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Lorenzi RM, Palesi F, Castellazzi G, Vitali P, Anzalone N, Bernini S, Cotta Ramusino M, Sinforiani E, Micieli G, Costa A, D’Angelo E, Gandini Wheeler-Kingshott CAM. Unsuspected Involvement of Spinal Cord in Alzheimer Disease. Front Cell Neurosci 2020; 14:6. [PMID: 32082122 PMCID: PMC7002560 DOI: 10.3389/fncel.2020.00006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 01/10/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer's disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients' classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.
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Affiliation(s)
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Neuroradiology Unit, Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Gloria Castellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Paolo Vitali
- Neuroradiology Unit, Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Sara Bernini
- Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Matteo Cotta Ramusino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Elena Sinforiani
- Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Giuseppe Micieli
- Department of Emergency Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Alfredo Costa
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Egidio D’Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Brain Connectivity Center (BCC), IRCCS Mondino Foundation, Pavia, Italy
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy
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252
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Liu H, Xiang QS, Tam R, Dvorak AV, MacKay AL, Kolind SH, Traboulsee A, Vavasour IM, Li DKB, Kramer JK, Laule C. Myelin water imaging data analysis in less than one minute. Neuroimage 2020; 210:116551. [PMID: 31978542 DOI: 10.1016/j.neuroimage.2020.116551] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Revised: 12/21/2019] [Accepted: 01/14/2020] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF). METHODS A NN was constructed and trained on MWI data acquired by a 32-echo 3D gradient and spin echo (GRASE) sequence. Ground truth labels were created by regularized non-negative least squares (NNLS) with stimulated echo corrections. Voxel-wise GRASE data from 5 brains (4 healthy, 1 multiple sclerosis (MS)) were used for NN training. The trained NN was tested on 2 healthy brains, 1 MS brain with segmented lesions, 1 healthy spinal cord, and 1 healthy brain acquired from a different scanner. RESULTS Production of whole brain MWF maps in approximately 33 s can be achieved by a trained NN without graphics card acceleration. For all testing regions, no visual differences between NN and NNLS MWF maps were observed, and no obvious regional biases were found. Quantitatively, all voxels exhibited excellent agreement between NN and NNLS (all R2>0.98, p < 0.001, mean absolute error <0.01). CONCLUSION The time for accurate MWF calculation can be dramatically reduced to less than 1 min by the proposed NN, addressing one of the barriers facing future clinical feasibility of MWI.
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Affiliation(s)
- Hanwen Liu
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada
| | - Qing-San Xiang
- Physics & Astronomy, University of British Columbia, Canada; Radiology, University of British Columbia, Canada
| | - Roger Tam
- Radiology, University of British Columbia, Canada; Biomedical Engineering, University of British Columbia, Canada
| | - Adam V Dvorak
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada
| | - Alex L MacKay
- Physics & Astronomy, University of British Columbia, Canada; Radiology, University of British Columbia, Canada
| | - Shannon H Kolind
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Radiology, University of British Columbia, Canada; Medicine, University of British Columbia, Canada
| | | | - Irene M Vavasour
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Radiology, University of British Columbia, Canada
| | - David K B Li
- Radiology, University of British Columbia, Canada; Medicine, University of British Columbia, Canada
| | - John K Kramer
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Kinesiology, University of British Columbia, Canada
| | - Cornelia Laule
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Radiology, University of British Columbia, Canada; Pathology & Laboratory Medicine, University of British Columbia, Canada.
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253
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Eden D, Gros C, Badji A, Dupont SM, De Leener B, Maranzano J, Zhuoquiong R, Liu Y, Granberg T, Ouellette R, Stawiarz L, Hillert J, Talbott J, Bannier E, Kerbrat A, Edan G, Labauge P, Callot V, Pelletier J, Audoin B, Rasoanandrianina H, Brisset JC, Valsasina P, Rocca MA, Filippi M, Bakshi R, Tauhid S, Prados F, Yiannakas M, Kearney H, Ciccarelli O, Smith SA, Andrada Treaba C, Mainero C, Lefeuvre J, Reich DS, Nair G, Shepherd TM, Charlson E, Tachibana Y, Hori M, Kamiya K, Chougar L, Narayanan S, Cohen-Adad J. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord. Brain 2020; 142:633-646. [PMID: 30715195 DOI: 10.1093/brain/awy352] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Revised: 10/25/2018] [Accepted: 11/20/2018] [Indexed: 12/12/2022] Open
Abstract
Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.
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Affiliation(s)
- Dominique Eden
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Atef Badji
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada
| | - Sara M Dupont
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada.,Department of Anatomy, Université de Québec à Trois-Rivières, Trois-Rivières, QC, Canada
| | - Ren Zhuoquiong
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, P. R. China
| | - Yaou Liu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, P. R. China.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, P. R. China
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Massachusetts General Hospital, Boston, USA
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Massachusetts General Hospital, Boston, USA
| | - Leszek Stawiarz
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jan Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jason Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Elise Bannier
- CHU Rennes, Radiology Department, Rennes, France.,Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France
| | - Anne Kerbrat
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France.,CHU Rennes, Neurology Department, Rennes, France
| | - Gilles Edan
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France.,CHU Rennes, Neurology Department, Rennes, France
| | - Pierre Labauge
- MS Unit, Department of Neurology, University Hospital of Montpellier, Montpellier, France
| | - Virginie Callot
- Aix Marseille University, CNRS, CRMBM, Marseille, France.,APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean Pelletier
- APHM, CHU Timone, CEMEREM, Marseille, France.,APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Bertrand Audoin
- APHM, CHU Timone, CEMEREM, Marseille, France.,APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Henitsoa Rasoanandrianina
- Aix Marseille University, CNRS, CRMBM, Marseille, France.,APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean-Christophe Brisset
- Observatoire Français de la Sclérose en Plaques (OFSEP) ; Université de Lyon, Université Claude Bernard Lyon 1; Hospices Civils de Lyon; CREATIS-LRMN, UMR 5220 CNRS and U 1044 INSERM; Lyon, France
| | - Paola Valsasina
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Rohit Bakshi
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Shahamat Tauhid
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Ferran Prados
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK.,Center for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Marios Yiannakas
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Hugh Kearney
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Olga Ciccarelli
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Jennifer Lefeuvre
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | | | - Erik Charlson
- Department of Radiology, NYU Langone Medical Center, New York, USA
| | | | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Kouhei Kamiya
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Lydia Chougar
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.,Hospital Cochin, Paris, France
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada.,Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
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254
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Anterior fissure, central canal, posterior septum and more: New insights into the cervical spinal cord gray and white matter regional organization using T1 mapping at 7T. Neuroimage 2020; 205:116275. [DOI: 10.1016/j.neuroimage.2019.116275] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 09/16/2019] [Accepted: 10/10/2019] [Indexed: 12/12/2022] Open
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255
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Generalised boundary shift integral for longitudinal assessment of spinal cord atrophy. Neuroimage 2019; 209:116489. [PMID: 31877375 DOI: 10.1016/j.neuroimage.2019.116489] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 12/18/2019] [Accepted: 12/21/2019] [Indexed: 12/18/2022] Open
Abstract
Spinal cord atrophy measurements obtained from structural magnetic resonance imaging (MRI) are associated with disability in many neurological diseases and serve as in vivo biomarkers of neurodegeneration. Longitudinal spinal cord atrophy rate is commonly determined from the numerical difference between two volumes (based on 3D surface fitting) or two cross-sectional areas (CSA, based on 2D edge detection) obtained at different time-points. Being an indirect measure, atrophy rates are susceptible to variable segmentation errors at the edge of the spinal cord. To overcome those limitations, we developed a new registration-based pipeline that measures atrophy rates directly. We based our approach on the generalised boundary shift integral (GBSI) method, which registers 2 scans and uses a probabilistic XOR mask over the edge of the spinal cord, thereby measuring atrophy more accurately than segmentation-based techniques. Using a large cohort of longitudinal spinal cord images (610 subjects with multiple sclerosis from a multi-centre trial and 52 healthy controls), we demonstrated that GBSI is a sensitive, quantitative and objective measure of longitudinal spinal cord volume change. The GBSI pipeline is repeatable, reproducible, and provides more precise measurements of longitudinal spinal cord atrophy than segmentation-based methods in longitudinal spinal cord atrophy studies.
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256
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Karlsson A, Peolsson A, Elliott J, Romu T, Ljunggren H, Borga M, Dahlqvist Leinhard O. The relation between local and distal muscle fat infiltration in chronic whiplash using magnetic resonance imaging. PLoS One 2019; 14:e0226037. [PMID: 31805136 PMCID: PMC6894804 DOI: 10.1371/journal.pone.0226037] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 11/17/2019] [Indexed: 12/13/2022] Open
Abstract
The objective of this study was to investigate the relationship between fat infiltration in the cervical multifidi and fat infiltration measured in the lower extremities to move further into understanding the complex signs and symptoms arising from a whiplash trauma. Thirty-one individuals with chronic whiplash associated disorders, stratified into a mild/moderate group and a severe group, together with 31 age- and gender matched controls were enrolled in this study. Magnetic resonance imaging was used to acquire a 3D volume of the neck and of the whole-body. Cervical multifidi was used to represent muscles local to the whiplash trauma and all muscles below the hip joint, the lower extremities, were representing widespread muscles distal to the site of the trauma. The fat infiltration was determined by fat fraction in the segmented images. There was a linear correlation between local and distal muscle fat infiltration (p<0.001, r2 = 0.28). The correlation remained significant when adjusting for age and WAD group (p = 0.009) as well as when correcting for age, WAD group and BMI (p = 0.002). There was a correlation between local and distal muscle fat infiltration within the severe WAD group (p = 0.0016, r2 = 0.69) and in the healthy group (p = 0.022, r2 = 0.17) but not in the mild/moderate group (p = 0.29, r2 = 0.06). No significant differences (p = 0.11) in the lower extremities’ MFI between the different groups were found. The absence of differences between the groups in terms of lower extremities’ muscle fat infiltration indicates that, in this particular population, the whiplash trauma has a local effect on muscle fat infiltration rather than a generalized.
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Affiliation(s)
- Anette Karlsson
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- * E-mail:
| | - Anneli Peolsson
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Department of Medical and Health Sciences, Physiotherapy, Linköping University, Linköping, Sweden
| | - James Elliott
- Faculty of Health Sciences, The University of Sydney, Northern Sydney Local Health District, The Kolling Institute, St Leonards, NSW, Australia
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America
| | - Thobias Romu
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Helena Ljunggren
- Department of Medical and Health Sciences, Physiotherapy, Linköping University, Linköping, Sweden
| | - Magnus Borga
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
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257
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Freund P, Seif M, Weiskopf N, Friston K, Fehlings MG, Thompson AJ, Curt A. MRI in traumatic spinal cord injury: from clinical assessment to neuroimaging biomarkers. Lancet Neurol 2019; 18:1123-1135. [DOI: 10.1016/s1474-4422(19)30138-3] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 03/22/2019] [Accepted: 03/28/2019] [Indexed: 01/18/2023]
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258
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Saliani A, Zaimi A, Nami H, Duval T, Stikov N, Cohen-Adad J. Construction of a rat spinal cord atlas of axon morphometry. Neuroimage 2019; 202:116156. [PMID: 31491525 DOI: 10.1016/j.neuroimage.2019.116156] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 08/26/2019] [Accepted: 09/02/2019] [Indexed: 12/27/2022] Open
Abstract
Atlases of the central nervous system are essential for understanding the pathophysiology of neurological diseases, which remains one of the greatest challenges in neuroscience research today. These atlases provide insight into the underlying white matter microstructure and have been created from a variety of animal models, including rats. Although existing atlases of the rat spinal cord provide some details of axon microstructure, there is currently no histological dataset that quantifies axon morphometry exhaustively in the entire spinal cord. In this study, we created the first comprehensive rat spinal cord atlas of the white matter microstructure with quantifiable axon and myelin morphometrics. Using full-slice scanning electron microscopy images and state-of-the-art segmentation algorithms, we generated an atlas of microstructural metrics such as axon diameter, axonal density and g-ratio. After registering the Watson spinal cord white matter atlas to our template, we computed statistics across metrics, spinal levels and tracts. We notably found that g-ratio is relatively constant, whereas axon diameter showed the greatest variation. The atlas, data and full analysis code are freely available at: https://github.com/neuropoly/atlas-rat.
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Affiliation(s)
- Ariane Saliani
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.
| | - Aldo Zaimi
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Harris Nami
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Tanguy Duval
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Montreal Heart Institute, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, QC, Canada.
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259
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Smith ZA, Weber KA, Paliwal M, Hopkins BS, Barry AJ, Cantrell D, Ganju A, Koski TR, Parrish TB, Dhaher Y. Magnetic Resonance Imaging Atlas-Based Volumetric Mapping of the Cervical Cord Gray Matter in Cervical Canal Stenosis. World Neurosurg 2019; 134:e497-e504. [PMID: 31669690 DOI: 10.1016/j.wneu.2019.10.109] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/18/2019] [Accepted: 10/18/2019] [Indexed: 02/02/2023]
Abstract
BACKGROUND White matter volume loss may be an anatomic driver in the development of clinical symptoms in cervical spondylotic myelopathy (CSM). Considerably less attention has been devoted to gray matter (GM) injury. Newly developed atlas-based mapping techniques may allow evaluation of GM cord volume alterations in CSM. METHODS There were 29 subjects evaluated: 15 patients with CSM (61.1 ± 8.7 years old) and 14 age-matched control subjects (56.1 ± 5.3 years old). All subjects underwent 3T magnetic resonance imaging of the cervical spine. Post-processing with the Spinal Cord Toolbox (v3.0) provided GM volumetric analysis. Clinical scores collected included modified Japanese Orthopaedic Association, neck and arm numeric rating scales, Nurick Scale, and Neck Disability Index. All volumes were normalized to account for anatomic variability. RESULTS Normalized mean ventral GM volume in the compression region was significantly lower in patients compared with control subjects (1.103 ± 0.21 vs. 1.35 ± 0.32, P = 0.027). Normalized mean dorsal volume in the compression region was decreased in patients compared with control subjects (0.90 ± 0.17 vs. 1.04 ± 0.15, P = 0.049). GM volumes were associated with clinical scores, including Neck Disability Index, arm numeric rating scale, modified Japanese Orthopaedic Association, and Nurick Scale scores (P = 0.022, P = 0.004, P = 0.027, and P = 0.016). CONCLUSIONS GM volume loss may be evaluated through atlas-based post-processing techniques and may correlate with clinical symptoms in CSM.
