neuroimaging methods has enabled major multi-site efforts to map the human connectome, which has heretofore been defined as containing all neural connections in the central nervous system (CNS). However, these efforts are not structured to examine the richness and complexity of the peripheral nervous system (PNS), which arguably forms the (neglected) rest of the connectome. Despite increasing interest in an atlas of the spinal cord (SC) and PNS which is simultaneously stereotactic, interactive, electronically dissectible, scalable, population-based and deformable, little attention has thus far been devoted to this task of critical importance. Nevertheless, the atlasing of these complete neural structures is essential for neurosurgical planning, neurological localization, and for mapping those components of the human connectome located outside of the CNS. Here we recommend a modification to the definition of the human connectome to include the SC and PNS, and argue for the creation of an inclusive atlas to complement current efforts to map the brain's human connectome, to enhance clinical education, and to assist progress in neuroscience research. In addition to providing a critical overview of existing neuroimaging techniques, image processing methodologies and algorithmic advances which can be combined for the creation of a full connectome atlas, we outline a blueprint for ultimately mapping the entire human nervous system and, thereby, for filling a critical gap in our scientific knowledge of neural connectivity.
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Affiliation(s)
- Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, 3715 McClintock Avenue, Los Angeles CA 90089, United States; Corwin D. Denney Research Center, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, 1042 Downey Way, Los Angeles, CA 90089, United States.
| | - John Darrell Van Horn
- Department of Psychology, University of Virginia, 485 McCormick Road, Gilmer Hall, Room 102, Charlottesville, Virginia 22903, United States; School of Data Science, University of Virginia, Dell 1, Charlottesville, Virginia 22903, United States.
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McLachlin S, Leung J, Sivan V, Quirion PO, Wilkie P, Cohen-Adad J, Whyne CM, Hardisty MR. Spatial correspondence of spinal cord white matter tracts using diffusion tensor imaging, fibre tractography, and atlas-based segmentation. Neuroradiology 2021; 63:373-380. [PMID: 33447915 DOI: 10.1007/s00234-021-02635-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 01/05/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE Neuroimaging provides great utility in complex spinal surgeries, particularly when anatomical geometry is distorted by pathology (tumour, degeneration, etc.). Spinal cord MRI diffusion tractography can be used to generate streamlines; however, it is unclear how well they correspond with white matter tract locations along the cord microstructure. The goal of this work was to evaluate the spatial correspondence of DTI tractography with anatomical MRI in healthy anatomy (where anatomical locations can be well defined in T1-weighted images). METHODS Ten healthy volunteers were scanned on a 3T system. T1-weighted (1 × 1 × 1 mm) and diffusion-weighted images (EPI readout, 2 × 2 × 2 mm, 30 gradient directions) were acquired and subsequently registered (Spinal Cord Toolbox (SCT)). Atlas-based (SCT) anatomic label maps of the left and right lateral corticospinal tracts were identified for each vertebral region (C2-C6) from T1 images. Tractography streamlines were generated with a customized approach, enabling seeding of specific spinal tract regions corresponding to individual vertebral levels. Spatial correspondence of generated fibre streamlines with anatomic tract segmentations was compared in unseeded regions of interest (ROIs). RESULTS Spatial correspondence of the lateral corticospinal tract streamlines was good over a single vertebral ROI (Dice's similarity coefficient (DSC) = 0.75 ± 0.08, Hausdorff distance = 1.08 ± 0.17 mm). Over larger ROI, fair agreement between tractography and anatomical labels was achieved (two levels: DSC = 0.67 ± 0.13, three levels: DSC = 0.52 ± 0.19). CONCLUSION DTI tractography produced good spatial correspondence with anatomic white matter tracts, superior to the agreement between multiple manual tract segmentations (DSC ~ 0.5). This supports further development of spinal cord tractography for computer-assisted neurosurgery.
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Affiliation(s)
- Stewart McLachlin
- Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, E7 3424, Waterloo, Ontario, N2L 3G1, Canada
| | - Jason Leung
- Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada
| | - Vignesh Sivan
- Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada
| | - Pierre-Olivier Quirion
- Department of Electrical Engineering, Polytechnique Montreal, Ecole Polytechnique, Pavillon Lassonde, 2700 Ch de la Tour, L-5610, Montréal, Quebec, H3T 1N8, Canada
| | - Phoenix Wilkie
- Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada
| | - Julien Cohen-Adad
- Department of Electrical Engineering, Polytechnique Montreal, Ecole Polytechnique, Pavillon Lassonde, 2700 Ch de la Tour, L-5610, Montréal, Quebec, H3T 1N8, Canada
| | - Cari Marisa Whyne
- Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada
- Department of Surgery, University of Toronto, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada
| | - Michael Raymond Hardisty
- Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada.
- Department of Surgery, University of Toronto, 2075 Bayview Ave, S621, Toronto, Ontario, M4N 3M5, Canada.
