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Valošek J, Cohen-Adad J. Reproducible Spinal Cord Quantitative MRI Analysis with the Spinal Cord Toolbox. Magn Reson Med Sci 2024; 23:307-315. [PMID: 38479843 DOI: 10.2463/mrms.rev.2023-0159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024] Open
Abstract
The spinal cord plays a pivotal role in the central nervous system, providing communication between the brain and the body and containing critical motor and sensory networks. Recent advancements in spinal cord MRI data acquisition and image analysis have shown a potential to improve the diagnostics, prognosis, and management of a variety of pathological conditions. In this review, we first discuss the significance of standardized spinal cord MRI acquisition protocol in multi-center and multi-manufacturer studies. Then, we cover open-access spinal cord MRI datasets, which are important for reproducible science and validation of new methods. Finally, we elaborate on the recent advances in spinal cord MRI data analysis techniques implemented in the open-source software package Spinal Cord Toolbox (SCT).
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Affiliation(s)
- Jan Valošek
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Department of Neurosurgery, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
- Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
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Hameed S, Muhammad F, Haynes G, Smith L, Khan AF, Smith ZA. Early neurological changes in aging cervical spine: insights from PROMIS mobility assessment. GeroScience 2024; 46:3123-3134. [PMID: 38198027 PMCID: PMC11009195 DOI: 10.1007/s11357-023-01050-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 12/19/2023] [Indexed: 01/11/2024] Open
Abstract
Many studies have shown that the prevalence of degenerative spinal cord compression increases with age. However, most cases at early stages are asymptomatic, and their diagnosis remains challenging. Asymptomatic cervical spinal cord compression (ASCC) patients are more likely to experience annular tears, herniated disks, and later develop symptomatic compression. Asymptomatic individuals do not typically undergo spinal cord imaging; therefore, an assessment test that is both sensitive and specific in diagnosing ASCC may be helpful. It has been demonstrated that the Patient Reported Outcome Measure Information System (PROMIS) mobility test is sensitive in detecting degenerative cervical myelopathy (DCM) symptoms. We investigated the use of the PROMIS mobility test in assessing clinical dysfunction in ASCC. In this study, 51 DCM patients and 42 age-matched healthy control (HC) were enrolled. The degree of cervical spinal cord compression was assessed using the high-resolution cervical spinal cord T2 Weighted (T2w) MRIs, which were available for 14 DCM patients. Measurements of the spinal cords anterior-posterior (AP) diameter at the region(s) that were visibly compressed as well as at different cervical spine levels were used to determine the degree of compression. The age-matched HC cohort had a similar MRI to establish the normal range for AP diameter. Twelve (12) participants in the HC cohort had MRI evidence of cervical spinal cord compression; these individuals were designated as the ASCC cohort. All participants completed the PROMIS mobility, PROMIS pain interference (PI), PROMIS upper extremity (UE), modified Japanese orthopedic association (mJOA), and neck disability index (NDI) scoring scales. We examined the correlation between the AP diameter measurements and the clinical assessment scores to determine their usefulness in the diagnosis of ASCC. Furthermore, we examine the sensitivity and specificity of PROMIS mobility test and mJOA. Compared to the HC group, the participants in the ASCC and DCM cohorts were significantly older (p = 0.006 and p < 0.0001, respectively). Age differences were not observed between ASCC and DCM (p > 0.999). Clinical scores between the ASCC and the HC group were not significantly different using the mJOA (p > 0.99), NDI (p > 0.99), PROMIS UE (p = 0.23), and PROMIS PI (p = 0.82). However, there were significant differences between the ASCC and HC in the PROMIS mobility score (p = 0.01). The spinal cord AP diameter and the PROMIS mobility score showed a significant correlation (r = 0.44, p = 0.002). Decreasing PROMIS mobility was significantly associated with a decrease in cervical spinal cord AP diameter independent of other assessment measures. PROMIS mobility score had a sensitivity of 77.3% and specificity of 79.4% compared to 59.1% and 88.2%, respectively, for mJOA in detecting cervical spinal cord compression. Certain elements of ASCC are not adequately captured with the traditional mJOA and NDI scales used in DCM evaluation. In contrast to other evaluation scales utilized in this investigation, PROMIS mobility score shows a significant association with the AP diameter of the cervical spinal cord, suggesting that it is a sensitive tool for identifying early disability associated with degenerative change in the aging spine. In a comparative analysis of PROMIS mobility test against the standard mJOA, the PROMIS mobility demonstrated higher sensitivity for detecting cervical spinal cord compression. These findings underscore the potential use of PROMIS mobility score in clinical evaluation of the aging spine.