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Affiliation(s)
- Zachary A Smith
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
| | - Kenneth A Weber
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, California, USA
| | - Monica Paliwal
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Benjamin S Hopkins
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | | | - Donald Cantrell
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Aruna Ganju
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tyler R Koski
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Todd B Parrish
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Yasin Dhaher
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Abstract
A wide range of medical devices have significant electronic components. Compared to open-source medical software, open (and open-source) electronic hardware has been less published in peer-reviewed literature. In this review, we explore the developments, significance, and advantages of using open platform electronic hardware for medical devices. Open hardware electronics platforms offer not just shorter development times, reduced costs, and customization; they also offer a key potential advantage which current commercial medical devices lack—seamless data sharing for machine learning and artificial intelligence. We explore how various electronic platforms such as microcontrollers, single board computers, field programmable gate arrays, development boards, and integrated circuits have been used by researchers to design medical devices. Researchers interested in designing low cost, customizable, and innovative medical devices can find references to various easily available electronic components as well as design methodologies to integrate those components for a successful design.
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Rasoanandrianina H, Massire A, Taso M, Guye M, Ranjeva JP, Kober T, Callot V. Regional T 1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence. NMR IN BIOMEDICINE 2019; 32:e4142. [PMID: 31393649 DOI: 10.1002/nbm.4142] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 05/20/2019] [Accepted: 06/18/2019] [Indexed: 06/10/2023]
Abstract
The recently-proposed MP2RAGE sequence was purposely optimized for cervical spinal cord imaging at 3T. Sequence parameters were chosen to optimize gray/white matter T1 contrast with sub-millimetric resolution and scan-time < 10 min while preserving reliable T1 determination with minimal B1+ variation effects within a range of values compatible with pathologies and surrounding structures. Results showed good agreements with IR-based measurements, high MP2RAGE-based T1 reproducibility and preliminary evidences of age- and tract-related T1 variations in the healthy spinal cord.
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Affiliation(s)
- Henitsoa Rasoanandrianina
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Aix-Marseille University, IFSTTAR, LBA UMR_T24, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Aurélien Massire
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Manuel Taso
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center & Harvard Medical School, Boston, Massachusetts, USA
| | - Maxime Guye
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Virginie Callot
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
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262
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Badhiwala JH, Ahuja CS, Fehlings MG. Time is spine: a review of translational advances in spinal cord injury. J Neurosurg Spine 2019; 30:1-18. [PMID: 30611186 DOI: 10.3171/2018.9.spine18682] [Citation(s) in RCA: 157] [Impact Index Per Article: 31.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 09/28/2018] [Indexed: 11/06/2022]
Abstract
Acute traumatic spinal cord injury (SCI) is a devastating event with far-reaching physical, emotional, and economic consequences for patients, families, and society at large. Timely delivery of specialized care has reduced mortality; however, long-term neurological recovery continues to be limited. In recent years, a number of exciting neuroprotective and regenerative strategies have emerged and have come under active investigation in clinical trials, and several more are coming down the translational pipeline. Among ongoing trials are RISCIS (riluzole), INSPIRE (Neuro-Spinal Scaffold), MASC (minocycline), and SPRING (VX-210). Microstructural MRI techniques have improved our ability to image the injured spinal cord at high resolution. This innovation, combined with serum and cerebrospinal fluid (CSF) analysis, holds the promise of providing a quantitative biomarker readout of spinal cord neural tissue injury, which may improve prognostication and facilitate stratification of patients for enrollment into clinical trials. Given evidence of the effectiveness of early surgical decompression and growing recognition of the concept that "time is spine," infrastructural changes at a systems level are being implemented in many regions around the world to provide a streamlined process for transfer of patients with acute SCI to a specialized unit. With the continued aging of the population, central cord syndrome is soon expected to become the most common form of acute traumatic SCI; characterization of the pathophysiology, natural history, and optimal treatment of these injuries is hence a key public health priority. Collaborative international efforts have led to the development of clinical practice guidelines for traumatic SCI based on robust evaluation of current evidence. The current article provides an in-depth review of progress in SCI, covering the above areas.
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Affiliation(s)
- Jetan H Badhiwala
- 1Division of Neurosurgery, Department of Surgery, and.,2Institute of Medical Science, University of Toronto; and
| | - Christopher S Ahuja
- 1Division of Neurosurgery, Department of Surgery, and.,2Institute of Medical Science, University of Toronto; and.,3Department of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Michael G Fehlings
- 1Division of Neurosurgery, Department of Surgery, and.,2Institute of Medical Science, University of Toronto; and.,3Department of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
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263
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Cadotte DW, Akbar MA, Fehlings MG, Stroman PW, Cohen-Adad J. What Has Been Learned from Magnetic Resonance Imaging Examination of the Injured Human Spinal Cord: A Canadian Perspective. J Neurotrauma 2019; 35:1942-1957. [PMID: 30074873 DOI: 10.1089/neu.2018.5903] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Magnetic resonance imaging (MRI) has transformed the way surgeons and researchers study and treat spinal cord injury. In this narrative review, we explore the historical context of imaging the human spinal cord and describe how MRI has evolved from providing the first visualization of the human spinal cord in the 1980s to a remarkable set of imaging tools today. The article focuses in particular on the role of Canadian researchers to this field. We begin by outlining the clinical context of traumatic injury to the human spinal cord and describe why current MRI standards fall short when it comes to treating this disabling condition. Parts 2 and 3 of this work explore an exciting and dramatic shift in the use of MRI technology to aid in our understanding and treatment of traumatic injury to the spinal cord. We explore the use of functional imaging (part 2) and structural imaging (part 3) and explore how these techniques have evolved, how they are used, and the challenges that we face for continued refinement and application to patients who live with the neurological and functional deficits caused by injury to the delicate spinal cord.
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Affiliation(s)
- David W Cadotte
- 1 University of Calgary Spine Program, Division of Neurosurgery, Department of Clinical Neurosciences, University of Calgary , Foothills Medical Centre, Calgary, Alberta, Canada
| | - M Ali Akbar
- 2 Department of Surgery, Division of Neurosurgery and Spinal Program, Toronto Western Hospital, University of Toronto , Toronto, Ontario, Canada
| | - Michael G Fehlings
- 2 Department of Surgery, Division of Neurosurgery and Spinal Program, Toronto Western Hospital, University of Toronto , Toronto, Ontario, Canada
| | - Patrick W Stroman
- 3 Centre for Neuroscience Studies, Queens University , Kingston, Ontario, Canada
| | - Julien Cohen-Adad
- 4 NeuroPoly Lab, Institute of Biomedical Engineering , Polytechnique Montreal, Montreal, Quebéc, Canada .,5 Functional Neuroimaging Unit, CRIUGM, Université de Montréal , Montreal, Quebéc, Canada
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264
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Kinany N, Pirondini E, Martuzzi R, Mattera L, Micera S, Van de Ville D. Functional imaging of rostrocaudal spinal activity during upper limb motor tasks. Neuroimage 2019; 200:590-600. [DOI: 10.1016/j.neuroimage.2019.05.036] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 05/12/2019] [Accepted: 05/13/2019] [Indexed: 11/25/2022] Open
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265
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Wilson JR, Badhiwala JH, Moghaddamjou A, Martin AR, Fehlings MG. Degenerative Cervical Myelopathy; A Review of the Latest Advances and Future Directions in Management. Neurospine 2019; 16:494-505. [PMID: 31476852 PMCID: PMC6790745 DOI: 10.14245/ns.1938314.157] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 08/26/2019] [Accepted: 08/26/2019] [Indexed: 01/23/2023] Open
Abstract
The assessment, diagnosis, operative and nonoperative management of degenerative cervical myelopathy (DCM) have evolved rapidly over the last 20 years. A clearer understanding of the pathobiology of DCM has led to attempts to develop objective measurements of the severity of myelopathy, including technology such as multiparametric magnetic resonance imaging, biomarkers, and ancillary clinical testing. New pharmacological treatments have the potential to alter the course of surgical outcomes, and greater innovation in surgical techniques have made surgery safer, more effective and less invasive. Future developments for the treatment of DCM will seek to improve the diagnostic accuracy of imaging, improve the objectivity of clinical assessment, and increase the use of surgical technology to ensure the best outcome is achieved for each individual patient.
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Affiliation(s)
- Jamie R.F. Wilson
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Spinal Program, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Jetan H. Badhiwala
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Spinal Program, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Ali Moghaddamjou
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Spinal Program, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Allan R. Martin
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Spinal Program, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Michael G. Fehlings
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Spinal Program, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
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266
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Tsagkas C, Horvath A, Altermatt A, Pezold S, Weigel M, Haas T, Amann M, Kappos L, Sprenger T, Bieri O, Cattin P, Parmar K. Automatic Spinal Cord Gray Matter Quantification: A Novel Approach. AJNR Am J Neuroradiol 2019; 40:1592-1600. [PMID: 31439628 DOI: 10.3174/ajnr.a6157] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 06/25/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND PURPOSE Currently, accurate and reproducible spinal cord GM segmentation remains challenging and a noninvasive broadly accepted reference standard for spinal cord GM measurements is still a matter of ongoing discussion. Our aim was to assess the reproducibility and accuracy of cervical spinal cord GM and WM cross-sectional area measurements using averaged magnetization inversion recovery acquisitions images and a fully-automatic postprocessing segmentation algorithm. MATERIALS AND METHODS The cervical spinal cord of 24 healthy subjects (14 women; mean age, 40 ± 11 years) was scanned in a test-retest fashion on a 3T MR imaging system. Twelve axial averaged magnetization inversion recovery acquisitions slices were acquired over a 48-mm cord segment. GM and WM were both manually segmented by 2 experienced readers and compared with an automatic variational segmentation algorithm with a shape prior modified for 3D data with a slice similarity prior. Precision and accuracy of the automatic method were evaluated using coefficients of variation and Dice similarity coefficients. RESULTS The mean GM area was 17.20 ± 2.28 mm2 and the mean WM area was 72.71 ± 7.55 mm2 using the automatic method. Reproducibility was high for both methods, while being better for the automatic approach (all mean automatic coefficients of variation, ≤4.77%; all differences, P < .001). The accuracy of the automatic method compared with the manual reference standard was excellent (mean Dice similarity coefficients: 0.86 ± 0.04 for GM and 0.90 ± 0.03 for WM). The automatic approach demonstrated similar coefficients of variation between intra- and intersession reproducibility as well as among all acquired spinal cord slices. CONCLUSIONS Our novel approach including the averaged magnetization inversion recovery acquisitions sequence and a fully-automated postprocessing segmentation algorithm demonstrated an accurate and reproducible spinal cord GM and WM segmentation. This pipeline is promising for both the exploration of longitudinal structural GM changes and application in clinical settings in disorders affecting the spinal cord.
