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Kreiter D, Postma AA, Hupperts R, Gerlach O. Hallmarks of spinal cord pathology in multiple sclerosis. J Neurol Sci 2024; 456:122846. [PMID: 38142540 DOI: 10.1016/j.jns.2023.122846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023]
Abstract
A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement.
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Affiliation(s)
- Daniel Kreiter
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands.
| | - Alida A Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Raymond Hupperts
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Oliver Gerlach
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
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Dvorak AV, Kumar D, Zhang J, Gilbert G, Balaji S, Wiley N, Laule C, Moore GW, MacKay AL, Kolind SH. The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity. Sci Adv 2023; 9:eadh9853. [PMID: 37910622 PMCID: PMC10619933 DOI: 10.1126/sciadv.adh9853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications.
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Affiliation(s)
- Adam V. Dvorak
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Dushyant Kumar
- Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jing Zhang
- Global MR Applications & Workflow, GE HealthCare Canada, Mississauga, ON, Canada
| | | | - Sharada Balaji
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Neale Wiley
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - G.R. Wayne Moore
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Alex L. MacKay
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Shannon H. Kolind
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada
- Radiology, University of British Columbia, Vancouver, BC, Canada
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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3
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Combes AJ, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J.E. Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Corresponding author at: 1161 21st Ave S, MCN AA1105, Nashville, TN 37232, USA.
| | - Margareta A. Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P. O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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4
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Mehdizadeh N, Wilman AH. Myelin water fraction mapping from multiple echo spin echoes and an independent B 1 + map. Magn Reson Med 2022; 88:1380-1390. [PMID: 35576121 PMCID: PMC9321077 DOI: 10.1002/mrm.29286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 03/23/2022] [Accepted: 04/13/2022] [Indexed: 11/11/2022]
Abstract
Purpose Myelin water fraction (MWF) is often obtained from a multiple echo spin echo (MESE) sequence using multi‐component T2 fitting with non‐negative least squares. This process fits many unknowns including B1+ to produce a T2 spectrum for each voxel. Presented is an alternative using a rapid B1+ mapping sequence to supply B1+ for the MWF fitting procedure. Methods Effects of B1+ errors on MWF calculations were modeled for 2D and 3D MESE using Bloch and extended phase graph simulations, respectively. Variations in SNR and relative refocusing widths were tested. Human brain experiments at 3 T used 2D MESE and an independent B1+ map. MWF maps were produced with the standard approach and with the use of the independent B1+ map. Differences in B1+ and mean MWF in specific brain regions were compared. Results For 2D MESE, MWF with the standard method was strongly affected by B1+ misestimations arising from limited SNR and response asymmetry around 180°, which decreased with increasing relative refocusing width. Using an independent B1+ map increased mean MWF and decreased coefficient of variation. Notable differences in vivo in 2D MESE were in areas of high B1+ such as thalamus and splenium where mean MWF increased by 88% and 31%, respectively (P < 0.001). Simulations also demonstrated the advantages of this approach for 3D MESE when SNR is <500. Conclusion For 2D MESE, because of increased complexity of decay curves and limited SNR, supplying B1+ improves MWF results in peripheral and central brain regions where flip angles differ substantially from 180°.
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Affiliation(s)
- Nima Mehdizadeh
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
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5
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McDowell AR, Petrova N, Carassiti D, Miquel ME, Thomas DL, Barker GJ, Schmierer K, Wood TC. High-resolution quantitative MRI of multiple sclerosis spinal cord lesions. Magn Reson Med 2022; 87:2914-2921. [PMID: 35014736 PMCID: PMC9208576 DOI: 10.1002/mrm.29152] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE Validation of quantitative MR measures for myelin imaging in the postmortem multiple sclerosis spinal cord. METHODS Four fixed spinal cord samples were imaged first with a 3T clinical MR scanner to identify areas of interest for scanning, and then with a 7T small bore scanner using a multicomponent-driven equilibrium single-pulse observation of T1 and T2 protocol to produce apparent proton density, T1 , T2 , myelin water, intracellular water, and free-water fraction maps. After imaging, the cords were sectioned and stained with histological markers (hematoxylin and eosin, myelin basic protein, and neurofilament protein), which were quantitatively compared with the MR maps. RESULTS Excellent correspondence was found between high-resolution MR parameter maps and histology, particularly for apparent proton density MRI and myelin basic protein staining. CONCLUSION High-resolution quantitative MRI of the spinal cord provides biologically meaningful measures, and could be beneficial to diagnose and track multiple sclerosis lesions in the spinal cord.
