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Kreiter DJ, van den Hurk J, Wiggins CJ, Hupperts RMM, Gerlach OHH. Ultra-high field spinal cord MRI in multiple sclerosis: Where are we standing? A literature review. Mult Scler Relat Disord 2021; 57:103436. [PMID: 34871855 DOI: 10.1016/j.msard.2021.103436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 11/18/2021] [Accepted: 11/27/2021] [Indexed: 12/24/2022]
Abstract
Magnetic resonance imaging (MRI) is a cornerstone in multiple sclerosis (MS) diagnostics and monitoring. Ultra-high field (UHF) MRI is being increasingly used and becoming more accessible. Due to the small diameter and mobility of the spinal cord, imaging this structure at ultra-high fields poses additional challenges compared to brain imaging. Here we review the potential benefits for the MS field by providing a literature overview of the use UHF spinal cord MRI in MS research and we elaborate on the challenges that are faced. Benefits include increased signal- and contrast-to-noise, enabling for higher spatial resolutions, which can improve MS lesion sensitivity in both the spinal white matter as well as grey matter. Additionally, these benefits can aid imaging of microstructural abnormalities in the spinal cord in MS using advanced MRI techniques like functional imaging, MR spectroscopy and diffusion-based techniques. Technical challenges include increased magnetic field inhomogeneities, distortions from physiological motion and optimalisation of sequences. Approaches including parallel imaging techniques, real time shimming and retrospective compensation of physiological motion are making it increasingly possible to unravel the potential of spinal cord UHF MRI in the context of MS research.
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Affiliation(s)
- Daniël J Kreiter
- Academic MS center Zuyderland, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands.
| | - Job van den Hurk
- Scannexus, Maastricht, The Netherlands; Maastricht University, Faculty of Health, Medicine & Life Sciences, Maastricht, The Netherlands
| | | | - Raymond M M Hupperts
- Academic MS center Zuyderland, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Oliver H H Gerlach
- Academic MS center Zuyderland, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands.
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2
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Sadeghi-Tarakameh A, Jungst S, Lanagan M, DelaBarre L, Wu X, Adriany G, Metzger GJ, Van de Moortele PF, Ugurbil K, Atalar E, Eryaman Y. A nine-channel transmit/receive array for spine imaging at 10.5 T: Introduction to a nonuniform dielectric substrate antenna. Magn Reson Med 2021; 87:2074-2088. [PMID: 34825735 DOI: 10.1002/mrm.29096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 11/04/2021] [Accepted: 11/05/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE The purpose of this study is to introduce a new antenna element with improved transmit performance, named the nonuniform dielectric substrate (NODES) antenna, for building transmit arrays at ultrahigh-field. METHODS We optimized a dipole antenna at 10.5 Tesla by maximizing the B 1 + -SAR efficiency in a phantom for a human spine target. The optimization parameters included permittivity variation in the substrate, substrate thickness, antenna length, and conductor geometry. We conducted electromagnetic simulations as well as phantom experiments to compare the transmit/receive performance of the proposed NODES antenna design with existing coil elements from the literature. RESULTS Single NODES element showed up to 18% and 30% higher B 1 + -SAR efficiency than the fractionated dipole and loop elements, respectively. The new element is substantially shorter than a commonly used dipole, which enables z-stacked array formation; it is additionally capable of providing a relatively uniform current distribution along its conductors. The nine-channel transmit/receive NODES array achieved 7.5% higher B 1 + homogeneity than a loop array with the same number of elements. Excitation with the NODES array resulted in 33% lower peak 10g-averaged SAR and required 34% lower input power than the loop array for the target anatomy of the spine. CONCLUSION In this study, we introduced a new RF coil element: the NODES antenna. NODES antenna outperformed the widely used loop and dipole elements and may provide improved transmit/receive performance for future ultrahigh field MRI applications.