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Biomechanical comparison of spinal cord compression types occurring in Degenerative Cervical Myelopathy. Clin Biomech (Bristol, Avon) 2021; 81:105174. [PMID: 33279293 DOI: 10.1016/j.clinbiomech.2020.105174] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 08/28/2020] [Accepted: 09/03/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Degenerative Cervical Myelopathy results from spine degenerations narrowing the spinal canal and inducing cord compressions. Prognosis is challenging. This study aimed at simulating typical spinal cord compressions observed in patients with a realistic model to better understand pathogenesis for later prediction of patients' evolution. METHODS A 30% reduction in cord cross-sectional area at C5-C6 was defined as myelopathy threshold based on Degenerative Cervical Myelopathy features from literature and MRI measurements in 20 patients. Four main compression types were extracted from MRIs and simulated with a comprehensive three-dimensional finite element spine model. Median diffuse, median focal and lateral types were modelled as disk herniation while circumferential type additionally involved ligamentum flavum hypertrophy. All stresses were quantified along inferior-superior axis, compression development and across atlas-defined spinal cord regions. FINDINGS Anterior gray and white matter globally received the highest stress while lateral pathways were the least affected. Median diffuse compression induced the highest stresses. Circumferential type focused stresses in posterior gray matter. Along inferior-superior axis, those two types showed a peak of constraints at compression site while median focal and lateral types showed lower values but extending further. INTERPRETATION Median diffuse type would be the most detrimental based on stress amplitude. Anterior regions would be the most at risk, except for circumferential type where posterior regions would be equally affected. In addition to applying constraints, ischemia could be a significant component explaining the early demyelination reported in lateral pathways. Moving towards patient-specific simulations, biomechanical models could become strong predictors for degenerative changes.
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Abstract
Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.
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Affiliation(s)
- Wieslaw L Nowinski
- John Paul II Center for Virtual Anatomy and Surgical Simulation, University of Cardinal Stefan Wyszynski, Woycickiego 1/3, Block 12, room 1220, 01-938, Warsaw, Poland.
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36
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Kerbrat A, Gros C, Badji A, Bannier E, Galassi F, Combès B, Chouteau R, Labauge P, Ayrignac X, Carra-Dalliere C, Maranzano J, Granberg T, Ouellette R, Stawiarz L, Hillert J, Talbott J, Tachibana Y, Hori M, Kamiya K, Chougar L, Lefeuvre J, Reich DS, Nair G, Valsasina P, Rocca MA, Filippi M, Chu R, Bakshi R, Callot V, Pelletier J, Audoin B, Maarouf A, Collongues N, De Seze J, Edan G, Cohen-Adad J. Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability. Brain 2020; 143:2089-2105. [PMID: 32572488 DOI: 10.1093/brain/awaa162] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 02/27/2020] [Accepted: 04/02/2020] [Indexed: 11/12/2022] Open
Abstract
Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P < 0.0001). Voxel-wise analyses confirmed that lesion frequency was higher in progressive compared to relapsing-remitting patients, with significant bilateral clusters in the spinal cord corticospinal tracts (P < 0.01). The baseline Expanded Disability Status Scale score was associated with lesion volume fraction within the brain (r = 0.31, P < 0.0001), brainstem (r = 0.45, P < 0.0001) and spinal cord (r = 0.57, P < 0.0001) corticospinal tracts. The spinal cord corticospinal tracts lesion volume fraction remained the strongest factor in the multiple linear regression model, independently from cord atrophy. Baseline spinal cord corticospinal tracts lesion volume fraction was also associated with disability progression at 2-year follow-up (P = 0.003). Our results suggest a cumulative effect of lesions within the corticospinal tracts along the brain, brainstem and spinal cord portions to explain physical disability in multiple sclerosis patients, with a predominant impact of intramedullary lesions.
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Affiliation(s)
- Anne Kerbrat
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.,CHU Rennes, Neurology department, Empenn U 1128 Inserm, CIC1414 Inserm, Rennes, France
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Atef Badji
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.,Department of Neurosciences, Faculty of Medicine, Université de Montréal, QC, Canada
| | - Elise Bannier
- CHU Rennes, Radiology department, Rennes, France.,Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1128, Rennes, France
| | - Francesca Galassi
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1128, Rennes, France
| | - Benoit Combès
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1128, Rennes, France
| | - Raphaël Chouteau
- CHU Rennes, Neurology department, Empenn U 1128 Inserm, CIC1414 Inserm, Rennes, France
| | - Pierre Labauge
- MS Unit, Department of Neurology, CHU Montpellier, Montpellier, France
| | - Xavier Ayrignac
- MS Unit, Department of Neurology, CHU Montpellier, Montpellier, France
| | | | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada.,University of Quebec in Trois-Rivieres, Quebec, Canada
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Leszek Stawiarz
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jan Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jason Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | | | - Masaaki Hori
- Toho University Omori Medical Center, Tokyo, Japan
| | | | - Lydia Chougar
- Department of Neuroradiology, La Pitié Salpêtrière Hospital, Paris, France
| | - Jennifer Lefeuvre
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Paola Valsasina
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Renxin Chu
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Rohit Bakshi