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Affiliation(s)
- Amy R McDowell
- Queen Square Centre for Neuromuscular Diseases, UCL, London, United Kingdom
| | - Natalia Petrova
- The Blizard Institute (Neuroscience, Surgery & Trauma), Queen Mary University of London, Barts and The London School of Medicine & Dentistry, London, United Kingdom
| | - Daniele Carassiti
- The Blizard Institute (Neuroscience, Surgery & Trauma), Queen Mary University of London, Barts and The London School of Medicine & Dentistry, London, United Kingdom
| | - Marc E Miquel
- Clinical Physics, Barts Health NHS Trust, London, United Kingdom
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | | | - Klaus Schmierer
- The Blizard Institute (Neuroscience, Surgery & Trauma), Queen Mary University of London, Barts and The London School of Medicine & Dentistry, London, United Kingdom.,Clinical Board Medicine (Neuroscience), Barts Health NHS Trust, The Royal London Hospital, London, United Kingdom
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6
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Liu H, Joseph TS, Xiang QS, Tam R, Kozlowski P, Li DKB, MacKay AL, Kramer JLK, Laule C. A data-driven T 2 relaxation analysis approach for myelin water imaging: Spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS). Magn Reson Med 2021; 87:915-931. [PMID: 34490909 DOI: 10.1002/mrm.29000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 08/16/2021] [Accepted: 08/17/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE The decomposition of multi-exponential decay data into a T2 spectrum poses substantial challenges for conventional fitting algorithms, including non-negative least squares (NNLS). Based on a combination of the resolution limit constraint and machine learning neural network algorithm, a data-driven and highly tailorable analysis method named spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS) was proposed. THEORY AND METHODS The theory of SAME-ECOS was derived. Then, a paradigm was presented to demonstrate the SAME-ECOS workflow, consisting of a series of calculation, simulation, and model training operations. The performance of the trained SAME-ECOS model was evaluated using simulations and six in vivo brain datasets. The code is available at https://github.com/hanwencat/SAME-ECOS. RESULTS Using NNLS as the baseline, SAME-ECOS achieved over 15% higher overall cosine similarity scores in producing the T2 spectrum, and more than 10% lower mean absolute error in calculating the myelin water fraction (MWF), as well as demonstrated better robustness to noise in the simulation tests. Applying to in vivo data, MWF from SAME-ECOS and NNLS was highly correlated among all study participants. However, a distinct separation of the myelin water peak and the intra/extra-cellular water peak was only observed in the mean T2 spectra determined using SAME-ECOS. In terms of data processing speed, SAME-ECOS is approximately 30 times faster than NNLS, achieving a whole-brain analysis in 3 min. CONCLUSION Compared with NNLS, the SAME-ECOS method yields much more reliable T2 spectra in a dramatically shorter time, increasing the feasibility of multi-component T2 decay analysis in clinical settings.
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Affiliation(s)
- Hanwen Liu
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tigris S Joseph
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Qing-San Xiang
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roger Tam
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - Piotr Kozlowski
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex L MacKay
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Kinesiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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7
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Lee LE, Vavasour IM, Dvorak A, Liu H, Abel S, Johnson P, Ristow S, Au S, Laule C, Tam R, Li DK, Cross H, Ackermans N, Schabas AJ, Chan J, Sayao AL, Devonshire V, Carruthers R, Traboulsee A, Kolind S. Cervical cord myelin abnormality is associated with clinical disability in multiple sclerosis. Mult Scler 2021; 27:2191-2198. [PMID: 33749378 PMCID: PMC8597183 DOI: 10.1177/13524585211001780] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Myelin water imaging (MWI) was recently optimized to provide quantitative in vivo measurement of spinal cord myelin, which is critically involved in multiple sclerosis (MS) disability. OBJECTIVE To assess cervical cord myelin measurements in relapsing-remitting multiple sclerosis (RRMS) and progressive multiple sclerosis (ProgMS) participants and evaluate the correlation between myelin measures and clinical disability. METHODS We used MWI data from 35 RRMS, 30 ProgMS, and 28 healthy control (HC) participants collected at cord level C2/C3 on a 3 T magnetic resonance imaging (MRI) scanner. Myelin heterogeneity index (MHI), a measurement of myelin variability, was calculated for whole cervical cord, global white matter, dorsal column, lateral and ventral funiculi. Correlations were assessed between MHI and Expanded Disability Status Scale (EDSS), 9-Hole Peg Test (9HPT), timed 25-foot walk, and disease duration. RESULTS In various regions of the cervical cord, ProgMS MHI was higher compared to HC (between 9.5% and 31%, p ⩽ 0.04) and RRMS (between 13% and 26%, p ⩽ 0.02), and ProgMS MHI was associated with EDSS (r = 0.42-0.52) and 9HPT (r = 0.45-0.52). CONCLUSION Myelin abnormalities within clinically eloquent areas are related to clinical disability. MWI metrics have a potential role for monitoring subclinical disease progression and adjudicating treatment efficacy for new therapies targeting ProgMS.