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Affiliation(s)
- Alireza Sadeghi-Tarakameh
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA.,Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
| | - Steve Jungst
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
| | - Mike Lanagan
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Lance DelaBarre
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
| | - Xiaoping Wu
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
| | - Gregor Adriany
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
| | - Gregory J Metzger
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Kamil Ugurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
| | - Ergin Atalar
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
| | - Yigitcan Eryaman
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA
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3
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Ineichen BV, Beck ES, Piccirelli M, Reich DS. New Prospects for Ultra-High-Field Magnetic Resonance Imaging in Multiple Sclerosis. Invest Radiol 2021; 56:773-784. [PMID: 34120128 PMCID: PMC8505164 DOI: 10.1097/rli.0000000000000804] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 05/09/2021] [Accepted: 05/09/2021] [Indexed: 11/26/2022]
Abstract
ABSTRACT There is growing interest in imaging multiple sclerosis (MS) through the ultra-high-field (UHF) lens, which currently means a static magnetic field strength of 7 T or higher. Because of higher signal-to-noise ratio and enhanced susceptibility effects, UHF magnetic resonance imaging improves conspicuity of MS pathological hallmarks, among them cortical demyelination and the central vein sign. This could, in turn, improve confidence in MS diagnosis and might also facilitate therapeutic monitoring of MS patients. Furthermore, UHF imaging offers unique insight into iron-related pathology, leptomeningeal inflammation, and spinal cord pathologies in neuroinflammation. Yet, limitations such as the longer scanning times to achieve improved resolution and incipient safety data on implanted medical devices need to be considered. In this review, we discuss applications of UHF imaging in MS, its advantages and limitations, and practical aspects of UHF in the clinical setting.
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Affiliation(s)
- Benjamin V. Ineichen
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Erin S. Beck
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Daniel S. Reich
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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4
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Madsen MAJ, Wiggermann V, Bramow S, Christensen JR, Sellebjerg F, Siebner HR. Imaging cortical multiple sclerosis lesions with ultra-high field MRI. NEUROIMAGE-CLINICAL 2021; 32:102847. [PMID: 34653837 PMCID: PMC8517925 DOI: 10.1016/j.nicl.2021.102847] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/19/2021] [Accepted: 08/25/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Cortical lesions are abundant in multiple sclerosis (MS), yet difficult to visualize in vivo. Ultra-high field (UHF) MRI at 7 T and above provides technological advances suited to optimize the detection of cortical lesions in MS. PURPOSE To provide a narrative and quantitative systematic review of the literature on UHF MRI of cortical lesions in MS. METHODS A systematic search of all literature on UHF MRI of cortical lesions in MS published before September 2020. Quantitative outcome measures included cortical lesion numbers reported using 3 T and 7 T MRI and between 7 T MRI sequences, along with sensitivity of UHF MRI towards cortical lesions verified by histopathology. RESULTS 7 T MRI detected on average 52 ± 26% (mean ± 95% confidence interval) more cortical lesions than the best performing image contrast at 3 T, with the largest increase in type II-IV intracortical lesion detection. Across all studies, the mean cortical lesion number was 17 ± 6 per patient. In progressive MS cohorts, approximately four times more cortical lesions were reported than in CIS/early RRMS, and RRMS. Yet, there was no difference in lesion type ratio between these MS subtypes. Furthermore, superiority of one MRI sequence over another could not be established from available data. Post-mortem lesion detection with UHF MRI agreed only modestly with pathological examinations. Mean pro- and retrospective sensitivity was 33 ± 6% and 71 ± 10%, respectively, with the highest sensitivity towards type I and type IV lesions. CONCLUSION UHF MRI improves cortical lesion detection in MS considerably compared to 3 T MRI, particularly for type II-IV lesions. Despite modest sensitivity, 7 T MRI is still capable of visualizing all aspects of cortical lesion pathology and could potentially aid clinicians in diagnosing and monitoring MS, and progressive MS in particular. However, standardization of acquisition and segmentation protocols is needed.
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Affiliation(s)
- Mads A J Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark.
| | - Vanessa Wiggermann
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark
| | - Stephan Bramow
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Jeppe Romme Christensen
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Finn Sellebjerg
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital - Bispebjerg, Bispebjerg Bakke 23, 2400 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
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5
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Wattjes MP, Ciccarelli O, Reich DS, Banwell B, de Stefano N, Enzinger C, Fazekas F, Filippi M, Frederiksen J, Gasperini C, Hacohen Y, Kappos L, Li DKB, Mankad K, Montalban X, Newsome SD, Oh J, Palace J, Rocca MA, Sastre-Garriga J, Tintoré M, Traboulsee A, Vrenken H, Yousry T, Barkhof F, Rovira À. 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 2021; 20:653-670. [PMID: 34139157 DOI: 10.1016/s1474-4422(21)00095-8] [Citation(s) in RCA: 280] [Impact Index Per Article: 93.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 02/15/2021] [Accepted: 03/12/2021] [Indexed: 12/11/2022]
Abstract
The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.
