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Rios NL, Gilbert KM, Papp D, Cereza G, Foias A, Rangaprakash D, May MW, Guerin B, Wald LL, Keil B, Stockmann JP, Barry RL, Cohen-Adad J. An 8-channel Tx dipole and 20-channel Rx loop coil array for MRI of the cervical spinal cord at 7 Tesla. NMR IN BIOMEDICINE 2023; 36:e5002. [PMID: 37439129 PMCID: PMC10733907 DOI: 10.1002/nbm.5002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/10/2023] [Accepted: 06/15/2023] [Indexed: 07/14/2023]
Abstract
The quality of cervical spinal cord images can be improved by the use of tailored radiofrequency (RF) coil solutions for ultrahigh field imaging; however, very few commercial and research 7-T RF coils currently exist for the spinal cord, and in particular, those with parallel transmission (pTx) capabilities. This work presents the design, testing, and validation of a pTx/Rx coil for the human neck and cervical/upper thoracic spinal cord. The pTx portion is composed of eight dipoles to ensure high homogeneity over this large region of the spinal cord. The Rx portion is made up of twenty semiadaptable overlapping loops to produce high signal-to-noise ratio (SNR) across the patient population. The coil housing is designed to facilitate patient positioning and comfort, while also being tight fitting to ensure high sensitivity. We demonstrate RF shimming capabilities to optimize B1 + uniformity, power efficiency, and/or specific absorption rate efficiency. B1 + homogeneity, SNR, and g-factor were evaluated in adult volunteers and demonstrated excellent performance from the occipital lobe down to the T4-T5 level. We compared the proposed coil with two state-of-the-art head and head/neck coils, confirming its superiority in the cervical and upper thoracic regions of the spinal cord. This coil solution therefore provides a convincing platform for producing the high image quality necessary for clinical and research scanning of the upper spinal cord.
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Affiliation(s)
- Nibardo Lopez Rios
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada
| | - Kyle M. Gilbert
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON, Canada
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada
| | - Gaspard Cereza
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada
| | - D. Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Markus W. May
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany
- High Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Bastien Guerin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Lawrence L. Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection, University of Applied Sciences Mittelhessen, Giessen, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps University of Marburg, Marburg, Germany
| | - Jason P. Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
- Mila – Quebec AI Institute, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada
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Milekovic T, Moraud EM, Macellari N, Moerman C, Raschellà F, Sun S, Perich MG, Varescon C, Demesmaeker R, Bruel A, Bole-Feysot LN, Schiavone G, Pirondini E, YunLong C, Hao L, Galvez A, Hernandez-Charpak SD, Dumont G, Ravier J, Le Goff-Mignardot CG, Mignardot JB, Carparelli G, Harte C, Hankov N, Aureli V, Watrin A, Lambert H, Borton D, Laurens J, Vollenweider I, Borgognon S, Bourre F, Goillandeau M, Ko WKD, Petit L, Li Q, Buschman R, Buse N, Yaroshinsky M, Ledoux JB, Becce F, Jimenez MC, Bally JF, Denison T, Guehl D, Ijspeert A, Capogrosso M, Squair JW, Asboth L, Starr PA, Wang DD, Lacour SP, Micera S, Qin C, Bloch J, Bezard E, Courtine G. A spinal cord neuroprosthesis for locomotor deficits due to Parkinson's disease. Nat Med 2023; 29:2854-2865. [PMID: 37932548 DOI: 10.1038/s41591-023-02584-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 09/08/2023] [Indexed: 11/08/2023]
Abstract
People with late-stage Parkinson's disease (PD) often suffer from debilitating locomotor deficits that are resistant to currently available therapies. To alleviate these deficits, we developed a neuroprosthesis operating in closed loop that targets the dorsal root entry zones innervating lumbosacral segments to reproduce the natural spatiotemporal activation of the lumbosacral spinal cord during walking. We first developed this neuroprosthesis in a non-human primate model that replicates locomotor deficits due to PD. This neuroprosthesis not only alleviated locomotor deficits but also restored skilled walking in this model. We then implanted the neuroprosthesis in a 62-year-old male with a 30-year history of PD who presented with severe gait impairments and frequent falls that were medically refractory to currently available therapies. We found that the neuroprosthesis interacted synergistically with deep brain stimulation of the subthalamic nucleus and dopaminergic replacement therapies to alleviate asymmetry and promote longer steps, improve balance and reduce freezing of gait. This neuroprosthesis opens new perspectives to reduce the severity of locomotor deficits in people with PD.
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Affiliation(s)
- Tomislav Milekovic
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
- Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Nicolo Macellari
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Charlotte Moerman
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Flavio Raschellà
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- NeuroX Institute, School of Bioengineering, EPFL, Lausanne, Switzerland
| | - Shiqi Sun
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Matthew G Perich
- Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Camille Varescon
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Robin Demesmaeker
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Alice Bruel
- Institute of Bioengineering, School of Engineering, EPFL, Lausanne, Switzerland
| | - Léa N Bole-Feysot
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Giuseppe Schiavone
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Laboratory for Soft Bioelectronic Interfaces (LSBI), NeuroX Institute, EPFL, Lausanne, Switzerland
| | - Elvira Pirondini
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Cheng YunLong
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | - Li Hao
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | - Andrea Galvez
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Sergio Daniel Hernandez-Charpak
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Gregory Dumont
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Jimmy Ravier
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Camille G Le Goff-Mignardot
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Jean-Baptiste Mignardot
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Gaia Carparelli
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Cathal Harte
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Nicolas Hankov
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Viviana Aureli
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | | | | | - David Borton
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
- School of Engineering, Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Jean Laurens
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Isabelle Vollenweider
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Simon Borgognon
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - François Bourre
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Michel Goillandeau
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Wai Kin D Ko
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | - Laurent Petit
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Qin Li
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | | | | | - Maria Yaroshinsky
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jean-Baptiste Ledoux
- Department of Diagnostic and Interventional Radiology, CHUV/UNIL, Lausanne, Switzerland
| | - Fabio Becce
- Department of Diagnostic and Interventional Radiology, CHUV/UNIL, Lausanne, Switzerland
| | | | - Julien F Bally
- Department of Neurology, CHUV/UNIL, Lausanne, Switzerland
| | | | - Dominique Guehl
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Auke Ijspeert
- Institute of Bioengineering, School of Engineering, EPFL, Lausanne, Switzerland
| | - Marco Capogrosso
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jordan W Squair
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Leonie Asboth
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Stéphanie P Lacour
- NeuroX Institute, School of Bioengineering, EPFL, Lausanne, Switzerland
- Laboratory for Soft Bioelectronic Interfaces (LSBI), NeuroX Institute, EPFL, Lausanne, Switzerland
| | - Silvestro Micera
- NeuroX Institute, School of Bioengineering, EPFL, Lausanne, Switzerland
- Department of Excellence in Robotics and AI, Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Chuan Qin
- China Academy of Medical Sciences, Beijing, China
| | - Jocelyne Bloch
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
- Department of Neurosurgery, CHUV, Lausanne, Switzerland.
| | - Erwan Bezard
- Motac Neuroscience, UK-M15 6WE, Manchester, UK.
- China Academy of Medical Sciences, Beijing, China.
- Institute of Laboratory Animal Sciences, Beijing, China.
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.
| | - G Courtine
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
- Department of Neurosurgery, CHUV, Lausanne, Switzerland.
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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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54
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Al-shaari H, J F, R M, CJ H. A systematic review of repeatability and reproducibility studies of diffusion tensor imaging of cervical spinal cord. Br J Radiol 2023; 96:20221019. [PMID: 37751162 PMCID: PMC10607424 DOI: 10.1259/bjr.20221019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 07/12/2023] [Accepted: 08/10/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVES Diffusion tensor imaging (DTI) techniques are being studied as a possible diagnostic and predictive tool for the evaluation of cervical spinal cord disease. This systematic review aims to evaluate the previous DTI studies that specifically investigated the repeatability and reproducibility of DTI in the cervical spinal cord. METHODS AND MATERIALS A search in the PubMed, Scopus, Web of Science and Ovid electronic databases was conducted for articles published between January 1990 and February 2022 that related to the repeatability and reproducibility of DTI in evaluating the cervical spinal cord using one of the following measurements: the intraclass correlation coefficient (ICC) and/or the coefficient of variation (CV), and/or Bland-Altman (BA) differences analysis methods. DTI studies that presented full statistical analysis of repeatability and/or reproducibility tests of the cervical spinal cord in peer-reviewed full-text publications published in journals were included. Articles that included at least one of the keywords within the titles or abstracts were identified. Additional full-text papers were found by searching the citations and reference lists of related articles. This review has followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance. Risk of bias was evaluated with 13 criteria weighted toward methodological quality of reported studies using the QuADS assessment criteria. This assessment only included full-text articles written in English. RESULTS A total of 11 studies were included and assessed for different characteristics, including sample size,(3-34) re-test time interval (<1 h to >3 months), test-retest reproducibility scores and acquisition method. Six studies used ICC which ranged from poor (ICC<0.37) to excellent reproducibility (ICC 0.91-0.99). Four studies reported an overall CV lower than 40% for all DTI metrics. Three studies reported the Bland-Altman (BA) differences and reported a minimum percentage showing no strong differences between repeated measurements. Quantitative analysis was not undertaken due to heterogeneity of methods. Repeatability and reproducibility measures were generally found to be good. CONCLUSION This study revealed that the application of DTI and its related measures in a clinical setting in the assessment of cervical spinal cord changes is feasible and reproducible. However, cervical spinal cord DTI suffers from some existing limitations that prevent it from being routinely used in research and clinical settings. ADVANCES IN KNOWLEDGE DTI with its parametric maps provide broad evaluation of the tissue structure of axonal white matter and are being studied as a possible diagnostic and predictive tool for the assessment of cervical spinal cord (CSC) disease.
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Affiliation(s)
| | - Fulford J
- Medical Imaging Department, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
| | - Meertens R
- Medical Imaging Department, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
| | - Heales CJ
- Medical Imaging Department, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
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Combes A, Narisetti L, Sengupta A, Rogers BP, Sweeney G, Prock L, Houston D, McKnight CD, Gore JC, Smith SA, O'Grady KP. Detection of resting-state functional connectivity in the lumbar spinal cord with 3T MRI. Sci Rep 2023; 13:18189. [PMID: 37875563 PMCID: PMC10597994 DOI: 10.1038/s41598-023-45302-0] [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: 03/14/2023] [Accepted: 10/18/2023] [Indexed: 10/26/2023] Open
Abstract
Functional MRI (fMRI) of the spinal cord is an expanding area of research with potential to investigate neuronal activity in the central nervous system. We aimed to characterize the functional connectivity features of the human lumbar spinal cord using resting-state fMRI (rs-fMRI) at 3T, using region-based and data-driven analysis approaches. A 3D multi-shot gradient echo resting-state blood oxygenation level dependent-sensitive rs-fMRI protocol was implemented in 26 healthy participants. Average temporal signal-to-noise ratio in the gray matter was 16.35 ± 4.79 after denoising. Evidence of synchronous signal fluctuations in the ventral and dorsal horns with their contralateral counterparts was observed in representative participants using interactive, exploratory seed-based correlations. Group-wise average in-slice Pearson's correlations were 0.43 ± 0.17 between ventral horns, and 0.48 ± 0.16 between dorsal horns. Group spatial independent component analysis (ICA) was used to identify areas of coherent activity¸ and revealed components within the gray matter corresponding to anatomical regions. Lower-dimensionality ICA revealed bilateral components corresponding to ventral and dorsal networks. Additional separate ICAs were run on two subsets of the participant group, yielding two sets of components that showed visual consistency and moderate spatial overlap. This work shows feasibility of rs-fMRI to probe the functional features and organization of the lumbar spinal cord.
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Affiliation(s)
- Anna Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Lipika Narisetti
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Grace Sweeney
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Logan Prock
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Delaney Houston
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA.
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA.
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56
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Lawless RD, McKnight CD, O’Grady KP, Combes AJE, Rogers BP. Detecting macromolecular differences of the CSF in low disability multiple sclerosis using quantitative MT MRI at 3T. Mult Scler J Exp Transl Clin 2023; 9:20552173231211396. [PMID: 38021451 PMCID: PMC10644741 DOI: 10.1177/20552173231211396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Background Imaging investigation of cerebrospinal fluid (CSF) in multiple sclerosis (MS) is understudied. Development of noninvasive methods to detect pathological CSF changes would have a profound effect on MS diagnosis and would offer insight into MS pathophysiology and mechanisms of neurological impairment. Objective We propose magnetization transfer (MT) MRI as a tool to detect macromolecular changes in spinal CSF. Methods MT and quantitative MT (qMT) data were acquired in the cervical region in 27 people with relapsing-remitting multiple sclerosis (pwRRMS) and 38 age and sex-matched healthy controls (HCs). MT ratio (MTR), the B1, B0, and R1 corrected qMT-derived pool size ratio (PSR) were quantified in the spinal cord and CSF of each group. Results Both CSF MTR and CSF qMT-derived PSR were significantly increased in pwRRMS compared to HC (p = 0.027 and p = 0.020, respectively). CSF PSR of pwRRMS was correlated to Expanded Disability Status Scale Scores (p = 0.045, R = 0.352). Conclusion Our findings demonstrate increased CSF macromolecular content in pwRRMS and link CSF macromolecular content with clinical impairment. This highlights the potential role of CSF in processing products of demyelination.
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Affiliation(s)
- Richard D Lawless
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - 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
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Anna JE Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Baxter P Rogers
- 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
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Branco LDMT, Rezende TJR, Reis F, França MC. Advanced Structural Magnetic Resonance Imaging of the Spinal Cord: Technical Aspects and Clinical Use. Semin Ultrasound CT MR 2023; 44:464-468. [PMID: 37581877 DOI: 10.1053/j.sult.2023.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
For a long time, technical obstacles have hampered the acquisition of high-resolution images and the development of reliable processing protocols for spinal cord (SC) MRI. Fortunately, this scenario has changed in the past 5-10 years, due to hardware and software improvements. Nowadays, with advanced protocols, SC MRI is considered a useful tool for several inherited and acquired neurologic diseases, not only for diagnosis approach but also for pathophysiological unraveling and as a biomarker for disease monitoring and clinical trials. In this review, we address advanced SC MRI sequences for macrostructural and microstructural evaluation, useful semiautomatic and automatic processing tools and clinical applications on several neurologic conditions such as hereditary cerebellar ataxia, hereditary spastic paraplegia, motor neuron diseases and multiple sclerosis.