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Affiliation(s)
- Lisa Eunyoung Lee
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Irene M Vavasour
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
| | - Adam Dvorak
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair and Discoveries, Vancouver, BC, Canada
| | - Hanwen Liu
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair and Discoveries, Vancouver, BC, Canada
| | - Shawna Abel
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Poljanka Johnson
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Stephen Ristow
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Shelly Au
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada; Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair and Discoveries, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Roger Tam
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
| | - David Kb Li
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada/Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
| | - Helen Cross
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Nathalie Ackermans
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alice J Schabas
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Jillian Chan
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Ana-Luiza Sayao
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Virginia Devonshire
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Robert Carruthers
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Shannon Kolind
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada; Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada; International Collaboration on Repair and Discoveries, Vancouver, BC, Canada
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8
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Bontempi P, Rozzanigo U, Amelio D, Scartoni D, Amichetti M, Farace P. Quantitative Multicomponent T2 Relaxation Showed Greater Sensitivity Than Flair Imaging to Detect Subtle Alterations at the Periphery of Lower Grade Gliomas. Front Oncol 2021; 11:651137. [PMID: 33828992 PMCID: PMC8019971 DOI: 10.3389/fonc.2021.651137] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 03/02/2021] [Indexed: 02/02/2023] Open
Abstract
Purpose To demonstrate that quantitative multicomponent T2 relaxation can be more sensitive than conventional FLAIR imaging for detecting cerebral tissue abnormalities. Methods Six patients affected by lower-grade non-enhancing gliomas underwent T2 relaxation and FLAIR imaging before a radiation treatment by proton therapy (PT) and were examined at follow-up. The T2 decay signal obtained by a thirty-two-echo sequence was decomposed into three main components, attributing to each component a different T2 range: water trapped in the lipid bilayer membrane of myelin, intra/extracellular water and cerebrospinal fluid. The T2 quantitative map of the intra/extracellular water was compared with FLAIR images. Results Before PT, in five patients a mismatch was observed between the intra/extracellular water T2 map and FLAIR images, with peri-tumoral areas of high T2 that typically extended outside the area of abnormal FLAIR hyper-intensity. Such mismatch regions evolved into two different types of patterns. The first type, observed in three patients, was a reduced extension of the abnormal regions on T2 map with respect to FLAIR images (T2 decrease pattern). The second type, observed in two patients, was the appearance of new areas of abnormal hyper-intensity on FLAIR images matching the anomalous T2 map extension (FLAIR increase pattern), that was considered as asymptomatic radiation induced damage. Conclusion Our preliminarily results suggest that quantitative T2 mapping of the intra/extracellular water component was more sensitive than conventional FLAIR imaging to subtle cerebral tissue abnormalities, deserving to be further investigated in future clinical studies.