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Virginie Callot
- AP-HM, Pôle d'imagerie médicale, Hôpital de la Timone, CEMEREM, Marseille, France.,Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
| | - Jean Pelletier
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Bertrand Audoin
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Adil Maarouf
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Nicolas Collongues
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, INSERM U1119, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Bâtiment 3 de la Faculté de Médecine, 67 000 Strasbourg, France.,Département de Neurologie, Centre Hospitalier Universitaire de Strasbourg, 67200 Strasbourg, France.,Centre d'investigation Clinique, INSERM U1434, Centre Hospitalier Universitaire de Strasbourg, 67000 Strasbourg, France
| | - Jérôme De Seze
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, INSERM U1119, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Bâtiment 3 de la Faculté de Médecine, 67 000 Strasbourg, France.,Département de Neurologie, Centre Hospitalier Universitaire de Strasbourg, 67200 Strasbourg, France.,Centre d'investigation Clinique, INSERM U1434, Centre Hospitalier Universitaire de Strasbourg, 67000 Strasbourg, France
| | - Gilles Edan
- CHU Rennes, Neurology department, Empenn U 1128 Inserm, CIC1414 Inserm, Rennes, France
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.,Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada
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Macromolecular changes in spinal cord white matter characterize whiplash outcome at 1-year post motor vehicle collision. Sci Rep 2020; 10:22221. [PMID: 33335188 PMCID: PMC7747591 DOI: 10.1038/s41598-020-79190-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 11/30/2020] [Indexed: 11/30/2022] Open
Abstract
Each year, whiplash injuries from motor vehicle collisions (MVC) affect millions worldwide, with no strong evidence of pathology. While the majority recover soon after the injury, the same is not true for roughly 20% reporting higher levels of pain and distress, without diagnostic options. This study used magnetization transfer (MT) imaging to quantify white matter integrity in 78 subjects with varying levels of pain, 1 year after MVC. MT images of the cervical spinal cord were collected parallel to the intervertebral disks. MT ratios (MTR) were calculated in select white matter tracts along with MTR homogeneity (MTRh) at each level. Significant differences were observed between clinical outcome groups in the left and right spinothalamic tracts (p = 0.003 and 0.020) and MTRh (p = 0.009). MTRh was elevated in females with poor recovery versus females reporting recovery (p < 0.001) or milder symptoms (p < 0.001), and in males reporting recovery (p = 0.007) or no recovery (p < 0.001). There was a significant interaction between recovery status and sex (p = 0.015). MT imaging identified tract specific and regional changes in white matter integrity suggesting potential insults to the cord. Additionally, significant MTRh differences between sexes were observed, characterizing the heterogeneity of whiplash recovery and worse outcomes in females.
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Rasoanandrianina H, Demortière S, Trabelsi A, Ranjeva JP, Girard O, Duhamel G, Guye M, Pelletier J, Audoin B, Callot V. Sensitivity of the Inhomogeneous Magnetization Transfer Imaging Technique to Spinal Cord Damage in Multiple Sclerosis. AJNR Am J Neuroradiol 2020; 41:929-937. [PMID: 32414903 DOI: 10.3174/ajnr.a6554] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 03/12/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND PURPOSE The inhomogeneous magnetization transfer technique has demonstrated high specificity for myelin, and has shown sensitivity to multiple sclerosis-related impairment in brain tissue. Our aim was to investigate its sensitivity to spinal cord impairment in MS relative to more established MR imaging techniques (volumetry, magnetization transfer, DTI). MATERIALS AND METHODS Anatomic images covering the cervical spinal cord from the C1 to C6 levels and DTI, magnetization transfer/inhomogeneous magnetization transfer images at the C2/C5 levels were acquired in 19 patients with MS and 19 paired healthy controls. Anatomic images were segmented in spinal cord GM and WM, both manually and using the AMU40 atlases. MS lesions were manually delineated. MR metrics were analyzed within normal-appearing and lesion regions in anterolateral and posterolateral WM and compared using Wilcoxon rank tests and z scores. Correlations between MR metrics and clinical scores in patients with MS were evaluated using the Spearman rank correlation. RESULTS AMU40-based C1-to-C6 GM/WM automatic segmentations in patients with MS were evaluated relative to manual delineation. Mean Dice coefficients were 0.75/0.89, respectively. All MR metrics (WM/GM cross-sectional areas, normal-appearing and lesion diffusivities, and magnetization transfer/inhomogeneous magnetization transfer ratios) were observed altered in patients compared with controls (P < .05). Additionally, the absolute inhomogeneous magnetization transfer ratio z scores were significantly higher than those of the other MR metrics (P < .0001), suggesting a higher inhomogeneous magnetization transfer sensitivity toward spinal cord impairment in MS. Significant correlations with the Expanded Disability Status Scale (ρ = -0.73/P = .02, ρ = -0.81/P = .004) and the total Medical Research Council scale (ρ = 0.80/P = .009, ρ = -0.74/P = .02) were observed for inhomogeneous magnetization transfer and magnetization transfer ratio z scores, respectively, in normal-appearing WM regions, while weaker and nonsignificant correlations were obtained for DTI metrics. CONCLUSIONS With inhomogeneous magnetization transfer being highly sensitive to spinal cord damage in MS compared with conventional magnetization transfer and DTI, it could generate great clinical interest for longitudinal follow-up and potential remyelinating clinical trials. In line with other advanced myelin techniques with which it could be compared, it opens perspectives for multicentric investigations.