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Affiliation(s)
- Lucas de M T Branco
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Thiago J R Rezende
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Fabiano Reis
- Department of Anesthesiology, Oncology and Radiology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Marcondes C França
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil.
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Masse‐Gignac N, Flórez‐Jiménez S, Mac‐Thiong J, Duong L. Attention-gated U-Net networks for simultaneous axial/sagittal planes segmentation of injured spinal cords. J Appl Clin Med Phys 2023; 24:e14123. [PMID: 37735825 PMCID: PMC10562020 DOI: 10.1002/acm2.14123] [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: 03/25/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 09/23/2023] Open
Abstract
Magnetic resonance imaging is currently the gold standard for the evaluation of spinal cord injuries. Automatic analysis of these injuries is however challenging, as MRI resolutions vary for different planes of analysis and physiological features are often distorted around these injuries. This study proposes a new CNN-based segmentation method in which information is exchanged between two networks analyzing the scans from different planes. Our aim was to develop a robust method for automatic segmentation of the spinal cord in patients having suffered traumatic injuries. The database consisted of 106 sagittal MRI scans from 94 patients with traumatic spinal cord injuries. Our method used an innovative approach where the scans were analyzed in series under the axial and sagittal plane by two different convolutional networks. The results were compared with those of Deepseg 2D from the Spinal Cord Toolbox (SCT), which was taken as state-of-the-art. Comparisons were evaluated using K-Fold cross-validation combined with statistical t-test results on separate test data. Our method achieved significantly better results than Deepseg 2D, with an average Dice coefficient of 0.95 against 0.88 for Deepseg 2D (p <0.001). Other metrics were also used to compare the segmentations, all of which showed significantly better results for our approach. In this study, we introduce a robust method for spinal cord segmentation which is capable of adequately segmenting spinal cords affected by traumatic injuries, improving upon the methods contained in SCT.
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Affiliation(s)
- Nicolas Masse‐Gignac
- Department of software and IT engineeringÉcole de technologie supérieureMontréalCanada
- Department of orthopedic surgeryHopital Sacré‐CoeurMontréalCanada
| | - Salomón Flórez‐Jiménez
- Department of software and IT engineeringÉcole de technologie supérieureMontréalCanada
- Department of orthopedic surgeryHopital Sacré‐CoeurMontréalCanada
| | - Jean‐Marc Mac‐Thiong
- Department of software and IT engineeringÉcole de technologie supérieureMontréalCanada
- Department of orthopedic surgeryHopital Sacré‐CoeurMontréalCanada
| | - Luc Duong
- Department of software and IT engineeringÉcole de technologie supérieureMontréalCanada
- Department of orthopedic surgeryHopital Sacré‐CoeurMontréalCanada
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Filimonova E, Vasilenko I, Kubetsky Y, Prokhorov O, Abdaev M, Rzaev J. Brainstem and subcortical regions volume loss in patients with degenerative cervical myelopathy and its association with spinal cord compression severity. Clin Neurol Neurosurg 2023; 233:107943. [PMID: 37634395 DOI: 10.1016/j.clineuro.2023.107943] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 08/29/2023]
Abstract
BACKGROUND In recent years, structural and functional reorganization of the brain and changes in brainstem structural connectivity have been shown in patients with degenerative cervical myelopathy (DCM). We hypothesized that volume loss in the basal ganglia, thalami, and brainstem structures exists and is associated with spinal cord compression severity in patients with DCM. METHODS Forty-seven patients with DCM and 25 patients with cervical radiculopathy were evaluated using cervical spinal cord and brain magnetic resonance imaging (MRI). Brainstem structures, basal ganglia, and thalami volumes were evaluated with FreeSurfer and compared between groups with correction for individual intracranial volume, as well as patient age and sex. Additionally, spinal cord MRI data were analysed with the Spinal Cord Toolbox, and cross-sectional area (CSA) and fractional anisotropy (FA) values were calculated. Correlations between MR-morphometry data and spinal cord structural changes, as well as disease duration, were also evaluated in patients with DCM. RESULTS A statistically significant reduction in the volume of the whole brainstem was revealed in the DCM group compared to the radiculopathy group (p < 0.01, FDR-corrected). Additionally, reductions in medulla oblongata, pons and midbrain volumes were found in patients with DCM (p < 0.01, p < 0.01 and p < 0.05, respectively, FDR-corrected). Additionally, a trend in the loss of volume of the left putamen was found (p = 0.087, FDR-corrected). Furthermore, medulla oblongata volume was correlated with spinal cord compression severity (R = 0.54, adjusted p < 0.001) and white matter damage (R = 0.46, adjusted p < 0.05) in patients with DCM. Negative correlations between the duration of the disease and the severity of spinal cord compression (R = -0.42, adjusted p < 0.05) and white matter damage (R = -0.49, adjusted p < 0.05) were also revealed, as well as a trend toward a negative association between the duration of the disease and the volume of the medulla oblongata (R = -0.35; adjusted p < 0.1). CONCLUSIONS We revealed a reduction in the volume of brainstem structures in patients with DCM compared to patients with radiculopathy. Moreover, we found that these changes are associated with cord compression severity.
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Affiliation(s)
- Elena Filimonova
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia; Novosibirsk State Medical University, Krasny Prospect St. 52, Novosibirsk 630091, Russia.
| | - Ivan Vasilenko
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia
| | - Yulij Kubetsky
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia
| | - Oleg Prokhorov
- Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Pirogov Str. 1, Novosibirsk 630090, Russia
| | - Mars Abdaev
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia
| | - Jamil Rzaev
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia; Novosibirsk State Medical University, Krasny Prospect St. 52, Novosibirsk 630091, Russia; Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Pirogov Str. 1, Novosibirsk 630090, Russia
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Chen LM, Wang F, Mishra A, Yang PF, Sengupta A, Reed JL, Gore JC. Longitudinal multiparametric MRI of traumatic spinal cord injury in animal models. Magn Reson Imaging 2023; 102:184-200. [PMID: 37343904 PMCID: PMC10528214 DOI: 10.1016/j.mri.2023.06.007] [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: 03/17/2022] [Revised: 06/14/2023] [Accepted: 06/17/2023] [Indexed: 06/23/2023]
Abstract
Multi-parametric MRI (mpMRI) technology enables non-invasive and quantitative assessments of the structural, molecular, and functional characteristics of various neurological diseases. Despite the recognized importance of studying spinal cord pathology, mpMRI applications in spinal cord research have been somewhat limited, partly due to technical challenges associated with spine imaging. However, advances in imaging techniques and improved image quality now allow longitudinal investigations of a comprehensive range of spinal cord pathological features by exploiting different endogenous MRI contrasts. This review summarizes the use of mpMRI techniques including blood oxygenation level-dependent (BOLD) functional MRI (fMRI), diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST) MRI in monitoring different aspects of spinal cord pathology. These aspects include cyst formation and axonal disruption, demyelination and remyelination, changes in the excitability of spinal grey matter and the integrity of intrinsic functional circuits, and non-specific molecular changes associated with secondary injury and neuroinflammation. These approaches are illustrated with reference to a nonhuman primate (NHP) model of traumatic cervical spinal cord injuries (SCI). We highlight the benefits of using NHP SCI models to guide future studies of human spinal cord pathology, and demonstrate how mpMRI can capture distinctive features of spinal cord pathology that were previously inaccessible. Furthermore, the development of mechanism-based MRI biomarkers from mpMRI studies can provide clinically useful imaging indices for understanding the mechanisms by which injured spinal cords progress and repair. These biomarkers can assist in the diagnosis, prognosis, and evaluation of therapies for SCI patients, potentially leading to improved outcomes.
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Affiliation(s)
- Li Min Chen
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Pai-Feng Yang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jamie L Reed
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, 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
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Althobity AA, Khan N, Sandrock CJ, Woodruff TM, Cowin GJ, Brereton IM, Kurniawan ND. Multiparametric magnetic resonance imaging for detection of pathological changes in the central nervous system of a mouse model of multiple sclerosis in vivo. NMR IN BIOMEDICINE 2023; 36:e4964. [PMID: 37122101 PMCID: PMC10909458 DOI: 10.1002/nbm.4964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 03/28/2023] [Accepted: 04/26/2023] [Indexed: 05/19/2023]
Abstract
Multiple sclerosis (MS) is an autoimmune disease involving demyelination and axonal damage in the central nervous system (CNS). In this study, we investigated pathological changes in the lumbar spinal cord of C57BL/6 mice induced with progressive experimental autoimmune encephalomyelitis (EAE) disease using 9.4-T magnetic resonance imaging (MRI). Multiparametric MRI measurements including MR spectroscopy, diffusion tensor imaging (DTI) and volumetric analyses were applied to detect metabolic changes in the CNS of EAE mice. Compared with healthy mice, EAE mice showed a significant reduction in N-acetyl aspartate and increases in choline, glycine, taurine and lactate. DTI revealed a significant reduction in fractional anisotropy and axial diffusivity and an increase in radial diffusivity in the lumbar spinal cord white matter (WM), while in the grey matter (GM), fractional anisotropy increased. High-resolution structural imaging also revealed lumbar spinal cord WM hypertrophy and GM atrophy. Importantly, these MRI changes were strongly correlated with EAE disease scoring and pathological changes in the lumbar (L2-L6), particularly WM demyelination lesions and aggregation of immune cells (microglia/macrophages and astrocytes) in this region. This study identified changes in MRI biomarker signatures that can be useful for evaluating the efficacy of novel drugs using EAE models in vivo.
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Affiliation(s)
- Abdullah A. Althobity
- Centre for Advanced ImagingThe University of QueenslandBrisbaneAustralia
- Al Azhar HospitalRiyadhSaudi Arabia
- Society of Artificial Intelligence in HealthcareRiyadhSaudi Arabia
- Department of Radiological Sciences and Medical Imaging, College of Applied Medical SciencesMajmaah UniversityMajmaahSaudi Arabia
| | - Nemat Khan
- Faculty of Medicine, School of Biomedical SciencesThe University of QueenslandBrisbaneAustralia
| | - Cheyenne J. Sandrock
- Faculty of Medicine, School of Biomedical SciencesThe University of QueenslandBrisbaneAustralia
| | - Trent M. Woodruff
- Faculty of Medicine, School of Biomedical SciencesThe University of QueenslandBrisbaneAustralia
- Queensland Brain InstituteThe University of QueenslandBrisbaneAustralia
| | - Gary J. Cowin
- Centre for Advanced ImagingThe University of QueenslandBrisbaneAustralia
- NCRIS Australian National Imaging FacilityThe University of QueenslandBrisbaneAustralia
| | - Ian M. Brereton
- Centre for Advanced ImagingThe University of QueenslandBrisbaneAustralia
- NCRIS Australian National Imaging FacilityThe University of QueenslandBrisbaneAustralia
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Constant C, Aubin CE, Kremers HM, Garcia DVV, Wyles CC, Rouzrokh P, Larson AN. The use of deep learning in medical imaging to improve spine care: A scoping review of current literature and clinical applications. NORTH AMERICAN SPINE SOCIETY JOURNAL 2023; 15:100236. [PMID: 37599816 PMCID: PMC10432249 DOI: 10.1016/j.xnsj.2023.100236] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 06/14/2023] [Indexed: 08/22/2023]
Abstract
Background Artificial intelligence is a revolutionary technology that promises to assist clinicians in improving patient care. In radiology, deep learning (DL) is widely used in clinical decision aids due to its ability to analyze complex patterns and images. It allows for rapid, enhanced data, and imaging analysis, from diagnosis to outcome prediction. The purpose of this study was to evaluate the current literature and clinical utilization of DL in spine imaging. Methods This study is a scoping review and utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the scientific literature from 2012 to 2021. A search in PubMed, Web of Science, Embased, and IEEE Xplore databases with syntax specific for DL and medical imaging in spine care applications was conducted to collect all original publications on the subject. Specific data was extracted from the available literature, including algorithm application, algorithms tested, database type and size, algorithm training method, and outcome of interest. Results A total of 365 studies (total sample of 232,394 patients) were included and grouped into 4 general applications: diagnostic tools, clinical decision support tools, automated clinical/instrumentation assessment, and clinical outcome prediction. Notable disparities exist in the selected algorithms and the training across multiple disparate databases. The most frequently used algorithms were U-Net and ResNet. A DL model was developed and validated in 92% of included studies, while a pre-existing DL model was investigated in 8%. Of all developed models, only 15% of them have been externally validated. Conclusions Based on this scoping review, DL in spine imaging is used in a broad range of clinical applications, particularly for diagnosing spinal conditions. There is a wide variety of DL algorithms, database characteristics, and training methods. Future studies should focus on external validation of existing models before bringing them into clinical use.