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Affiliation(s)
- C Tsagkas
- From the Neurologic Clinic and Policlinic (C.T., M.A., L.K., T.S., K.P.), Department of Medicine and Biomedical Engineering.,Translational Imaging in Neurology Basel (C.T., A.A., M.A., M.W., L.K., K.P.), Department of Medicine and Biomedical Engineering.,Medical Image Analysis Center (C.T., A.A., M.A.), Basel, Switzerland
| | - A Horvath
- Department of Biomedical Engineering (A.H., A.A., S.P., M.W., O.B., P.C.), University of Basel, Allschwil, Switzerland
| | - A Altermatt
- Translational Imaging in Neurology Basel (C.T., A.A., M.A., M.W., L.K., K.P.), Department of Medicine and Biomedical Engineering.,Medical Image Analysis Center (C.T., A.A., M.A.), Basel, Switzerland.,Department of Biomedical Engineering (A.H., A.A., S.P., M.W., O.B., P.C.), University of Basel, Allschwil, Switzerland
| | - S Pezold
- Department of Biomedical Engineering (A.H., A.A., S.P., M.W., O.B., P.C.), University of Basel, Allschwil, Switzerland
| | - M Weigel
- Translational Imaging in Neurology Basel (C.T., A.A., M.A., M.W., L.K., K.P.), Department of Medicine and Biomedical Engineering.,Division of Radiological Physics (M.W., T.H., O.B.), Department of Radiology.,Department of Biomedical Engineering (A.H., A.A., S.P., M.W., O.B., P.C.), University of Basel, Allschwil, Switzerland
| | - T Haas
- Division of Radiological Physics (M.W., T.H., O.B.), Department of Radiology
| | - M Amann
- From the Neurologic Clinic and Policlinic (C.T., M.A., L.K., T.S., K.P.), Department of Medicine and Biomedical Engineering.,Translational Imaging in Neurology Basel (C.T., A.A., M.A., M.W., L.K., K.P.), Department of Medicine and Biomedical Engineering.,Division of Diagnostic and Interventional Neuroradiology (M.A.), Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland.,Medical Image Analysis Center (C.T., A.A., M.A.), Basel, Switzerland
| | - L Kappos
- From the Neurologic Clinic and Policlinic (C.T., M.A., L.K., T.S., K.P.), Department of Medicine and Biomedical Engineering.,Translational Imaging in Neurology Basel (C.T., A.A., M.A., M.W., L.K., K.P.), Department of Medicine and Biomedical Engineering
| | - T Sprenger
- From the Neurologic Clinic and Policlinic (C.T., M.A., L.K., T.S., K.P.), Department of Medicine and Biomedical Engineering.,Department of Neurology (T.S.), DKD HELIOS Klinik, Wiesbaden, Germany
| | - O Bieri
- Division of Radiological Physics (M.W., T.H., O.B.), Department of Radiology.,Department of Biomedical Engineering (A.H., A.A., S.P., M.W., O.B., P.C.), University of Basel, Allschwil, Switzerland
| | - P Cattin
- Department of Biomedical Engineering (A.H., A.A., S.P., M.W., O.B., P.C.), University of Basel, Allschwil, Switzerland
| | - K Parmar
- From the Neurologic Clinic and Policlinic (C.T., M.A., L.K., T.S., K.P.), Department of Medicine and Biomedical Engineering .,Translational Imaging in Neurology Basel (C.T., A.A., M.A., M.W., L.K., K.P.), Department of Medicine and Biomedical Engineering
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267
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Moccia M, Prados F, Filippi M, Rocca MA, Valsasina P, Brownlee WJ, Zecca C, Gallo A, Rovira A, Gass A, Palace J, Lukas C, Vrenken H, Ourselin S, Gandini Wheeler‐Kingshott CAM, Ciccarelli O, Barkhof F. Longitudinal spinal cord atrophy in multiple sclerosis using the generalized boundary shift integral. Ann Neurol 2019; 86:704-713. [DOI: 10.1002/ana.25571] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/29/2019] [Accepted: 08/01/2019] [Indexed: 11/10/2022]
Affiliation(s)
- Marcello Moccia
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College London London United Kingdom
- Multiple Sclerosis Clinical Care and Research Center, Department of NeurosciencesFederico II University Naples Italy
| | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College London London United Kingdom
- Centre for Medical Image Computing, Department of Medical Physics and BioengineeringUniversity College London London United Kingdom
- National Institute for Health ResearchUniversity College London Hospitals Biomedical Research Centre London United Kingdom
- Open University of Catalonia Barcelona Spain
| | - Massimo Filippi
- Division of Neuroscience, San Raffaele Scientific Institute, Vita‐Salute San Raffaele UniversityNeuroimaging Research Unit, Institute of Experimental Neurology Milan Italy
- Department of NeurologySan Raffaele Scientific Institute Milan Italy
| | - Maria A. Rocca
- Division of Neuroscience, San Raffaele Scientific Institute, Vita‐Salute San Raffaele UniversityNeuroimaging Research Unit, Institute of Experimental Neurology Milan Italy
- Department of NeurologySan Raffaele Scientific Institute Milan Italy
| | - Paola Valsasina
- Division of Neuroscience, San Raffaele Scientific Institute, Vita‐Salute San Raffaele UniversityNeuroimaging Research Unit, Institute of Experimental Neurology Milan Italy
| | - Wallace J. Brownlee
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College London London United Kingdom
| | - Chiara Zecca
- Neurocenter of Southern SwitzerlandLugano Regional Hospital Lugano Switzerland
| | - Antonio Gallo
- 3T‐MRI Research Center, Department of Advanced Medical and Surgical SciencesUniversity of Campania Luigi Vanvitelli Naples Italy
| | - Alex Rovira
- Section of Neuroradiology, Department of RadiologyVall d'Hebron University Hospital, Autonomous University of Barcelona Barcelona Spain
| | - Achim Gass
- Department of NeurologyUniversitätsmedizin Mannheim, University of Heidelberg Mannheim Germany
| | - Jacqueline Palace
- Nuffield Department of Clinical NeurosciencesJohn Radcliffe Hospital Oxford United Kingdom
| | | | - Hugo Vrenken
- Department of Radiology and Nuclear MedicineVU University Medical Center Amsterdam the Netherlands
| | - Sebastien Ourselin
- Department of Imaging and Biomedical EngineeringKing's College London London United Kingdom
| | - Claudia A. M. Gandini Wheeler‐Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College London London United Kingdom
- Department of Brain and Behavioral SciencesUniversity of Pavia Pavia Italy
- Brain MRI 3T Research Center, Mondino FoundationScientific Institute for Research and Health Care Pavia Italy
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College London London United Kingdom
- National Institute for Health ResearchUniversity College London Hospitals Biomedical Research Centre London United Kingdom
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College London London United Kingdom
- Centre for Medical Image Computing, Department of Medical Physics and BioengineeringUniversity College London London United Kingdom
- National Institute for Health ResearchUniversity College London Hospitals Biomedical Research Centre London United Kingdom
- Department of Radiology and Nuclear MedicineVU University Medical Center Amsterdam the Netherlands
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268
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van der Burgh HK, Westeneng HJ, Meier JM, van Es MA, Veldink JH, Hendrikse J, van den Heuvel MP, van den Berg LH. Cross-sectional and longitudinal assessment of the upper cervical spinal cord in motor neuron disease. NEUROIMAGE-CLINICAL 2019; 24:101984. [PMID: 31499409 PMCID: PMC6734179 DOI: 10.1016/j.nicl.2019.101984] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 08/12/2019] [Accepted: 08/13/2019] [Indexed: 11/28/2022]
Abstract
Background Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease characterized by both upper and lower motor neuron degeneration. While neuroimaging studies of the brain can detect upper motor neuron degeneration, these brain MRI scans also include the upper part of the cervical spinal cord, which offers the possibility to expand the focus also towards lower motor neuron degeneration. Here, we set out to investigate cross-sectional and longitudinal disease effects in the upper cervical spinal cord in patients with ALS, progressive muscular atrophy (PMA: primarily lower motor neuron involvement) and primary lateral sclerosis (PLS: primarily upper motor neuron involvement), and their relation to disease severity and grey and white matter brain measurements. Methods We enrolled 108 ALS patients without C9orf72 repeat expansion (ALS C9–), 26 ALS patients with C9orf72 repeat expansion (ALS C9+), 28 PLS patients, 56 PMA patients and 114 controls. During up to five visits, longitudinal T1-weighted brain MRI data were acquired and used to segment the upper cervical spinal cord (UCSC, up to C3) and individual cervical segments (C1 to C4) to calculate cross-sectional areas (CSA). Using linear (mixed-effects) models, the CSA differences were assessed between groups and correlated with disease severity. Furthermore, a relationship between CSA and brain measurements was examined in terms of cortical thickness of the precentral gyrus and white matter integrity of the corticospinal tract. Results Compared to controls, CSAs at baseline showed significantly thinner UCSC in all groups in the MND spectrum. Over time, ALS C9– patients demonstrated significant thinning of the UCSC and, more specifically, of segment C3 compared to controls. Progressive thinning over time was also observed in C1 of PMA patients, while ALS C9+ and PLS patients did not show any longitudinal changes. Longitudinal spinal cord measurements showed a significant relationship with disease severity and we found a significant correlation between spinal cord and motor cortex thickness or corticospinal tract integrity for PLS and PMA, but not for ALS patients. Discussion Our findings demonstrate atrophy of the upper cervical spinal cord in the motor neuron disease spectrum, which was progressive over time for all but PLS patients. Cervical spinal cord imaging in ALS seems to capture different disease effects than brain neuroimaging. Atrophy of the cervical spinal cord is therefore a promising additional biomarker for both diagnosis and disease progression and could help in the monitoring of treatment effects in future clinical trials. Atrophy of upper cervical spinal cord is shown in the motor neuron disease spectrum. Progressive cervical spinal cord thinning occurs over time for all but PLS patients. Cervical spinal cord imaging is a potential biomarker for disease progression in ALS.
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Affiliation(s)
- Hannelore K van der Burgh
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Henk-Jan Westeneng
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Jil M Meier
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Michael A van Es
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Jan H Veldink
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Jeroen Hendrikse
- Department of Radiology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam, The Netherlands.
| | - Leonard H van den Berg
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
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269
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Liu H, Ljungberg E, Dvorak AV, Lee LE, Yik JT, MacMillan EL, Barlow L, Li DKB, Traboulsee A, Kolind SH, Kramer JLK, Laule C. Myelin Water Fraction and Intra/Extracellular Water Geometric Mean T 2 Normative Atlases for the Cervical Spinal Cord from 3T MRI. J Neuroimaging 2019; 30:50-57. [PMID: 31407400 DOI: 10.1111/jon.12659] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 07/19/2019] [Accepted: 07/23/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND AND PURPOSE Acquiring and interpreting quantitative myelin-specific MRI data at an individual level is challenging because of technical difficulties and natural myelin variation in the population. To overcome these challenges, we used multiecho T2 myelin water imaging (MWI) to create T2 metric healthy population atlases that depict the mean and variation of myelin water fraction (MWF), and intra- and extracellular water mobility as described by geometric mean T2 (IEGMT2 ). METHODS Cervical cord MWI was performed at 3T on 20 healthy individuals (10M/10F, mean age: 36 years) and 3 relapsing remitting multiple sclerosis (RRMS) participants (1M/2F, age: 39/42/37 years). Anatomical data were collected for the purpose of image segmentation and registration. Atlases were created by coregistering and averaging T2 metrics from all controls. Voxel-wise z-score maps from 3 RRMS participants were produced to demonstrate the preliminary utility of the MWF and IEGMT2 atlases. RESULTS The average MWF atlas provides a representation of myelin in the spinal cord consistent with well-known spinal cord anatomical characteristics. The IEGMT2 atlas also depicted structural variations in the spinal cord. Z-score analysis illustrated distinct abnormalities in MWF and IEGMT2 in the 3 RRMS cases. CONCLUSIONS Our findings highlight the potential for using a quantitative T2 relaxation metric atlas to visualize and detect pathology in spinal cord. Our MWF and IEGMT2 atlases (URL: https://sourceforge.net/projects/mwi-spinal-cord-atlases/) can serve as normative references in the cervical spinal cord for other studies.
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Affiliation(s)
- Hanwen Liu
- Department of Physics & Astronomy, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada
| | - Emil Ljungberg
- Department of Neuroimaging, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK
| | - Adam V Dvorak
- Department of Physics & Astronomy, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada
| | - Lisa Eunyoung Lee
- Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Jackie T Yik
- Department of Physics & Astronomy, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada
| | - Erin L MacMillan
- Philips, Markham, Canada.,School of Mechatronic Systems Engineering, Simon Fraser University, Canada.,Department of Radiology, University of British Columbia, Vancouver, Canada
| | | | - David K B Li
- Department of Medicine, University of British Columbia, Vancouver, Canada.,Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Anthony Traboulsee
- Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Shannon H Kolind
- Department of Physics & Astronomy, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada.,Department of Medicine, University of British Columbia, Vancouver, Canada.,Department of Radiology, University of British Columbia, Vancouver, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada.,School of Kinesiology, University of British Columbia, Vancouver, Canada
| | - Cornelia Laule
- Department of Physics & Astronomy, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada.,Department of Radiology, University of British Columbia, Vancouver, Canada.,Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
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270
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Brainstem and spinal cord MRI identifies altered sensorimotor pathways post-stroke. Nat Commun 2019; 10:3524. [PMID: 31388003 PMCID: PMC6684621 DOI: 10.1038/s41467-019-11244-3] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 06/27/2019] [Indexed: 02/06/2023] Open
Abstract
Damage to the corticospinal tract is widely studied following unilateral subcortical stroke, whereas less is known about changes to other sensorimotor pathways. This may be due to the fact that many studies investigated morphological changes in the brain, where the majority of descending and ascending brain pathways are overlapping, and did not investigate the brainstem where they separate. Moreover, these pathways continue passing through separate regions in the spinal cord. Here, using a high-resolution structural MRI of both the brainstem and the cervical spinal cord, we were able to identify a number of microstructurally altered pathways, in addition to the corticospinal tract, post stroke. Moreover, decreases in ipsi-lesional corticospinal tract integrity and increases in contra-lesional medial reticulospinal tract integrity were correlated with motor impairment severity in individuals with stroke. There are few studies of structural changes in ascending and descending sensorimotor pathways after stroke, beyond the corticospinal tract, in the brain. Here the authors identify changes in white matter structure in brainstem and spinal cord following stroke, and show its relationship to motor impairment.
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271
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Weeda MM, Middelkoop SM, Steenwijk MD, Daams M, Amiri H, Brouwer I, Killestein J, Uitdehaag BMJ, Dekker I, Lukas C, Bellenberg B, Barkhof F, Pouwels PJW, Vrenken H. Validation of mean upper cervical cord area (MUCCA) measurement techniques in multiple sclerosis (MS): High reproducibility and robustness to lesions, but large software and scanner effects. NEUROIMAGE-CLINICAL 2019; 24:101962. [PMID: 31416017 PMCID: PMC6704046 DOI: 10.1016/j.nicl.2019.101962] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 07/12/2019] [Accepted: 07/26/2019] [Indexed: 11/15/2022]
Abstract
Introduction Atrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking. Methods Five methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3 T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3 T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations. Results In dataset A, MUCCA differed between MR machines (p < 0.001) and methods (p < 0.001) used, but not between scan sessions. With respect to MUCCA values, Xinapse JIM showed the highest within-scanner reproducibility (ICC absolute agreement = 0.995) while Xinapse JIM and SCT-PropSeg showed the highest between-scanner robustness (ICC consistency = 0.981 and 0.976, respectively). Reproducibility of segmentations between scan sessions was highest in Xinapse JIM and SCT-PropSeg segmentations (median SI ≥ 0.921), with a significant main effect of method (p < 0.001), but not of MR machine or subject group. In dataset B, SI with manual outlines did not differ between patients with or without cervical lesions for any of the segmentation methods (p > 0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p < 0.001). Highest volumetric and voxel wise agreement was obtained with Xinapse JIM (ICC absolute agreement = 0.940 and median SI = 0.962). Conclusion Although MUCCA is highly reproducible within a scanner for each individual measurement method, MUCCA differs between scanners and between methods. Cervical cord lesions do not affect MUCCA measurement performance. Mean upper cervical cord area (MUCCA) was obtained with five different methods. MUCCA was determined in a unique scan-rescan multi-vendor MR study. Reproducibility: MUCCA did not differ between scan-rescan images for any method. Robustness: MUCCA differed between methods and between scanners. Performance of MUCCA methods was not affected by the presence of lesions.