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Affiliation(s)
- H Rasoanandrianina
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France.,Laboratoire de Biomécanique Appliquée, Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Reseaux, Aix-Marseille Université; iLab-Spine International Associated Laboratory (H.R., J.P.R., V.C.), Marseille-Montreal, France-Canada
| | - S Demortière
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France.,Department of Neurology (S.D., J.P., B.A.), Centre Hospitalier Universitaire Timone, Assistance Publique-Hopitaux de Marseille, Marseille, France
| | - A Trabelsi
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - J P Ranjeva
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France.,Laboratoire de Biomécanique Appliquée, Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Reseaux, Aix-Marseille Université; iLab-Spine International Associated Laboratory (H.R., J.P.R., V.C.), Marseille-Montreal, France-Canada
| | - O Girard
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - G Duhamel
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - M Guye
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - J Pelletier
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France.,Department of Neurology (S.D., J.P., B.A.), Centre Hospitalier Universitaire Timone, Assistance Publique-Hopitaux de Marseille, Marseille, France
| | - B Audoin
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France.,Department of Neurology (S.D., J.P., B.A.), Centre Hospitalier Universitaire Timone, Assistance Publique-Hopitaux de Marseille, Marseille, France
| | - V Callot
- From the Center for Magnetic Resonance in Biology and Medicine (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Centre National de la Recherche Scientifique, Aix-Marseille Université, Marseille, France .,Centre d'Exploration Métabolique par Résonance Magnétique (H.R., S.D., A.T., J.P.R., O.G., G.D., M.G., J.P., B.A., V.C.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France.,Laboratoire de Biomécanique Appliquée, Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Reseaux, Aix-Marseille Université; iLab-Spine International Associated Laboratory (H.R., J.P.R., V.C.), Marseille-Montreal, France-Canada
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Labounek R, Valošek J, Horák T, Svátková A, Bednařík P, Vojtíšek L, Horáková M, Nestrašil I, Lenglet C, Cohen-Adad J, Bednařík J, Hluštík P. HARDI-ZOOMit protocol improves specificity to microstructural changes in presymptomatic myelopathy. Sci Rep 2020; 10:17529. [PMID: 33067520 PMCID: PMC7567840 DOI: 10.1038/s41598-020-70297-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 07/21/2020] [Indexed: 12/12/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) proved promising in patients with non-myelopathic degenerative cervical cord compression (NMDCCC), i.e., without clinically manifested myelopathy. Aim of the study is to present a fast multi-shell HARDI-ZOOMit dMRI protocol and validate its usability to detect microstructural myelopathy in NMDCCC patients. In 7 young healthy volunteers, 13 age-comparable healthy controls, 18 patients with mild NMDCCC and 15 patients with severe NMDCCC, the protocol provided higher signal-to-noise ratio, enhanced visualization of white/gray matter structures in microstructural maps, improved dMRI metric reproducibility, preserved sensitivity (SE = 87.88%) and increased specificity (SP = 92.31%) of control-patient group differences when compared to DTI-RESOLVE protocol (SE = 87.88%, SP = 76.92%). Of the 56 tested microstructural parameters, HARDI-ZOOMit yielded significant patient-control differences in 19 parameters, whereas in DTI-RESOLVE data, differences were observed in 10 parameters, with mostly lower robustness. Novel marker the white-gray matter diffusivity gradient demonstrated the highest separation. HARDI-ZOOMit protocol detected larger number of crossing fibers (5–15% of voxels) with physiologically plausible orientations than DTI-RESOLVE protocol (0–8% of voxels). Crossings were detected in areas of dorsal horns and anterior white commissure. HARDI-ZOOMit protocol proved to be a sensitive and practical tool for clinical quantitative spinal cord imaging.
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Affiliation(s)
- René Labounek
- Department of Biomedical Engineering, University Hospital Olomouc, 779 00, Olomouc, Czech Republic.,Department of Neurology, Palacký University, 779 00, Olomouc, Czech Republic.,Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Jan Valošek
- Department of Biomedical Engineering, University Hospital Olomouc, 779 00, Olomouc, Czech Republic.,Department of Neurology, Palacký University, 779 00, Olomouc, Czech Republic
| | - Tomáš Horák
- Central European Institute of Technology, Masaryk University, 625 00, Brno, Czech Republic.,Department of Neurology, University Hospital Brno, 625 00, Brno, Czech Republic.,Faculty of Medicine, Masaryk University, 625 00, Brno, Czech Republic
| | - Alena Svátková
- Central European Institute of Technology, Masaryk University, 625 00, Brno, Czech Republic.,Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, 1090, Vienna, Austria.,Department of Imaging Methods, Faculty of Medicine, University of Ostrava, 701 03, Ostrava, Czech Republic
| | - Petr Bednařík
- Central European Institute of Technology, Masaryk University, 625 00, Brno, Czech Republic.,High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - Lubomír Vojtíšek
- Central European Institute of Technology, Masaryk University, 625 00, Brno, Czech Republic
| | - Magda Horáková
- Central European Institute of Technology, Masaryk University, 625 00, Brno, Czech Republic.,Department of Neurology, University Hospital Brno, 625 00, Brno, Czech Republic.,Faculty of Medicine, Masaryk University, 625 00, Brno, Czech Republic
| | - Igor Nestrašil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, 55414, USA.,Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Julien Cohen-Adad
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Josef Bednařík
- Central European Institute of Technology, Masaryk University, 625 00, Brno, Czech Republic.,Department of Neurology, University Hospital Brno, 625 00, Brno, Czech Republic.,Faculty of Medicine, Masaryk University, 625 00, Brno, Czech Republic
| | - Petr Hluštík
- Department of Neurology, Palacký University, 779 00, Olomouc, Czech Republic. .,Department of Neurology, University Hospital Olomouc, 779 00, Olomouc, Czech Republic.