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Affiliation(s)
- Caroline Constant
- Orthopedic Surgery AI Laboratory, Mayo Clinic, 200 1st St Southwest, Rochester, MN, 55902, United States
- Polytechnique Montreal, 2500 Chem. de Polytechnique, Montréal, QC H3T 1J4, Canada
- AO Research Institute Davos, Clavadelerstrasse 8, CH 7270, Davos, Switzerland
| | - Carl-Eric Aubin
- Polytechnique Montreal, 2500 Chem. de Polytechnique, Montréal, QC H3T 1J4, Canada
| | - Hilal Maradit Kremers
- Orthopedic Surgery AI Laboratory, Mayo Clinic, 200 1st St Southwest, Rochester, MN, 55902, United States
| | - Diana V. Vera Garcia
- Orthopedic Surgery AI Laboratory, Mayo Clinic, 200 1st St Southwest, Rochester, MN, 55902, United States
| | - Cody C. Wyles
- Orthopedic Surgery AI Laboratory, Mayo Clinic, 200 1st St Southwest, Rochester, MN, 55902, United States
- Department of Orthopedic Surgery, Mayo Clinic, 200, 1st St Southwest, Rochester, MN, 55902, United States
| | - Pouria Rouzrokh
- Orthopedic Surgery AI Laboratory, Mayo Clinic, 200 1st St Southwest, Rochester, MN, 55902, United States
- Radiology Informatics Laboratory, Mayo Clinic, 200, 1st St Southwest, Rochester, MN, 55902, United States
| | - Annalise Noelle Larson
- Orthopedic Surgery AI Laboratory, Mayo Clinic, 200 1st St Southwest, Rochester, MN, 55902, United States
- Department of Orthopedic Surgery, Mayo Clinic, 200, 1st St Southwest, Rochester, MN, 55902, United States
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de Oliveira CM, Leotti VB, Polita S, Anes M, Cappelli AH, Rocha AG, Ecco G, Bolzan G, Kersting N, Duarte JA, Saraiva-Pereira ML, Junior MCF, Rezende TJR, Jardim LB. The longitudinal progression of MRI changes in pre-ataxic carriers of SCA3/MJD. J Neurol 2023; 270:4276-4287. [PMID: 37193796 PMCID: PMC10187509 DOI: 10.1007/s00415-023-11763-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/02/2023] [Accepted: 05/03/2023] [Indexed: 05/18/2023]
Abstract
BACKGROUND The natural history of magnetic resonance imaging (MRI) in pre-ataxic stages of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) is not well known. We report cross-sectional and longitudinal data obtained at this stage. METHODS Baseline (follow-up) observations included 32 (17) pre-ataxic carriers (SARA < 3) and 20 (12) related controls. The mutation length was used to estimate the time to onset (TimeTo) of gait ataxia. Clinical scales and MRIs were performed at baseline and after a median (IQR) of 30 (7) months. Cerebellar volumetries (ACAPULCO), deep gray-matter (T1-Multiatlas), cortical thickness (FreeSurfer), cervical spinal cord area (SCT) and white matter (DTI-Multiatlas) were assessed. Baseline differences between groups were described; variables that presented a p < 0.1 after Bonferroni correction were assessed longitudinally, using TimeTo and study time. For TimeTo strategy, corrections for age, sex and intracranial volume were done with Z-score progression. A significance level of 5% was adopted. RESULTS SCT at C1 level distinguished pre-ataxic carriers from controls. DTI measures of the right inferior cerebellar peduncle (ICP), bilateral middle cerebellar peduncles (MCP) and bilateral medial lemniscus (ML), also distinguished pre-ataxic carriers from controls, and progressed over TimeTo, with effect sizes varying from 0.11 to 0.20, larger than those of the clinical scales. No MRI variable showed progression over study time. DISCUSSION DTI parameters of the right ICP, left MCP and right ML were the best biomarkers for the pre-ataxic stage of SCA3/MJD. TimeTo is an interesting timescale, since it captured the longitudinal worsening of these structures.
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Affiliation(s)
- Camila Maria de Oliveira
- Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Vanessa Bielefeldt Leotti
- Departamento de Estatística, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Programa de Pós-Graduação em Epidemiologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Sandra Polita
- Serviço de Radiologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Mauricio Anes
- Serviço de Física Médica e Radioproteção, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Amanda Henz Cappelli
- Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Gabriela Ecco
- Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Gabriela Bolzan
- Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nathalia Kersting
- Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Juliana Avila Duarte
- Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Serviço de Radiologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Maria-Luiza Saraiva-Pereira
- Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Serviço de Genética Médica, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Departamento de Bioquímica, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Marcondes Cavalcante França Junior
- Departamento de Neurologia, Faculdade de Ciências Médicas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
- Neuroimaging Laboratory, Rua Vital Brasil, 89-99, Cidade Universitária "Zeferino Vaz", Campinas, SP, 13083-888, Brazil
| | - Thiago Junqueira Ribeiro Rezende
- Departamento de Neurologia, Faculdade de Ciências Médicas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
- Neuroimaging Laboratory, Rua Vital Brasil, 89-99, Cidade Universitária "Zeferino Vaz", Campinas, SP, 13083-888, Brazil.
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos 2350, Porto Alegre, 90035-003, Brazil.
| | - Laura Bannach Jardim
- Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
- Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
- Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
- Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
- Serviço de Genética Médica, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
- Departamento de Medicina Interna, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos 2350, Porto Alegre, 90035-003, Brazil.
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Bédard S, Bouthillier M, Cohen-Adad J. Pontomedullary junction as a reference for spinal cord cross-sectional area: validation across neck positions. Sci Rep 2023; 13:13527. [PMID: 37598229 PMCID: PMC10439961 DOI: 10.1038/s41598-023-40731-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023] Open
Abstract
Spinal cord cross-sectional area (CSA) is an important MRI biomarker to assess spinal cord atrophy in various neurodegenerative and traumatic spinal cord diseases. However, the conventional method of computing CSA based on vertebral levels is inherently flawed, as the prediction of spinal levels from vertebral levels lacks reliability, leading to considerable variability in CSA measurements. Computing CSA from an intrinsic neuroanatomical reference, the pontomedullary junction (PMJ), has been proposed in previous work to overcome limitations associated with using a vertebral reference. However, the validation of this alternative approach, along with its variability across and within participants under variable neck extensions, remains unexplored. The goal of this study was to determine if the variability of CSA across neck flexions/extensions is reduced when using the PMJ, compared to vertebral levels. Ten participants underwent a 3T MRI T2w isotropic scan at 0.6 mm3 for 3 neck positions: extension, neutral and flexion. Spinal cord segmentation, vertebral labeling, PMJ labeling, and CSA were computed automatically while spinal segments were labeled manually. Mean coefficient of variation for CSA across neck positions was 3.99 ± 2.96% for the PMJ method vs. 4.02 ± 3.01% for manual spinal segment method vs. 4.46 ± 3.10% for the disc method. These differences were not statistically significant. The PMJ method was slightly more reliable than the disc-based method to compute CSA at specific spinal segments, although the difference was not statistically significant. This suggests that the PMJ can serve as a valuable alternative and reliable method for estimating CSA when a disc-based approach is challenging or not feasible, such as in cases involving fused discs in individuals with spinal cord injuries.
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Affiliation(s)
- Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.
| | - Maxime Bouthillier
- Centre Hospitalier de l'Université de Montréal, University of Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada
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65
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Devrome M, Van Laere K, Koole M. Multiplex core of the human brain using structural, functional and metabolic connectivity derived from hybrid PET-MR imaging. FRONTIERS IN NEUROIMAGING 2023; 2:1115965. [PMID: 37645694 PMCID: PMC10461102 DOI: 10.3389/fnimg.2023.1115965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 07/06/2023] [Indexed: 08/31/2023]
Abstract
With the increasing success of mapping brain networks and availability of multiple MR- and PET-based connectivity measures, the need for novel methodologies to unravel the structure and function of the brain at multiple spatial and temporal scales is emerging. Therefore, in this work, we used hybrid PET-MR data of healthy volunteers (n = 67) to identify multiplex core nodes in the human brain. First, monoplex networks of structural, functional and metabolic connectivity were constructed, and consequently combined into a multiplex SC-FC-MC network by linking the same nodes categorically across layers. Taking into account the multiplex nature using a tensorial approach, we identified a set of core nodes in this multiplex network based on a combination of eigentensor centrality and overlapping degree. We introduced a coreness coefficient, which mitigates the effect of modeling parameters to obtain robust results. The proposed methodology was applied onto young and elderly healthy volunteers, where differences observed in the monoplex networks persisted in the multiplex as well. The multiplex core showed a decreased contribution to the default mode and salience network, while an increased contribution to the dorsal attention and somatosensory network was observed in the elderly population. Moreover, a clear distinction in eigentensor centrality was found between young and elderly healthy volunteers.
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Affiliation(s)
- Martijn Devrome
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
- Division of Nuclear Medicine, Universitair Ziekenhuis (UZ) Leuven, Leuven, Belgium
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
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66
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Hemmerling KJ, Hoggarth MA, Sandhu MS, Parrish TB, Bright MG. Spatial distribution of hand-grasp motor task activity in spinal cord functional magnetic resonance imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.25.537883. [PMID: 37503173 PMCID: PMC10370018 DOI: 10.1101/2023.04.25.537883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Upper extremity motor paradigms during spinal cord functional magnetic resonance imaging (fMRI) can provide insight into the functional organization of the cord. Hand-grasping is an important daily function with clinical significance, but previous studies of similar squeezing movements have not reported consistent areas of activity and are limited by sample size and simplistic analysis methods. Here, we study spinal cord fMRI activation using a unimanual isometric hand-grasping task that is calibrated to participant maximum voluntary contraction (MVC). Two task modeling methods were considered: (1) a task regressor derived from an idealized block design (Ideal) and (2) a task regressor based on the recorded force trace normalized to individual MVC (%MVC). Across these two methods, group motor activity was highly lateralized to the hemicord ipsilateral to the side of the task. Activation spanned C5-C8 and was primarily localized to the C7 spinal cord segment. Specific differences in spatial distribution are also observed, such as an increase in C8 and dorsal cord activity when using the %MVC regressor. Furthermore, we explored the impact of data quantity and spatial smoothing on sensitivity to hand-grasp motor task activation. This analysis shows a large increase in number of active voxels associated with the number of fMRI runs, sample size, and spatial smoothing, demonstrating the impact of experimental design choices on motor activation.
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Affiliation(s)
- Kimberly J. Hemmerling
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Mark A. Hoggarth
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Physical Therapy, North Central College, Naperville, IL, United States
| | - Milap S. Sandhu
- Shirley Ryan Ability Lab, Chicago, IL, United States
- Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Todd B. Parrish
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Molly G. Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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67
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Kim H, Lim C, Lee JS, Kim D, Song CB, Dhaher Y. Effect of Non-invasive Spinal Stimulation on Self-sustained Firing Motoneuron Model: In-Silico Study Using Human Body Model. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083191 DOI: 10.1109/embc40787.2023.10340056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Transcutaneous spinal electrical stimulation (tSCS) is a non-invasive neuromodulation approach using a low intensity direct current. Recent developments in the technique have opened the possibility that tSCS can help restore motor function after spinal cord injury (SCI). However, the exact mechanism of action tSCS has on the spinal circuits is still unknown. Due to the complexity of experimental synthesis in a human model to delineate the mechanisms, models that link the stimulation paradigm and circuit behaviors are advantageous. Thus, this study aims to simulate the underlying changes in motor circuit firing rates in response to external stimuli induced by tSCS. Serial stimulations combining a high-fidelity finite element model with the human torso and spinal cord with a lumped motor neuron model is constructed. The parameters for both components of the model were derived from previous studies. We focused our analysis on a lumped motor neuron model that describes sustained firing behavior of the motor neuron driven primarily by persistent inward current (PIC), a signature behavior of the motor neuron after SCI. Modulation of the PIC behaviors was achieved by stimulating voltage-dependent calcium and sodium channels in the dendrite using a tSCS-induced electric field (E-field) expressed at different a spatial locations of the motor neuron in the gray matter. The PIC behaviors of spinal motor neurons in the left ventral horn were suppressed, while for the most part invariant in the right ventral horn. These initial simulations will provide a steppingstone for future examinations that incorporate additional neuronal models of inhibitory and excitatory interneurons to access the circuit-level effect of spinal stimulation.
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68
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Tsivaka D, Williams SCR, Medina S, Kowalczyk OS, Brooks JCW, Howard MA, Lythgoe DJ, Tsougos I. A second-order and slice-specific linear shimming technique to improve spinal cord fMRI. Magn Reson Imaging 2023:S0730-725X(23)00108-X. [PMID: 37353180 DOI: 10.1016/j.mri.2023.06.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/20/2023] [Accepted: 06/17/2023] [Indexed: 06/25/2023]
Abstract
PURPOSE To develop a second-order and slice-specific linear shimming technique and investigate its efficiency in the mitigation of signal loss and distortions, and the increase of temporal signal-to-noise ratio (tSNR) within the spinal cord during functional Magnetic Resonance Imaging (fMRI) of the human cervical spinal cord. METHODS All scans were performed on a General Electric Discovery MR750 3 T scanner, using a head, neck and spine coil and a neurovascular array. To improve B0 homogeneity, a field map was acquired, and second-order shims (SOS) were optimized over manually defined regions of interest (ROIs). Signal loss from dephasing by susceptibility-induced gradients was reduced by optimizing slice-specific x-, y- and z-shims to maximize signal within the spinal cord. Spectral-spatial excitation pulses were used in both the slice-specific linear shimming calibration scan and fMRI acquisitions. The shimming technique's efficiency was initially tested on eight healthy volunteers by comparing tSNR between images acquired with the manufacturer's standard linear shimming and with our SOS and xyz-shimming technique. Subsequently, using an increased spatial resolution as needed for fMRI of the spinal cord, tSNR measurements were performed on resting-state fMRI images from 14 healthy participants. RESULTS Spinal fMRI images acquired with only the standard linear shimming suffered from severe signal loss below the C5 vertebral level. The developed shimming technique compensated for this loss especially at levels C6 and C7, while tSNR was significantly higher at all vertebral levels with SOS and xyz-shimming than without it. CONCLUSION A comprehensive shimming approach which includes the use of spectral-spatial excitation pulses along with both second-order and slice-specific linear shim optimization reduces regional signal loss and increases tSNR along the c-spine (C3-C7), improving the ability to record functional signals from the human spinal cord.
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Affiliation(s)
- D Tsivaka
- Medical Physics Department, Medical School, University of Thessaly, Larisa, Greece; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - S C R Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - S Medina
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - O S Kowalczyk
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - J C W Brooks
- School of Psychology, University of East Anglia, Norwich, UK
| | - M A Howard
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - D J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - I Tsougos
- Medical Physics Department, Medical School, University of Thessaly, Larisa, Greece; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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Mongay-Ochoa N, Pareto D, Alberich M, Tintore M, Montalban X, Rovira À, Sastre-Garriga J. Validation of a New Semiautomated Segmentation Pipeline Based on the Spinal Cord Toolbox DeepSeg Algorithm to Estimate the Cervical Canal Area. AJNR Am J Neuroradiol 2023:ajnr.A7899. [PMID: 37290816 PMCID: PMC10337626 DOI: 10.3174/ajnr.a7899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 05/11/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND PURPOSE As in the brain reserve concept, a larger cervical canal area may also protect against disability. In this context, a semiautomated pipeline has been developed to obtain quantitative estimations of the cervical canal area. The aim of the study was to validate the pipeline, to evaluate the consistency of the cervical canal area measurements during a 1-year period, and to compare cervical canal area estimations obtained from brain and cervical MRI acquisitions. MATERIALS AND METHODS Eight healthy controls and 18 patients with MS underwent baseline and follow-up 3T brain and cervical spine sagittal 3D MPRAGE. The cervical canal area was measured in all acquisitions, and estimations obtained with the proposed pipeline were compared with manual segmentations performed by 1 evaluator using the Dice similarity coefficient. The cervical canal area estimations obtained on baseline and follow-up T1WI were compared; brain and cervical cord acquisitions were also compared using the individual and average intraclass correlation coefficients. RESULTS The agreement between the manual cervical canal area masks and the masks provided by the proposed pipeline was excellent, with a mean Dice similarity coefficient mean of 0.90 (range, 0.73-0.97). The cervical canal area estimations obtained from baseline and follow-up scans showed a good level of concordance (intraclass correlation coefficient = 0.76; 95% CI, 0.44-0.88); estimations obtained from brain and cervical MRIs also had good agreement (intraclass correlation coefficient = 0.77; 95% CI, 0.45-0.90). CONCLUSIONS The proposed pipeline is a reliable tool to estimate the cervical canal area. The cervical canal area is a stable measure across time; moreover, when cervical sequences are not available, the cervical canal area could be estimated using brain T1WI.