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Affiliation(s)
- Pietro Bontempi
- Proton Therapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - Umberto Rozzanigo
- Radiology Department, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - Dante Amelio
- Proton Therapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - Daniele Scartoni
- Proton Therapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - Maurizio Amichetti
- Proton Therapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - Paolo Farace
- Proton Therapy Unit, Hospital of Trento, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
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9
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Bagnato F, Gauthier SA, Laule C, Moore GRW, Bove R, Cai Z, Cohen-Adad J, Harrison DM, Klawiter EC, Morrow SA, Öz G, Rooney WD, Smith SA, Calabresi PA, Henry RG, Oh J, Ontaneda D, Pelletier D, Reich DS, Shinohara RT, Sicotte NL. Imaging Mechanisms of Disease Progression in Multiple Sclerosis: Beyond Brain Atrophy. J Neuroimaging 2021; 30:251-266. [PMID: 32418324 DOI: 10.1111/jon.12700] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 02/04/2020] [Accepted: 02/18/2020] [Indexed: 12/11/2022] Open
Abstract
Clinicians involved with different aspects of the care of persons with multiple sclerosis (MS) and scientists with expertise on clinical and imaging techniques convened in Dallas, TX, USA on February 27, 2019 at a North American Imaging in Multiple Sclerosis Cooperative workshop meeting. The aim of the workshop was to discuss cardinal pathobiological mechanisms implicated in the progression of MS and novel imaging techniques, beyond brain atrophy, to unravel these pathologies. Indeed, although brain volume assessment demonstrates changes linked to disease progression, identifying the biological mechanisms leading up to that volume loss are key for understanding disease mechanisms. To this end, the workshop focused on the application of advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging techniques to assess and measure disease progression in both the brain and the spinal cord. Clinical translation of quantitative MRI was recognized as of vital importance, although the need to maintain a relatively short acquisition time mandated by most radiology departments remains the major obstacle toward this effort. Regarding PET, the panel agreed upon its utility to identify ongoing pathological processes. However, due to costs, required expertise, and the use of ionizing radiation, PET was not considered to be a viable option for ongoing care of persons with MS. Collaborative efforts fostering robust study designs and imaging technique standardization across scanners and centers are needed to unravel disease mechanisms leading to progression and discovering medications halting neurodegeneration and/or promoting repair.
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Affiliation(s)
- Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
| | - Susan A Gauthier
- Judith Jaffe Multiple Sclerosis Center, Department of Neurology, Feil Family Brain and Mind Institute, and Department of Radiology, Weill Cornell Medicine, New York, NY
| | - Cornelia Laule
- Department of Radiology, Pathology, and Laboratory Medicine, Department of Physics and Astronomy, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - George R Wayne Moore
- Department of Pathology and Laboratory Medicine, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - Riley Bove
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA
| | - Zhengxin Cai
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, CT
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal and Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada
| | - Daniel M Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD
| | - Eric C Klawiter
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Sarah A Morrow
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
| | - Gülin Öz
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN
| | - William D Rooney
- Advanced Imaging Research Center, Departments of Biomedical Engineering, Neurology, and Behavioral Neuroscience, Oregon Health & Science University, Portland, OR
| | - Seth A Smith
- Radiology and Radiological Sciences and Vanderbilt University Imaging Institute, Vanderbilt University Medical Center, and Biomedical Engineering, Vanderbilt University, Nashville, TN
| | - Peter A Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Roland G Henry
- Departments of Neurology, Radiology and Biomedical Imaging, and the UC San Francisco & Berkeley Bioengineering Graduate Group, University of California San Francisco, San Francisco, CA
| | - Jiwon Oh
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD.,Division of Neurology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Daniel Pelletier
- Department of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA
| | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
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- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN
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10
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Dvorak AV, Ljungberg E, Vavasour IM, Lee LE, Abel S, Li DKB, Traboulsee A, MacKay AL, Kolind SH. Comparison of multi echo T 2 relaxation and steady state approaches for myelin imaging in the central nervous system. Sci Rep 2021; 11:1369. [PMID: 33446710 PMCID: PMC7809349 DOI: 10.1038/s41598-020-80585-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 12/22/2020] [Indexed: 12/11/2022] Open
Abstract
The traditional approach for measuring myelin-associated water with quantitative magnetic resonance imaging (MRI) uses multi-echo T2 relaxation data to calculate the myelin water fraction (MWF). A fundamentally different approach, abbreviated “mcDESPOT”, uses a more efficient steady-state acquisition to generate an equivalent metric (fM). Although previous studies have demonstrated inherent instability and bias in the complex mcDESPOT analysis procedure, fM has often been used as a surrogate for MWF. We produced and compared multivariate atlases of MWF and fM in healthy human brain and cervical spinal cord (available online) and compared their ability to detect multiple sclerosis pathology. A significant bias was found in all regions (p < 10–5), albeit reversed for spinal cord (fM-MWF = − 3.4%) compared to brain (+ 6.2%). MWF and fM followed an approximately linear relationship for regions with MWF < ~ 10%. For MWF > ~ 10%, the relationship broke down and fM no longer increased in tandem with MWF. For multiple sclerosis patients, MWF and fM Z score maps showed overlapping areas of low Z score and similar trends between patients and brain regions, although those of fM generally had greater spatial extent and magnitude of severity. These results will guide future choice of myelin-sensitive quantitative MRI and improve interpretation of studies using either myelin imaging approach.