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40
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Tinnermann A, Büchel C, Cohen-Adad J. Cortico-spinal imaging to study pain. Neuroimage 2020; 224:117439. [PMID: 33039624 DOI: 10.1016/j.neuroimage.2020.117439] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/21/2020] [Accepted: 10/01/2020] [Indexed: 12/15/2022] Open
Abstract
Functional magnetic resonance imaging of the brain has helped to reveal mechanisms of pain perception in health and disease. Recently, imaging approaches have been developed that allow recording neural activity simultaneously in the brain and in the spinal cord. These approaches offer the possibility to examine pain perception in the entire central pain system and in addition, to investigate cortico-spinal interactions during pain processing. Although cortico-spinal imaging is a promising technique, it bears challenges concerning data acquisition and data analysis strategies. In this review, we discuss studies that applied simultaneous imaging of the brain and spinal cord to explore central pain processing. Furthermore, we describe different MR-related acquisition techniques, summarize advantages and disadvantages of approaches that have been implemented so far and present software that has been specifically developed for the analysis of spinal fMRI data to address challenges of spinal data analysis.
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Affiliation(s)
- Alexandra Tinnermann
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Max Planck School of Cognition, Leipzig, Germany.
| | - Christian Büchel
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Max Planck School of Cognition, Leipzig, Germany
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, Quebec, Canada.
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Magnetization Transfer Ratio and Morphometrics of the Spinal Cord Associates with Surgical Recovery in Patients with Degenerative Cervical Myelopathy. World Neurosurg 2020; 144:e939-e947. [PMID: 33010502 DOI: 10.1016/j.wneu.2020.09.148] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 11/21/2022]
Abstract
OBJECTIVES We assessed the prognostic value of the preoperative magnetization transfer ratio (MTR) and morphometrics of the spinal cord in patients with degenerative cervical myelopathy (DCM) in a longitudinal cohort study. METHODS Thirteen subjects with DCM underwent 3T magnetization transfer imaging. The MTR was calculated for the spinal cord regions and specific white matter tracts. Morphometric measures were extracted. Clinical (modified Japanese Orthopaedics Association [mJOA] and Nurick scale scores) and health-related quality of life scores were assessed before and after cervical decompression surgery. The association between the magnetic resonance imaging (MRI) metrics and postoperative recovery was assessed (Spearman's correlation). Receiver operating characteristics were used to assess the accuracy of MRI metrics in identifying ≥50% recovery in function. RESULTS Preoperative anterior cord MTRs were associated with recovery in mJOA scores (ρ = 0.608; P = 0.036; area under the curve [AUC], 0.66). Preoperative lateral cord MTR correlated with the neck disability index (ρ = 0.699; P = 0.011) and pain interference scale (ρ = 0.732; P = 0.007). Preoperative rubrospinal tract MTR was associated with mJOA score recovery (ρ = 0.573; P = 0.041; AUC, 0.86). Preoperative corticospinal tract and reticulospinal MTRs were related to recovery in pain interference scores (ρ = 0.591; P = 0.033; and ρ = 0.583; P = 0.035, respectively). Eccentricity of the cord was associated with Nurick scores (ρ = 0.606; P = 0.028) and mJOA scores (ρ = 0.651; P = 0.025; AUC, 0.92). CONCLUSIONS Preoperative MTR and eccentricity measurements of the spinal cord have prognostic value in assessing the response to surgery and recovery in patients with DCM. Advanced MRI and atlas-based postprocessing techniques can inform interventions and advance the healthcare received by patients with DCM.
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Kinany N, Pirondini E, Micera S, Van De Ville D. Dynamic Functional Connectivity of Resting-State Spinal Cord fMRI Reveals Fine-Grained Intrinsic Architecture. Neuron 2020; 108:424-435.e4. [PMID: 32910894 DOI: 10.1016/j.neuron.2020.07.024] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/23/2020] [Accepted: 07/18/2020] [Indexed: 12/24/2022]
Abstract
The neuroimaging community has shown tremendous interest in exploring the brain's spontaneous activity using functional magnetic resonance imaging (fMRI). On the contrary, the spinal cord has been largely overlooked despite its pivotal role in processing sensorimotor signals. Only a handful of studies have probed the organization of spinal resting-state fluctuations, always using static measures of connectivity. Many innovative approaches have emerged for analyzing dynamics of brain fMRI, but they have not yet been applied to the spinal cord, although they could help disentangle its functional architecture. Here, we leverage a dynamic connectivity method based on the clustering of hemodynamic-informed transients to unravel the rich dynamic organization of spinal resting-state signals. We test this approach in 19 healthy subjects, uncovering fine-grained spinal components and highlighting their neuroanatomical and physiological nature. We provide a versatile tool, the spinal innovation-driven co-activation patterns (SpiCiCAP) framework, to characterize spinal circuits during rest and task, as well as their disruption in neurological disorders.