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Affiliation(s)
- Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Olga Ciccarelli
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Brenda Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicola de Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria; Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jette Frederiksen
- Department of Neurology, Rigshospitalet Glostrup, University Hospital of Copenhagen, Glostrup, Denmark
| | - Claudio Gasperini
- Department of Neurology, San Camillo-Forlanini Hospital, Roma, Italy
| | - Yael Hacohen
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; Department of Paediatric Neurology, Great Ormond Street Hospital for Children, London, UK
| | - Ludwig Kappos
- Department of Neurology and Research Center for Clinical Neuroimmunology and Neuroscience, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Kshitij Mankad
- Department of Neuroradiology, Great Ormond Street Hospital for Children, London, UK
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain; Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Scott D Newsome
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jiwon Oh
- Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jaume Sastre-Garriga
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Anthony Traboulsee
- Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, London, UK; Neuroradiological Academic Unit, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands; Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain.
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6
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Tavaf N, Lagore RL, Jungst S, Gunamony S, Radder J, Grant A, Moeller S, Auerbach E, Ugurbil K, Adriany G, Van de Moortele PF. A self-decoupled 32-channel receive array for human-brain MRI at 10.5 T. Magn Reson Med 2021; 86:1759-1772. [PMID: 33780032 DOI: 10.1002/mrm.28788] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/02/2021] [Accepted: 03/07/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE Receive array layout, noise mitigation, and B0 field strength are crucial contributors to SNR and parallel-imaging performance. Here, we investigate SNR and parallel-imaging gains at 10.5 T compared with 7 T using 32-channel receive arrays at both fields. METHODS A self-decoupled 32-channel receive array for human brain imaging at 10.5 T (10.5T-32Rx), consisting of 31 loops and one cloverleaf element, was co-designed and built in tandem with a 16-channel dual-row loop transmitter. Novel receive array design and self-decoupling techniques were implemented. Parallel imaging performance, in terms of SNR and noise amplification (g-factor), of the 10.5T-32Rx was compared with the performance of an industry-standard 32-channel receiver at 7 T (7T-32Rx) through experimental phantom measurements. RESULTS Compared with the 7T-32Rx, the 10.5T-32Rx provided 1.46 times the central SNR and 2.08 times the peripheral SNR. Minimum inverse g-factor value of the 10.5T-32Rx (min[1/g] = 0.56) was 51% higher than that of the 7T-32Rx (min[1/g] = 0.37) with R = 4 × 4 2D acceleration, resulting in significantly enhanced parallel-imaging performance at 10.5 T compared with 7 T. The g-factor values of 10.5 T-32 Rx were on par with those of a 64-channel receiver at 7 T (eg, 1.8 vs 1.9, respectively, with R = 4 × 4 axial acceleration). CONCLUSION Experimental measurements demonstrated effective self-decoupling of the receive array as well as substantial gains in SNR and parallel-imaging performance at 10.5 T compared with 7 T.
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Affiliation(s)
- Nader Tavaf
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Russell L Lagore
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Steve Jungst
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Shajan Gunamony
- Center for Cognitive Neuroimaging, University of Glasgow, Glasgow, Scotland
| | - Jerahmie Radder
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Andrea Grant
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Edward Auerbach
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Gregor Adriany
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
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7
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Ouellette R, Treaba CA, Granberg T, Herranz E, Barletta V, Mehndiratta A, De Leener B, Tauhid S, Yousuf F, Dupont SM, Klawiter EC, Sloane JA, Bakshi R, Cohen-Adad J, Mainero C. 7 T imaging reveals a gradient in spinal cord lesion distribution in multiple sclerosis. Brain 2021; 143:2973-2987. [PMID: 32935834 DOI: 10.1093/brain/awaa249] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 06/03/2020] [Accepted: 06/29/2020] [Indexed: 12/11/2022] Open
Abstract
We used 7 T MRI to: (i) characterize the grey and white matter pathology in the cervical spinal cord of patients with early relapsing-remitting and secondary progressive multiple sclerosis; (ii) assess the spinal cord lesion spatial distribution and the hypothesis of an outside-in pathological process possibly driven by CSF-mediated immune cytotoxic factors; and (iii) evaluate the association of spinal cord pathology with brain burden and its contribution to neurological disability. We prospectively recruited 20 relapsing-remitting, 15 secondary progressive multiple sclerosis participants and 11 age-matched healthy control subjects to undergo 7 T imaging of the cervical spinal cord and brain as well as conventional 3 T brain acquisition. Cervical spinal cord imaging at 7 T was used to segment grey and white matter, including lesions therein. Brain imaging at 7 T was used to segment cortical and white matter lesions and 3 T imaging for cortical thickness estimation. Cervical spinal cord lesions were mapped voxel-wise as a function of distance from the inner central canal CSF pool to the outer subpial surface. Similarly, brain white matter lesions were mapped voxel-wise as a function of distance from the ventricular system. Subjects with relapsing-remitting multiple sclerosis showed a greater predominance of spinal cord lesions nearer the outer subpial surface compared to secondary progressive cases. Inversely, secondary progressive participants presented with more centrally located lesions. Within the brain, there was a strong gradient of lesion formation nearest the ventricular system that was most evident in participants with secondary progressive multiple sclerosis. Lesion fractions within the spinal cord grey and white matter were related to the lesion fraction in cerebral white matter. Cortical thinning was the primary determinant of the Expanded Disability Status Scale, white matter lesion fractions in the spinal cord and brain of the 9-Hole Peg Test and cortical thickness and spinal cord grey matter cross-sectional area of the Timed 25-Foot Walk. Spinal cord lesions were localized nearest the subpial surfaces for those with relapsing-remitting and the central canal CSF surface in progressive disease, possibly implying CSF-mediated pathogenic mechanisms in lesion development that may differ between multiple sclerosis subtypes. These findings show that spinal cord lesions involve both grey and white matter from the early multiple sclerosis stages and occur mostly independent from brain pathology. Despite the prevalence of cervical spinal cord lesions and atrophy, brain pathology seems more strongly related to physical disability as measured by the Expanded Disability Status Scale.