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Affiliation(s)
- Adam V Dvorak
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada. .,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.
| | - Emil Ljungberg
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Irene M Vavasour
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Lisa Eunyoung Lee
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Shawna Abel
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - David K B Li
- Radiology, University of British Columbia, Vancouver, BC, Canada.,Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Alex L MacKay
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Shannon H Kolind
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada.,Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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11
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van der Weijden CWJ, García DV, Borra RJH, Thurner P, Meilof JF, van Laar PJ, Dierckx RAJO, Gutmann IW, de Vries EFJ. Myelin quantification with MRI: A systematic review of accuracy and reproducibility. Neuroimage 2020; 226:117561. [PMID: 33189927 DOI: 10.1016/j.neuroimage.2020.117561] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 10/27/2020] [Accepted: 11/07/2020] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVES Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods. METHODS Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies. RESULTS The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R2=0.54 (SD=0.30) for animal studies, and R2=0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R2=0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51). CONCLUSIONS Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet.
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Affiliation(s)
- Chris W J van der Weijden
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.
| | - David Vállez García
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.
| | - Ronald J H Borra
- Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.
| | - Patrick Thurner
- Universitätsklinik für Radiologie und Nuklearmedizin, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090 Wien, Austria.
| | - Jan F Meilof
- Multiple Sclerosis Center Noord Nederland, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.
| | - Peter-Jan van Laar
- Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands; Department of Radiology, Zorggroep Twente, Zilvermeeuw 1, 7609 PP Almelo, the Netherlands.
| | - Rudi A J O Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.
| | - Ingomar W Gutmann
- Physics of Functional Material, Faculty of Physics, University of Vienna, Boltzmanngasse 5, 1090 Vienna, Austria.
| | - Erik F J de Vries
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands.
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12
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Grussu F, Battiston M, Veraart J, Schneider T, Cohen-Adad J, Shepherd TM, Alexander DC, Fieremans E, Novikov DS, Gandini Wheeler-Kingshott CAM. Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising. Neuroimage 2020; 217:116884. [PMID: 32360689 PMCID: PMC7378937 DOI: 10.1016/j.neuroimage.2020.116884] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 03/18/2020] [Accepted: 04/23/2020] [Indexed: 12/11/2022] Open
Abstract
Multi-parametric quantitative MRI (qMRI) of the spinal cord is a promising non-invasive tool to probe early microstructural damage in neurological disorders. It is usually performed in vivo by combining acquisitions with multiple signal readouts, which exhibit different thermal noise levels, geometrical distortions and susceptibility to physiological noise. This ultimately hinders joint multi-contrast modelling and makes the geometric correspondence of parametric maps challenging. We propose an approach to overcome these limitations, by implementing state-of-the-art microstructural MRI of the spinal cord with a unified signal readout in vivo (i.e. with matched spatial encoding parameters across a range of imaging contrasts). We base our acquisition on single-shot echo planar imaging with reduced field-of-view, and obtain data from two different vendors (vendor 1: Philips Achieva; vendor 2: Siemens Prisma). Importantly, the unified acquisition allows us to compare signal and noise across contrasts, thus enabling overall quality enhancement via multi-contrast image denoising methods. As a proof-of-concept, here we provide a demonstration with one such method, known as Marchenko-Pastur (MP) Principal Component Analysis (PCA) denoising. MP-PCA is a singular value (SV) decomposition truncation approach that relies on redundant acquisitions, i.e. such that the number of measurements is large compared to the number of components that are maintained in the truncated SV decomposition. Here we used in vivo and synthetic data to test whether a unified readout enables more efficient MP-PCA denoising of less redundant acquisitions, since these can be denoised jointly with more redundant ones. We demonstrate that a unified readout provides robust multi-parametric maps, including diffusion and kurtosis tensors from diffusion MRI, myelin metrics from two-pool magnetisation transfer, and T1 and T2 from relaxometry. Moreover, we show that MP-PCA improves the quality of our multi-contrast acquisitions, since it reduces the coefficient of variation (i.e. variability) by up to 17% for mean kurtosis, 8% for bound pool fraction (myelin-sensitive), and 13% for T1, while enabling more efficient denoising of modalities limited in redundancy (e.g. relaxometry). In conclusion, multi-parametric spinal cord qMRI with unified readout is feasible and provides robust microstructural metrics with matched resolution and distortions, whose quality benefits from multi-contrast denoising methods such as MP-PCA.