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Affiliation(s)
- M M Weeda
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands.
| | - S M Middelkoop
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - M D Steenwijk
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - location VUmc, Amsterdam, the Netherlands
| | - M Daams
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - H Amiri
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - I Brouwer
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - J Killestein
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - location VUmc, Amsterdam, the Netherlands
| | - B M J Uitdehaag
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - location VUmc, Amsterdam, the Netherlands
| | - I Dekker
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands; Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC - location VUmc, Amsterdam, the Netherlands
| | - C Lukas
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, St. Josef Hospital, Ruhr University, Bochum, Germany
| | - B Bellenberg
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, St. Josef Hospital, Ruhr University, Bochum, Germany
| | - F Barkhof
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - P J W Pouwels
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - H Vrenken
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
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272
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Barry RL, Smith SA. Measurement of T 2* in the human spinal cord at 3T. Magn Reson Med 2019; 82:743-748. [PMID: 30924198 PMCID: PMC6510624 DOI: 10.1002/mrm.27755] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 03/06/2019] [Accepted: 03/06/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE To measure the transverse relaxation time T2* in healthy human cervical spinal cord gray matter (GM) and white matter (WM) at 3T. METHODS Thirty healthy volunteers were recruited. Axial images were acquired using an averaged multi-echo gradient-echo (mFFE) T2*-weighted sequence with 5 echoes. We used the signal equation for an mFFE sequence with constant dephasing gradients after each echo to jointly estimate the spin density and T2* for each voxel. RESULTS No global difference in T2* was observed between all GM (41.3 ± 5.6 ms) and all WM (39.8 ± 5.4 ms). No significant differences were observed between left (43.2 ± 6.8 ms) and right (43.4 ± 5.5 ms) ventral GM, left (38.3 ± 6.1 ms) and right (38.6 ± 6.5 ms) dorsal GM, and left (39.4 ± 5.8 ms) and right (40.3 ± 5.8 ms) lateral WM. However, significant regional differences were observed between ventral (43.4 ± 5.7 ms) and dorsal (38.4 ± 6.0 ms) GM (p < 0.05), as well as between ventral (42.9 ± 6.5 ms) and dorsal (37.9 ± 6.2 ms) WM (p < 0.05). In analyses across slices, inferior T2* was longer than superior T2* in GM (44.7 ms vs. 40.1 ms; p < 0.01) and in WM (41.8 ms vs. 35.9 ms; p < 0.01). CONCLUSIONS Significant differences in T2* are observed between ventral and dorsal GM, ventral and dorsal WM, and superior and inferior GM and WM. There is no evidence for bilateral asymmetry in T2* in the healthy cord. These values of T2* in the spinal cord are notably lower than most reported values of T2* in the cortex.
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Affiliation(s)
- Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA,Department of Radiology, Harvard Medical School, Boston, MA, USA,Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
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273
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Atik AF, Calabrese E, Gramer R, Adil SM, Rahimpour S, Pagadala P, Johnson GA, Lad SP. Structural mapping with fiber tractography of the human cuneate fasciculus at microscopic resolution in cervical region. Neuroimage 2019; 196:200-206. [PMID: 30981859 DOI: 10.1016/j.neuroimage.2019.04.030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 02/04/2019] [Accepted: 04/08/2019] [Indexed: 11/30/2022] Open
Abstract
Human spinal white matter tract anatomy has been mapped using post mortem histological information with the help of molecular tracing studies in animal models. This study used 7 Tesla diffusion MR tractography on a human cadaver that was harvested 24 hours post mortem to evaluate cuneate fasciculus anatomy in cervical spinal cord. Based on this method, for the first time much more nuanced tractographic anatomy was used to investigate possible new routes for cuneate fasciculus in the posterior and lateral funiculus. Additionally, current molecular tracing studies were reviewed, and confirmatory data was presented along with our radiological results. Both studies confirm that upon entry to the spinal cord, upper cervical level tracts (C1-2-3) travel inside lateral funiculus and lower level tracts travel medially inside the posterior funiculus after entry at posterolateral sulcus which is different than traditional knowledge of having cuneate fasciculus tracts concentrated in the lateral part of posterior funiculus.
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Affiliation(s)
- Ahmet Fatih Atik
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA.
| | - Evan Calabrese
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Robert Gramer
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
| | - Syed M Adil
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
| | - Promila Pagadala
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
| | - G Allan Johnson
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Shivanand P Lad
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
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274
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Schilling KG, By S, Feiler HR, Box BA, O'Grady KP, Witt A, Landman BA, Smith SA. Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis. Neuroimage 2019; 201:116026. [PMID: 31326569 DOI: 10.1016/j.neuroimage.2019.116026] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 07/12/2019] [Accepted: 07/16/2019] [Indexed: 12/14/2022] Open
Abstract
Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven valuable in the brain, offering novel indices sensitive to the tissue microstructural environment in vivo on clinical MRI scanners. However, application, characterization, and validation of these models in the spinal cord remain relatively under-studied. In this study, we apply a diffusion "signal" model (diffusion tensor imaging, DTI) and two commonly implemented "microstructural" models (neurite orientation dispersion and density imaging, NODDI; spherical mean technique, SMT) in the human cervical spinal cord of twenty-one healthy controls. We first provide normative values of DTI, SMT, and NODDI indices in a number of white matter ascending and descending pathways, as well as various gray matter regions. We then aim to validate the sensitivity and specificity of these diffusion-derived contrasts by relating these measures to indices of the tissue microenvironment provided by a histological template. We find that DTI indices are sensitive to a number of microstructural features, but lack specificity. The microstructural models also show sensitivity to a number of microstructure features; however, they do not capture the specific microstructural features explicitly modelled. Although often regarded as a simple extension of the brain in the central nervous system, it may be necessary to re-envision, or specifically adapt, diffusion microstructural models for application to the human spinal cord with clinically feasible acquisitions - specifically, adjusting, adapting, and re-validating the modeling as it relates to both theory (i.e. relevant biology, assumptions, and signal regimes) and parameter estimation (for example challenges of acquisition, artifacts, and processing).
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Affiliation(s)
- Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Samantha By
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Haley R Feiler
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bailey A Box
- Vanderbilt University Institute of Imaging Science, 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
| | - Atlee Witt
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
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275
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Conrad BN, Barry RL, Rogers BP, Maki S, Mishra A, Thukral S, Sriram S, Bhatia A, Pawate S, Gore JC, Smith SA. Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord. Brain 2019; 141:1650-1664. [PMID: 29648581 DOI: 10.1093/brain/awy083] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 02/04/2018] [Indexed: 11/13/2022] Open
Abstract
Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.
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Affiliation(s)
- Benjamin N Conrad
- Neuroscience Graduate Program, Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Baxter P Rogers
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Satoshi Maki
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Saakshi Thukral
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Subramaniam Sriram
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Aashim Bhatia
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Siddharama Pawate
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John C Gore
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Seth A Smith
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
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276
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Seif M, Gandini Wheeler-Kingshott CA, Cohen-Adad J, Flanders AE, Freund P. Guidelines for the conduct of clinical trials in spinal cord injury: Neuroimaging biomarkers. Spinal Cord 2019; 57:717-728. [PMID: 31267015 PMCID: PMC6760553 DOI: 10.1038/s41393-019-0309-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 05/20/2019] [Accepted: 05/21/2019] [Indexed: 12/16/2022]
Abstract
Traumatic spinal cord injury (SCI) leads to immediate neuronal and axonal damage at the focal injury site and triggers secondary pathologic series of events resulting in sensorimotor and autonomic dysfunction below the level of injury. Although there is no cure for SCI, neuroprotective and regenerative therapies show promising results at the preclinical stage. There is a pressing need to develop non-invasive outcome measures that can indicate whether a candidate therapeutic agent or a cocktail of therapeutic agents are positively altering the underlying disease processes. Recent conventional MRI studies have quantified spinal cord lesion characteristics and elucidated their relationship between severity of injury to clinical impairment and recovery. Next to the quantification of the primary cord damage, quantitative MRI measures of spinal cord (rostrocaudally to the lesion site) and brain integrity have demonstrated progressive and specific neurodegeneration of afferent and efferent neuronal pathways. MRI could therefore play a key role to ultimately uncover the relationship between clinical impairment/recovery and injury-induced neurodegenerative changes in the spinal cord and brain. Moreover, neuroimaging biomarkers hold promises to improve clinical trial design and efficiency through better patient stratification. The purpose of this narrative review is therefore to propose a guideline of clinically available MRI sequences and their derived neuroimaging biomarkers that have the potential to assess tissue damage at the macro- and microstructural level after SCI. In this piece, we make a recommendation for the use of key MRI sequences-both conventional and advanced-for clinical work-up and clinical trials.
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Affiliation(s)
- Maryam Seif
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
| | - Claudia Am Gandini Wheeler-Kingshott
- Faculty of Brain Sciences, Queen Square MS Centre, UCL Queen Square Institute of Neurology, London, United Kingdom.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Adam E Flanders
- Regional Spinal Cord Injury Center of the Delaware Valley, Department of Radiology, Division of Neuroradiology, Thomas Jefferson University, 1087 Main Building, 132 South 10th Street, Philadelphia, PA, 19107, USA
| | - Patrick Freund
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland. .,Faculty of Brain Sciences, Queen Square MS Centre, UCL Queen Square Institute of Neurology, London, United Kingdom. .,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. .,Department of Neurology, University Hospital Zurich, Zurich, Switzerland.
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277
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Querin G, Bede P, El Mendili MM, Li M, Pélégrini-Issac M, Rinaldi D, Catala M, Saracino D, Salachas F, Camuzat A, Marchand-Pauvert V, Cohen-Adad J, Colliot O, Le Ber I, Pradat PF. Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study. Ann Neurol 2019; 86:158-167. [PMID: 31177556 DOI: 10.1002/ana.25520] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 06/03/2019] [Accepted: 06/06/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVE C9orf72 hexanucleotide repeats expansions account for almost half of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases. Recent imaging studies in asymptomatic C9orf72 carriers have demonstrated cerebral white (WM) and gray matter (GM) degeneration before the age of 40 years. The objective of this study was to characterize cervical spinal cord (SC) changes in asymptomatic C9orf72 hexanucleotide carriers. METHODS Seventy-two asymptomatic individuals were enrolled in a prospective study of first-degree relatives of ALS and FTD patients carrying the c9orf72 hexanucleotide expansion. Forty of them carried the pathogenic mutation (C9+ ). Each subject underwent quantitative cervical cord imaging. Structural GM and WM metrics and diffusivity parameters were evaluated at baseline and 18 months later. Data were analyzed in C9+ and C9- subgroups, and C9+ subjects were further stratified by age. RESULTS At baseline, significant WM atrophy was detected at each cervical vertebral level in C9+ subjects older than 40 years without associated changes in GM and diffusion tensor imaging parameters. At 18-month follow-up, WM atrophy was accompanied by significant corticospinal tract (CST) fractional anisotropy (FA) reductions. Intriguingly, asymptomatic C9+ subjects older than 40 years with family history of ALS (as opposed to FTD) also exhibited significant CST FA reduction at baseline. INTERPRETATION Cervical SC imaging detects WM atrophy exclusively in C9+ subjects older than 40 years, and progressive CST FA reductions can be identified on 18-month follow-up. Cervical SC magnetic resonance imaging readily captures presymptomatic pathological changes and disease propagation in c9orf72-associated conditions. ANN NEUROL 2019;86:158-167.