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Affiliation(s)
- Sanaa Hameed
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N. Lincoln Blvd, Oklahoma City, OK, 73104-3252, US
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N. Lincoln Blvd, Oklahoma City, OK, 73104-3252, US.
| | - Grace Haynes
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N. Lincoln Blvd, Oklahoma City, OK, 73104-3252, US
| | - Lonnie Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N. Lincoln Blvd, Oklahoma City, OK, 73104-3252, US
| | - Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N. Lincoln Blvd, Oklahoma City, OK, 73104-3252, US
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N. Lincoln Blvd, Oklahoma City, OK, 73104-3252, US
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Zhao Y, Ding Y, Lau V, Man C, Su S, Xiao L, Leong ATL, Wu EX. Whole-body magnetic resonance imaging at 0.05 Tesla. Science 2024; 384:eadm7168. [PMID: 38723062 DOI: 10.1126/science.adm7168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 03/19/2024] [Indexed: 05/31/2024]
Abstract
Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.
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Affiliation(s)
- Yujiao Zhao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Ye Ding
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Vick Lau
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Christopher Man
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Shi Su
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Linfang Xiao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Alex T L Leong
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
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Horak T, Horakova M, Kerkovsky M, Dostal M, Hlustik P, Valosek J, Svatkova A, Bednarik P, Vlckova E, Bednarik J. Evidence-based commentary on the diagnosis, management, and further research of degenerative cervical spinal cord compression in the absence of clinical symptoms of myelopathy. Front Neurol 2024; 15:1341371. [PMID: 38798708 PMCID: PMC11116587 DOI: 10.3389/fneur.2024.1341371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 04/18/2024] [Indexed: 05/29/2024] Open
Abstract
Degenerative cervical myelopathy (DCM) represents the final consequence of a series of degenerative changes in the cervical spine, resulting in cervical spinal canal stenosis and mechanical stress on the cervical spinal cord. This process leads to subsequent pathophysiological processes in the spinal cord tissues. The primary mechanism of injury is degenerative compression of the cervical spinal cord, detectable by magnetic resonance imaging (MRI), serving as a hallmark for diagnosing DCM. However, the relative resilience of the cervical spinal cord to mechanical compression leads to clinical-radiological discordance, i.e., some individuals may exhibit MRI findings of DCC without the clinical signs and symptoms of myelopathy. This degenerative compression of the cervical spinal cord without clinical signs of myelopathy, potentially serving as a precursor to the development of DCM, remains a somewhat controversial topic. In this review article, we elaborate on and provide commentary on the terminology, epidemiology, natural course, diagnosis, predictive value, risks, and practical management of this condition-all of which are subjects of ongoing debate.
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Affiliation(s)
- Tomas Horak
- Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurology, University Hospital Brno, Brno, Czechia
| | - Magda Horakova
- Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurology, University Hospital Brno, Brno, Czechia
| | - Milos Kerkovsky
- Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Radiology and Nuclear Medicine, University Hospital Brno, Brno, Czechia
| | - Marek Dostal
- Department of Radiology and Nuclear Medicine, University Hospital Brno, Brno, Czechia
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Petr Hlustik
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia
- Department of Neurology, University Hospital Olomouc, Olomouc, Czechia
| | - Jan Valosek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia
- Department of Neurosurgery, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czechia
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila—Quebec AI Institute, Montreal, QC, Canada
| | - Alena Svatkova
- Danish Research Center for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Department of Radiology, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
| | - Petr Bednarik
- Danish Research Center for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Department of Radiology, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
| | - Eva Vlckova
- Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurology, University Hospital Brno, Brno, Czechia
| | - Josef Bednarik
- Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurology, University Hospital Brno, Brno, Czechia
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Schilling KG, Combes AJE, Ramadass K, Rheault F, Sweeney G, Prock L, Sriram S, Cohen-Adad J, Gore JC, Landman BA, Smith SA, O'Grady KP. Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord. Magn Reson Imaging 2024; 108:11-21. [PMID: 38309376 PMCID: PMC11218893 DOI: 10.1016/j.mri.2024.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/04/2024] [Accepted: 01/14/2024] [Indexed: 02/05/2024]
Abstract
Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Anna J E Combes