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Affiliation(s)
- Francesco Grussu
- Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
| | - Marco Battiston
- Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Jelle Veraart
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | | | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, Canada
| | - Timothy M Shepherd
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, USA
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
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13
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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14
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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15
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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: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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16
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Drenthen GS, Backes WH, Aldenkamp AP, Jansen JF. Applicability and reproducibility of 2D multi-slice GRASE myelin water fraction with varying acquisition acceleration. Neuroimage 2019; 195:333-339. [DOI: 10.1016/j.neuroimage.2019.04.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 03/20/2019] [Accepted: 04/03/2019] [Indexed: 12/12/2022] Open
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17
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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 Clin 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] [What about the content of this article? (0)] [Affiliation(s)] [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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18
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Lee LE, Ljungberg E, Shin D, Figley CR, Vavasour IM, Rauscher A, Cohen-Adad J, Li DKB, Traboulsee AL, MacKay AL, Lee J, Kolind SH. Inter-Vendor Reproducibility of Myelin Water Imaging Using a 3D Gradient and Spin Echo Sequence. Front Neurosci 2018; 12:854. [PMID: 30519158 PMCID: PMC6258882 DOI: 10.3389/fnins.2018.00854] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 11/01/2018] [Indexed: 01/22/2023] Open
Abstract
Myelin water imaging can be achieved using multicomponent T2 relaxation analysis to quantify in vivo measurement of myelin content, termed the myelin water fraction (MWF). Therefore, myelin water imaging can be a valuable tool to better understand the underlying white matter pathology in demyelinating diseases, such as multiple sclerosis. To apply myelin water imaging in multisite studies and clinical applications, it must be acquired in a clinically feasible scan time (less than 15 min) and be reproducible across sites and scanner vendors. Here, we assessed the reproducibility of MWF measurements in regional and global white matter in 10 healthy human brains across two sites with two different 3 T magnetic resonance imaging scanner vendors (Philips and Siemens), using a 32-echo gradient and spin echo (GRASE) sequence. A strong correlation was found between the MWF measurements in the global white matter (Pearson's r = 0.91; p < 0.001) for all participants across the two sites. The mean intersite MWF coefficient of variation across participants was 2.77% in the global white matter and ranged from 4.47% (splenium of the corpus callosum) to 17.89% (genu of the corpus callosum) in white matter regions of interest. Bland-Altman analysis showed a good agreement in MWF measurements between the two sites with small bias of 0.002. Overall, MWF estimates were in good agreement across the two sites and scanner vendors. Our findings support the use of quantitative multi-echo T2 relaxation metrics, such as the MWF, in multicenter studies and clinical trials to gain deeper understanding about the pathological processes resulting from the underlying disease progression in neurodegenerative diseases.
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Affiliation(s)
- Lisa Eunyoung Lee
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Emil Ljungberg
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada.,Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Dongmyung Shin
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea
| | - Chase R Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
| | - Irene M Vavasour
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
| | - Alexander Rauscher
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada.,Department of Pediatrics, The University of British Columbia, Vancouver, BC, Canada.,Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, 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
| | - David K B Li
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
| | - Anthony L Traboulsee
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alex L MacKay
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada.,Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea
| | - Shannon H Kolind
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada.,Department of Radiology, The University of British Columbia, Vancouver, BC, Canada.,Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC, Canada
