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Aigner CS, Sánchez Alarcon MF, D'Astous A, Alonso-Ortiz E, Cohen-Adad J, Schmitter S. Calibration-free parallel transmission of the cervical, thoracic, and lumbar spinal cord at 7T. Magn Reson Med 2024; 92:1496-1510. [PMID: 38733068 DOI: 10.1002/mrm.30137] [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: 02/16/2024] [Revised: 04/16/2024] [Accepted: 04/16/2024] [Indexed: 05/13/2024]
Abstract
PURPOSE To address the limitations of spinal cord imaging at ultra-high field (UHF) due to time-consuming parallel transmit (pTx) adjustments. This study introduces calibration-free offline computed universal shim modes that can be applied seamlessly for different pTx RF coils and spinal cord target regions, substantially enhancing spinal cord imaging efficiency at UHF. METHODS A library of channel-wise relativeB 1 + $$ {B}_1^{+} $$ maps for the cervical spinal cord (six datasets) and thoracic and lumbar spinal cord (nine datasets) was constructed to optimize transmit homogeneity and efficiency for these regions. A tailored B0 shim was optimized for the cervical spine to enhance spatial magnetic field homogeneity further. The performance of the universal shims was validated using absolute saturation basedB 1 + $$ {B}_1^{+} $$ mapping and high-resolution 2D and 3D multi-echo gradient-recalled echo (GRE) data to assess the image quality. RESULTS The proposed universal shims demonstrated a 50% improvement inB 1 + $$ {B}_1^{+} $$ efficiency compared to the default (zero phase) shim mode.B 1 + $$ {B}_1^{+} $$ homogeneity was also improved by 20%. The optimized universal shims achieved performance comparable to subject-specific pTx adjustments, while eliminating the need for lengthy pTx calibration times, saving about 10 min per experiment. CONCLUSION The development of universal shims represents a significant advance by eliminating time-consuming subject-specific pTx adjustments. This approach is expected to make UHF spinal cord imaging more accessible and user-friendly, particularly for non-pTx experts.
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Affiliation(s)
- Christoph S Aigner
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Manuel F Sánchez Alarcon
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, A Joint Cooperation between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Alexandre D'Astous
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Quebec, Canada
| | - Eva Alonso-Ortiz
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, Quebec, Canada
- Mila-Quebec AI Institute, Montréal, Quebec, Canada
| | - Julien Cohen-Adad
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, Quebec, Canada
- Mila-Quebec AI Institute, Montréal, Quebec, Canada
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Sebastian Schmitter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
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Luchetti L, Prados F, Cortese R, Gentile G, Calabrese M, Mortilla M, De Stefano N, Battaglini M. Evaluation of cervical spinal cord atrophy using a modified SIENA approach. Neuroimage 2024; 298:120775. [PMID: 39106936 DOI: 10.1016/j.neuroimage.2024.120775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 07/12/2024] [Accepted: 08/02/2024] [Indexed: 08/09/2024] Open
Abstract
Spinal cord (SC) atrophy obtained from structural magnetic resonance imaging has gained relevance as an indicator of neurodegeneration in various neurological disorders. The common method to assess SC atrophy is by comparing numerical differences of the cross-sectional spinal cord area (CSA) between time points. However, this indirect approach leads to considerable variability in the obtained results. Studies showed that this limitation can be overcome by using a registration-based technique. The present study introduces the Structural Image Evaluation using Normalization of Atrophy on the Spinal Cord (SIENA-SC), which is an adapted version of the original SIENA method, designed to directly calculate the percentage of SC volume change over time from clinical brain MRI acquired with an extended field of view to cover the superior part of the cervical SC. In this work, we compared SIENA-SC with the Generalized Boundary Shift Integral (GBSI) and the CSA change. On a scan-rescan dataset, SIENA-SC was shown to have the lowest measurement error than the other two methods. When comparing a group of 190 Healthy Controls with a group of 65 Multiple Sclerosis patients, SIENA-SC provided significantly higher yearly rates of atrophy in patients than in controls and a lower sample size when measured for treatment effect sizes of 50%, 30% and 10%. Our findings indicate that SIENA-SC is a robust, reproducible, and sensitive approach for assessing longitudinal changes in spinal cord volume, providing neuroscientists with an accessible and automated tool able to reduce the need for manual intervention and minimize variability in measurements.