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Karthik Ramadass
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Francois Rheault
- Medical Imaging and Neuroinformatic (MINi) Lab, Department of Computer Science, University of Sherbrooke, Canada
| | - Grace Sweeney
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Logan Prock
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Subramaniam Sriram
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada; Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
| | - John C Gore
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Seth A Smith
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kristin P O'Grady
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
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Bédard S, Bouthillier M, Cohen-Adad J. Pontomedullary junction as a reference for spinal cord cross-sectional area: validation across neck positions. Sci Rep 2023; 13:13527. [PMID: 37598229 PMCID: PMC10439961 DOI: 10.1038/s41598-023-40731-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023] Open
Abstract
Spinal cord cross-sectional area (CSA) is an important MRI biomarker to assess spinal cord atrophy in various neurodegenerative and traumatic spinal cord diseases. However, the conventional method of computing CSA based on vertebral levels is inherently flawed, as the prediction of spinal levels from vertebral levels lacks reliability, leading to considerable variability in CSA measurements. Computing CSA from an intrinsic neuroanatomical reference, the pontomedullary junction (PMJ), has been proposed in previous work to overcome limitations associated with using a vertebral reference. However, the validation of this alternative approach, along with its variability across and within participants under variable neck extensions, remains unexplored. The goal of this study was to determine if the variability of CSA across neck flexions/extensions is reduced when using the PMJ, compared to vertebral levels. Ten participants underwent a 3T MRI T2w isotropic scan at 0.6 mm3 for 3 neck positions: extension, neutral and flexion. Spinal cord segmentation, vertebral labeling, PMJ labeling, and CSA were computed automatically while spinal segments were labeled manually. Mean coefficient of variation for CSA across neck positions was 3.99 ± 2.96% for the PMJ method vs. 4.02 ± 3.01% for manual spinal segment method vs. 4.46 ± 3.10% for the disc method. These differences were not statistically significant. The PMJ method was slightly more reliable than the disc-based method to compute CSA at specific spinal segments, although the difference was not statistically significant. This suggests that the PMJ can serve as a valuable alternative and reliable method for estimating CSA when a disc-based approach is challenging or not feasible, such as in cases involving fused discs in individuals with spinal cord injuries.
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Affiliation(s)
- Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.
| | - Maxime Bouthillier
- Centre Hospitalier de l'Université de Montréal, University of Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada
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Schading S, Seif M, Leutritz T, Hupp M, Curt A, Weiskopf N, Freund P. Reliability of spinal cord measures based on synthetic T 1-weighted MRI derived from multiparametric mapping (MPM). Neuroimage 2023; 271:120046. [PMID: 36948280 DOI: 10.1016/j.neuroimage.2023.120046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/14/2023] [Accepted: 03/18/2023] [Indexed: 03/24/2023] Open
Abstract
Short MRI acquisition time, high signal-to-noise ratio, and high reliability are crucial for image quality when scanning healthy volunteers and patients. Cross-sectional cervical cord area (CSA) has been suggested as a marker of neurodegeneration and potential outcome measure in clinical trials and is conventionally measured on T1-weigthed 3D Magnetization Prepared Rapid Acquisition Gradient-Echo (MPRAGE) images. This study aims to reduce the acquisition time for the comprehensive assessment of the spinal cord, which is typically based on MPRAGE for morphometry and multi-parameter mapping (MPM) for microstructure. The MPRAGE is replaced by a synthetic T1-w MRI (synT1-w) estimated from the MPM, in order to measure CSA. SynT1-w images were reconstructed using the MPRAGE signal equation based on quantitative maps of proton density (PD), longitudinal (R1) and effective transverse (R2*) relaxation rates. The reliability of CSA measurements from synT1-w images was determined within a multi-center test-retest study format and validated against acquired MPRAGE scans by assessing the agreement between both methods. The response to pathological changes was tested by longitudinally measuring spinal cord atrophy following spinal cord injury (SCI) for synT1-w and MPRAGE using linear mixed effect models. CSA measurements based on the synT1-w MRI showed high intra-site (Coefficient of variation [CoV]: 1.43% to 2.71%) and inter-site repeatability (CoV: 2.90% to 5.76%), and only a minor deviation of -1.65 mm2 compared to MPRAGE. Crucially, by assessing atrophy rates and by comparing SCI patients with healthy controls longitudinally, differences between synT1-w and MPRAGE were negligible. These results demonstrate that reliable estimates of CSA can be obtained from synT1-w images, thereby reducing scan time significantly.