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Affiliation(s)
- Giorgia Querin
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Peter Bede
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Computational Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
| | - Mohamed Mounir El Mendili
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Menghan Li
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Mélanie Pélégrini-Issac
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Daisy Rinaldi
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Reference Center for Rare or Early Dementia, Pitié-Salpêtrière Hospital, Paris, France
| | - Martin Catala
- Department of Neurology, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Sorbonne University, National Center for Scientific Research Mixed Unit of Research 7622, National Institute of Health and Medical Research Accademic Research Unit 1156, Biology Institute Paris-Seine, Paris, France
| | - Dario Saracino
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - François Salachas
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France
| | - Agnes Camuzat
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - Véronique Marchand-Pauvert
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Julien Cohen-Adad
- NeuroPoly Laboratory, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,Functional Neuroimaging Unit, Research Center of the University Institute of Geriatrics of Montreal, University of Montreal, Montreal, Quebec, Canada
| | - Olivier Colliot
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Aramis Project Team, Inria Research Center of Paris, Paris, France.,Center for Image Acquisition and Processing, Brain and Spinal Cord Institute, Paris, France
| | - Isabelle Le Ber
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Reference Center for Rare or Early Dementia, Pitié-Salpêtrière Hospital, Paris, France.,Institute of Memory and Alzheimer's Disease, Center of Excellence of Neurodegenerative Disease, Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France
| | - Pierre-François Pradat
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, Clinical-Translational Research and Innovation Center, Altnagelvin Hospital, Londonderry, United Kingdom
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278
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Dvorak AV, Ljungberg E, Vavasour IM, Liu H, Johnson P, Rauscher A, Kramer JLK, Tam R, Li DKB, Laule C, Barlow L, Briemberg H, MacKay AL, Traboulsee A, Kozlowski P, Cashman N, Kolind SH. Rapid myelin water imaging for the assessment of cervical spinal cord myelin damage. NEUROIMAGE-CLINICAL 2019; 23:101896. [PMID: 31276928 PMCID: PMC6611998 DOI: 10.1016/j.nicl.2019.101896] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 06/08/2019] [Accepted: 06/11/2019] [Indexed: 12/13/2022]
Abstract
Background Rapid myelin water imaging (MWI) using a combined gradient and spin echo (GRASE) sequence can produce myelin specific metrics for the human brain. Spinal cord MWI could be similarly useful, but technical challenges have hindered routine application. GRASE rapid MWI was recently successfully implemented for imaging of healthy cervical spinal cord and may complement other advanced imaging methods, such as diffusion tensor imaging (DTI) and quantitative T1 (qT1). Objective To demonstrate the feasibility of cervical cord GRASE rapid MWI in multiple sclerosis (MS), primary lateral sclerosis (PLS) and neuromyelitis optica spectrum disorder (NMO), with comparison to DTI and qT1 metrics. Methods GRASE MWI, DTI and qT1 data were acquired in 2 PLS, 1 relapsing-remitting MS (RRMS), 1 primary-progressive MS (PPMS) and 2 NMO subjects, as well as 6 age (±3 yrs) and sex matched healthy controls (HC). Internal cord structure guided template registrations, used for region of interest (ROI) analysis. Z score maps were calculated for the difference between disease subject and mean HC metric values. Results PLS subjects had low myelin water fraction (MWF) in the lateral funiculi compared to HC. RRMS subject MWF was heterogeneous within the cord. The PPMS subject showed no trends in ROI results but had a region of low MWF Z score corresponding to a focal lesion. The NMO subject with a longitudinally extensive transverse myelitis lesion had low values for whole cord mean MWF of 12.8% compared to 24.3% (standard deviation 2.2%) for HC. The NMO subject without lesions also had low MWF compared to HC. DTI and qT1 metrics showed similar trends, corroborating the MWF results and providing complementary information. Conclusion GRASE is sufficiently sensitive to detect decreased myelin within MS spinal cord plaques, NMO lesions, and PLS diffuse spinal cord injury. Decreased MWF in PLS is consistent with demyelination secondary to motor neuron degeneration. GRASE MWI is a feasible method for rapid assessment of myelin content in the cervical spinal cord and provides complementary information to that of DTI and qT1 measures. Downstream myelin changes in motor tracts of primary lateral sclerosis spinal cord. Low myelin water fraction in multiple sclerosis and neuromyelitis optica cord lesions. Diffuse demyelination evidence in neuromyelitis optica normal-appearing white matter. Myelin water imaging provides complementary information to diffusion and T1 metrics.
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Affiliation(s)
- Adam V Dvorak
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada.
| | - Emil Ljungberg
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park PO89, London SE5 8AF, United Kingdom
| | - Irene M Vavasour
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada
| | - Hanwen Liu
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada
| | - Poljanka Johnson
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada
| | - Alexander Rauscher
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; Pediatrics, University of British Columbia, 4480 Oak Street BC Children's Hospital Vancouver, BC V6H 3V4, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; School of Kinesiology, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC V6T 1Z1, Canada
| | - Roger Tam
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; School of Biomedical Engineering, University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
| | - David K B Li
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Cornelia Laule
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; Pathology & Laboratory Medicine, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC V6T 2B5, Canada
| | - Laura Barlow
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Hannah Briemberg
- Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Alex L MacKay
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada
| | - Anthony Traboulsee
- Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Piotr Kozlowski
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Neil Cashman
- Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Shannon H Kolind
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
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279
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Chouteau R, Combès B, Bannier E, Snoussi H, Ferré JC, Barillot C, Edan G, Sauleau P, Kerbrat A. Joint assessment of brain and spinal cord motor tract damage in patients with early RRMS: predominant impact of spinal cord lesions on motor function. J Neurol 2019; 266:2294-2303. [PMID: 31175433 DOI: 10.1007/s00415-019-09419-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/30/2019] [Accepted: 06/01/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND In patients with MS, the effect of structural damage to the corticospinal tract (CST) has been separately evaluated in the brain and spinal cord (SC), even though a cumulative impact is suspected. OBJECTIVE To evaluate CST damages on both the cortex and cervical SC, and examine their relative associations with motor function, measured both clinically and by electrophysiology. METHODS We included 43 patients with early relapsing-remitting MS. Lesions were manually segmented on SC (axial T2*) and brain (3D FLAIR) scans. The CST was automatically segmented using an atlas (SC) or tractography (brain). Lesion volume fractions and diffusion parameters were calculated for SC, brain and CST. Central motor conduction time (CMCT) and triple stimulation technique amplitude ratio were measured for 42 upper limbs, from 22 patients. RESULTS Mean lesion volume fractions were 5.2% in the SC portion of the CST and 0.9% in the brain portion. We did not find a significant correlation between brain and SC lesion volume fraction (r = 0.06, p = 0.68). The pyramidal EDSS score and CMCT were both significantly correlated with the lesion fraction in the SC CST (r = 0.39, p = 0.01 and r = 0.33, p = 0.03), but not in the brain CST. CONCLUSION Our results highlight the major contribution of SC lesions to CST damage and motor function abnormalities.
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Affiliation(s)
- Raphaël Chouteau
- Neurology Department, CHU Rennes, Rennes, France.,Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France
| | - Benoit Combès
- Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France
| | - Elise Bannier
- Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France.,Radiology Department, CHU Rennes, Rennes, France
| | - Haykel Snoussi
- Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France
| | - Jean-Christophe Ferré
- Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France.,Radiology Department, CHU Rennes, Rennes, France
| | - Christian Barillot
- Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France
| | - Gilles Edan
- Neurology Department, CHU Rennes, Rennes, France.,Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France.,Plurithematic Clinical Investigation Center (CIC-P 1414), INSERM, Rennes, France
| | - Paul Sauleau
- Neurophysiology Department, CHU Rennes, Rennes, France.,Behavior and Basal Ganglia Research Unit (EA4712), Rennes 1 University, Rennes, France
| | - Anne Kerbrat
- Neurology Department, CHU Rennes, Rennes, France. .,Univ Rennes, CHU Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, VISAGES (Vision, Action Et Gestion Des Informations en santé), ERL U 1228, 35000, Rennes, France.
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280
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Vannesjo SJ, Clare S, Kasper L, Tracey I, Miller KL. A method for correcting breathing-induced field fluctuations in T2*-weighted spinal cord imaging using a respiratory trace. Magn Reson Med 2019; 81:3745-3753. [PMID: 30737825 PMCID: PMC6492127 DOI: 10.1002/mrm.27664] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 12/01/2018] [Accepted: 12/27/2018] [Indexed: 02/04/2023]
Abstract
PURPOSE Spinal cord MRI at ultrahigh field is hampered by time-varying magnetic fields associated with the breathing cycle, giving rise to ghosting artifacts in multi-shot acquisitions. Here, we suggest a correction approach based on linking the signal from a respiratory bellows to field changes inside the spinal cord. The information is used to correct the data at the image reconstruction level. METHODS The correction was demonstrated in the context of multi-shot T2*-weighted imaging of the cervical spinal cord at 7T. A respiratory trace was acquired during a high-resolution multi-echo gradient-echo sequence, used for structural imaging and quantitative T2* mapping, and a multi-shot EPI time series, as would be suitable for fMRI. The coupling between the trace and the breathing-induced fields was determined by a short calibration scan in each individual. Images were reconstructed with and without trace-based correction. RESULTS In the multi-echo acquisition, breathing-induced fields caused severe ghosting in images with long TE, which led to a systematic underestimation of T2* in the spinal cord. The trace-based correction reduced the ghosting and increased the estimated T2* values. Breathing-related ghosting was also observed in the multi-shot EPI images. The correction largely removed the ghosting, thereby improving the temporal signal-to-noise ratio of the time series. CONCLUSIONS Trace-based retrospective correction of breathing-induced field variations can reduce ghosting and improve quantitative metrics in multi-shot structural and functional T2*-weighted imaging of the spinal cord. The method is straightforward to implement and does not rely on sequence modifications or additional hardware beyond a respiratory bellows.
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Affiliation(s)
- S. Johanna Vannesjo
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Stuart Clare
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Lars Kasper
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurichSwitzerland
- Translational Neuromodeling Unit, Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurichSwitzerland
| | - Irene Tracey
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
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281
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Kaushal M, Shabani S, Budde M, Kurpad S. Diffusion Tensor Imaging in Acute Spinal Cord Injury: A Review of Animal and Human Studies. J Neurotrauma 2019; 36:2279-2286. [PMID: 30950317 DOI: 10.1089/neu.2019.6379] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Diffusion tensor imaging (DTI), based on the property of preferential diffusion of water molecules in biological tissue, is seeing increasing clinical application in the pathologies of the central nervous system. Spinal cord injury (SCI) is one such area where the use of DTI allows for the evaluation of changes to microstructure of the spinal cord not detected on routine conventional magnetic resonance imaging. The insights obtained from pre-clinical models of SCI indicate correlation of quantitative DTI indices with histology and function, which points to the potential of DTI as a non-invasive, viable biomarker for integrity of white matter tracts in the spinal cord. In this review, we describe DTI alterations in the acute phase of SCI in both animal models and human subjects and explore the underlying pathophysiology behind these changes.
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Affiliation(s)
- Mayank Kaushal
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Saman Shabani
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Matthew Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Shekar Kurpad
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
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282
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Moccia M, Ruggieri S, Ianniello A, Toosy A, Pozzilli C, Ciccarelli O. Advances in spinal cord imaging in multiple sclerosis. Ther Adv Neurol Disord 2019; 12:1756286419840593. [PMID: 31040881 PMCID: PMC6477770 DOI: 10.1177/1756286419840593] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 03/03/2019] [Indexed: 11/18/2022] Open
Abstract
The spinal cord is frequently affected in multiple sclerosis (MS), causing motor, sensory and autonomic dysfunction. A number of pathological abnormalities, including demyelination and neuroaxonal loss, occur in the MS spinal cord and are studied in vivo with magnetic resonance imaging (MRI). The aim of this review is to summarise and discuss recent advances in spinal cord MRI. Advances in conventional spinal cord MRI include improved identification of MS lesions, recommended spinal cord MRI protocols, enhanced recognition of MRI lesion characteristics that allow MS to be distinguished from other myelopathies, evidence for the role of spinal cord lesions in predicting prognosis and monitoring disease course, and novel post-processing methods to obtain lesion probability maps. The rate of spinal cord atrophy is greater than that of brain atrophy (-1.78% versus -0.5% per year), and reflects neuroaxonal loss in an eloquent site of the central nervous system, suggesting that it can become an important outcome measure in clinical trials, especially in progressive MS. Recent developments allow the calculation of spinal cord atrophy from brain volumetric scans and evaluation of its progression over time with registration-based techniques. Fully automated analysis methods, including segmentation of grey matter and intramedullary lesions, will facilitate the use of spinal cord atrophy in trial designs and observational studies. Advances in quantitative imaging techniques to evaluate neuroaxonal integrity, myelin content, metabolic changes, and functional connectivity, have provided new insights into the mechanisms of damage in MS. Future directions of research and the possible impact of 7T scanners on spinal cord imaging will be discussed.
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Affiliation(s)
- Marcello Moccia
- Queen Square MS Centre, NMR Research Unit, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences, Federico II University of Naples, via Sergio Pansini, 5, Edificio 17 - piano terra, Napoli, 80131 Naples, Italy
| | - Serena Ruggieri
- Department of Human Neuroscience, Sapienza University of Rome, Italy
| | - Antonio Ianniello
- Department of Human Neuroscience, Sapienza University of Rome, Italy
| | - Ahmed Toosy
- Queen Square MS Centre, NMR Research Unit, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Carlo Pozzilli
- Department of Human Neuroscience, Sapienza University of Rome, Italy
| | - Olga Ciccarelli
- Queen Square MS Centre, NMR Research Unit, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research, University College London Hospitals Biomedical Research Centre, London, UK
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283
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El Mendili MM, Querin G, Bede P, Pradat PF. Spinal Cord Imaging in Amyotrophic Lateral Sclerosis: Historical Concepts-Novel Techniques. Front Neurol 2019; 10:350. [PMID: 31031688 PMCID: PMC6474186 DOI: 10.3389/fneur.2019.00350] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 03/21/2019] [Indexed: 01/13/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease with no effective disease modifying therapies at present. Spinal cord degeneration is a hallmark feature of ALS, highlighted in the earliest descriptions of the disease by Lockhart Clarke and Jean-Martin Charcot. The anterior horns and corticospinal tracts are invariably affected in ALS, but up to recently it has been notoriously challenging to detect and characterize spinal pathology in vivo. With recent technological advances, spinal imaging now offers unique opportunities to appraise lower motor neuron degeneration, sensory involvement, metabolic alterations, and interneuron pathology in ALS. Quantitative spinal imaging in ALS has now been used in cross-sectional and longitudinal study designs, applied to presymptomatic mutation carriers, and utilized in machine learning applications. Despite its enormous clinical and academic potential, a number of physiological, technological, and methodological challenges limit the routine use of computational spinal imaging in ALS. In this review, we provide a comprehensive overview of emerging spinal cord imaging methods and discuss their advantages, drawbacks, and biomarker potential in clinical applications, clinical trial settings, monitoring, and prognostic roles.