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Affiliation(s)
- N Mongay-Ochoa
- From the Department of Neurology (N.M.-O., M.T., X.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia
| | - D Pareto
- Section of Neuroradiology (D.P., M.A., À.R.), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - M Alberich
- Section of Neuroradiology (D.P., M.A., À.R.), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - M Tintore
- From the Department of Neurology (N.M.-O., M.T., X.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia
| | - X Montalban
- From the Department of Neurology (N.M.-O., M.T., X.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia
| | - À Rovira
- Section of Neuroradiology (D.P., M.A., À.R.), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - J Sastre-Garriga
- From the Department of Neurology (N.M.-O., M.T., X.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia
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70
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Mahmud SZ, Denney TS, Bashir A. Feasibility of spinal cord imaging at 7 T using rosette trajectory with magnetization transfer preparation and compressed sensing. Sci Rep 2023; 13:8777. [PMID: 37258697 DOI: 10.1038/s41598-023-35853-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/24/2023] [Indexed: 06/02/2023] Open
Abstract
MRI is a valuable diagnostic tool to investigate spinal cord (SC) pathology. SC MRI can benefit from the increased signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) at ultra-high fields such as 7 T. However, SC MRI acquisitions with routine Cartesian readouts are prone to image artifacts caused by physiological motion. MRI acquisition techniques with non-Cartesian readouts such as rosette can help reduce motion artifacts. The purpose of this study was to demonstrate the feasibility of high-resolution SC imaging using rosette trajectory with magnetization transfer preparation (MT-prep) and compressed sensing (CS) at 7 T. Five healthy volunteers participated in the study. Images acquired with rosette readouts demonstrated reduced motion artifacts compared to the standard Cartesian readouts. The combination of multi-echo rosette-readout images improved the CNR by approximately 50% between the gray matter (GM) and white matter (WM) compared to single-echo images. MT-prep images showed excellent contrast between the GM and WM with magnetization transfer ratio (MTR) and cerebrospinal fluid normalized MT signal (MTCSF) = 0.12 ± 0.017 and 0.74 ± 0.013, respectively, for the GM; and 0.18 ± 0.011 and 0.58 ± 0.009, respectively, for the WM. Under-sampled acquisition using rosette readout with CS reconstruction demonstrated up to 6 times faster scans with comparable image quality as the fully-sampled acquisition.
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Affiliation(s)
- Sultan Z Mahmud
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
- Auburn University MRI Research Center, Auburn University, Auburn, AL, USA
| | - Thomas S Denney
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
- Auburn University MRI Research Center, Auburn University, Auburn, AL, USA
| | - Adil Bashir
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA.
- Auburn University MRI Research Center, Auburn University, Auburn, AL, USA.
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Koch KM, Nencka AS, Klein A, Wang M, Kurpad S, Vedantam A, Budde M. Diffusion-weighted MRI of the spinal cord in cervical spondylotic myelopathy after instrumented fusion. Front Neurol 2023; 14:1172833. [PMID: 37273696 PMCID: PMC10236479 DOI: 10.3389/fneur.2023.1172833] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/02/2023] [Indexed: 06/06/2023] Open
Abstract
Introduction This study investigated tissue diffusion properties within the spinal cord of individuals treated for cervical spondylotic myelopathy (CSM) using post-decompression stabilization hardware. While previous research has indicated the potential of diffusion-weighted MRI (DW-MRI) markers of CSM, the metallic implants often used to stabilize the decompressed spine hamper conventional DW-MRI. Methods Utilizing recent developments in DW-MRI metal-artifact suppression technologies, imaging data was acquired from 38 CSM study participants who had undergone instrumented fusion, as well as asymptomatic (non-instrumented) control participants. Apparent diffusion coefficients were determined in axial slice sections and split into four categories: a) instrumented levels, b) non-instrumented CSM levels, c) adjacent-segment (to instrumentation) CSM levels, and d) non-instrumented control levels. Multi-linear regression models accounting for age, sex, and body mass index were used to investigate ADC measures within each category. Furthermore, the cord diffusivity within CSM subjects was correlated with symptom scores and the duration since fusion procedures. Results ADC measures of the spinal cord in CSM subjects were globally reduced relative to control subjects (p = 0.005). In addition, instrumented levels within the CSM subjects showed reduced diffusivity relative to controls (p = 0.003), while ADC within non-instrumented CSM levels did not statistically deviate from control levels (p = 0.107). Discussion Multi-spectral DW-MRI technology can be effectively employed to evaluate cord diffusivity near fusion hardware in subjects who have undergone surgery for CSM. Leveraging this advanced technology, this study had identified significant reductions in cord diffusivity, relative to control subjects, in CSM patients treated with conventional metallic fusion instrumentation.
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Affiliation(s)
- Kevin M. Koch
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Andrew S. Nencka
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Andrew Klein
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Marjorie Wang
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Shekar Kurpad
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Aditya Vedantam
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Matthew Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
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Kinany N, Khatibi A, Lungu O, Finsterbusch J, Büchel C, Marchand-Pauvert V, Ville DVD, Vahdat S, Doyon J. Decoding cerebro-spinal signatures of human behavior: application to motor sequence learning. Neuroimage 2023; 275:120174. [PMID: 37201642 DOI: 10.1016/j.neuroimage.2023.120174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/12/2023] [Accepted: 05/15/2023] [Indexed: 05/20/2023] Open
Abstract
Mapping the neural patterns that drive human behavior is a key challenge in neuroscience. Even the simplest of our everyday actions stem from the dynamic and complex interplay of multiple neural structures across the central nervous system (CNS). Yet, most neuroimaging research has focused on investigating cerebral mechanisms, while the way the spinal cord accompanies the brain in shaping human behavior has been largely overlooked. Although the recent advent of functional magnetic resonance imaging (fMRI) sequences that can simultaneously target the brain and spinal cord has opened up new avenues for studying these mechanisms at multiple levels of the CNS, research to date has been limited to inferential univariate techniques that cannot fully unveil the intricacies of the underlying neural states. To address this, we propose to go beyond traditional analyses and instead use a data-driven multivariate approach leveraging the dynamic content of cerebro-spinal signals using innovation-driven coactivation patterns (iCAPs). We demonstrate the relevance of this approach in a simultaneous brain-spinal cord fMRI dataset acquired during motor sequence learning (MSL), to highlight how large-scale CNS plasticity underpins rapid improvements in early skill acquisition and slower consolidation after extended practice. Specifically, we uncovered cortical, subcortical and spinal functional networks, which were used to decode the different stages of learning with a high accuracy and, thus, delineate meaningful cerebro-spinal signatures of learning progression. Our results provide compelling evidence that the dynamics of neural signals, paired with a data-driven approach, can be used to disentangle the modular organization of the CNS. While we outline the potential of this framework to probe the neural correlates of motor learning, its versatility makes it broadly applicable to explore the functioning of cerebro-spinal networks in other experimental or pathological conditions.
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Affiliation(s)
- N Kinany
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, 1211, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, 1202, Switzerland.
| | - A Khatibi
- Center of Precision Rehabilitation for Spinal Pain, School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, United Kingdom
| | - O Lungu
- McConnell Brain Imaging Center, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - J Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | - C Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | - V Marchand-Pauvert
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie biomédicale, Paris F-75006, France
| | - D Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, 1211, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, 1202, Switzerland
| | - S Vahdat
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, FL 32611, United States
| | - J Doyon
- McConnell Brain Imaging Center, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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73
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Koning E, Powers JM, Ioachim G, Stroman PW. A Comparison of Functional Connectivity in the Human Brainstem and Spinal Cord Associated with Noxious and Innocuous Thermal Stimulation Identified by Means of Functional MRI. Brain Sci 2023; 13:brainsci13050777. [PMID: 37239249 DOI: 10.3390/brainsci13050777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/30/2023] [Accepted: 05/05/2023] [Indexed: 05/28/2023] Open
Abstract
The somatosensory system is multidimensional and processes important information for survival, including the experience of pain. The brainstem and spinal cord serve pivotal roles in both transmitting and modulating pain signals from the periphery; although, they are studied less frequently with neuroimaging when compared to the brain. In addition, imaging studies of pain often lack a sensory control condition, failing to differentiate the neural processes associated with pain versus innocuous sensations. The purpose of this study was to investigate neural connectivity between key regions involved in descending modulation of pain in response to a hot, noxious stimulus as compared to a warm, innocuous stimulus. This was achieved with functional magnetic resonance imaging (fMRI) of the brainstem and spinal cord in 20 healthy men and women. Functional connectivity was observed to vary between specific regions across painful and innocuous conditions. However, the same variations were not observed in the period of anticipation prior to the onset of stimulation. Specific connections varied with individual pain scores only during the noxious stimulation condition, indicating a significant role of individual differences in the experience of pain which are distinct from that of innocuous sensation. The results also illustrate significant differences in descending modulation before and during stimulation in both conditions. These findings contribute to a deeper understanding of the mechanisms underlying pain processing at the level of the brainstem and spinal cord, and how pain is modulated.
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Affiliation(s)
- Elena Koning
- Centre for Neuroscience Studies, Queen's University, Kingston, ON K7L 3N6, Canada
| | - Jocelyn M Powers
- Centre for Neuroscience Studies, Queen's University, Kingston, ON K7L 3N6, Canada
| | - Gabriela Ioachim
- Centre for Neuroscience Studies, Queen's University, Kingston, ON K7L 3N6, Canada
| | - Patrick W Stroman
- Centre for Neuroscience Studies, Queen's University, Kingston, ON K7L 3N6, Canada
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON K7L 3N6, Canada
- Department of Physics, Queen's University, Kingston, ON K7L 3N6, Canada
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74
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Khan AF, Haynes G, Mohammadi E, Muhammad F, Hameed S, Smith ZA. Utility of MRI in Quantifying Tissue Injury in Cervical Spondylotic Myelopathy. J Clin Med 2023; 12:jcm12093337. [PMID: 37176777 PMCID: PMC10179707 DOI: 10.3390/jcm12093337] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/28/2023] [Accepted: 05/05/2023] [Indexed: 05/15/2023] Open
Abstract
Cervical spondylotic myelopathy (CSM) is a progressive disease that worsens over time if untreated. However, the rate of progression can vary among individuals and may be influenced by various factors, such as the age of the patients, underlying conditions, and the severity and location of the spinal cord compression. Early diagnosis and prompt treatment can help slow the progression of CSM and improve symptoms. There has been an increased use of magnetic resonance imaging (MRI) methods in diagnosing and managing CSM. MRI methods provide detailed images and quantitative structural and functional data of the cervical spinal cord and brain, allowing for an accurate evaluation of the extent and location of tissue injury. This review aims to provide an understanding of the use of MRI methods in interrogating functional and structural changes in the central nervous system in CSM. Further, we identified several challenges hindering the clinical utility of these neuroimaging methods.
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Affiliation(s)
- Ali Fahim Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Esmaeil Mohammadi
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Sanaa Hameed
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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Kaptan M, Horn U, Vannesjo SJ, Mildner T, Weiskopf N, Finsterbusch J, Brooks JCW, Eippert F. Reliability of resting-state functional connectivity in the human spinal cord: assessing the impact of distinct noise sources. Neuroimage 2023; 275:120152. [PMID: 37142169 DOI: 10.1016/j.neuroimage.2023.120152] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 04/20/2023] [Accepted: 05/01/2023] [Indexed: 05/06/2023] Open
Abstract
The investigation of spontaneous fluctuations of the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord, where it has stimulated interest from a clinical perspective. A number of resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated robust functional connectivity between the time series of BOLD fluctuations in bilateral dorsal horns and between those in bilateral ventral horns, in line with the functional neuroanatomy of the spinal cord. A necessary step prior to extension to clinical studies is assessing the reliability of such resting-state signals, which we aimed to do here in a group of 45 healthy young adults at the clinically prevalent field strength of 3T. When investigating connectivity in the entire cervical spinal cord, we observed fair to good reliability for dorsal-dorsal and ventral-ventral connectivity, whereas reliability was poor for within- and between-hemicord dorsal-ventral connectivity. Considering how prone spinal cord fMRI is to noise, we extensively investigated the impact of distinct noise sources and made two crucial observations: removal of physiological noise led to a reduction in functional connectivity strength and reliability - due to the removal of stable and participant-specific noise patterns - whereas removal of thermal noise considerably increased the detectability of functional connectivity without a clear influence on reliability. Finally, we also assessed connectivity within spinal cord segments and observed that while the pattern of connectivity was similar to that of whole cervical cord, reliability at the level of single segments was consistently poor. Taken together, our results demonstrate the presence of reliable resting-state functional connectivity in the human spinal cord even after thoroughly accounting for physiological and thermal noise, but at the same time urge caution if focal changes in connectivity (e.g. due to segmental lesions) are to be studied, especially in a longitudinal manner.
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Affiliation(s)
- Merve Kaptan
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Ulrike Horn
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - S Johanna Vannesjo
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
| | - Toralf Mildner
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - 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, University of Leipzig, Leipzig, Germany
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonathan C W Brooks
- School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), Norwich, United Kingdom
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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76
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Baker AK, Park SH, Weber KA, Martucci KT. Reduced Spinal Cord Gray Matter in Patients with Fibromyalgia Using Opioids Long-term. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.02.23289401. [PMID: 37205383 PMCID: PMC10187444 DOI: 10.1101/2023.05.02.23289401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Objective Chronic pain involves alterations in brain gray matter volume (GMV). Moreover, opioid medications are known to reduce GMV in numerous brain regions involved in pain processing. However, no research has evaluated (1) chronic pain-related GMV alterations in the spinal cord or (2) the effect of opioids on spinal cord GMV. Accordingly, this study evaluated spinal cord GMV in health controls and patients with fibromyalgia who were using and not using opioids long-term. Methods We analyzed average C5 - C7 GMV of the spinal cord dorsal and ventral horns in separate female cohorts of healthy controls (HC, n = 30), fibromyalgia patients not using opioids (FMN, n = 31), and fibromyalgia patients using opioids long-term (FMO, n = 27). To assess the effect of group on average dorsal and ventral horn GMV, we conducted a one-way multivariate analysis of covariance. Results After controlling for age, we observed a significant effect of group on ventral horn GMV (p = 0.03, η2 = 0.09), and on dorsal horn GMV (p = 0.05, η2 = 0.08). Tukey's posthoc comparisons showed that, compared to HC participants, FMOs had significantly lower ventral (p = 0.01) and dorsal (p = 0.02) GMVs. Among FMOs only, ventral horn GMV was significantly positively associated with pain severity and interference, and both dorsal and ventral GMVs were significantly positively associated with cold pain tolerance. Conclusion Long-term opioid use may impact sensory processing in fibromyalgia via gray matter changes within the cervical spinal cord.