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Affiliation(s)
- Simon Schading
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Maryam Seif
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Markus Hupp
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Armin Curt
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
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Schilling KG, Fadnavis S, Batson J, Visagie M, Combes AJE, By S, McKnight CD, Bagnato F, Garyfallidis E, Landman BA, Smith SA, O'Grady KP. Denoising of diffusion MRI in the cervical spinal cord - effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity. Neuroimage 2023; 266:119826. [PMID: 36543265 PMCID: PMC9843739 DOI: 10.1016/j.neuroimage.2022.119826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 11/02/2022] [Accepted: 12/17/2022] [Indexed: 12/23/2022] Open
Abstract
Quantitative diffusion MRI (dMRI) is a promising technique for evaluating the spinal cord in health and disease. However, low signal-to-noise ratio (SNR) can impede interpretation and quantification of these images. The purpose of this study is to evaluate several dMRI denoising approaches on their ability to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. We evaluate three denoising approaches (Non-Local Means, Marchenko-Pastur PCA, and a newly proposed Patch2Self algorithm) and conduct five experiments to validate the denoising performance on clinical-quality and commonly-acquired dMRI acquisitions: 1) a phantom experiment to assess denoising error and bias; 2) a multi-vendor, multi-acquisition open experiment for both qualitative and quantitative evaluation of noise residuals; 3) a bootstrapping experiment to estimate uncertainty of parametric maps; 4) an assessment of spinal cord lesion conspicuity in a multiple sclerosis group; and 5) an evaluation of denoising for advanced parametric multi-compartment modeling. We find that all methods improve signal-to-noise ratio and conspicuity of MS lesions in individual diffusion weighted images (DWIs), but MPPCA and Patch2Self excel at improving the quality and intra-cord contrast of diffusion weighted images - removing signal fluctuations due to thermal noise while improving precision of estimation of diffusion parameters even with very few DWIs (i.e., 16-32) typical of clinical acquisitions. These denoising approaches hold promise for facilitating reliable diffusion observations and measurements in the spinal cord to investigate biological and pathological processes.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States.
| | - Shreyas Fadnavis
- Department of Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States
| | - Joshua Batson
- The Public Health Company, California, United States
| | - Mereze Visagie
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Anna J E Combes
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Samantha By
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Neurology, VA Hospital, TN Valley Healthcare System, Nashville, TN, United States
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, IN, United States
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - Seth A Smith
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Kristin P O'Grady
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.
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Zhang JK, Jayasekera D, Song C, Greenberg JK, Javeed S, Dibble CF, Blum J, Sun P, Song SK, Ray WZ. Diffusion Basis Spectrum Imaging Provides Insights Into Cervical Spondylotic Myelopathy Pathology. Neurosurgery 2023; 92:102-109. [PMID: 36519861 PMCID: PMC10158908 DOI: 10.1227/neu.0000000000002183] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/11/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Diffusion basis spectrum imaging (DBSI) is a noninvasive quantitative imaging modality that may improve understanding of cervical spondylotic myelopathy (CSM) pathology through detailed evaluations of spinal cord microstructural compartments. OBJECTIVE To determine the utility of DBSI as a biomarker of CSM disease severity. METHODS A single-center prospective cohort study enrolled 50 patients with CSM and 20 controls from 2018 to 2020. All patients underwent clinical evaluation and diffusion-weighted MRI, followed by diffusion tensor imaging and DBSI analyses. Diffusion-weighted MRI metrics assessed white matter integrity by fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. In addition, DBSI further evaluates extra-axonal changes by isotropic restricted and nonrestricted fraction. Including an intra-axonal diffusion compartment, DBSI improves estimations of axonal injury through intra-axonal axial diffusivity. Patients were categorized into mild, moderate, and severe CSM using modified Japanese Orthopedic Association classifications. Imaging parameters were compared among patient groups using independent samples t tests and ANOVA. RESULTS Twenty controls, 27 mild (modified Japanese Orthopedic Association 15-17), 12 moderate (12-14), and 11 severe (0-11) patients with CSM were enrolled. Diffusion tensor imaging and DBSI fractional anisotropy, axial diffusivity, and radial diffusivity were significantly different between control and patients with CSM ( P < .05). DBSI fiber fraction, restricted fraction, and nonrestricted fraction were significantly different between groups ( P < .01). DBSI intra-axonal axial diffusivity was lower in mild compared with moderate (mean difference [95% CI]: 1.1 [0.3-2.1], P < .01) and severe (1.9 [1.3-2.4], P < .001) CSM. CONCLUSION DBSI offers granular data on white matter tract integrity in CSM that provide novel insights into disease pathology, supporting its potential utility as a biomarker of CSM disease progression.