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Affiliation(s)
- Ludovico Luchetti
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy; Siena Imaging S.r.l., Siena, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering Department, University College London, London, United Kingdom; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | | | - Massimilano Calabrese
- Department of Neuroscience, Biomedicine and Movements, The Multiple Sclerosis Center of the University Hospital of Verona, Verona, Italy
| | - Marzia Mortilla
- Anna Meyer Children's University Hospital-IRCCS, Florence, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy; Siena Imaging S.r.l., Siena, Italy.
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Rezende TJR, Petit E, Park YW, Tezenas du Montcel S, Joers JM, DuBois JM, Moore Arnold H, Povazan M, Banan G, Valabregue R, Ehses P, Faber J, Coupé P, Onyike CU, Barker PB, Schmahmann JD, Ratai EM, Subramony SH, Mareci TH, Bushara KO, Paulson H, Klockgether T, Durr A, Ashizawa T, Lenglet C, Öz G. Sensitivity of Advanced Magnetic Resonance Imaging to Progression over Six Months in Early Spinocerebellar Ataxia. Mov Disord 2024. [PMID: 39056163 DOI: 10.1002/mds.29934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 06/11/2024] [Accepted: 07/02/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Clinical trials for upcoming disease-modifying therapies of spinocerebellar ataxias (SCA), a group of rare movement disorders, lack endpoints sensitive to early disease progression, when therapeutics will be most effective. In addition, regulatory agencies emphasize the importance of biological outcomes. OBJECTIVES READISCA, a transatlantic clinical trial readiness consortium, investigated whether advanced multimodal magnetic resonance imaging (MRI) detects pathology progression over 6 months in preataxic and early ataxic carriers of SCA mutations. METHODS A total of 44 participants (10 SCA1, 25 SCA3, and 9 controls) prospectively underwent 3-T MR scanning at baseline and a median [interquartile range] follow-up of 6.2 [5.9-6.7] months; 44% of SCA participants were preataxic. Blinded analyses of annual changes in structural, diffusion MRI, MR spectroscopy, and the Scale for Assessment and Rating of Ataxia (SARA) were compared between groups using nonparametric testing. Sample sizes were estimated for 6-month interventional trials with 50% to 100% treatment effect size, leveraging existing large cohort data (186 SCA1, 272 SCA3) for the SARA estimate. RESULTS Rate of change in microstructural integrity (decrease in fractional anisotropy, increase in diffusivities) in the middle cerebellar peduncle, corona radiata, and superior longitudinal fasciculus significantly differed in SCAs from controls (P < 0.005), with high effect sizes (Cohen's d = 1-2) and moderate-to-high responsiveness (|standardized response mean| = 0.6-0.9) in SCAs. SARA scores did not change, and their rate of change did not differ between groups. CONCLUSIONS Diffusion MRI is sensitive to disease progression at very early-stage SCA1 and SCA3 and may provide a >5-fold reduction in sample sizes relative to SARA as endpoint for 6-month-long trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Thiago J R Rezende
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas, Brazil
| | - Emilien Petit
- Sorbonne Université, Paris Brain Institute, Inserm, INRIA, CNRS, APHP, Paris, France
| | - Young Woo Park
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - James M Joers
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | | | | | - Michal Povazan
- Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
| | - Guita Banan
- Norman Fixel Center for Neurological Disorders, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Romain Valabregue
- Sorbonne Université, Paris Brain Institute, Inserm, INRIA, CNRS, APHP, Paris, France
| | - Philipp Ehses
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Jennifer Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Pierrick Coupé
- Laboratoire Bordelais de Recherche en Informatique, Université de Bordeaux, Talence, France
| | - Chiadi U Onyike
- Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
| | - Peter B Barker
- Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
| | - Jeremy D Schmahmann
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Eva-Maria Ratai
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Sub H Subramony
- Norman Fixel Center for Neurological Disorders, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Thomas H Mareci
- Norman Fixel Center for Neurological Disorders, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Khalaf O Bushara
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Henry Paulson
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
| | - Thomas Klockgether
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute, Inserm, INRIA, CNRS, APHP, Paris, France
| | - Tetsuo Ashizawa
- Department of Neurology, The Houston Methodist Research Institute, Houston, Texas, USA
| | - Christophe Lenglet
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Gülin Öz
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