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Affiliation(s)
- Anne K. Baker
- Human Affect and Pain Neuroscience Laboratory, Department of Anesthesiology, Duke University School of Medicine, Durham NC 27710
- Center for Translational Pain Medicine, Duke University Medical Center, Durham NC 27710
| | - Su Hyoun Park
- Human Affect and Pain Neuroscience Laboratory, Department of Anesthesiology, Duke University School of Medicine, Durham NC 27710
- Center for Translational Pain Medicine, Duke University Medical Center, Durham NC 27710
| | - Kenneth A. Weber
- Systems Neuroscience and Pain Lab, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School fo Medicine, Palo Alto, CA 94304
| | - Katherine T. Martucci
- Human Affect and Pain Neuroscience Laboratory, Department of Anesthesiology, Duke University School of Medicine, Durham NC 27710
- Center for Translational Pain Medicine, Duke University Medical Center, Durham NC 27710
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77
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Pareto D, Corral JF, Garcia-Vidal A, Alberich M, Auger C, Rio J, Mongay N, Sastre-Garriga J, Rovira À. Assessing the Equivalence of Brain-Derived Measures from Two 3D T1-Weighted Acquisitions: One Covering the Brain and One Covering the Brain and Spinal Cord. AJNR Am J Neuroradiol 2023; 44:569-573. [PMID: 37080719 PMCID: PMC10171373 DOI: 10.3174/ajnr.a7843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 02/01/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND AND PURPOSE In MS, it is common to acquire brain and spinal cord MR imaging sequences separately to assess the extent of the disease. The goal of this study was to see how replacing the traditional brain T1-weighted images (brain-T1) with an acquisition that included both the brain and the cervical spinal cord (cns-T1) affected brain- and spinal cord-derived measures. MATERIALS AND METHODS Thirty-six healthy controls (HC) and 42 patients with MS were included. Of those, 18 HC and 35 patients with MS had baseline and follow-up at 1 year acquired on a 3T magnet. Two 3D T1-weighted images (brain-T1 and cns-T1) were acquired at each time point. Regional cortical thickness and volumes were determined with FastSurfer, and the percentage brain volume change per year was obtained with SIENA. The spinal cord area was estimated with the Spinal Cord Toolbox. Intraclass correlation coefficients (ICC) were calculated to check for consistency of measures obtained from brain-T1 and cns-T1. RESULTS Cortical thickness measures showed an ICC >0.75 in 94% of regions in healthy controls and 80% in patients with MS. Estimated regional volumes had an ICC >0.88, and the percentage brain volume change had an ICC >0.79 for both groups. The spinal cord area measures had an ICC of 0.68 in healthy controls and 0.92 in patients with MS. CONCLUSIONS Brain measurements obtained from 3D cns-T1 are highly equivalent to those obtained from a brain-T1, suggesting that it could be feasible to replace the brain-T1 with cns-T1.
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Affiliation(s)
- D Pareto
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - J F Corral
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - A Garcia-Vidal
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
| | - M Alberich
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - C Auger
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
| | - J Rio
- Department of Neurology and Neuroimmunology (J.R., N.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - N Mongay
- Department of Neurology and Neuroimmunology (J.R., N.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - J Sastre-Garriga
- Department of Neurology and Neuroimmunology (J.R., N.M., J.S.-G.), Multiple Sclerosis Centre of Catalonia, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - À Rovira
- From the Neuroradiology Group (D.P., J.F.C., A.G.-V., C.A., À.R.), Vall d'Hebron Research Institute, Barcelona, Spain
- Section of Neuroradiology (D.P., J.F.C., M.A., À.R.), Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
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Meyer BP, Lee SY, Kurpad SN, Budde MD. Differential Trajectory of Diffusion and Perfusion Magnetic Resonance Imaging of Rat Spinal Cord Injury. J Neurotrauma 2023; 40:918-930. [PMID: 36226406 PMCID: PMC10150724 DOI: 10.1089/neu.2022.0283] [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] [Indexed: 11/13/2022] Open
Abstract
Traumatic spinal cord injury causes rapid neuronal and vascular injury, and predictive biomarkers are needed to facilitate acute patient management. This study examined the progression of magnetic resonance imaging (MRI) biomarkers after spinal cord injury and their ability to predict long-term neurological outcomes in a rodent model, with an emphasis on diffusion-weighted imaging (DWI) markers of axonal injury and perfusion-weighted imaging of spinal cord blood flow (SCBF). Adult Sprague-Dawley rats received a cervical contusion injury of varying severity (injured = 30, sham = 9). MRI at 4 h, 48-h, and 12-weeks post-injury included T1, T2, perfusion, and DWI. Locomotor outcome was assessed up to 12 weeks post-injury. At 4 h, the deficit in SCBF was larger than the DWI lesion, and although SCBF partially recovered by 48 h, the DWI lesion expanded. At 4 h, the volume of the SCBF deficit (R2 = 0.56, padj < 0.01) was significantly correlated with 12-week locomotor outcome, whereas DWI (R2 = 0.30, padj < 0.01) was less predictive of outcome. At 48 h, SCBF (R2 = 0.41, padj < 0.01) became less associated with outcome, and DWI (R2 = 0.38, padj < 0.01) lesion volume became more closely related to outcome. Spinal cord perfusion has unique spatiotemporal dynamics compared with diffusion measures of axonal damage and highlights the importance of acute perfusion abnormalities. Perfusion and diffusion offer complementary and clinically relevant insight into physiological and structural abnormalities following spinal cord injury beyond those afforded by T1 or T2 contrasts.
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Affiliation(s)
- Briana P. Meyer
- Neuroscience Doctoral Program, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Seung-Yi Lee
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Shekar N. Kurpad
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Matthew D. Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Clement J. Zablocki Veterans' Affairs Medical Center, Milwaukee, Wisconsin, USA
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79
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Schaefer SD, Davies BM, Newcombe VF, Sutcliffe MP. Could spinal cord oscillation contribute to spinal cord injury in degenerative cervical myelopathy? BRAIN & SPINE 2023; 3:101743. [PMID: 37383476 PMCID: PMC10293319 DOI: 10.1016/j.bas.2023.101743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/20/2023] [Accepted: 04/12/2023] [Indexed: 06/30/2023]
Abstract
Introduction Degenerative Cervical Myelopathy [DCM] is a slow-motion spinal cord injury. Compression and dynamic compression have been considered disease hallmarks. However, this is likely an oversimplification, as compression is more commonly incidental and has only modest correlation to disease severity. MRI studies have recently suggested spinal cord oscillation could play a role. Research question To determine if spinal cord oscillation could contribute to spinal cord injury in degenerative cervical myelopathy. Material and methods A computational model of an oscillating spinal cord was developed from imaging of a healthy volunteer. Using finite element analysis, the observed implications of stress and strain, were measured in the context of a simulated disc herniation. The significance was bench marked by comparison to a more recognised dynamic injury mechanism; a flexion extension model of dynamic compression. Results Spinal cord oscillation altered both compressive and shear strain on the spinal cord. Following initial compression, compressive strain moves from within the spinal cord to the spinal cord surface, whilst shear strain is magnified by 0.1-0.2, depending on the amplitude of oscillation. These orders of magnitude are equivalent to a dynamic compression model. Discussion and conclusion Spinal cord oscillation could significantly contribute to spinal cord damage across DCM. Its repeated occurrence with every heartbeat, draws parallels to the concept of fatigue damage, which could reconcile differing theories on the origins of DCM. This remains hypothetical at this stage, and further investigations are required.
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80
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D’Astous A, Cereza G, Papp D, Gilbert KM, Stockmann JP, Alonso-Ortiz E, Cohen-Adad J. Shimming toolbox: An open-source software toolbox for B0 and B1 shimming in MRI. Magn Reson Med 2023; 89:1401-1417. [PMID: 36441743 PMCID: PMC9910837 DOI: 10.1002/mrm.29528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/21/2022] [Accepted: 10/25/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE Introduce Shimming Toolbox ( https://shimming-toolbox.org), an open-source software package for prototyping new methods and performing static, dynamic, and real-time B0 shimming as well as B1 shimming experiments. METHODS Shimming Toolbox features various field mapping techniques, manual and automatic masking for the brain and spinal cord, B0 and B1 shimming capabilities accessible through a user-friendly graphical user interface. Validation of Shimming Toolbox was demonstrated in three scenarios: (i) B0 dynamic shimming in the brain at 7T using custom AC/DC coils, (ii) B0 real-time shimming in the spinal cord at 3T, and (iii) B1 static shimming in the spinal cord at 7T. RESULTS The B0 dynamic shimming of the brain at 7T took about 10 min to perform. It showed a 47% reduction in the standard deviation of the B0 field, associated with noticeable improvements in geometric distortions in EPI images. Real-time dynamic xyz-shimming in the spinal cord took about 5 min and showed a 30% reduction in the standard deviation of the signal distribution. B1 static shimming experiments in the spinal cord took about 10 min to perform and showed a 40% reduction in the coefficient of variation of the B1 field. CONCLUSION Shimming Toolbox provides an open-source platform where researchers can collaborate, prototype and conveniently test B0 and B1 shimming experiments. Future versions will include additional field map preprocessing techniques, optimization algorithms, and compatibility across multiple MRI manufacturers.
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Affiliation(s)
- Alexandre D’Astous
- NeuroPoly Lab, Institute of Biomedical Engineering,
Polytechnique Montréal, Montréal, QC, Canada
| | - Gaspard Cereza
- NeuroPoly Lab, Institute of Biomedical Engineering,
Polytechnique Montréal, Montréal, QC, Canada
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering,
Polytechnique Montréal, Montréal, QC, Canada
| | - Kyle M. Gilbert
- Centre for Functional and Metabolic Mapping, The
University of Western Ontario, London, Ontario, Canada
| | - Jason P. Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering,
Polytechnique Montréal, Montréal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering,
Polytechnique Montréal, Montréal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de
Montréal, Montréal, QC, Canada
- Mila - Quebec AI Institute, Montréal, QC,
Canada
- Centre de recherche du CHU Sainte-Justine,
Université de Montréal, Montréal, QC, Canada
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Schading S, Seif M, Leutritz T, Hupp M, Curt A, Weiskopf N, Freund P. Reliability of spinal cord measures based on synthetic T 1-weighted MRI derived from multiparametric mapping (MPM). Neuroimage 2023; 271:120046. [PMID: 36948280 DOI: 10.1016/j.neuroimage.2023.120046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/14/2023] [Accepted: 03/18/2023] [Indexed: 03/24/2023] Open
Abstract
Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T1-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T1-w MRI (synT1-w) estimated from the MPM, in order to measure CSA. SynT1-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R1) and effective transverse (R2*) relaxation rates. The reliability of CSA measurements from synT1-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT1-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT1-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm2 compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT1-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT1-w images, thereby reducing scan time significantly.
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Affiliation(s)
- Simon Schading
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Maryam Seif
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Markus Hupp
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Armin Curt
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
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Alonso-Ortiz E, Papp D, D'Astous A, Cohen-Adad J. Dynamic shimming in the cervical spinal cord for multi-echo gradient-echo imaging at 3 T. NEUROIMAGE: REPORTS 2023. [DOI: 10.1016/j.ynirp.2022.100150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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83
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Wenzel N, Wittayer M, Weber CE, Platten M, Gass A, Eisele P. Multiple sclerosis iron rim lesions are linked to impaired cervical spinal cord integrity using the T1/T2-weighted ratio. J Neuroimaging 2023; 33:240-246. [PMID: 36504270 DOI: 10.1111/jon.13076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/27/2022] [Accepted: 11/29/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND AND PURPOSE In multiple sclerosis (MS), iron rim lesions (IRLs) are characterized by pronounced tissue matrix damage. The T1/T2-weighted (T1/T2w) ratio represents a postprocessing MRI approach to investigate tissue integrity, but studies investigating spinal cord pathology are missing until now. The aim of this study was to characterize tissue integrity using the T1/T2w ratio in lesions and the normal-appearing white and gray matter (NAWM, NAGM) in the spinal cord and brain in MS patients with and without brain IRLs. METHODS Forty MS patients (20 patients with at least one brain IRL and 20 age- and sex-matched patients without IRLs) were included. Normalized cross-sectional area (nCSA) of the upper cervical cord was calculated in addition to T1/T2w values and standard brain and spinal cord MRI parameters. RESULTS Patients with IRLs had higher disability scores, a smaller nCSA, and a higher cervical T2 lesion volume. T1/T2w values of brain IRLs were significantly lower compared to non-IRLs (p < .001). Furthermore, T1/T2w values of lesions were significantly lower compared to the NAGM and NAWM, both in the brain and the spinal cord (p < .05 for all comparisons). T1/T2w values of the NAGM and NAWM in the brain and spinal cord did not statistically differ between the IRL group and the non-IRL group. CONCLUSION IRLs constitute an imaging marker of disease severity. T1/T2w ratio maps represent an interesting technique to capture diffuse tissue properties. Calculation of T1/T2w ratio maps of the spinal cord might provide additional insights into the pathophysiological processes of MS.