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Affiliation(s)
- Justin K. Zhang
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Dinal Jayasekera
- Department of Biomedical Engineering, Washington University in St. Louis McKelvey School of Engineering, Saint Louis, Missouri, USA
| | - Chunyu Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jacob K. Greenberg
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Saad Javeed
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Christopher F. Dibble
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Jacob Blum
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Wilson Z. Ray
- Department of Neurological Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA
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10
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Bédard S, Cohen-Adad J. Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction. FRONTIERS IN NEUROIMAGING 2022; 1:1031253. [PMID: 37555172 PMCID: PMC10406309 DOI: 10.3389/fnimg.2022.1031253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 10/04/2022] [Indexed: 08/10/2023]
Abstract
Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models required manual intervention and used vertebral levels as a reference, which is an imprecise prediction of the spinal levels. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated factors to explain variability, and developed normalization strategies on a large cohort (N = 804). Following automatic spinal cord segmentation, vertebral labeling and PMJ labeling, the spinal cord CSA was computed on T1w MRI scans from the UK Biobank database. The CSA was computed using two methods. For the first method, the CSA was computed at the level of the C2-C3 intervertebral disc. For the second method, the CSA was computed at 64 mm caudally from the PMJ, this distance corresponding to the average distance between the PMJ and the C2-C3 disc across all participants. The effect of various demographic and anatomical factors was explored, and a stepwise regression found significant predictors; the coefficients of the best fit model were used to normalize CSA. CSA measured at C2-C3 disc and using the PMJ differed significantly (paired t-test, p-value = 0.0002). The best normalization model included thalamus, brain volume, sex and the interaction between brain volume and sex. The coefficient of variation went down for PMJ CSA from 10.09 (without normalization) to 8.59%, a reduction of 14.85%. For CSA at C2-C3, it went down from 9.96 to 8.42%, a reduction of 15.13 %. This study introduces an end-to-end automatic pipeline to measure and normalize cord CSA from a neurological reference. This approach requires further validation to assess atrophy in longitudinal studies. The inter-subject variability of CSA can be partly accounted for by demographics and anatomical factors.
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Affiliation(s)
- Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, Centre de recherche de l'Institut universitaire de gériatrie de Montréal (CRIUGM), University of Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
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11
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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] [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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12
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Joers JM, Adanyeguh IM, Deelchand DK, Hutter DH, Eberly LE, Iltis I, Bushara KO, Lenglet C, Henry PG. Spinal cord magnetic resonance imaging and spectroscopy detect early-stage alterations and disease progression in Friedreich ataxia. Brain Commun 2022; 4:fcac246. [PMID: 36300142 PMCID: PMC9581897 DOI: 10.1093/braincomms/fcac246] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 06/04/2022] [Accepted: 09/23/2022] [Indexed: 02/01/2023] Open
Abstract
Friedreich ataxia is the most common hereditary ataxia. Atrophy of the spinal cord is one of the hallmarks of the disease. MRI and magnetic resonance spectroscopy are powerful and non-invasive tools to investigate pathological changes in the spinal cord. A handful of studies have reported cross-sectional alterations in Friedreich ataxia using MRI and diffusion MRI. However, to our knowledge no longitudinal MRI, diffusion MRI or MRS results have been reported in the spinal cord. Here, we investigated early-stage cross-sectional alterations and longitudinal changes in the cervical spinal cord in Friedreich ataxia, using a multimodal magnetic resonance protocol comprising morphometric (anatomical MRI), microstructural (diffusion MRI), and neurochemical (1H-MRS) assessments.We enrolled 28 early-stage individuals with Friedreich ataxia and 20 age- and gender-matched controls (cross-sectional study). Disease duration at baseline was 5.5 ± 4.0 years and Friedreich Ataxia Rating Scale total neurological score at baseline was 42.7 ± 13.6. Twenty-one Friedreich ataxia participants returned for 1-year follow-up, and 19 of those for 2-year follow-up (cohort study). Each visit consisted in clinical assessments and magnetic resonance scans. Controls were scanned at baseline only. At baseline, individuals with Friedreich ataxia had significantly lower spinal cord cross-sectional area (-31%, P = 8 × 10-17), higher eccentricity (+10%, P = 5 × 10-7), lower total N-acetyl-aspartate (tNAA) (-36%, P = 6 × 10-9) and higher myo-inositol (mIns) (+37%, P = 2 × 10-6) corresponding to a lower ratio tNAA/mIns (-52%, P = 2 × 10-13), lower fractional anisotropy (-24%, P = 10-9), as well as higher radial diffusivity (+56%, P = 2 × 10-9), mean diffusivity (+35%, P = 10-8) and axial diffusivity (+17%, P = 4 × 10-5) relative to controls. Longitudinally, spinal cord cross-sectional area decreased by 2.4% per year relative to baseline (P = 4 × 10-4), the ratio tNAA/mIns decreased by 5.8% per year (P = 0.03), and fractional anisotropy showed a trend to decrease (-3.2% per year, P = 0.08). Spinal cord cross-sectional area correlated strongly with clinical measures, with the strongest correlation coefficients found between cross-sectional area and Scale for the Assessment and Rating of Ataxia (R = -0.55, P = 7 × 10-6) and between cross-sectional area and Friedreich ataxia Rating Scale total neurological score (R = -0.60, P = 4 × 10-7). Less strong but still significant correlations were found for fractional anisotropy and tNAA/mIns. We report here the first quantitative longitudinal magnetic resonance results in the spinal cord in Friedreich ataxia. The largest longitudinal effect size was found for spinal cord cross-sectional area, followed by tNAA/mIns and fractional anisotropy. Our results provide direct evidence that abnormalities in the spinal cord result not solely from hypoplasia, but also from neurodegeneration, and show that disease progression can be monitored non-invasively in the spinal cord.