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Affiliation(s)
- Nawal Kinany
- Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland; Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Elvira Pirondini
- Department of Radiology and Medical Informatics, University of Geneva, 1211 Geneva, Switzerland
| | - Silvestro Micera
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland; The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56025 Pontedera, Italy.
| | - Dimitri Van De Ville
- Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, 1211 Geneva, Switzerland.
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Grussu F, Battiston M, Veraart J, Schneider T, Cohen-Adad J, Shepherd TM, Alexander DC, Fieremans E, Novikov DS, Gandini Wheeler-Kingshott CAM. Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising. Neuroimage 2020; 217:116884. [PMID: 32360689 PMCID: PMC7378937 DOI: 10.1016/j.neuroimage.2020.116884] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 03/18/2020] [Accepted: 04/23/2020] [Indexed: 12/11/2022] Open
Abstract
Multi-parametric quantitative MRI (qMRI) of the spinal cord is a promising non-invasive tool to probe early microstructural damage in neurological disorders. It is usually performed in vivo by combining acquisitions with multiple signal readouts, which exhibit different thermal noise levels, geometrical distortions and susceptibility to physiological noise. This ultimately hinders joint multi-contrast modelling and makes the geometric correspondence of parametric maps challenging. We propose an approach to overcome these limitations, by implementing state-of-the-art microstructural MRI of the spinal cord with a unified signal readout in vivo (i.e. with matched spatial encoding parameters across a range of imaging contrasts). We base our acquisition on single-shot echo planar imaging with reduced field-of-view, and obtain data from two different vendors (vendor 1: Philips Achieva; vendor 2: Siemens Prisma). Importantly, the unified acquisition allows us to compare signal and noise across contrasts, thus enabling overall quality enhancement via multi-contrast image denoising methods. As a proof-of-concept, here we provide a demonstration with one such method, known as Marchenko-Pastur (MP) Principal Component Analysis (PCA) denoising. MP-PCA is a singular value (SV) decomposition truncation approach that relies on redundant acquisitions, i.e. such that the number of measurements is large compared to the number of components that are maintained in the truncated SV decomposition. Here we used in vivo and synthetic data to test whether a unified readout enables more efficient MP-PCA denoising of less redundant acquisitions, since these can be denoised jointly with more redundant ones. We demonstrate that a unified readout provides robust multi-parametric maps, including diffusion and kurtosis tensors from diffusion MRI, myelin metrics from two-pool magnetisation transfer, and T1 and T2 from relaxometry. Moreover, we show that MP-PCA improves the quality of our multi-contrast acquisitions, since it reduces the coefficient of variation (i.e. variability) by up to 17% for mean kurtosis, 8% for bound pool fraction (myelin-sensitive), and 13% for T1, while enabling more efficient denoising of modalities limited in redundancy (e.g. relaxometry). In conclusion, multi-parametric spinal cord qMRI with unified readout is feasible and provides robust microstructural metrics with matched resolution and distortions, whose quality benefits from multi-contrast denoising methods such as MP-PCA.
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Affiliation(s)
- Francesco Grussu
- Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
| | - Marco Battiston
- Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Jelle Veraart
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | | | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, Canada
| | - Timothy M Shepherd
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
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Bonacchi R, Pagani E, Meani A, Cacciaguerra L, Preziosa P, De Meo E, Filippi M, Rocca MA. Clinical Relevance of Multiparametric MRI Assessment of Cervical Cord Damage in Multiple Sclerosis. Radiology 2020; 296:605-615. [PMID: 32573387 DOI: 10.1148/radiol.2020200430] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background In multiple sclerosis (MS), knowledge about how spinal cord abnormalities translate into clinical manifestations is incomplete. Comprehensive, multiparametric MRI studies are useful in this perspective, but studies for the spinal cord are lacking. Purpose To identify MRI features of cervical spinal cord damage that could help predict disability and disease course in MS by using a comprehensive, multiparametric MRI approach. Materials and Methods In this retrospective hypothesis-driven analysis of longitudinally acquired data between June 2017 and April 2019, 120 patients with MS (58 with relapsing-remitting MS [RRMS] and 62 with progressive MS [PMS]) and 30 age- and sex-matched healthy control participants underwent 3.0-T MRI of the brain and cervical spinal cord. Cervical spinal cord MRI was performed with three-dimensional (3D) T1-weighted, T2-weighted, and diffusion-weighted imaging; sagittal two-dimensional (2D) short inversion time inversion-recovery imaging; and axial 2D phase-sensitive inversion-recovery imaging at the C2-C3 level. Brain MRI was performed with 3D T1-weighted, fluid-attenuated inversion-recovery and T2-weighted sequences. Associations between MRI variables and disability were explored with age-, sex- and phenotype-adjusted linear models. Results In patients with MS, multivariable analysis identified phenotype, cervical spinal cord gray matter (GM) cross-sectional area (CSA), lateral funiculi fractional anisotropy (FA), and brain GM volume as independent predictors of Expanded Disability Status Scale (EDSS) score (R2 = 0.86). The independent predictors of EDSS score in RRMS were lateral funiculi FA, normalized brain volume, and cervical spinal cord GM T2 lesion volume (R2 = 0.51). The independent predictors of EDSS score in PMS were cervical spinal cord GM CSA and brain GM volume (R2 = 0.44). Logistic regression analysis identified cervical spinal cord GM CSA and T2 lesion volume as independent predictors of phenotype (area under the receiver operating characteristic curve = 0.95). An optimal cervical spinal cord GM CSA cut-off value of 11.1 mm2 was found to enable accurate differentiation of patients with PMS, having values below the threshold, from those with RRMS (sensitivity = 90% [56 of 62], specificity = 91% [53 of 58]). Conclusion Cervical spinal cord MRI involvement has a central role in explaining disability in multiple sclerosis (MS): Lesion-induced damage in the lateral funiculi and gray matter (GM) in relapsing-remitting MS and GM atrophy in patients with progressive MS are the most relevant variables. Cervical spinal cord GM atrophy is an accurate predictor of progressive phenotype. Cervical spinal cord GM lesions may subsequently cause GM atrophy, which may contribute to evolution to PMS. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Zivadinov and Bergsland in this issue.