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19
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Choi JY, Jeong IH, Oh S, Oh C, Park NY, Kim HJ, Lee J. Evaluation of Normal‐Appearing White Matter in Multiple Sclerosis Using Direct Visualization of Short Transverse Relaxation Time Component (ViSTa) Myelin Water Imaging and Gradient Echo and Spin Echo (GRASE) Myelin Water Imaging. J Magn Reson Imaging 2018; 49:1091-1098. [DOI: 10.1002/jmri.26278] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Accepted: 07/13/2018] [Indexed: 11/09/2022] Open
Affiliation(s)
- Joon Yul Choi
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National University Seoul Republic of Korea
| | - In Hye Jeong
- Department of NeurologyResearch Institute and Hospital of National Cancer Center Gyeonggi‐do Republic of Korea
| | - Se‐Hong Oh
- Department of Biomedical EngineeringHankuk University of Foreign Studies Gyeonggi‐do Republic of Korea
| | - Chang‐Hyun Oh
- Department of Electronics and Information EngineeringKorea University Sejong Republic of Korea
| | - Na Young Park
- Department of NeurologyResearch Institute and Hospital of National Cancer Center Gyeonggi‐do Republic of Korea
| | - Ho Jin Kim
- Department of NeurologyResearch Institute and Hospital of National Cancer Center Gyeonggi‐do Republic of Korea
| | - Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer EngineeringSeoul National University Seoul Republic of Korea
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20
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Cohen-Adad J. Microstructural imaging in the spinal cord and validation strategies. Neuroimage 2018; 182:169-183. [PMID: 29635029 DOI: 10.1016/j.neuroimage.2018.04.009] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 03/02/2018] [Accepted: 04/06/2018] [Indexed: 12/13/2022] Open
Abstract
In vivo histology using magnetic resonance imaging (MRI) is a newly emerging research field that aims to non-invasively characterize tissue microstructure. The implications of in vivo histology are many, from discovering novel biomarkers to studying human development, to providing tools for disease diagnosis and monitoring the effects of novel treatments on tissue. This review focuses on quantitative MRI (qMRI) techniques that are used to map spinal cord microstructure. Opening with a rationale for non-invasive imaging of the spinal cord, this article continues with a brief overview of the existing MRI techniques for axon and myelin imaging, followed by the specific challenges and potential solutions for acquiring and processing such data. The final part of this review focuses on histological validation, with suggested tissue preparation, acquisition and processing protocols for large-scale microscopy.
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Affiliation(s)
- J 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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21
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Lévy S, Guertin MC, Khatibi A, Mezer A, Martinu K, Chen JI, Stikov N, Rainville P, Cohen-Adad J. Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations. PLoS One 2018; 13:e0189944. [PMID: 29293550 PMCID: PMC5749716 DOI: 10.1371/journal.pone.0189944] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2017] [Accepted: 12/05/2017] [Indexed: 01/06/2023] Open
Abstract
PURPOSE To implement a statistical framework for assessing the precision of several quantitative MRI metrics sensitive to myelin in the human spinal cord: T1, Magnetization Transfer Ratio (MTR), saturation imposed by an off-resonance pulse (MTsat) and Macromolecular Tissue Volume (MTV). METHODS Thirty-three healthy subjects within two age groups (young, elderly) were scanned at 3T. Among them, 16 underwent the protocol twice to assess repeatability. Statistical reliability indexes such as the Minimal Detectable Change (MDC) were compared across metrics quantified within different cervical levels and white matter (WM) sub-regions. The differences between pathways and age groups were quantified and interpreted in context of the test-retest repeatability of the measurements. RESULTS The MDC was respectively 105.7ms, 2.77%, 0.37% and 4.08% for T1, MTR, MTsat and MTV when quantified over all WM, while the standard-deviation across subjects was 70.5ms, 1.34%, 0.20% and 2.44%. Even though particular WM regions did exhibit significant differences, these differences were on the same order as test-retest errors. No significant difference was found between age groups for all metrics. CONCLUSION While T1-based metrics (T1 and MTV) exhibited better reliability than MT-based measurements (MTR and MTsat), the observed differences between subjects or WM regions were comparable to (and often smaller than) the MDC. This makes it difficult to determine if observed changes are due to variations in myelin content, or simply due to measurement error. Measurement error remains a challenge in spinal cord myelin imaging, but this study provides statistical guidelines to standardize the field and make it possible to conduct large-scale multi-center studies.