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Affiliation(s)
- Russell Ouellette
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Radiology, Karolinska University Hospital, Stockholm, Sweden
| | - Constantina A Treaba
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Tobias Granberg
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Radiology, Karolinska University Hospital, Stockholm, Sweden.,Harvard Medical School, Boston, MA, USA
| | - Elena Herranz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Valeria Barletta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Ambica Mehndiratta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Benjamin De Leener
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Shahamat Tauhid
- Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Boston, MA, USA
| | - Fawad Yousuf
- Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Boston, MA, USA
| | - Sarah M Dupont
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Eric C Klawiter
- Harvard Medical School, Boston, MA, USA.,Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Jacob A Sloane
- Harvard Medical School, Boston, MA, USA.,Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Rohit Bakshi
- Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Boston, MA, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
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8
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Sati P, Reich DS. 7 Tesla MRI will soon be helpful to guide clinical practice in multiple sclerosis centers - Commentary. Mult Scler 2021; 27:364-365. [PMID: 33404368 DOI: 10.1177/1352458520981738] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Pascal Sati
- Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
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9
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Gonzalez-Escamilla G, Ciolac D, De Santis S, Radetz A, Fleischer V, Droby A, Roebroeck A, Meuth SG, Muthuraman M, Groppa S. Gray matter network reorganization in multiple sclerosis from 7-Tesla and 3-Tesla MRI data. Ann Clin Transl Neurol 2020; 7:543-553. [PMID: 32255566 PMCID: PMC7187719 DOI: 10.1002/acn3.51029] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 03/13/2020] [Accepted: 03/13/2020] [Indexed: 12/21/2022] Open
Abstract
Objective The objective of this study was to determine the ability of 7T‐MRI for characterizing brain tissue integrity in early relapsing‐remitting MS patients compared to conventional 3T‐MRI and to investigate whether 7T‐MRI improves the performance for detecting cortical gray matter neurodegeneration and its associated network reorganization dynamics. Methods Seven early relapsing‐remitting MS patients and seven healthy individuals received MRI at 7T and 3T, whereas 30 and 40 healthy controls underwent separate 3T‐ and 7T‐MRI sessions, respectively. Surface‐based cortical thickness (CT) and gray‐to‐white contrast (GWc) measures were used to model morphometric networks, analyzed with graph theory by means of modularity, clustering coefficient, path length, and small‐worldness. Results 7T‐MRI had lower CT and higher GWc compared to 3T‐MRI in MS. CT and GWc measures robustly differentiated MS from controls at 3T‐MRI. 7T‐ and 3T‐MRI showed high regional correspondence for CT (r = 0.72, P = 2e‐78) and GWc (r = 0.83, P = 5.5e‐121) in MS patients. MS CT and GWc morphometric networks at 7T‐MRI showed higher modularity, clustering coefficient, and small‐worldness than 3T, also compared to controls. Interpretation 7T‐MRI allows to more precisely quantify morphometric alterations across the cortical mantle and captures more sensitively MS‐related network reorganization. Our findings open new avenues to design more accurate studies quantifying brain tissue loss and test treatment effects on tissue repair.
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Affiliation(s)
- Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | | | - Angela Radetz
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Amgad Droby
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Sven G Meuth
- Department of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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