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Affiliation(s)
- Nicolas Wenzel
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Matthias Wittayer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Claudia E Weber
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany.,DKTK CCU Neuroimmunology and Brain Tumor Immunology, DKFZ, Heidelberg, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Philipp Eisele
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
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84
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Chu Y, Fricke B, Finsterbusch J. Improving T2*-weighted human cortico-spinal acquisitions with a dedicated algorithm for region-wise shimming. Neuroimage 2023; 268:119868. [PMID: 36646161 DOI: 10.1016/j.neuroimage.2023.119868] [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: 09/21/2022] [Revised: 01/06/2023] [Accepted: 01/08/2023] [Indexed: 01/14/2023] Open
Abstract
Cortico-spinal fMRI acquisitions aim to investigate direct interactions between brain and spinal cord, e.g. during motor output or pain processing, by covering both regions in a single measurement. Due to their large distance and location in the body, a dynamic shim update of constant and linear shim terms is required when using echo-planar imaging (EPI) to achieve reasonable image quality in both target regions. A previously presented approach with region-wise shim settings is based on a standard single-region shim algorithm and suffers from (i) non-optimal shim settings because it combines linear and second-order shim terms optimized for different volumes, and (ii) significant user interactions making it rather cumbersome, time consuming, and error-prone. Here, a dedicated ("CoSpi") shim algorithm for cortico-spinal fMRI is presented that performs joint optimization of static second-order shim terms and one set of linear and constant shim terms for each region in a single run and with minimal user interaction. Field map and T2*-weighted EPI measurements were performed on a clinical 3 T whole-body MR system in water phantoms and five healthy volunteers using the conventional region-wise and CoSpi shim settings as well as "gold standard" shim settings optimized for one of the target regions only. With CoSpi shim settings, (i) overall field inhomogeneity was reduced by about 65% / 75% (brain / spinal cord volume) compared to the conventional region-wise approach and in vivo was within 5% of the values obtained with the single-volume shim settings, (ii) geometric distortions derived from voxel displacement maps were reduced on average by about 35% / 70%, (iii) the temporal SNR determined from an EPI time series that may reflect the impact of through-slice dephasing, was increased by about 17% / 10%, and (iv) the variation of the mean field between slices, a measure targeting the predisposition to insufficient fat saturation and GRAPPA-related ghosting artifacts, was reduced by about 90% / 45%. Thus, the presented algorithm not only speeds up and simplifies the shim procedure considerably, but also provides a better field homogeneity and image quality, which both could help to significantly improve the applicability of cortico-spinal fMRI.
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Affiliation(s)
- Ying Chu
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Geb. W34, Hamburg, 20246, Germany
| | - Björn Fricke
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Geb. W34, Hamburg, 20246, Germany
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Geb. W34, Hamburg, 20246, Germany.
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85
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Deep Learning-Based Auto-Segmentation of Spinal Cord Internal Structure of Diffusion Tensor Imaging in Cervical Spondylotic Myelopathy. Diagnostics (Basel) 2023; 13:diagnostics13050817. [PMID: 36899962 PMCID: PMC10000612 DOI: 10.3390/diagnostics13050817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/14/2023] [Accepted: 02/19/2023] [Indexed: 02/24/2023] Open
Abstract
Cervical spondylotic myelopathy (CSM) is a chronic disorder of the spinal cord. ROI-based features on diffusion tensor imaging (DTI) provide additional information about spinal cord status, which would benefit the diagnosis and prognosis of CSM. However, the manual extraction of the DTI-related features on multiple ROIs is time-consuming and laborious. In total, 1159 slices at cervical levels from 89 CSM patients were analyzed, and corresponding fractional anisotropy (FA) maps were calculated. Eight ROIs were drawn, covering both sides of lateral, dorsal, ventral, and gray matter. The UNet model was trained with the proposed heatmap distance loss for auto-segmentation. Mean Dice coefficients on the test dataset for dorsal, lateral, and ventral column and gray matter were 0.69, 0.67, 0.57, 0.54 on the left side and 0.68, 0.67, 0.59, 0.55 on the right side. The ROI-based mean FA value based on segmentation model strongly correlated with the value based on manual drawing. The percentages of the mean absolute error between the two values of multiple ROIs were 0.07, 0.07, 0.11, and 0.08 on the left side and 0.07, 0.1, 0.1, 0.11, and 0.07 on the right side. The proposed segmentation model has the potential to offer a more detailed spinal cord segmentation and would be beneficial for quantifying a more detailed status of the cervical spinal cord.
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86
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Landelle C, Dahlberg LS, Lungu O, Misic B, De Leener B, Doyon J. Altered Spinal Cord Functional Connectivity Associated with Parkinson's Disease Progression. Mov Disord 2023; 38:636-645. [PMID: 36802374 DOI: 10.1002/mds.29354] [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: 11/17/2022] [Revised: 01/13/2023] [Accepted: 01/30/2023] [Indexed: 02/23/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) has traditionally been viewed as an α-synucleinopathy brain pathology. Yet evidence based on postmortem human and animal experimental models indicates that the spinal cord may also be affected. OBJECTIVE Functional magnetic resonance imaging (fMRI) seems to be a promising candidate to better characterize spinal cord functional organization in PD patients. METHODS Resting-state spinal fMRI was performed in 70 PD patients and 24 age-matched healthy controls, the patients being divided into three groups based on their motor symptom severity: PDlow (n = 24), PDmed (n = 22), and PDadv (n = 24) groups. A combination of independent component analysis (ICA) and a seed-based approach was applied. RESULTS When pooling all participants, the ICA revealed distinct ventral and dorsal components distributed along the rostro-caudal axis. This organization was highly reproducible within subgroups of patients and controls. PD severity, assessed by Unified Parkinson's Disease Rating Scale (UPDRS) scores, was associated with a decrease in spinal functional connectivity (FC). Notably, we observed a reduced intersegmental correlation in PD as compared to controls, the latter being negatively associated with patients' upper-limb UPDRS scores (P = 0.0085). This negative association between FC and upper-limb UPDRS scores was significant between adjacent C4-C5 (P = 0.015) and C5-C6 (P = 0.20) cervical segments, levels associated with upper-limb functions. CONCLUSIONS The present study provides the first evidence of spinal cord FC changes in PD and opens new avenues for the effective diagnosis and therapeutic strategies in PD. This underscores how spinal cord fMRI can serve as a powerful tool to characterize, in vivo, spinal circuits for a variety of neurological diseases. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Caroline Landelle
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Linda Solstrand Dahlberg
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Ovidiu Lungu
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Bratislav Misic
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Benjamin De Leener
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,CHU Sainte-Justine Research Centre, Montreal, Quebec, Canada
| | - Julien Doyon
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Association of volumetric MRI measures and disability in MS patients of the same age: Descriptions from a birth year cohort. Mult Scler Relat Disord 2023; 71:104568. [PMID: 36805177 DOI: 10.1016/j.msard.2023.104568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 01/20/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023]
Abstract
BACKGROUND AND OBJECTIVES Although MRI-based markers of neuroinflammation have proven crucial for the diagnosis of multiple sclerosis (MS), predicting clinical progression with inflammation remains difficult. Neurodegenerative markers such as brain volume loss show stronger clinical (predictive) correlations, but also harbor age-related variation that must be disentangled from disease duration. In this study we investigated how clinical disability is related to volumetric MRI measures in a cohort of MS patients and healthy controls (HC) of the same age: Project Y. METHODS This study included 234 MS patients born in 1966 and 112 HC born between 1965 and 1967 in the Netherlands. Disability was quantified using the expanded disability status scale (EDSS), nine hole peg test (9HPT), and timed 25 foot walking test (T25FWT). Volumes were quantified on 3T MRI as normalized whole brain (NBV) and regional gray matter (GM) volumes using the same scanner and MRI protocol: cortical (normalized cortical gray matter volume; NCGMV), deep (NDGMV), thalamic (NThalV), and cerebellar (NCbV) GM volumes. In addition, mean upper cervical cord area (MUCCA), white matter lesion volume (LV), and spinal cord lesions were assessed. These measures were compared between patients and HC, and related to disability measures using linear regression. RESULTS Mean age of people with MS (PwMS) was 52.8 years (SD 0.9) and median disease duration 15.8 years (IQR 8.7-24.8). All global and regional brain measures were lower in MS patients compared to HC. Univariate regression models showed that NDGMV (β = -0.20) and MUCCA (β = -0.38) were most strongly related to the EDSS in all PwMS. After subtype stratification, MUCCA was most strongly related to the EDSS (β = -0.60) and 9HPT (β = -0.55) in secondary progressive PwMS. Multivariate regression models demonstrated that in all PwMS, the EDSS was best explained by lower MUCCA, longer disease durations and a progressive disease course (adjusted-R (Sastre-Garriga et al., 2017) = 0.26, p < 0.001). MUCCA was a consistent correlate in separate models of the EDSS for all PwMS, relapsing and progressive onset PwMS. The 9HPT (adjusted-R (Sastre-Garriga et al., 2017) = 0.20, p < 0.001) was best explained by lower MUCCA, higher LV and pack years, while lower limb disability (adjusted-R (Sastre-Garriga et al., 2017) = 0.11, p < 0.001) was best explained by lower MUCCA, progressive onset MS and female sex. DISCUSSION Our results indicate that in a cohort unbiased by age differences, spinal cord and deep gray matter volumes best related to physical disability. Our results support the use of these measures in clinical practice and trials.
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Rios NL, Gilbert KM, Papp D, Cereza G, Foias A, Rangaprakash D, May MW, Guerin B, Wald LL, Keil B, Stockmann JP, Barry RL, Cohen-Adad J. 8-channel Tx dipole and 20-channel Rx loop coil array for MRI of the cervical spinal cord at 7 Tesla. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.08.527664. [PMID: 36798276 PMCID: PMC9934596 DOI: 10.1101/2023.02.08.527664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The quality of cervical spinal cord images can be improved by the use of tailored radiofrequency coil solutions for ultra-high field imaging; however, very few commercial and research 7 Tesla radiofrequency coils currently exist for the spinal cord, and in particular those with parallel transmit capabilities. This work presents the design, testing and validation of a pTx/Rx coil for the human neck and cervical/upper-thoracic spinal cord. The pTx portion is composed of 8 dipoles to ensure high homogeneity over this large region of the spinal cord. The Rx portion is made of 20 semi-adaptable overlapping loops to produce high Signal-to-noise ratio (SNR) across the patient population. The coil housing is designed to facilitate patient positioning and comfort, while being tight fitting to ensure high sensitivity. We demonstrate RF shimming capabilities to optimize B 1 + uniformity, power efficiency and/or specific absorption rate (SAR) efficiency. B 1 + homogeneity, SNR and g-factor was evaluated in adult volunteers and demonstrated excellent performance from the occipital lobe down to the T4-T5 level. We compared the proposed coil with two state-of-the-art head and head/neck coils, confirming its superiority in the cervical and upper-thoracic regions of the spinal cord. This coil solution therefore provides a convincing platform for producing the high image quality necessary for clinical and research scanning of the upper spinal cord.
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Affiliation(s)
- Nibardo Lopez Rios
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada
| | - Kyle M. Gilbert
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON, Canada
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada
| | - Gaspard Cereza
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada
| | - D. Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Markus W. May
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany
- High Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Bastien Guerin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Lawrence L. Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection, University of Applied Sciences Mittelhessen, Giessen, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps University of Marburg, Marburg, Germany
| | - Jason P. Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
- Mila – Quebec AI Institute, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada
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Wu X, Wang Y, Chang J, Zhu K, Zhang S, Li Y, Zuo J, Chen S, Jin W, Yan T, Yang K, Xu P, Song P, Wu Y, Qian Y, Shen C, Yu Y, Dong F. Remodeling of the brain correlates with gait instability in cervical spondylotic myelopathy. Front Neurosci 2023; 17:1087945. [PMID: 36816111 PMCID: PMC9932596 DOI: 10.3389/fnins.2023.1087945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction Cervical spondylotic myelopathy (CSM) is a common form of non-traumatic spinal cord injury (SCI) and usually leads to remodeling of the brain and spinal cord. In CSM with gait instability, the remodeling of the brain and cervical spinal cord is unclear. We attempted to explore the remodeling of these patients' brains and spinal cords, as well as the relationship between the remodeling of the brain and spinal cord and gait instability. Methods According to the CSM patients' gait, we divided patients into two groups: normal gait patients (nPT) and abnormal gait patients (aPT). Voxel-wise z-score transformation amplitude of low-frequency fluctuations (zALFF) and resting-state functional connectivity (rs-FC) were performed for estimating brain changes. Cross-sectional area (CSA) and fractional anisotropy (FA) of the spinal cord were computed by Spinal cord toolbox. Correlations of these measures and the modified Japanese Orthopedic Association (mJOA) score were analyzed. Results We found that the zALFF of caudate nucleus in aPT was higher than that in healthy controls (HC) and lower than that in nPT. The zALFF of the right postcentral gyrus and paracentral lobule in HC was higher than those of aPT and nPT. Compared with the nPT, the aPT showed increased functional connectivity between the caudate nucleus and left angular gyrus, bilateral precuneus and bilateral posterior cingulate cortex (PCC), which constitute a vital section of the default mode network (DMN). No significantly different FA values or CSA of spinal tracts at the C2 level were observed between the HC, nPT and aPT groups. In CSM, the right paracentral lobule's zALFF was negatively correlated with the FA value of fasciculus gracilis (FCG), and the right caudate zALFF was positively correlated with the FA value of the fasciculus cuneatus (FCC). The results showed that the functional connectivity between the right caudate nucleus and DMN was negatively correlated with the CSA of the lateral corticospinal tract (CST). Discussion The activation of the caudate nucleus and the strengthening functional connectivity between the caudate nucleus and DMN were associated with gait instability in CSM patients. Correlations between spinal cord and brain function might be related to the clinical symptoms in CSM.