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Affiliation(s)
- Simon Lévy
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Marie-Claude Guertin
- Montreal Health Innovations Coordinating Center (MHICC), Montreal Heart Institute, Montreal, QC, Canada
| | - Ali Khatibi
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
- Psychology Department, Bilkent University, Ankara, Turkey
- Interdisciplinary program in Neuroscience, Bilkent University, Ankara, Turkey
- National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
| | - Aviv Mezer
- The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Kristina Martinu
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Jen-I Chen
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
- Department of Stomatology, Faculty of Dentistry, Université de Montréal, Montreal, QC, Canada
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Montreal Heart Institute, Montreal, QC, Canada
| | - Pierre Rainville
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
- Department of Stomatology, Faculty of Dentistry, Université de Montréal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
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22
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Liu H, MacMillan EL, Jutzeler CR, Ljungberg E, MacKay AL, Kolind SH, Mädler B, Li DKB, Dvorak MF, Curt A, Laule C, Kramer JLK. Assessing structure and function of myelin in cervical spondylotic myelopathy: Evidence of demyelination. Neurology 2017; 89:602-610. [PMID: 28701500 PMCID: PMC5562959 DOI: 10.1212/wnl.0000000000004197] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 05/12/2017] [Indexed: 11/15/2022] Open
Abstract
PURPOSE To assess the extent of demyelination in cervical spondylotic myelopathy (CSM) using myelin water imaging (MWI) and electrophysiologic techniques. METHODS Somatosensory evoked potentials (SSEPs) and MWI were acquired in 14 patients with CSM and 18 age-matched healthy controls. MWI was performed on a 3.0T whole body magnetic resonance scanner. Myelin water fraction (MWF) was extracted for the dorsal columns and whole cord. SSEPs and MWF were also compared with conventional MRI outcomes, including T2 signal intensity, compression ratio, maximum spinal cord compression (MSCC), and maximum canal compromise (MCC). RESULTS Group analysis showed marked differences in T2 signal intensity, compression ratio, MSCC, and MCC between healthy controls and patients with CSM. There were no group differences in MWF and SSEP latencies. However, patients with CSM with pathologic SSEPs exhibited reduction in MWF (p < 0.05). MWF was also correlated with SSEP latencies. CONCLUSION Our findings provide evidence of decreased myelin content in the spinal cord associated with impaired spinal cord conduction in patients with CSM. While conventional MRI are of great value to define the extent of cord compression, they show a limited correlation with functional deficits (i.e., delayed SSEPs). MWI provides independent and complementary readouts to spinal cord compression, with a high specificity to detect impaired conduction.
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Affiliation(s)
- Hanwen Liu
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany.
| | - Erin L MacMillan
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Catherine R Jutzeler
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Emil Ljungberg
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Alex L MacKay
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Shannon H Kolind
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Burkhard Mädler
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - David K B Li
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Marcel F Dvorak
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Armin Curt
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - Cornelia Laule
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
| | - John L K Kramer
- From Physics and Astronomy (H.L., A.L.M., B.M.), ICORD (H.L., C.R.J., M.F.D., C.L., J.L.K.K.), Medicine (Neurology) (E.L.M., E.L., S.H.K., D.K.B.L.), Radiology (A.L.M., D.K.B.L., C.L.), Orthopaedics (M.F.D.), Pathology & Laboratory Medicine (C.L.), and School of Kinesiology (J.L.K.K.), University of British Columbia, Vancouver, Canada; Spinal Cord Injury Center (C.R.J., A.C.), University Hospital Balgrist, University of Zurich, Switzerland; and Philips Healthcare (B.M.), Hamburg, Germany
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23
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Ljungberg E, Vavasour I, Tam R, Yoo Y, Rauscher A, Li DK, Traboulsee A, MacKay A, Kolind S. Rapid myelin water imaging in human cervical spinal cord. Magn Reson Med 2016; 78:1482-1487. [DOI: 10.1002/mrm.26551] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 09/23/2016] [Accepted: 10/20/2016] [Indexed: 01/12/2023]
Affiliation(s)
- Emil Ljungberg
- Division of Neurology, Department of Medicine; University of British Columbia; Vancouver BC Canada
- Department of Physics and Astronomy; University of British Columbia; Vancouver BC Canada
| | - Irene Vavasour
- Department of Radiology; University of British Columbia; Vancouver BC Canada
| | - Roger Tam
- Division of Neurology, Department of Medicine; University of British Columbia; Vancouver BC Canada
- Department of Radiology; University of British Columbia; Vancouver BC Canada
| | - Youngjin Yoo
- Department of Electrical and Computer Engineering; University of British Columbia; Vancouver BC Canada
| | - Alexander Rauscher
- Department of Pediatrics; University of British Columbia; Vancouver BC Canada
| | - David K.B. Li
- Division of Neurology, Department of Medicine; University of British Columbia; Vancouver BC Canada
- Department of Radiology; University of British Columbia; Vancouver BC Canada
| | - Anthony Traboulsee
- Division of Neurology, Department of Medicine; University of British Columbia; Vancouver BC Canada
| | - Alex MacKay
- Department of Physics and Astronomy; University of British Columbia; Vancouver BC Canada
- Department of Radiology; University of British Columbia; Vancouver BC Canada
| | - Shannon Kolind
- Division of Neurology, Department of Medicine; University of British Columbia; Vancouver BC Canada
- Department of Radiology; University of British Columbia; Vancouver BC Canada
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