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Affiliation(s)
- Mohamed Mounir El Mendili
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.,Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France
| | - Giorgia Querin
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France
| | - Peter Bede
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France.,Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Pierre-François Pradat
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France
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284
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Papinutto N, Henry RG. Evaluation of Intra- and Interscanner Reliability of MRI Protocols for Spinal Cord Gray Matter and Total Cross-Sectional Area Measurements. J Magn Reson Imaging 2019; 49:1078-1090. [PMID: 30198209 PMCID: PMC6620602 DOI: 10.1002/jmri.26269] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 07/04/2018] [Accepted: 07/05/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND In vivo quantification of spinal cord atrophy in neurological diseases using MRI has attracted increasing attention. PURPOSE To compare across different platforms the most promising imaging techniques to assess human spinal cord atrophy. STUDY TYPE Test/retest multiscanner study. SUBJECTS Twelve healthy volunteers. FIELD STRENGTH/SEQUENCE Three different 3T scanner platforms (Siemens, Philips, and GE) / optimized phase sensitive inversion recovery (PSIR), T1 -weighted (T1 -w), and T2 *-weighted (T2 *-w) protocols. ASSESSMENT On all images acquired, two operators assessed contrast-to-noise ratio (CNR) between gray matter (GM) and white matter (WM), and between WM and cerebrospinal fluid (CSF); one experienced operator measured total cross-sectional area (TCA) and GM area using JIM and the Spinal Cord Toolbox (SCT). STATISTICAL TESTS Coefficient of variation (COV); intraclass correlation coefficient (ICC); mixed effect models; analysis of variance (t-tests). RESULTS For all the scanners, GM/WM CNR was higher for PSIR than T2 *-w (P < 0.0001) and WM/CSF CNR for T1 -w was the highest (P < 0.0001). For TCA, using JIM, median COVs were smaller than 1.5% and ICC >0.95, while using SCT, median COVs were in the range 2.2-2.75% and ICC 0.79-0.95. For GM, despite some failures of the automatic segmentation, median COVs using SCT on T2 *-w were smaller than using JIM manual PSIR segmentations. In the mixed effect models, the subject was always the main contributor to the variance of area measurements and scanner often contributed to TCA variance (P < 0.05). Using JIM, TCA measurements on T2 *-w were different than on PSIR (P = 0.0021) and T1 -w (P = 0.0018), while using SCT, no notable differences were found between T1 -w and T2 *-w (P = 0.18). JIM and SCT-derived TCA were not different on T1 -w (P = 0.66), while they were different for T2 *-w (P < 0.0001). GM area derived using SCT/T2 *-w versus JIM/PSIR were different (P < 0.0001). DATA CONCLUSION The present work sets reference values for the magnitude of the contribution of different effects to cord area measurement intra- and interscanner variability. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;49:1078-1090.
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Affiliation(s)
- Nico Papinutto
- Department of NeurologyUniversity of California San Francisco94158San FranciscoCAUSA
| | - Roland G. Henry
- Department of NeurologyUniversity of California San Francisco94158San FranciscoCAUSA
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285
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McCoy DB, Dupont SM, Gros C, Cohen-Adad J, Huie RJ, Ferguson A, Duong-Fernandez X, Thomas LH, Singh V, Narvid J, Pascual L, Kyritsis N, Beattie MS, Bresnahan JC, Dhall S, Whetstone W, Talbott JF. Convolutional Neural Network-Based Automated Segmentation of the Spinal Cord and Contusion Injury: Deep Learning Biomarker Correlates of Motor Impairment in Acute Spinal Cord Injury. AJNR Am J Neuroradiol 2019; 40:737-744. [PMID: 30923086 DOI: 10.3174/ajnr.a6020] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 02/11/2019] [Indexed: 12/19/2022]
Abstract
BACKGROUND AND PURPOSE Our aim was to use 2D convolutional neural networks for automatic segmentation of the spinal cord and traumatic contusion injury from axial T2-weighted MR imaging in a cohort of patients with acute spinal cord injury. MATERIALS AND METHODS Forty-seven patients who underwent 3T MR imaging within 24 hours of spinal cord injury were included. We developed an image-analysis pipeline integrating 2D convolutional neural networks for whole spinal cord and intramedullary spinal cord lesion segmentation. Linear mixed modeling was used to compare test segmentation results between our spinal cord injury convolutional neural network (Brain and Spinal Cord Injury Center segmentation) and current state-of-the-art methods. Volumes of segmented lesions were then used in a linear regression analysis to determine associations with motor scores. RESULTS Compared with manual labeling, the average test set Dice coefficient for the Brain and Spinal Cord Injury Center segmentation model was 0.93 for spinal cord segmentation versus 0.80 for PropSeg and 0.90 for DeepSeg (both components of the Spinal Cord Toolbox). Linear mixed modeling showed a significant difference between Brain and Spinal Cord Injury Center segmentation compared with PropSeg (P < .001) and DeepSeg (P < .05). Brain and Spinal Cord Injury Center segmentation showed significantly better adaptability to damaged areas compared with PropSeg (P < .001) and DeepSeg (P < .02). The contusion injury volumes based on automated segmentation were significantly associated with motor scores at admission (P = .002) and discharge (P = .009). CONCLUSIONS Brain and Spinal Cord Injury Center segmentation of the spinal cord compares favorably with available segmentation tools in a population with acute spinal cord injury. Volumes of injury derived from automated lesion segmentation with Brain and Spinal Cord Injury Center segmentation correlate with measures of motor impairment in the acute phase. Targeted convolutional neural network training in acute spinal cord injury enhances algorithm performance for this patient population and provides clinically relevant metrics of cord injury.
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Affiliation(s)
- D B McCoy
- From the Departments of Radiology and Biomedical Imaging (D.B.M., S.M.D., J.N., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - S M Dupont
- From the Departments of Radiology and Biomedical Imaging (D.B.M., S.M.D., J.N., J.F.T.)
| | - C Gros
- NeuroPoly Lab (C.G., J.C.-A.), Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - J Cohen-Adad
- NeuroPoly Lab (C.G., J.C.-A.), Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - R J Huie
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - A Ferguson
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - X Duong-Fernandez
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - L H Thomas
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - V Singh
- Departments of Neurology (V.S.)
| | - J Narvid
- From the Departments of Radiology and Biomedical Imaging (D.B.M., S.M.D., J.N., J.F.T.)
| | - L Pascual
- Orthopedic Surgery (L.P.), Zuckerberg San Francisco General Hospital, University of California, San Francisco, San Francisco, California
| | - N Kyritsis
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - M S Beattie
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - J C Bresnahan
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - S Dhall
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - W Whetstone
- Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.).,Brain and Spinal Injury Center (D.B.M., R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W.)
| | - J F Talbott
- From the Departments of Radiology and Biomedical Imaging (D.B.M., S.M.D., J.N., J.F.T.) .,Neurological Surgery (R.J.H., A.F., X.D.-F., L.H.T., N.K., M.S.B., J.C.B., S.D., W.W., J.F.T.)
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286
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Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants. World Neurosurg 2019; 127:e436-e442. [PMID: 30922901 DOI: 10.1016/j.wneu.2019.03.165] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 03/14/2019] [Accepted: 03/15/2019] [Indexed: 11/21/2022]
Abstract
BACKGROUND Cervical spondylotic myelopathy (CSM) severity and presence of symptoms are often difficult to predict based simply on clinical imaging alone. Similarly, improved machine learning techniques provide new tools with immense clinical potential. METHODS A total of 14 patients with CSM and 14 controls underwent imaging of the cervical spine. Two different artificial neural network models were trained; 1) to predict CSM diagnosis; and 2) to predict CSM severity. Model 1 consisted of 6 inputs including 3 common imaging scales for the evaluation of cord compression, alongside 3 objective magnetic resonance imaging measurements. The outcome for model 1 was binary to predict CSM diagnosis. Model 2 consisted of 23 input variables derived from probabilistic volume mapping measurements of white matter tracts in the region of compression. The outcome of model 2 was linear, to predict the modified Japanese Orthopedic Association (mJOA) score. RESULTS Model 1 was used in predicting CSM. The mean cross-validated accuracy of the trained model was 86.50% (95% confidence interval, 85.16%-87.83%) with a median accuracy of 90.00%. Area under the curve (AUC) was calculated for each repetition. Average AUC for each repetition was 0.947 with a median AUC of 1.0. Average sensitivity, specificity, positive predictive value, and negative predictive value were 90.25%, 85.05%, 81.58%, and 91.94%, respectively. Model 2 was used in modeling mJOA. The mJOA model predicted scores, with a mean and median error of -0.29 mJOA points and -0.08 mJOA points, respectively, mean error per batch was 0.714 mJOA points. CONCLUSIONS Machine learning provides a promising method for prediction, diagnosis, and even prognosis in patients with CSM.
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287
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David G, Seif M, Huber E, Hupp M, Rosner J, Dietz V, Weiskopf N, Mohammadi S, Freund P. In vivo evidence of remote neural degeneration in the lumbar enlargement after cervical injury. Neurology 2019; 92:e1367-e1377. [PMID: 30770423 PMCID: PMC6511094 DOI: 10.1212/wnl.0000000000007137] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 11/07/2018] [Indexed: 01/14/2023] Open
Abstract
OBJECTIVE To characterize remote secondary neurodegeneration of spinal tracts and neurons below a cervical spinal cord injury (SCI) and its relation to the severity of injury, the integrity of efferent and afferent pathways, and clinical impairment. METHODS A comprehensive high-resolution MRI protocol was acquired in 17 traumatic cervical SCI patients and 14 controls at 3T. At the cervical lesion, a sagittal T2-weighted scan provided information on the width of preserved midsagittal tissue bridges. In the lumbar enlargement, high-resolution T2*-weighted and diffusion-weighted scans were used to calculate tissue-specific cross-sectional areas and diffusion indices, respectively. Regression analyses determined associations between MRI readouts and the electrophysiologic and clinical measures. RESULTS At the cervical injury level, preserved midsagittal tissue bridges were present in the majority of patients. In the lumbar enlargement, neurodegeneration-in terms of macrostructural and microstructural MRI changes-was evident in the white matter and ventral and dorsal horns. Patients with thinner midsagittal tissue bridges had smaller ventral horn area, higher radial diffusivity in the gray matter, smaller motor evoked potential amplitude from the lower extremities, and lower motor score. In addition, smaller width of midsagittal tissue bridges was also associated with smaller tibialis sensory evoked potential amplitude and lower light-touch score. CONCLUSIONS This study shows extensive tissue-specific cord pathology in infralesional spinal networks following cervical SCI, its magnitude relating to lesion severity, electrophysiologic integrity, and clinical impairment of the lower extremity. The clinical eloquence of remote neurodegenerative changes speaks to the application of neuroimaging biomarkers in diagnostic workup and planning of clinical trials.
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Affiliation(s)
- Gergely David
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maryam Seif
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Eveline Huber
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Markus Hupp
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Rosner
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Volker Dietz
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nikolaus Weiskopf
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Siawoosh Mohammadi
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Patrick Freund
- From the Spinal Cord Injury Center Balgrist (G.D., M.S., E.H., M.H., J.R., V.D., P.F.), University Hospital Zurich, University of Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging (N.W., S.M., P.F.), UCL Institute of Neurology, London, UK; Department of Neurophysics (M.S., N.W., P.F.), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig; and Department of Systems Neuroscience (S.M.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
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288
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Schmierer K, Miquel ME. Magnetic resonance imaging correlates of neuro-axonal pathology in the MS spinal cord. Brain Pathol 2019; 28:765-772. [PMID: 30375114 DOI: 10.1111/bpa.12648] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 07/18/2018] [Indexed: 12/21/2022] Open
Abstract
In people with multiple sclerosis (MS), the spinal cord is the structure most commonly affected by clinically detectable pathology at presentation, and a key part of the central nervous system involved in chronic disease deterioration. Indices, such as the spinal cord cross-sectional area at the level C2 have been developed as tools to predict future disability, and-by inference-axonal loss. However, this and other histo-pathological correlates of spinal cord magnetic resonance imaging (MRI) changes in MS remain incompletely understood. In recent years, there has been a surge of interest in developing quantitative MRI tools to measure specific tissue features, including axonal density, myelin content, neurite density, and orientation, among others, with an emphasis on the spinal cord. Quantitative MRI techniques including T1 and T2 , magnetization transfer and a number of diffusion-derived indices have all been applied to MS spinal cord. Particularly diffusion-based MRI techniques combined with microscopic resolution achievable using high magnetic field scanners enable a new level of anatomical detail and quantification of indices that are clinically meaningful.