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Affiliation(s)
- Xianyong Wu
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ying Wang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jianchao Chang
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Kun Zhu
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Siya Zhang
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China,School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Yan Li
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Junxun Zuo
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Senlin Chen
- Department of Orthopedics, Dongcheng Branch of The First Affiliated Hospital of Anhui Medical University (Feidong People’s Hospital), Hefei, China
| | - Weiming Jin
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Tingfei Yan
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Kun Yang
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Peng Xu
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Peiwen Song
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yuanyuan Wu
- Department of Medical Imaging, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Yuanyuan Wu,
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Cailiang Shen
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China,Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Fulong Dong
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China,*Correspondence: Fulong Dong,
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90
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Matusche B, Litvin L, Schneider R, Bellenberg B, Mühlau M, Pongratz V, Berthele A, Groppa S, Muthuraman M, Zipp F, Paul F, Wiendl H, Meuth SG, Sämann P, Weber F, Linker RA, Kümpfel T, Gold R, Lukas C. Early spinal cord pseudoatrophy in interferon-beta-treated multiple sclerosis. Eur J Neurol 2023; 30:453-462. [PMID: 36318271 DOI: 10.1111/ene.15620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 10/26/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Brain pseudoatrophy has been shown to play a pivotal role in the interpretation of brain atrophy measures during the first year of disease-modifying therapy in multiple sclerosis. Whether pseudoatrophy also affects the spinal cord remains unclear. The aim of this study was to analyze the extent of pseudoatrophy in the upper spinal cord during the first 2 years after therapy initiation and compare this to the brain. METHODS A total of 129 patients from a prospective longitudinal multicentric national cohort study for whom magnetic resonance imaging scans at baseline, 12 months, and 24 months were available were selected for brain and spinal cord volume quantification. Annual percentage brain volume and cord area change were calculated using SIENA (Structural Image Evaluation of Normalized Atrophy) and NeuroQLab, respectively. Linear mixed model analyses were performed to compare patients on interferon-beta therapy (n = 84) and untreated patients (n = 45). RESULTS Patients treated with interferon-beta demonstrated accelerated annual percentage brain volume and cervical cord area change in the first year after treatment initiation, whereas atrophy rates stabilized to a similar and not significantly different level compared to untreated patients during the second year. CONCLUSIONS These results suggest that pseudoatrophy occurs not only in the brain, but also in the spinal cord during the first year of interferon-beta treatment.
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Affiliation(s)
- Britta Matusche
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Ludmila Litvin
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Ruth Schneider
- Department of Neurology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Barbara Bellenberg
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Mark Mühlau
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Viola Pongratz
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine-Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine-Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine-Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Heinz Wiendl
- Department of Neurology, Institute of Translational Neurology, University of Münster, Münster, Germany
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Frank Weber
- Neurological Clinic, Sana Clinic Cham, Cham, Germany
| | - Ralf A Linker
- Department of Neurology, University of Regensburg, Regensburg, Germany
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, Biomedical Center and University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Ralf Gold
- Department of Neurology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Carsten Lukas
- Institute for Neuroradiology, St Josef Hospital, Ruhr University Bochum, Bochum, Germany
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91
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Tsagkas C, Horvath-Huck A, Haas T, Amann M, Todea A, Altermatt A, Müller J, Cagol A, Leimbacher M, Barakovic M, Weigel M, Pezold S, Sprenger T, Kappos L, Bieri O, Granziera C, Cattin P, Parmar K. Fully Automatic Method for Reliable Spinal Cord Compartment Segmentation in Multiple Sclerosis. AJNR Am J Neuroradiol 2023; 44:218-227. [PMID: 36702504 PMCID: PMC9891337 DOI: 10.3174/ajnr.a7756] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 12/05/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE Fully automatic quantification methods of spinal cord compartments are needed to study pathologic changes of the spinal cord GM and WM in MS in vivo. We propose a novel method for automatic spinal cord compartment segmentation (SCORE) in patients with MS. MATERIALS AND METHODS The cervical spinal cords of 24 patients with MS and 24 sex- and age-matched healthy controls were scanned on a 3T MR imaging system, including an averaged magnetization inversion recovery acquisition sequence. Three experienced raters manually segmented the spinal cord GM and WM, anterior and posterior horns, gray commissure, and MS lesions. Subsequently, manual segmentations were used to train neural segmentation networks of spinal cord compartments with multidimensional gated recurrent units in a 3-fold cross-validation fashion. Total intracranial volumes were quantified using FreeSurfer. RESULTS The intra- and intersession reproducibility of SCORE was high in all spinal cord compartments (eg, mean relative SD of GM and WM: ≤ 3.50% and ≤1.47%, respectively) and was better than manual segmentations (all P < .001). The accuracy of SCORE compared with manual segmentations was excellent, both in healthy controls and in patients with MS (Dice similarity coefficients of GM and WM: ≥ 0.84 and ≥0.92, respectively). Patients with MS had lower total WM areas (P < .05), and total anterior horn areas (P < .01 respectively), as measured with SCORE. CONCLUSIONS We demonstrate a novel, reliable quantification method for spinal cord tissue segmentation in healthy controls and patients with MS and other neurologic disorders affecting the spinal cord. Patients with MS have reduced areas in specific spinal cord tissue compartments, which may be used as MS biomarkers.
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Affiliation(s)
- C Tsagkas
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
| | - A Horvath-Huck
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - T Haas
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
| | - M Amann
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
- Medical Image Analysis Center AG (M.A., A.A.), Basel, Switzerland
| | - A Todea
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Radiology; Department of Neuroradiology (A.T.), Clinic for Radiology & Nuclear Medicine; and Research Center for Clinical Neuroimmunology
| | - A Altermatt
- Medical Image Analysis Center AG (M.A., A.A.), Basel, Switzerland
| | - J Müller
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
| | - A Cagol
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - M Leimbacher
- Medical Faculty (M.L., P.C.), University of Basel, Basel, Switzerland
| | - M Barakovic
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - M Weigel
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - S Pezold
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - T Sprenger
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Department of Neurology (T.S.), DKD Helios Klinik Wiesbaden, Wiesbaden, Germany
| | - L Kappos
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Neuroscience Basel (RC2NB) (L.K.), Departments of Medicine, Clinical Research, and Biomedical Imaging, University Hospital Basel and University of Basel, Basel, Switzerland
| | - O Bieri
- Department of Medicine and Biomedical Engineering; Division of Radiological Physics (T.H., M.W., O.B.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - C Granziera
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
| | - P Cattin
- Department of Biomedical Engineering (A.H.-H., M.A., A.C., M.B., M.W., S.P., O.B., C.G., P.C.), University of Basel, Allschwil, Switzerland
- Medical Faculty (M.L., P.C.), University of Basel, Basel, Switzerland
| | - K Parmar
- From the Neurologic Clinic and Policlinic, Departments of Medicine (C.T., M.A., J.M., M.W., T.S., L.K., C.G., K.P.), Clinical Research and Biomedical Engineering
- Translational Imaging in Neurology Basel (C.T., A.T., J.M., A.C., M.B., M.W., C.G., K.P.)
- Reha Rheinfelden (K.P.), Rheinfelden, Switzerland
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92
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Schilling KG, Fadnavis S, Batson J, Visagie M, Combes AJE, By S, McKnight CD, Bagnato F, Garyfallidis E, Landman BA, Smith SA, O'Grady KP. Denoising of diffusion MRI in the cervical spinal cord - effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity. Neuroimage 2023; 266:119826. [PMID: 36543265 PMCID: PMC9843739 DOI: 10.1016/j.neuroimage.2022.119826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 11/02/2022] [Accepted: 12/17/2022] [Indexed: 12/23/2022] Open
Abstract
Quantitative diffusion MRI (dMRI) is a promising technique for evaluating the spinal cord in health and disease. However, low signal-to-noise ratio (SNR) can impede interpretation and quantification of these images. The purpose of this study is to evaluate several dMRI denoising approaches on their ability to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. We evaluate three denoising approaches (Non-Local Means, Marchenko-Pastur PCA, and a newly proposed Patch2Self algorithm) and conduct five experiments to validate the denoising performance on clinical-quality and commonly-acquired dMRI acquisitions: 1) a phantom experiment to assess denoising error and bias; 2) a multi-vendor, multi-acquisition open experiment for both qualitative and quantitative evaluation of noise residuals; 3) a bootstrapping experiment to estimate uncertainty of parametric maps; 4) an assessment of spinal cord lesion conspicuity in a multiple sclerosis group; and 5) an evaluation of denoising for advanced parametric multi-compartment modeling. We find that all methods improve signal-to-noise ratio and conspicuity of MS lesions in individual diffusion weighted images (DWIs), but MPPCA and Patch2Self excel at improving the quality and intra-cord contrast of diffusion weighted images - removing signal fluctuations due to thermal noise while improving precision of estimation of diffusion parameters even with very few DWIs (i.e., 16-32) typical of clinical acquisitions. These denoising approaches hold promise for facilitating reliable diffusion observations and measurements in the spinal cord to investigate biological and pathological processes.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States.
| | - Shreyas Fadnavis
- Department of Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States
| | - Joshua Batson
- The Public Health Company, California, United States
| | - Mereze Visagie
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Anna J E Combes
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Samantha By
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Neurology, VA Hospital, TN Valley Healthcare System, Nashville, TN, United States
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - Seth A Smith
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Kristin P O'Grady
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.
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93
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Taso M, Munsch F, Girard OM, Duhamel G, Alsop DC, Varma G. Fast-spin-echo versus rapid gradient-echo for 3D magnetization-prepared acquisitions: Application to inhomogeneous magnetization transfer. Magn Reson Med 2023; 89:550-564. [PMID: 36306334 PMCID: PMC10848167 DOI: 10.1002/mrm.29461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/23/2022] [Accepted: 08/26/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE To evaluate the benefits of fast spin echo (FSE) imaging over rapid gradient-echo (RAGE) for magnetization-prepared inhomogeneous magnetization transfer (ihMT) imaging. METHODS A 3D FSE sequence was modified to include an ihMT preparation (ihMT-FSE) with an optional CSF suppression based on an inversion-recovery (ihMT-FLAIR). After numeric simulations assessing SNR benefits of FSE and the potential impact of an additional inversion-recovery, ihMT-RAGE, ihMT-FSE, and ihMT-FLAIR sequences were compared in a group of six healthy volunteers, evaluating image quality, thermal, and physiological noise as well as quantification using an ihMT saturation (ihMTsat) approach. A preliminary exploration in the cervical spinal cord was also conducted in a group of three healthy volunteers. RESULTS Several fold improvements in thermal SNR were observed with ihMT-FSE in agreement with numerical simulations. However, we observed significantly higher physiological noise in ihMT-FSE compared to ihMT-RAGE that was mitigated in ihMT-FLAIR, which provided the best total SNR (+74% and +49% compared to ihMT-RAGE in the white and gray matter, P ≤ 0.004). IhMTsat quantification was successful in all cases with strong correlation between all sequences (r2 > 0.75). Early experiments showed potential for spinal cord imaging. CONCLUSIONS FSE generally offers higher SNR compared to gradient-echo based acquisitions for magnetization-prepared contrasts as illustrated here in the case of ihMT. However, physiological noise has a significant effect, but an inversion-recovery-based CSF suppression was shown to be efficient in mitigating effects of CSF motion.
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Affiliation(s)
- Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Fanny Munsch
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | | | | | - David C. Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Gopal Varma
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
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94
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Sastre-Garriga J, Rovira A, García-Vidal A, Carbonell-Mirabent P, Alberich M, Vidal-Jordana A, Auger C, Tintore M, Montalban X, Pareto D. Spinal cord reserve in multiple sclerosis. J Neurol Neurosurg Psychiatry 2023:jnnp-2022-330613. [PMID: 36690430 DOI: 10.1136/jnnp-2022-330613] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/10/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND The spinal cord (SC) is a preferential target of multiple sclerosis (MS) damage highly relevant towards disability. Differential impact of such damage could be due to the initial amount of SC tissue, as described for the brain parenchyma (brain reserve concept). We aimed to test the existence of SC reserve by using spinal canal area (SCaA) as a proxy. METHODS Brain sagittal three-dimensional T1-weighted scans covering down to C5 level were acquired in 2930 people with MS and 43 healthy controls (HCs) in a cross-sectional, multicentre study. SC area (SCA) and SCaA were obtained with the Spinal Cord Toolbox. Demographical data and patient-derived disability scores were obtained. SC parameters were compared between groups with age-adjusted and sex-adjusted linear regression models. The main outcome of the study, the existence of an association between SCaA and Patient Determined Disease Steps, was tested with scaled linear models. RESULTS 1747 persons with MS (mean age: 46.35 years; 73.2% female) and 42 HCs (mean age: 45.56 years; 78.6% female) were analysed after exclusion of post-processing errors and application of quality criteria. SCA (60.41 mm2 vs 65.02 mm2, p<0.001) was lower in people with MS compared with HC; no differences in SCaA were observed (213.24 mm2 vs 212.61 mm2, p=0.125). Adjusted scaled linear models showed that a larger SCaA was significantly associated with lower scores on Patient Determined Disease Steps (beta coefficient: -0.12, p=0.0124) independently of spinal cord atrophy, brain T2 lesion volume, age and sex. CONCLUSIONS A larger SCaA may be protective against disability in MS, possibly supporting the existence of SC reserve.
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Affiliation(s)
- Jaume Sastre-Garriga
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Alex Rovira
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Aran García-Vidal
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Pere Carbonell-Mirabent
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Manel Alberich
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Angela Vidal-Jordana
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Cristina Auger
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Mar Tintore
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Xavier Montalban
- Servei de Neurologia / Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Deborah Pareto
- Secció de Neuroradiologia, Servei de Radiologia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
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95
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Cortese R, Prados Carrasco F, Tur C, Bianchi A, Brownlee W, De Angelis F, De La Paz I, Grussu F, Haider L, Jacob A, Kanber B, Magnollay L, Nicholas RS, Trip A, Yiannakas M, Toosy AT, Hacohen Y, Barkhof F, Ciccarelli O. Differentiating Multiple Sclerosis From AQP4-Neuromyelitis Optica Spectrum Disorder and MOG-Antibody Disease With Imaging. Neurology 2023; 100:e308-e323. [PMID: 36192175 PMCID: PMC9869760 DOI: 10.1212/wnl.0000000000201465] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 09/09/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Relapsing-remitting multiple sclerosis (RRMS), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may have overlapping clinical features. There is an unmet need for imaging markers that differentiate between them when serologic testing is unavailable or ambiguous. We assessed whether imaging characteristics typical of MS discriminate RRMS from AQP4-NMOSD and MOGAD, alone and in combination. METHODS Adult, nonacute patients with RRMS, APQ4-NMOSD, and MOGAD and healthy controls were prospectively recruited at the National Hospital for Neurology and Neurosurgery (London, United Kingdom) and the Walton Centre (Liverpool, United Kingdom) between 2014 and 2019. They underwent conventional and advanced brain, cord, and optic nerve MRI and optical coherence tomography (OCT). RESULTS A total of 91 consecutive patients (31 RRMS, 30 APQ4-NMOSD, and 30 MOGAD) and 34 healthy controls were recruited. The most accurate measures differentiating RRMS from AQP4-NMOSD were the proportion of lesions with the central vein sign (CVS) (84% vs 33%, accuracy/specificity/sensitivity: 91/88/93%, p < 0.001), followed by cortical lesions (median: 2 [range: 1-14] vs 1 [0-1], accuracy/specificity/sensitivity: 84/90/77%, p = 0.002) and white matter lesions (mean: 39.07 [±25.8] vs 9.5 [±14], accuracy/specificity/sensitivity: 78/84/73%, p = 0.001). The combination of higher proportion of CVS, cortical lesions, and optic nerve magnetization transfer ratio reached the highest accuracy in distinguishing RRMS from AQP4-NMOSD (accuracy/specificity/sensitivity: 95/92/97%, p < 0.001). The most accurate measures favoring RRMS over MOGAD were white matter lesions (39.07 [±25.8] vs 1 [±2.3], accuracy/specificity/sensitivity: 94/94/93%, p = 0.006), followed by cortical lesions (2 [1-14] vs 1 [0-1], accuracy/specificity/sensitivity: 84/97/71%, p = 0.004), and retinal nerve fiber layer thickness (RNFL) (mean: 87.54 [±13.83] vs 75.54 [±20.33], accuracy/specificity/sensitivity: 80/79/81%, p = 0.009). Higher cortical lesion number combined with higher RNFL thickness best differentiated RRMS from MOGAD (accuracy/specificity/sensitivity: 84/92/77%, p < 0.001). DISCUSSION Cortical lesions, CVS, and optic nerve markers achieve a high accuracy in distinguishing RRMS from APQ4-NMOSD and MOGAD. This information may be useful in clinical practice, especially outside the acute phase and when serologic testing is ambiguous or not promptly available. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that selected conventional and advanced brain, cord, and optic nerve MRI and OCT markers distinguish adult patients with RRMS from AQP4-NMOSD and MOGAD.