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Affiliation(s)
- Raffaello Bonacchi
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Alessandro Meani
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Laura Cacciaguerra
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Ermelinda De Meo
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
| | - Maria A Rocca
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (R.B., E.P., A.M., L.C., P.P., E.D.M., M.F., M.A.R.), Neurology Unit (R.B., L.C., P.P., E.D.M., M.F., M.A.R.), and Neurophysiology Unit (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20132, Italy; and Vita-Salute San Raffaele University, Milan, Italy (R.B., L.C., E.D.M., M.F.)
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Lévy S, Rapacchi S, Massire A, Troalen T, Feiweier T, Guye M, Callot V. Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises. Magn Reson Med 2020; 84:1198-1217. [DOI: 10.1002/mrm.28195] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 12/16/2019] [Accepted: 01/10/2020] [Indexed: 12/15/2022]
Affiliation(s)
- Simon Lévy
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
- Aix‐Marseille Univ, IFSTTAR, LBA Marseille France
- iLab‐Spine International Associated Laboratory Marseille‐Montreal France‐Canada
| | - Stanislas Rapacchi
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
| | - Aurélien Massire
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
- iLab‐Spine International Associated Laboratory Marseille‐Montreal France‐Canada
| | | | | | - Maxime Guye
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
| | - Virginie Callot
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
- iLab‐Spine International Associated Laboratory Marseille‐Montreal France‐Canada
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46
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Lorenzi RM, Palesi F, Castellazzi G, Vitali P, Anzalone N, Bernini S, Cotta Ramusino M, Sinforiani E, Micieli G, Costa A, D’Angelo E, Gandini Wheeler-Kingshott CAM. Unsuspected Involvement of Spinal Cord in Alzheimer Disease. Front Cell Neurosci 2020; 14:6. [PMID: 32082122 PMCID: PMC7002560 DOI: 10.3389/fncel.2020.00006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 01/10/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer's disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients' classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.
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Affiliation(s)
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Neuroradiology Unit, Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Gloria Castellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Paolo Vitali
- Neuroradiology Unit, Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Sara Bernini
- Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Matteo Cotta Ramusino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Elena Sinforiani
- Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Giuseppe Micieli
- Department of Emergency Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Alfredo Costa
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Egidio D’Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Brain Connectivity Center (BCC), IRCCS Mondino Foundation, Pavia, Italy
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
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47
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Eden D, Gros C, Badji A, Dupont SM, De Leener B, Maranzano J, Zhuoquiong R, Liu Y, Granberg T, Ouellette R, Stawiarz L, Hillert J, Talbott J, Bannier E, Kerbrat A, Edan G, Labauge P, Callot V, Pelletier J, Audoin B, Rasoanandrianina H, Brisset JC, Valsasina P, Rocca MA, Filippi M, Bakshi R, Tauhid S, Prados F, Yiannakas M, Kearney H, Ciccarelli O, Smith SA, Andrada Treaba C, Mainero C, Lefeuvre J, Reich DS, Nair G, Shepherd TM, Charlson E, Tachibana Y, Hori M, Kamiya K, Chougar L, Narayanan S, Cohen-Adad J. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord. Brain 2020; 142:633-646. [PMID: 30715195 DOI: 10.1093/brain/awy352] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Revised: 10/25/2018] [Accepted: 11/20/2018] [Indexed: 12/12/2022] Open
Abstract
Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.