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Affiliation(s)
- Klaus Schmierer
- Queen Mary University of London, Barts and The London School of Medicine & Dentistry, Blizard Institute (Neuroscience), London, UK.,Barts Health NHS Trust, Clinical Board Medicine (Neuroscience), The Royal London Hospital, London, UK
| | - Marc E Miquel
- Barts Health NHS Trust, Clinical Physics, London, UK
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289
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Martucci KT, Weber KA, Mackey SC. Altered Cervical Spinal Cord Resting-State Activity in Fibromyalgia. Arthritis Rheumatol 2019; 71:441-450. [PMID: 30281205 DOI: 10.1002/art.40746] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Accepted: 09/27/2018] [Indexed: 12/26/2022]
Abstract
OBJECTIVE Altered afferent input and central neural modulation are thought to contribute to fibromyalgia symptoms, and these processes converge within the spinal cord. We undertook this study to investigate the hypothesis that, using resting-state functional magnetic resonance imaging (rs-fMRI) of the cervical spinal cord, we would observe altered frequency-dependent activity in fibromyalgia. METHODS Cervical spinal cord rs-fMRI was conducted in fibromyalgia patients (n = 16) and healthy controls (n = 17). We analyzed the amplitude of low-frequency fluctuations (ALFF), a measure of low-frequency oscillatory power, for frequencies of 0.01-0.198 Hz and frequency sub-bands to determine regional and frequency-specific alterations in fibromyalgia. Functional connectivity and graph metrics were also analyzed. RESULTS As compared to healthy controls (n = 14), greater ventral and lesser dorsal mean ALFF of the cervical spinal cord was observed in fibromyalgia patients ( n = 15) (uncorrected P < 0.05) for frequencies of 0.01-0.198 Hz and all sub-bands. Additionally, lesser mean ALFF within the right dorsal quadrant (corrected P < 0.05) for frequencies of 0.01-0.198 Hz and sub-band frequencies of 0.073-0.198 Hz was observed in fibromyalgia. Regional mean ALFF was not correlated with pain; however, regional lesser mean ALFF was correlated with fatigue in patients (r = 0.763, P = 0.001). Functional connectivity and graph metrics were similar between groups. CONCLUSION Our results indicate unbalanced activity between the ventral and dorsal cervical spinal cord in fibromyalgia. Increased ventral neural processes and decreased dorsal neural processes may reflect the presence of central sensitization and contribute to fatigue and other bodily symptoms in fibromyalgia.
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Affiliation(s)
- Katherine T Martucci
- Stanford University, Stanford, California, and Duke University, Durham, North Carolina
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290
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Islam H, Law CSW, Weber KA, Mackey SC, Glover GH. Dynamic per slice shimming for simultaneous brain and spinal cord fMRI. Magn Reson Med 2019; 81:825-838. [PMID: 30284730 PMCID: PMC6649677 DOI: 10.1002/mrm.27388] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 05/10/2018] [Accepted: 05/13/2018] [Indexed: 12/11/2022]
Abstract
PURPOSE Simultaneous brain and spinal cord functional MRI is emerging as a new tool to study the central nervous system but is challenging. Poor B0 homogeneity and small size of the spinal cord are principal obstacles to this nascent technology. Here we extend a dynamic shimming approach, first posed by Finsterbusch, by shimming per slice for both the brain and spinal cord. METHODS We shim dynamically by a simple and fast optimization of linear field gradients and frequency offset separately for each slice in order to minimize off-resonance for both the brain and spinal cord. Simultaneous acquisition of brain and spinal cord fMRI is achieved with high spatial resolution in the spinal cord by means of an echo-planar RF pulse for reduced FOV. Brain slice acquisition is full FOV. RESULTS T2*-weighted images of brain and spinal cord are acquired with high clarity and minimal observable image artifacts. Fist-clenching fMRI experiments reveal task-consistent activation in motor cortices, cerebellum, and C6-T1 spinal segments. CONCLUSIONS High quality functional results are obtained for a sensory-motor task. Consistent activation in both the brain and spinal cord is observed at individual levels, not only at group level. Because reduced FOV excitation is applicable to any spinal cord section, future continuation of these methods holds great potential.
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Affiliation(s)
- Haisam Islam
- Department of Bioengineering, Stanford University, Stanford, California
| | - Christine S. W. Law
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, California
| | - Kenneth A. Weber
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, California
| | - Sean C. Mackey
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, California
| | - Gary H. Glover
- Department of Radiology, Stanford University, Stanford, California
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291
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Gros C, De Leener B, Badji A, Maranzano J, Eden D, Dupont SM, Talbott J, Zhuoquiong R, Liu Y, Granberg T, Ouellette R, Tachibana Y, Hori M, Kamiya K, Chougar L, Stawiarz L, Hillert J, Bannier E, Kerbrat A, Edan G, Labauge P, Callot V, Pelletier J, Audoin B, Rasoanandrianina H, Brisset JC, Valsasina P, Rocca MA, Filippi M, Bakshi R, Tauhid S, Prados F, Yiannakas M, Kearney H, Ciccarelli O, Smith S, Treaba CA, Mainero C, Lefeuvre J, Reich DS, Nair G, Auclair V, McLaren DG, Martin AR, Fehlings MG, Vahdat S, Khatibi A, Doyon J, Shepherd T, Charlson E, Narayanan S, Cohen-Adad J. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage 2019; 184:901-915. [PMID: 30300751 PMCID: PMC6759925 DOI: 10.1016/j.neuroimage.2018.09.081] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 09/05/2018] [Accepted: 09/28/2018] [Indexed: 12/12/2022] Open
Abstract
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework - robust to variability in both image parameters and clinical condition - for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n = 30). Data spanned three contrasts (T1-, T2-, and T2∗-weighted) for a total of 1943 vol and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p ≤ 0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.
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Affiliation(s)
- Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Atef Badji
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Dominique Eden
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Sara M. Dupont
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Jason Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Ren Zhuoquiong
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, P. R. China
| | - Yaou Liu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, P. R. China
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, P. R. China
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, USA
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, USA
| | | | | | | | - Lydia Chougar
- Juntendo University Hospital, Tokyo, Japan
- Hospital Cochin, Paris, France
| | - Leszek Stawiarz
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jan Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Elise Bannier
- CHU Rennes, Radiology Department
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages U1128, France
| | - Anne Kerbrat
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages U1128, France
- CHU Rennes, Neurology Department
| | - Gilles Edan
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages U1128, France
- CHU Rennes, Neurology Department
| | - Pierre Labauge
- MS Unit. DPT of Neurology. University Hospital of Montpellier
| | - Virginie Callot
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean Pelletier
- APHM, CHU Timone, CEMEREM, Marseille, France
- APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Bertrand Audoin
- APHM, CHU Timone, CEMEREM, Marseille, France
- APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | | | - Jean-Christophe Brisset
- Observatoire Français de la Sclérose en Plaques (OFSEP) ; Univ Lyon, Université Claude Bernard Lyon 1 ; Hospices Civils de Lyon ; CREATIS-LRMN, UMR 5220 CNRS & U 1044 INSERM ; Lyon, France
| | - Paola Valsasina
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A. Rocca
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Rohit Bakshi
- Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
| | - Shahamat Tauhid
- Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
| | - Ferran Prados
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London (UK)
- Center for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Marios Yiannakas
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London (UK)
| | - Hugh Kearney
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London (UK)
| | - Olga Ciccarelli
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London (UK)
| | | | | | - Caterina Mainero
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, USA
| | - Jennifer Lefeuvre
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Daniel S. Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | | | | | - Allan R. Martin
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Michael G. Fehlings
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Shahabeddin Vahdat
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
- Neurology Department, Stanford University, US
| | - Ali Khatibi
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
| | | | | | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
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292
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Shokur S, Donati ARC, Campos DSF, Gitti C, Bao G, Fischer D, Almeida S, Braga VAS, Augusto P, Petty C, Alho EJL, Lebedev M, Song AW, Nicolelis MAL. Training with brain-machine interfaces, visuo-tactile feedback and assisted locomotion improves sensorimotor, visceral, and psychological signs in chronic paraplegic patients. PLoS One 2018; 13:e0206464. [PMID: 30496189 PMCID: PMC6264837 DOI: 10.1371/journal.pone.0206464] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 10/12/2018] [Indexed: 01/05/2023] Open
Abstract
Spinal cord injury (SCI) induces severe deficiencies in sensory-motor and autonomic functions and has a significant negative impact on patients' quality of life. There is currently no systematic rehabilitation technique assuring recovery of the neurological impairments caused by a complete SCI. Here, we report significant clinical improvement in a group of seven chronic SCI patients (six AIS A, one AIS B) following a 28-month, multi-step protocol that combined training with non-invasive brain-machine interfaces, visuo-tactile feedback and assisted locomotion. All patients recovered significant levels of nociceptive sensation below their original SCI (up to 16 dermatomes, average 11 dermatomes), voluntary motor functions (lower-limbs muscle contractions plus multi-joint movements) and partial sensory function for several modalities (proprioception, tactile, pressure, vibration). Patients also recovered partial intestinal, urinary and sexual functions. By the end of the protocol, all patients had their AIS classification upgraded (six from AIS A to C, one from B to C). These improvements translated into significant changes in the patients' quality of life as measured by standardized psychological instruments. Reexamination of one patient that discontinued the protocol after 12 months of training showed that the 16-month break resulted in neurological stagnation and no reclassification. We suggest that our neurorehabilitation protocol, based uniquely on non-invasive technology (therefore necessitating no surgical operation), can become a promising therapy for patients diagnosed with severe paraplegia (AIS A, B), even at the chronic phase of their lesion.
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Affiliation(s)
- Solaiman Shokur
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
| | - Ana R. C. Donati
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
- Associação de Assistência à Criança Deficiente (AACD), São Paulo, Brazil
| | - Debora S. F. Campos
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
| | - Claudia Gitti
- Associação de Assistência à Criança Deficiente (AACD), São Paulo, Brazil
| | - Guillaume Bao
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
| | - Dora Fischer
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
- Associação de Assistência à Criança Deficiente (AACD), São Paulo, Brazil
| | - Sabrina Almeida
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
- Associação de Assistência à Criança Deficiente (AACD), São Paulo, Brazil
| | - Vania A. S. Braga
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
| | - Patricia Augusto
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
| | - Chris Petty
- Brain Imaging and Analysis Center, Duke Univ Medical Center, Durham, NC, United States of America
| | - Eduardo J. L. Alho
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
- Department of Neurosurgery, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Mikhail Lebedev
- Department of Neurobiology, Duke University Medical Center, Durham, NC, United States of America
- Duke Center for Neuroengineering, Duke University, Durham, NC, United States of America
| | - Allen W. Song
- Brain Imaging and Analysis Center, Duke Univ Medical Center, Durham, NC, United States of America
| | - Miguel A. L. Nicolelis
- Neurorehabilitation Laboratory, Associação Alberto Santos Dumont para Apoio à Pesquisa (AASDAP), São Paulo, Brazil
- Department of Neurobiology, Duke University Medical Center, Durham, NC, United States of America
- Duke Center for Neuroengineering, Duke University, Durham, NC, United States of America
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Neurology, Duke University, Durham, NC, United States of America
- Department of Neurosurgery, Duke University, Durham, NC, United States of America
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States of America
- Edmond and Lily Safra International Institute of Neuroscience, Macaíba, Brazil
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293
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Querin G, El Mendili MM, Lenglet T, Behin A, Stojkovic T, Salachas F, Devos D, Le Forestier N, Del Mar Amador M, Debs R, Lacomblez L, Meininger V, Bruneteau G, Cohen-Adad J, Lehéricy S, Laforêt P, Blancho S, Benali H, Catala M, Li M, Marchand-Pauvert V, Hogrel JY, Bede P, Pradat PF. The spinal and cerebral profile of adult spinal-muscular atrophy: A multimodal imaging study. NEUROIMAGE-CLINICAL 2018; 21:101618. [PMID: 30522974 PMCID: PMC6413472 DOI: 10.1016/j.nicl.2018.101618] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Revised: 11/17/2018] [Accepted: 11/26/2018] [Indexed: 12/13/2022]
Abstract
Spinal muscular atrophy (SMA) type III and IV are autosomal recessive, slowly progressive lower motor neuron syndromes. Nevertheless, wider cerebral involvement has been consistently reported in mouse models. The objective of this study is the characterisation of spinal and cerebral pathology in adult forms of SMA using multimodal quantitative imaging. Methods Twenty-five type III and IV adult SMA patients and 25 age-matched healthy controls were enrolled in a spinal cord and brain imaging study. Structural measures of grey and white matter involvement and diffusion parameters of white matter integrity were evaluated at each cervical spinal level. Whole-brain and region-of-interest analyses were also conducted in the brain to explore cortical thickness, grey matter density and tract-based white matter alterations. Results In the spinal cord, considerable grey matter atrophy was detected between C2-C6 vertebral levels. In the brain, increased grey matter density was detected in motor and extra-motor regions of SMA patients. No white matter pathology was identified neither at brain and spinal level. Conclusions Adult forms of SMA are associated with selective grey matter degeneration in the spinal cord with preserved white matter integrity. The observed increased grey matter density in the motor cortex may represent adaptive reorganisation. (SMA) type 3 and 4 is a lower motor neuron syndrome. Nevertheless, wider involvement of the nervous system might be possible. 25 adults type 3 and 4 SMA patients were studied using brain and cervical spinal cord neuroimaging techniques. Grey matter atrophy was observed in the spinal cord. No white matter degeneration was present at brain and spinal level. Increased grey matter density was detected in cerebral motor regions and explained as compensatory mechanism.