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Affiliation(s)
- Rosa Cortese
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Ferran Prados Carrasco
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Carmen Tur
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Alessia Bianchi
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Wallace Brownlee
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Floriana De Angelis
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Isabel De La Paz
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Francesco Grussu
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Lukas Haider
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Anu Jacob
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Baris Kanber
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Lise Magnollay
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Richard S Nicholas
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Anand Trip
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Marios Yiannakas
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Ahmed T Toosy
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Yael Hacohen
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Frederik Barkhof
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Olga Ciccarelli
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands.
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96
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Nigri A, Dalla Bella E, Ferraro S, Medina Carrion JP, Demichelis G, Bersano E, Consonni M, Bischof A, Stanziano M, Palermo S, Lauria G, Bruzzone MG, Papinutto N. Cervical spinal cord atrophy in amyotrophic lateral sclerosis across disease stages. Ann Clin Transl Neurol 2023; 10:213-224. [PMID: 36599092 PMCID: PMC9930423 DOI: 10.1002/acn3.51712] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/11/2022] [Accepted: 11/21/2022] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE Spinal cord degeneration is a hallmark of amyotrophic lateral sclerosis. The assessment of gray matter and white matter cervical spinal cord atrophy across clinical stages defined using the King's staging system could advance the understanding of amyotrophic lateral sclerosis progression. METHODS We assessed the in vivo spatial pattern of gray and white matter atrophy along cervical spinal cord (C2 to C6 segments) using 2D phase-sensitive inversion recovery imaging in a cohort of 44 amyotrophic lateral sclerosis patients, evaluating its change across the King's stages and the correlation with disability scored by the amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) and disease duration. A mathematical model inferring the potential onset of cervical gray matter atrophy was developed. RESULTS In amyotrophic lateral sclerosis patients at King's stage 1, significant cervical spinal cord alterations were mainly identified in gray matter, whereas they involved both gray and white matter in patients at King's stage ≥ 2. Gray and white matter areas correlated with clinical disability at all cervical segments. C3-C4 level was the segment showing early gray matter atrophy starting about 7 to 20 months before symptom onset according to our model. INTERPRETATION Our findings suggest that cervical spinal cord atrophy spreads from gray to white matter across King's stages in amyotrophic lateral sclerosis, making spinal cord magnetic resonance imaging an in vivo assessment tool to measure the progression of the disease.
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Affiliation(s)
- Anna Nigri
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Eleonora Dalla Bella
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Stefania Ferraro
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,School of Life Science and Technology, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | | | - Greta Demichelis
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Enrica Bersano
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,Department of Medical Biotechnology and Translational MedicineUniversity of MilanMilanItaly
| | - Monica Consonni
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Antje Bischof
- Weill Institute for Neurosciences, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA,Department of Neurology with Institute for Translational NeurologyUniversity Hospital MünsterMünsterGermany
| | - Mario Stanziano
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,ALS Centre, “Rita Levi Montalcini” Department of NeuroscienceUniversity of TurinTurinItaly
| | - Sara Palermo
- Neuroradiology UnitFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly
| | - Giuseppe Lauria
- 3rd Neurology Unit and Motor Neuron Disease CentreFondazione IRCCS Istituto Neurologico Carlo BestaMilanItaly,Department of Medical Biotechnology and Translational MedicineUniversity of MilanMilanItaly
| | | | - Nico Papinutto
- Weill Institute for Neurosciences, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
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97
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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: 0] [Impact Index Per Article: 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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98
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Rocca MA, Valsasina P, Meani A, Gobbi C, Zecca C, Barkhof F, Schoonheim MM, Strijbis EM, Vrenken H, Gallo A, Bisecco A, Ciccarelli O, Yiannakas M, Rovira A, Sastre-Garriga J, Palace J, Matthews L, Gass A, Eisele P, Lukas C, Bellenberg B, Margoni M, Preziosa P, Filippi M. Spinal cord lesions and brain grey matter atrophy independently predict clinical worsening in definite multiple sclerosis: a 5-year, multicentre study. J Neurol Neurosurg Psychiatry 2023; 94:10-18. [PMID: 36171105 DOI: 10.1136/jnnp-2022-329854] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/05/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVES To evaluate the combined contribution of brain and cervical cord damage in predicting 5-year clinical worsening in a multicentre cohort of definite multiple sclerosis (MS) patients. METHODS Baseline 3.0T brain and cervical cord T2-weighted and three-dimensional T1-weighted MRI was acquired in 367 patients with MS (326 relapse-onset and 41 progressive-onset) and 179 healthy controls. Expanded Disability Status Scale (EDSS) score was obtained at baseline and after a median follow-up of 5.1 years (IQR=4.8-5.2). At follow-up, patients were classified as clinically stable/worsened according to EDSS changes. Generalised linear mixed models identified predictors of clinical worsening, evolution to secondary progressive (SP) MS and reaching EDSS=3.0, 4.0 and 6.0 milestones at 5 years. RESULTS At follow-up, 120/367 (33%) patients with MS worsened clinically; 36/256 (14%) patients with relapsing-remitting evolved to SPMS. Baseline predictors of EDSS worsening were progressive-onset versus relapse-onset MS (standardised beta (β)=0.97), higher EDSS (β=0.41), higher cord lesion number (β=0.41), lower normalised cortical volume (β=-0.15) and lower cord area (β=-0.28) (C-index=0.81). Older age (β=0.86), higher EDSS (β=1.40) and cord lesion number (β=0.87) independently predicted SPMS conversion (C-index=0.91). Predictors of reaching EDSS=3.0 after 5 years were higher baseline EDSS (β=1.49), cord lesion number (β=1.02) and lower normalised cortical volume (β=-0.56) (C-index=0.88). Baseline age (β=0.30), higher EDSS (β=2.03), higher cord lesion number (β=0.66) and lower cord area (β=-0.41) predicted EDSS=4.0 (C-index=0.92). Finally, higher baseline EDSS (β=1.87) and cord lesion number (β=0.54) predicted EDSS=6.0 (C-index=0.91). CONCLUSIONS Spinal cord damage and, to a lesser extent, cortical volume loss helped predicting worse 5-year clinical outcomes in MS.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy .,Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Claudio Gobbi
- Neurology Clinic, MS Center/Headache Center, Neurocenter of Southern Switzerland EOC, Lugano, Switzerland.,Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Chiara Zecca
- Neurology Clinic, MS Center/Headache Center, Neurocenter of Southern Switzerland EOC, Lugano, Switzerland.,Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Frederik Barkhof
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - Locatie VUMC, Amsterdam, Netherlands.,Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - Locatie VUMC, Amsterdam, Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Locatie VUmc, Amsterdam, Netherlands
| | - Eva M Strijbis
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - Locatie VUMC, Amsterdam, Netherlands
| | - Hugo Vrenken
- Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - Locatie VUMC, Amsterdam, Netherlands.,Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - Locatie VUMC, Amsterdam, Netherlands
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, and 3T MRI-Center, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Alvino Bisecco
- Department of Advanced Medical and Surgical Sciences, and 3T MRI-Center, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Marios Yiannakas
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology/Neuroimmunology, Multiple Sclerosis Centre of Catalonia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Lucy Matthews
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Achim Gass
- Department of Neurology, and Mannheim Center of Translational Neurosciences (MCTN), Ruprecht Karls University Heidelberg Faculty of Medicine Mannheim, Mannheim, Germany
| | - Philipp Eisele
- Department of Neurology, and Mannheim Center of Translational Neurosciences (MCTN), Ruprecht Karls University Heidelberg Faculty of Medicine Mannheim, Mannheim, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany.,Department of Radiology and Nuclear Medicine, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Barbara Bellenberg
- Institute of Neuroradiology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy.,Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy.,Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy.,Neurorehabilitation Unit, IRCCS Ospedale San Raffaele, Milano, Italy.,Neurophysiology Service, IRCCS Ospedale San Raffaele, Milano, Italy
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99
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Zhang JK, Jayasekera D, Song C, Greenberg JK, Javeed S, Dibble CF, Blum J, Sun P, Song SK, Ray WZ. Diffusion Basis Spectrum Imaging Provides Insights Into Cervical Spondylotic Myelopathy Pathology. Neurosurgery 2023; 92:102-109. [PMID: 36519861 PMCID: PMC10158908 DOI: 10.1227/neu.0000000000002183] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/11/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Diffusion basis spectrum imaging (DBSI) is a noninvasive quantitative imaging modality that may improve understanding of cervical spondylotic myelopathy (CSM) pathology through detailed evaluations of spinal cord microstructural compartments. OBJECTIVE To determine the utility of DBSI as a biomarker of CSM disease severity. METHODS A single-center prospective cohort study enrolled 50 patients with CSM and 20 controls from 2018 to 2020. All patients underwent clinical evaluation and diffusion-weighted MRI, followed by diffusion tensor imaging and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. In addition, DBSI further evaluates extra-axonal changes by isotropic restricted and nonrestricted fraction. Including an intra-axonal diffusion compartment, DBSI improves estimations of axonal injury through intra-axonal axial diffusivity. Patients were categorized into mild, moderate, and severe CSM using modified Japanese Orthopedic Association classifications. Imaging parameters were compared among patient groups using independent samples t tests and ANOVA. RESULTS Twenty controls, 27 mild (modified Japanese Orthopedic Association 15-17), 12 moderate (12-14), and 11 severe (0-11) patients with CSM were enrolled. Diffusion tensor imaging and DBSI fractional anisotropy, axial diffusivity, and radial diffusivity were significantly different between control and patients with CSM ( P < .05). DBSI fiber fraction, restricted fraction, and nonrestricted fraction were significantly different between groups ( P < .01). DBSI intra-axonal axial diffusivity was lower in mild compared with moderate (mean difference [95% CI]: 1.1 [0.3-2.1], P < .01) and severe (1.9 [1.3-2.4], P < .001) CSM. CONCLUSION DBSI offers granular data on white matter tract integrity in CSM that provide novel insights into disease pathology, supporting its potential utility as a biomarker of CSM disease progression.
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Affiliation(s)
- Justin K. Zhang
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Dinal Jayasekera
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, Saint Louis, Missouri, USA
| | - Chunyu Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jacob K. Greenberg
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Saad Javeed
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Christopher F. Dibble
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Wilson Z. Ray
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
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100
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Nozawa K, Maki S, Furuya T, Okimatsu S, Inoue T, Yunde A, Miura M, Shiratani Y, Shiga Y, Inage K, Eguchi Y, Ohtori S, Orita S. Magnetic resonance image segmentation of the compressed spinal cord in patients with degenerative cervical myelopathy using convolutional neural networks. Int J Comput Assist Radiol Surg 2023; 18:45-54. [PMID: 36342593 DOI: 10.1007/s11548-022-02783-0] [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: 04/06/2022] [Accepted: 10/20/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE Spinal cord segmentation is the first step in atlas-based spinal cord image analysis, but segmentation of compressed spinal cords from patients with degenerative cervical myelopathy is challenging. We applied convolutional neural network models to segment the spinal cord from T2-weighted axial magnetic resonance images of DCM patients. Furthermore, we assessed the correlation between the cross-sectional area segmented by this network and the neurological symptoms of the patients. METHODS The CNN architecture was built using U-Net and DeepLabv3 + and PyTorch. The CNN was trained on 2762 axial slices from 174 patients, and an additional 517 axial slices from 33 patients were held out for validation and 777 axial slices from 46 patients for testing. The performance of the CNN was evaluated on a test dataset with Dice coefficients as the outcome measure. The ratio of CSA at the maximum compression level to CSA at the C2 level, as segmented by the CNN, was calculated. The correlation between the spinal cord CSA ratio and the Japanese Orthopaedic Association score in DCM patients from the test dataset was investigated using Spearman's rank correlation coefficient. RESULTS The best Dice coefficient was achieved when U-Net was used as the architecture and EfficientNet-b7 as the model for transfer learning. Spearman's rs between the spinal cord CSA ratio and the JOA score of DCM patients was 0.38 (p = 0.007), showing a weak correlation. CONCLUSION Using deep learning with magnetic resonance images of deformed spinal cords as training data, we were able to segment compressed spinal cords of DCM patients with a high concordance with expert manual segmentation. In addition, the spinal cord CSA ratio was weakly, but significantly, correlated with neurological symptoms. Our study demonstrated the first steps needed to implement automated atlas-based analysis of DCM patients.
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Affiliation(s)
- Kyohei Nozawa
- Department of Medical Engineering, Graduate School of Science and Engineering, Chiba University, Chiba, Japan
| | - Satoshi Maki
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan.
- Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.
| | - Takeo Furuya
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Sho Okimatsu
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Takaki Inoue
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Atsushi Yunde
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Masataka Miura
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Yuki Shiratani
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Yasuhiro Shiga
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Kazuhide Inage
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Yawara Eguchi
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Seiji Ohtori
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Sumihisa Orita
- Department of Orthopaedic Surgery, Chiba University Graduate School of Medicine, Chiba, Japan
- Center for Frontier Medical Engineering, Chiba University, Chiba, Japan
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