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Affiliation(s)
- Dominique Eden
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Atef Badji
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada
| | - Sara M Dupont
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada.,Department of Anatomy, Université de Québec à Trois-Rivières, Trois-Rivières, QC, Canada
| | - Ren Zhuoquiong
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, P. R. China
| | - Yaou Liu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, P. R. China.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, P. R. China
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Massachusetts General Hospital, Boston, USA
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Massachusetts General Hospital, Boston, USA
| | - Leszek Stawiarz
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jan Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jason Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Elise Bannier
- CHU Rennes, Radiology Department, Rennes, France.,Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France
| | - Anne Kerbrat
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France.,CHU Rennes, Neurology Department, Rennes, France
| | - Gilles Edan
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France.,CHU Rennes, Neurology Department, Rennes, France
| | - Pierre Labauge
- MS Unit, Department of Neurology, University Hospital of Montpellier, Montpellier, France
| | - Virginie Callot
- Aix Marseille University, CNRS, CRMBM, Marseille, France.,APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean Pelletier
- APHM, CHU Timone, CEMEREM, Marseille, France.,APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Bertrand Audoin
- APHM, CHU Timone, CEMEREM, Marseille, France.,APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Henitsoa Rasoanandrianina
- Aix Marseille University, CNRS, CRMBM, Marseille, France.,APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean-Christophe Brisset
- Observatoire Français de la Sclérose en Plaques (OFSEP) ; Université de Lyon, Université Claude Bernard Lyon 1; Hospices Civils de Lyon; CREATIS-LRMN, UMR 5220 CNRS and U 1044 INSERM; Lyon, France
| | - Paola Valsasina
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Rohit Bakshi
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Shahamat Tauhid
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Ferran Prados
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK.,Center for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Marios Yiannakas
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Hugh Kearney
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Olga Ciccarelli
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Jennifer Lefeuvre
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | | | - Erik Charlson
- Department of Radiology, NYU Langone Medical Center, New York, USA
| | | | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Kouhei Kamiya
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Lydia Chougar
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.,Hospital Cochin, Paris, France
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada.,Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
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48
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Anterior fissure, central canal, posterior septum and more: New insights into the cervical spinal cord gray and white matter regional organization using T1 mapping at 7T. Neuroimage 2020; 205:116275. [DOI: 10.1016/j.neuroimage.2019.116275] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 09/16/2019] [Accepted: 10/10/2019] [Indexed: 12/12/2022] Open
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49
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Smith ZA, Weber KA, Paliwal M, Hopkins BS, Barry AJ, Cantrell D, Ganju A, Koski TR, Parrish TB, Dhaher Y. Magnetic Resonance Imaging Atlas-Based Volumetric Mapping of the Cervical Cord Gray Matter in Cervical Canal Stenosis. World Neurosurg 2019; 134:e497-e504. [PMID: 31669690 DOI: 10.1016/j.wneu.2019.10.109] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/18/2019] [Accepted: 10/18/2019] [Indexed: 02/02/2023]
Abstract
BACKGROUND White matter volume loss may be an anatomic driver in the development of clinical symptoms in cervical spondylotic myelopathy (CSM). Considerably less attention has been devoted to gray matter (GM) injury. Newly developed atlas-based mapping techniques may allow evaluation of GM cord volume alterations in CSM. METHODS There were 29 subjects evaluated: 15 patients with CSM (61.1 ± 8.7 years old) and 14 age-matched control subjects (56.1 ± 5.3 years old). All subjects underwent 3T magnetic resonance imaging of the cervical spine. Post-processing with the Spinal Cord Toolbox (v3.0) provided GM volumetric analysis. Clinical scores collected included modified Japanese Orthopaedic Association, neck and arm numeric rating scales, Nurick Scale, and Neck Disability Index. All volumes were normalized to account for anatomic variability. RESULTS Normalized mean ventral GM volume in the compression region was significantly lower in patients compared with control subjects (1.103 ± 0.21 vs. 1.35 ± 0.32, P = 0.027). Normalized mean dorsal volume in the compression region was decreased in patients compared with control subjects (0.90 ± 0.17 vs. 1.04 ± 0.15, P = 0.049). GM volumes were associated with clinical scores, including Neck Disability Index, arm numeric rating scale, modified Japanese Orthopaedic Association, and Nurick Scale scores (P = 0.022, P = 0.004, P = 0.027, and P = 0.016). CONCLUSIONS GM volume loss may be evaluated through atlas-based post-processing techniques and may correlate with clinical symptoms in CSM.
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Affiliation(s)
- Zachary A Smith
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
| | - Kenneth A Weber
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, California, USA
| | - Monica Paliwal
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Benjamin S Hopkins
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | | | - Donald Cantrell
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Aruna Ganju
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tyler R Koski
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Todd B Parrish
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Yasin Dhaher
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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50
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Rasoanandrianina H, Massire A, Taso M, Guye M, Ranjeva JP, Kober T, Callot V. Regional T 1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence. NMR IN BIOMEDICINE 2019; 32:e4142. [PMID: 31393649 DOI: 10.1002/nbm.4142] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 05/20/2019] [Accepted: 06/18/2019] [Indexed: 06/10/2023]
Abstract
The recently-proposed MP2RAGE sequence was purposely optimized for cervical spinal cord imaging at 3T. Sequence parameters were chosen to optimize gray/white matter T1 contrast with sub-millimetric resolution and scan-time < 10 min while preserving reliable T1 determination with minimal B1+ variation effects within a range of values compatible with pathologies and surrounding structures. Results showed good agreements with IR-based measurements, high MP2RAGE-based T1 reproducibility and preliminary evidences of age- and tract-related T1 variations in the healthy spinal cord.
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Affiliation(s)
- Henitsoa Rasoanandrianina
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Aix-Marseille University, IFSTTAR, LBA UMR_T24, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Aurélien Massire
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Manuel Taso
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center & Harvard Medical School, Boston, Massachusetts, USA
| | - Maxime Guye
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Virginie Callot
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
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