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Affiliation(s)
| | | | - Dinesh K Deelchand
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Diane H Hutter
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Lynn E Eberly
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Isabelle Iltis
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Khalaf O Bushara
- Department of Neurology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | | | - Pierre-Gilles Henry
- Correspondence to: Pierre-Gilles Henry, Ph.D Associate Professor, Center for Magnetic Resonance Research 2021 6th Street SE Minneapolis MN 55455, USA E-mail:
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13
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Karakuzu A, Biswas L, Cohen-Adad J, Stikov N. Vendor-neutral sequences and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI. Magn Reson Med 2022; 88:1212-1228. [PMID: 35657066 DOI: 10.1002/mrm.29292] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 12/20/2022]
Abstract
PURPOSE We developed an end-to-end workflow that starts with a vendor-neutral acquisition and tested the hypothesis that vendor-neutral sequences decrease inter-vendor variability of T1, magnetization transfer ratio (MTR), and magnetization transfer saturation-index (MTsat) measurements. METHODS We developed and deployed a vendor-neutral 3D spoiled gradient-echo (SPGR) sequence on three clinical scanners by two MRI vendors. We then acquired T1 maps on the ISMRM-NIST system phantom, as well as T1, MTR, and MTsat maps in three healthy participants. We performed hierarchical shift function analysis in vivo to characterize the differences between scanners when the vendor-neutral sequence is used instead of commercial vendor implementations. Inter-vendor deviations were compared for statistical significance to test the hypothesis. RESULTS In the phantom, the vendor-neutral sequence reduced inter-vendor differences from 8% to 19.4% to 0.2% to 5% with an overall accuracy improvement, reducing ground truth T1 deviations from 7% to 11% to 0.2% to 4%. In vivo, we found that the variability between vendors is significantly reduced (p = 0.015) for all maps (T1, MTR, and MTsat) using the vendor-neutral sequence. CONCLUSION We conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor variability using vendor-neutral sequences has important implications for qMRI research and for the reliability of multicenter clinical trials.
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Affiliation(s)
- Agah Karakuzu
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.,Montréal Heart Institute, Montréal, Quebec, Canada
| | - Labonny Biswas
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.,Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, Quebec, Canada.,Mila - Quebec AI Institute, Montreal, Quebec, Canada
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.,Montréal Heart Institute, Montréal, Quebec, Canada.,Center for Advanced Interdisciplinary Research, Ss. Cyril and Methodius University, Skopje, North Macedonia
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14
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Valošek J, Bednařík P, Keřkovský M, Hluštík P, Bednařík J, Svatkova A. Quantitative MR Markers in Non-Myelopathic Spinal Cord Compression: A Narrative Review. J Clin Med 2022; 11:2301. [PMID: 35566426 PMCID: PMC9105390 DOI: 10.3390/jcm11092301] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 02/01/2023] Open
Abstract
Degenerative spinal cord compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical spinal cord compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, and magnetic resonance spectroscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients consistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels, caused by demyelination and axonal injury, MT and 1H-MRS, along with advanced and tract-specific diffusion MRI, recently revealed microstructural alterations, also rostrally pointing to Wallerian degeneration. Recent studies also disclosed a significant relationship between microstructural damage and functional deficits, as assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI, in combination with electrophysiology, critically extends our understanding of the underlying pathophysiology of degenerative spinal cord compression and may provide predictive markers of DCM development for accurate patient management. However, the prognostic value must be validated in longitudinal studies.
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Affiliation(s)
- Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic; (J.V.); (P.H.)
- Department of Radiology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
- Department of Biomedical Engineering, University Hospital Olomouc, 779 00 Olomouc, Czech Republic
| | - Petr Bednařík
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark;
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark
| | - Miloš Keřkovský
- Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic; (M.K.); (J.B.)
- Department of Radiology and Nuclear Medicine, University Hospital Brno, 625 00 Brno, Czech Republic
| | - Petr Hluštík
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic; (J.V.); (P.H.)
- Department of Neurology, University Hospital Olomouc, 779 00 Olomouc, Czech Republic
| | - Josef Bednařík
- Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic; (M.K.); (J.B.)