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Affiliation(s)
- Giorgia Querin
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - Mohamed-Mounir El Mendili
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; Icahn School of Medicine at Mount Sinai, Department of Neurology, New York, USA
| | - Timothée Lenglet
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; APHP, Hôpital Pitié-Salpêtriere, Service d'Explorations Fonctionnelles, Paris, France
| | - Anthony Behin
- APHP, Centre de Référence Maladies Neuromusculaires Paris-Est, Institut de Myologie, Hôpital Pitié-Salpêtrière, Paris, France
| | - Tanya Stojkovic
- APHP, Centre de Référence Maladies Neuromusculaires Paris-Est, Institut de Myologie, Hôpital Pitié-Salpêtrière, Paris, France
| | - François Salachas
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - David Devos
- Department of Neurology, ALS Centre, Lille University, INSERM UMRS_1171, University Hospital Centre, LICEND COEN Centre, Lille, France; Department of Medical Pharmacology, Lille University, INSERM UMRS_1171, University Hospital Centre, LICEND COEN Centre, Lille, France
| | - Nadine Le Forestier
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Département de recherche en éthique, EA 1610: Etudes des sciences et techniques, Université Paris Sud/Paris Saclay, Paris, France
| | - Maria Del Mar Amador
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Rabab Debs
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Lucette Lacomblez
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Vincent Meininger
- Hôpital des Peupliers, Ramsay Générale de Santé, F-75013 Paris, France
| | - Gaëlle Bruneteau
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
| | - Stéphane Lehéricy
- APHP, Hôpital Pitié-Salpêtriere, Service de Neuroradiologie, Paris, France; Sorbonne Université, UMR-S975, Inserm U975, CNRS UMR7225, Centre de recherche de l'Institut du Cerveau et de la Moelle épinière - CRICM, Centre de Neuroimagerie de Recherche - CENIR, Paris, France
| | - Pascal Laforêt
- Neurology Department, Nord/Est/Ile de France neuromuscular center, Raymond-Poincaré Hospital, Garches, France; INSERM U1179, END-ICAP, Versailles Saint-Quentin-en-Yvelines University, Montigny-le-Bretonneux
| | - Sophie Blancho
- Institut pour la Recherche sur la Moelle Epinière et l'Encéphale (IRME), Paris, France
| | - Habib Benali
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; Concordia University, PERFORM Centre, Electrical & Computer Engineering Division, Canada
| | - Martin Catala
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Sorbonne Université, CNRS UMR7622, INSERM ERL 1156, IBPS, Paris, France
| | - Menghan Li
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | | | - Jean-Yves Hogrel
- Institute of Myology, Neuromuscular Investigation Center, Paris, France
| | - Peter Bede
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Computational Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Ireland
| | - Pierre-François Pradat
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre référent SLA, Paris, France; Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute Ulster University, C-TRIC, Altnagelvin Hospital, Derry, Londonderry, United Kingdom.
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294
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Theme 8 Clinical imaging and electrophysiology. Amyotroph Lateral Scler Frontotemporal Degener 2018; 19:240-263. [DOI: 10.1080/21678421.2018.1510575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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295
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Motovylyak A, Skinner NP, Schmit BD, Wilkins N, Kurpad SN, Budde MD. Longitudinal In Vivo Diffusion Magnetic Resonance Imaging Remote from the Lesion Site in Rat Spinal Cord Injury. J Neurotrauma 2018; 36:1389-1398. [PMID: 30259800 DOI: 10.1089/neu.2018.5964] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Diffusion tensor imaging (DTI) has demonstrated success as a biomarker of spinal cord injury (SCI) severity as shown from numerous pre-clinical studies. However, artifacts from stabilization hardware at the lesion have precluded its use for longitudinal assessments. Previous research has documented ex vivo diffusion changes in the spinal cord both caudal and cranial to the injury epicenter. The aim of this study was to use a rat contusion model of SCI to evaluate the utility of in vivo cervical DTI after a thoracic injury. Forty Sprague-Dawley rats underwent a thoracic contusion (T8) of mild, moderate, severe, or sham severity. Magnetic resonance imaging (MRI) of the cervical cord was performed at 2, 30, and 90 days post-injury, and locomotor performance was assessed weekly using the Basso, Bresnahan, and Beattie (BBB) scoring scale. The relationships between BBB scores and MRI were assessed using region of interest analysis and voxel-wise linear regression of DTI, and free water elimination (FWE) modeling to reduce partial volume effects. At 90 days, axial diffusivity (ADFWE), mean diffusivity (MDFWE), and free water fraction (FWFFWE) using the FWE model were found to be significantly correlated with BBB score. FWE was found to be more predictive of injury severity than conventional DTI, specifically at later time-points. This study validated the use of FWE technique in spinal cord and demonstrated its sensitivity to injury remotely.
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Affiliation(s)
- Alice Motovylyak
- 1 Department of Biomedical Engineering, Marquette University/Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Nathan P Skinner
- 2 Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin.,3 Medical Scientist Training Program, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Brian D Schmit
- 1 Department of Biomedical Engineering, Marquette University/Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Natasha Wilkins
- 2 Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Shekar N Kurpad
- 2 Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Matthew D Budde
- 2 Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
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296
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A practical protocol for measurements of spinal cord functional connectivity. Sci Rep 2018; 8:16512. [PMID: 30410122 PMCID: PMC6224587 DOI: 10.1038/s41598-018-34841-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Accepted: 10/25/2018] [Indexed: 11/08/2022] Open
Abstract
Resting state functional magnetic resonance imaging (fMRI) has been used to study human brain function for over two decades, but only recently has this technique been successfully translated to the human spinal cord. The spinal cord is structurally and functionally unique, so resting state fMRI methods developed and optimized for the brain may not be appropriate when applied to the cord. This report therefore investigates the relative impact of different acquisition and processing choices (including run length, echo time, and bandpass filter width) on the detectability of resting state spinal cord networks at 3T. Our results suggest that frequencies beyond 0.08 Hz should be included in resting state analyses, a run length of ~8-12 mins is appropriate for reliable detection of the ventral (motor) network, and longer echo times - yet still shorter than values typically used for fMRI in the brain - may increase the detectability of the dorsal (sensory) network. Further studies are required to more fully understand and interpret the nature of resting state spinal cord networks in health and in disease, and the protocols described in this report are designed to assist such studies.
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297
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Combès B, Monteau L, Bannier E, Callot V, Labauge P, Ayrignac X, Carra Dallière C, Pelletier J, Maarouf A, de Seze J, Collongues N, Barillot C, Edan G, Ferré JC, Kerbrat A. Measurement of magnetization transfer ratio (MTR) from cervical spinal cord: Multicenter reproducibility and variability. J Magn Reson Imaging 2018; 49:1777-1785. [PMID: 30350328 DOI: 10.1002/jmri.26537] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 09/19/2018] [Accepted: 09/20/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Assessing the multicenter variability of magnetization transfer ratio (MTR) measurements in the spinal cord of healthy controls is the first step toward investigating its clinical use as a biomarker. PURPOSE To analyze the between-session, between-participant, and between-scanner variability of MTR measurements in automatically extracted regions of interest in the cervical cord of healthy controls. STUDY TYPE Control study. POPULATION Forty-four participants, distributed across five MRI scanners (all from the same manufacturer). Ten participants were scanned twice in the same scanner, and 10 others were scanned twice in two different scanners. FIELD STRENGTH/SEQUENCE 3D-gradient echo images, centered on C5, without and with magnetization transfer prepulse at 3T. ASSESSMENT We calculated the mean MTR for different vertebral levels in the whole cord (WC), as well as in the white matter and gray matter, and determined the between-session, between-participant, and between-scanner variabilities. STATISTICAL TESTS Coefficients of variation and intraclass correlations (ICCs) for the different variabilities and their associated confidence intervals. RESULTS The MTR measurements for Levels C4-C6 (near the slab center) exhibited a mean value in WC of 34.6 pu and a pooled standard deviation of 0.9 pu. The between-session coefficient of variation was estimated as 2.3% (ICC = 0.63), the between-participant coefficient as 1.6% (ICC = 0.32), and the between-scanner coefficient as 0.7% (ICC = 0.05). The resulting aggregate coefficient of variation was 2.9%, which was sufficiently low to detect an MTR reduction of 1 pu between groups of about 45 participants (Type-I error rate: 0.05; Type-II error rate: 0.10). DATA CONCLUSION The good between-scanner reproducibility and low overall variability in cervical spinal cord MTR measurements in a control population might pave the way for multicenter analyses in various neurological diseases with moderate cohort sizes. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1777-1785.
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Affiliation(s)
- Benoit Combès
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France
| | - Laureline Monteau
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France.,CHU Rennes, Radiology Department, F-35033, Rennes, France
| | - Elise Bannier
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France.,CHU Rennes, Radiology Department, F-35033, Rennes, France
| | - Virginie Callot
- AP-HM, Pôle d'imagerie médicale, Hôpital de la Timone, CEMEREM, Marseille, France.,Aix-Marseille Université, CNRS, UMR 7339, CRMBM, Marseille, France
| | | | | | | | - Jean Pelletier
- AP-HM, Pôle d'imagerie médicale, Hôpital de la Timone, CEMEREM, Marseille, France.,AP-HM, CHU Timone, Pole de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Adil Maarouf
- AP-HM, Pôle d'imagerie médicale, Hôpital de la Timone, CEMEREM, Marseille, France.,AP-HM, CHU Timone, Pole de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Jerome de Seze
- Strasbourg University Hospital, France; CIC Strasbourg INSERM 1434, Strasbourg, France
| | - Nicolas Collongues
- Strasbourg University Hospital, France; CIC Strasbourg INSERM 1434, Strasbourg, France
| | - Christian Barillot
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France
| | - Gilles Edan
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France.,Neurology Department, Rennes University Hospital, France
| | - Jean Christophe Ferré
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France.,CHU Rennes, Radiology Department, F-35033, Rennes, France
| | - Anne Kerbrat
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Visages, U1128, France.,Neurology Department, Rennes University Hospital, France
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298
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Abstract
STUDY DESIGN Case-control. OBJECTIVE The aim of this study was to understand the role of high-resolution magnetic resonance (MR) in identifying regional cord volume loss in cervical spondylotic myelopathy (CSM). SUMMARY OF BACKGROUND DATA Preliminary studies suggest that compression of the ventral region of the cord may contribute disproportionately to CSM symptomology; however, tract-specific data are lacking in the CSM population. The current study is the first to use 3T MR imaging (MRI) images of CSM patients to determine specific volume loss at the level of detail of individual descending white matter tracts. METHODS Twelve patients with CSM and 14 age-matched were enrolled prospectively and underwent 3-Tesla MRI of the cervical spine. Using the high-resolution images of the spinal cord, straightening and alignment with a template was performed and specific spinal cord tract volumes were measured using Spinal Cord Tool-box version 3.0.7. Modified Japanese orthopedic association (mJOA) and Nurick disability scores were collected in a prospective manner and were analyzed in relation to descending spinal tract volumes. RESULTS Having CSM was predicted by anterior/posterior diameter, eccentricity of the cord [odds ratio (OR) 0.000000621, P = 0.004], ventral reticulospinal tract volume (OR 1.167, P = 0.063), lateral corticospinal tract volume (OR 1.034, P = 0.046), rubrospinal tract volume (OR 1.072, P = 0.011), and ventrolateral reticulospinal tract volume (OR 1.474, P = 0.005) on single variable logistic regression. Single variable linear regression showed decreases in anterior/posterior spinal cord diameter (P = 0.022), ventral reticulospinal tract volumes (P = 0.007), and ventrolateral reticulospinal tract volumes (P = 0.017) to significantly predict worsening mJOA scores. Similarly, decreases in ventral reticulospinal tract volumes significantly predicted increasing Nurick scores (P = 0.039). CONCLUSION High-resolution 3T MRI can detect tract-specific volume loss in descending spinal cord tracts in CSM patients. Anterior/posterior spinal cord diameter, ventral reticulospinal tract, ventrolateral reticulospinal tract, lateral corticospinal tract, and rubrospinal tract volume loss are associated with CSM symptoms. LEVEL OF EVIDENCE 2.
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299
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Duval T, Saliani A, Nami H, Nanci A, Stikov N, Leblond H, Cohen-Adad J. Axons morphometry in the human spinal cord. Neuroimage 2018; 185:119-128. [PMID: 30326296 DOI: 10.1016/j.neuroimage.2018.10.033] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 10/05/2018] [Accepted: 10/10/2018] [Indexed: 12/15/2022] Open
Abstract
Due to the technical challenges of large-scale microscopy and analysis, to date only limited knowledge has been made available about axon morphometry (diameter, shape, myelin thickness, volume fraction), thereby limiting our understanding of neuronal microstructure and slowing down research on neurodegenerative pathologies. This study addresses this knowledge gap by establishing a state-of-the-art acquisition and analysis framework for mapping axon morphometry, and providing the first comprehensive mapping of axon morphometry in the human spinal cord. We dissected, fixed and stained a human spinal cord with osmium tetroxide, and used a scanning electron microscope to image the entirety of 23 axial slices, covering C1 to L5 spinal levels. An automatic method based on deep learning was then used to segment each axon and myelin sheath to produce maps of axon morphometry. These maps were then registered to a standard spinal cord magnetic resonance imaging (MRI) template. Between 500,000 (lumbar) and 1 million (cervical) myelinated axons were segmented at each level of this human spinal cord. Morphometric features show a large disparity between tracts, but high right-left symmetry. Our results suggest a modality-based organization of the dorsal column in the human, as it has been observed in the rat. The generated axon morphometry template is publicly available at https://osf.io/8k7jr/ and could be used as a reference for quantitative MRI studies. The proposed framework for axon morphometry mapping could be extended to other parts of the central or peripheral nervous system that exhibit coherently-oriented axons.
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Affiliation(s)
- Tanguy Duval
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Ariane Saliani
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Harris Nami
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Antonio Nanci
- Laboratory for the Study of Calcified Tissues and Biomaterials, Faculty of Dental Medicine, University of Montreal, Montreal, QC, Canada
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Montreal Heart Institute, Montreal, QC, Canada
| | - Hugues Leblond
- Anatomy department, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, QC, Canada.
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300
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Fouladivanda M, Kazemi K, Helfroush MS, Shakibafard A. Morphological active contour driven by local and global intensity fitting for spinal cord segmentation from MR images. J Neurosci Methods 2018; 308:116-128. [DOI: 10.1016/j.jneumeth.2018.07.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 07/18/2018] [Accepted: 07/18/2018] [Indexed: 10/28/2022]
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