- Department of Neurology, University Hospital Brno, 625 00 Brno, Czech Republic
- Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic
| | - Alena Svatkova
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark;
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, 2650 Hvidovre, Denmark
- Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, 1090 Vienna, Austria
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15
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Cohen‐Adad J, Alonso‐Ortiz E, Alley S, Lagana MM, Baglio F, Vannesjo SJ, Karbasforoushan H, Seif M, Seifert AC, Xu J, Kim J, Labounek R, Vojtíšek L, Dostál M, Valošek J, Samson RS, Grussu F, Battiston M, Gandini Wheeler‐Kingshott CAM, Yiannakas MC, Gilbert G, Schneider T, Johnson B, Prados F. Comparison of multicenter
MRI
protocols for visualizing the spinal cord gray matter. Magn Reson Med 2022; 88:849-859. [DOI: 10.1002/mrm.29249] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 12/28/2022]
Affiliation(s)
- Julien Cohen‐Adad
- NeuroPoly Lab Institute of Biomedical Engineering, Polytechnique Montreal Montreal Canada
- Functional Neuroimaging Unit, CRIUGM University of Montreal Montreal Canada
- Mila ‐ Quebec AI Institute Montreal Canada
| | - Eva Alonso‐Ortiz
- NeuroPoly Lab Institute of Biomedical Engineering, Polytechnique Montreal Montreal Canada
| | - Stephanie Alley
- NeuroPoly Lab Institute of Biomedical Engineering, Polytechnique Montreal Montreal Canada
| | | | | | - Signe Johanna Vannesjo
- Wellcome Center for Integrative Neuroimaging, FMRIB University of Oxford, John Radcliffe Hospital Oxford UK
- Department of Physics Norwegian University of Science and Technology Trondheim Norway
| | - Haleh Karbasforoushan
- Interdepartmental Neuroscience Program Northwestern University School of Medicine Chicago IL USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine Stanford University Stanford CA USA
| | - Maryam Seif
- Spinal Cord Injury Center, Balgrist University Hospital University of Zurich Zurich Switzerland
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Alan C. Seifert
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences Icahn School of Medicine at Mount Sinai New York NY USA
| | - Junqian Xu
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences Icahn School of Medicine at Mount Sinai New York NY USA
| | - Joo‐Won Kim
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences Icahn School of Medicine at Mount Sinai New York NY USA
| | - René Labounek
- Departments of Neurology and Biomedical Engineering University Hospital Olomouc Olomouc Czech Republic
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics Masonic Institute for the Developing Brain, University of Minnesota Minneapolis MN USA
| | - Lubomír Vojtíšek
- Central European Institute of Technology Masaryk University Brno Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine University Hospital Brno Brno Czech Republic
| | - Jan Valošek
- Departments of Neurology and Biomedical Engineering University Hospital Olomouc Olomouc Czech Republic
| | - Rebecca S. Samson
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
| | - Francesco Grussu
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
- Radiomics Group, Vall d'Hebron Institute of Oncology Vall d'Hebron Barcelona Hospital Campus Barcelona Spain
| | - Marco Battiston
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
| | - Claudia A. M. Gandini Wheeler‐Kingshott
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
- Department of Brain and Behavioral Sciences University of Pavia Pavia Italy
- Brain MRI 3T Research Center C. Mondino National Neurological Institute Pavia Italy
| | - Marios C. Yiannakas
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
| | | | | | - Brian Johnson
- MR Clinical Development, Philips North America Gainesville FL USA
| | - Ferran Prados
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences University College London London UK
- e‐Health Center, Universitat Oberta de Catalunya Barcelona Spain
- Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, University College London London UK
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16
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Towards reliable spinal cord fMRI: assessment of common imaging protocols. Neuroimage 2022; 250:118964. [DOI: 10.1016/j.neuroimage.2022.118964] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/07/2022] [Accepted: 02/01/2022] [Indexed: 01/29/2023] Open
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17
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Uhrenholt L, Brix L, Wichmann TO, Pedersen M, Ringgaard S, Jensen TS. Advanced magnetic resonance imaging of chronic whiplash patients: a clinical practice-based feasibility study. Chiropr Man Therap 2022; 30:2. [PMID: 34996490 PMCID: PMC8742358 DOI: 10.1186/s12998-022-00410-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 12/30/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Whiplash injury is common following road traffic crashes affecting millions worldwide, with up to 50% of the injured developing chronic symptoms and 15% having a reduced working capability due to ongoing disability. Many of these patients receive treatment in primary care settings based upon clinical and diagnostic imaging findings. Despite the identification of different types of injuries in the whiplash patients, clinically significant relationships between injuries and chronic symptoms remains to be fully established. This study investigated the feasibility of magnetic resonance imaging (MRI) techniques including quantitative diffusion weighted imaging and measurements of cerebrospinal fluid (CSF) flow as novel non-invasive biomarkers in a population of healthy volunteers and chronic whiplash patients recruited from a chiropractic clinic for the purpose of improving our understanding of whiplash injury. METHODS Twenty chronic whiplash patients and 18 healthy age- and gender matched control subjects were included [mean age ± SD (sex ratio; females/males), case group: 37.8 years ± 9.1 (1.22), control group: 35.1 years ± 9.2 (1.25)]. Data was collected from May 2019 to July 2020. Data from questionnaires pertaining to the car crash, acute and current symptoms were retrieved and findings from clinical examination and MRI including morphologic, diffusion weighted and phase-contrast images were recorded. The apparent diffusion coefficient and fractional anisotropy were calculated, and measurement and analysis of CSF flow was conducted. Statistical analyses included Fisher's exact test, Mann Whitney U test and analysis of variance between groups. RESULTS The studied population was described in detail using readily available clinical tools. No statistically significant differences were found between the groups on MRI. CONCLUSIONS This study did not show that MRI-based measures of morphology, spinal cord and nerve root diffusion or cerebrospinal fluid flow are sensitive biomarkers to distinguish between chronic whiplash patients and healthy controls. The detailed description of the chronic whiplash patients using readily available clinical tools may be of great relevance to the clinician. In the context of feasibility, clinical practice-based advanced imaging studies with a technical setup similar to the presented can be expected to have a high likelihood of successful completion.
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Affiliation(s)
- Lars Uhrenholt
- Department of Forensic Medicine, Aarhus University, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark. .,Nortvig & Uhrenholt Kiropraktisk Klinik, 8200, Aarhus, Denmark.
| | - Lau Brix
- Department of Radiology, Diagnostic Centre, University Research Clinic for Innovative Patient Pathways, Silkeborg Regional Hospital, Falkevej 1-3, 8600, Silkeborg, Denmark.,Department of Procurement and Biomedical Engineering, Region Midt, Aarhus N, Denmark
| | | | - Michael Pedersen
- Department of Forensic Medicine, Aarhus University, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark.,Comparative Medicine Lab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Steffen Ringgaard
- MR Research Centre, Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Tue Secher Jensen
- Department of Radiology, Diagnostic Centre, University Research Clinic for Innovative Patient Pathways, Silkeborg Regional Hospital, Falkevej 1-3, 8600, Silkeborg, Denmark.,Chiropractic Knowledge Hub, Odense, Denmark.,Department of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
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Jogia T, Kopp MA, Schwab JM, Ruitenberg MJ. Peripheral white blood cell responses as emerging biomarkers for patient stratification and prognosis in acute spinal cord injury. Curr Opin Neurol 2021; 34:796-803. [PMID: 34608075 PMCID: PMC8631147 DOI: 10.1097/wco.0000000000000995] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
PURPOSE OF REVIEW To date, prognostication of patients after acute traumatic spinal cord injury (SCI) mostly relies on the neurological assessment of residual function attributed to lesion characteristics. With emerging treatment candidates awaiting to be tested in early clinical trials, there is a need for wholistic high-yield prognostic biomarkers that integrate both neurogenic and nonneurogenic SCI pathophysiology as well as premorbid patient characteristics. RECENT FINDINGS It is becoming clearer that effective prognostication after acute SCI would benefit from integrating an assessment of pathophysiological changes on a systemic level, and with that, extend from a lesion-centric approach. Immunological markers mirror tissue injury as well as host immune function and are easily accessible through routine blood sampling. New studies have highlighted the value of circulating white blood cells, neutrophils and lymphocytes in particular, as prognostic systemic indicators of SCI severity and outcomes. SUMMARY We survey recent advances in methods and approaches that may allow for a more refined diagnosis and better prognostication after acute SCI, discuss how these may help deepen our understanding of SCI pathophysiology, and be of use in clinical trials.
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Affiliation(s)
- Trisha Jogia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Marcel A. Kopp
- Spinal Cord Injury Research (Neuroparaplegiology), Department of Neurology and Experimental Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Jan M. Schwab
- Spinal Cord Injury Research (Neuroparaplegiology), Department of Neurology and Experimental Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology, Belford Center for Spinal Cord Injury, Departments of Neuroscience and Physical Medicine and Rehabilitation, The Neurological Institute, The Ohio State University, Wexner Medical Center, Columbus, Ohio, USA
| | - Marc J. Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
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Generic acquisition protocol for quantitative MRI of the spinal cord. Nat Protoc 2021; 16:4611-4632. [PMID: 34400839 PMCID: PMC8811488 DOI: 10.1038/s41596-021-00588-0] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 06/10/2021] [Indexed: 02/08/2023]
Abstract
Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.
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