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Song Q, Wang C, Jiang W, Wang J, Li J, Guo H, Chen H, Han X. Pre-operative spinal cord perfusion quantified by DSC MRI as a predictor of post-operative prognosis in patients with cervical spondylotic myelopathy. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2024:10.1007/s00586-024-08417-0. [PMID: 39048843 DOI: 10.1007/s00586-024-08417-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 03/26/2024] [Accepted: 07/15/2024] [Indexed: 07/27/2024]
Abstract
OBJECTIVE This study aims to investigate the potential of preoperative blood supply condition measured by dynamic susceptibility contract (DSC) MRI in prediction of postoperative outcomes for patients with cervical spondylotic myelopathy (CSM). MATERIALS AND METHOD Thirty-nine patients (Age: 61 ± 7, male: 23, female: 16) with CSM who underwent laminoplasty were enrolled. All patients received DSC MRI before the operation. Five parameters include Enhance, rEnhance, full width at half maxima (FWHM), Slope1 and Slope2 in DSC MRI, were calculated at all the compressed spinal cord segments. Clinical outcomes were evaluated by modified Japanese Orthopaedic Association (mJOA) scores. Patients were divided into two groups based on mJOA recovery rate of 5 years: good recovery (> 50%) or poor recovery (≤ 50%). The difference between two groups were compared. The value of DSC MRI to CSM was evaluated by logistic and receiver operating characteristic (ROC) curve analysis. RESULTS There were 26 patients in good recovery group and 13 patients in poor recovery group. The baseline characteristics, including age, gender, preoperative mJOA score, and smoking status showed no significant difference between the two groups (all p > 0.05). The FWHM was significantly higher in the poor recovery group (9.77 ± 2.78) compared to the good recovery group (6.64 ± 1.65) (p = 0.002). Logistic regression analysis indicated that an increased FWHM was a significant risk factor for poor prognosis recovery (p = 0.013, OR = 0.392, 95%CI: 0.187-0.822). The AUC of FWHM for ROC was 0.843 (95% CI: 0.710-0.975) with a p value of 0.001. In addition, an FWHM greater than 5.87, with a sensitivity of 92.3% and specificity of 69.2%, was found to be an independent risk factor for poor postoperative recovery in patients with CSM. CONCLUSION In this study, we successfully quantified the spinal cord blood supply condition by DSC MRI technique. We found that an increase in FWHM was an independent risk factor for poor postoperative recovery in CSM patients. Specifically, patients with FWHM > 5.87 have a poor postoperative recovery.
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Affiliation(s)
- Qingpeng Song
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Chunyao Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Wen Jiang
- Department of Radiology, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Jinchao Wang
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Jiuheng Li
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
| | - Xiao Han
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
- Beijing Research Institute of Traumatology and Orthopaedics, Beijing, China.
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Muhammad F, Weber KA, Bédard S, Haynes G, Smith L, Khan AF, Hameed S, Gray K, McGovern K, Rohan M, Ding L, Van Hal M, Dickson D, Tamimi MA, Parrish T, Dhaher Y, Smith ZA. Cervical spinal cord morphometrics in degenerative cervical myelopathy: quantification using semi-automated normalized technique and correlation with neurological dysfunctions. Spine J 2024:S1529-9430(24)00886-6. [PMID: 39038658 DOI: 10.1016/j.spinee.2024.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/27/2024] [Accepted: 07/07/2024] [Indexed: 07/24/2024]
Abstract
BACKGROUND CONTEXT Degenerative cervical myelopathy (DCM) is characterized by spinal cord atrophy. Accurate estimation of spinal cord atrophy is key to the understanding of neurological diseases, including DCM. However, its clinical application is hampered by difficulties in its precise and consistent estimation due to significant variability in spinal cord morphometry along the cervical spine, both within and between individuals. PURPOSE To characterize morphometrics of the compressed spinal cord in DCM patients. We employed our semiautomated analysis framework that incorporates the Spinal Cord Toolbox (SCT) and a normalization approach to effectively address the challenges posed by cord compression in these patients. Additionally, we examined the clinical relevance of these morphometric measures to enhance our understanding of DCM pathophysiology. STUDY DESIGN Prospective study. PATIENT SAMPLE This study investigated 36 DCM patients and 31 healthy controls (HCs). OUTCOME MEASURES Clinical scores including 9-hole peg test for hand dexterity, hand grip strength, balance, gait speed, modified Japanese Orthopaedic Association (mJOA) score, and imaging-based spinal cord morphometrics. METHOD Using the generic spine acquisition protocol and our semiautomated analysis pipeline, spinal cord morphometrics, including cross-sectional area (CSA), anterior-posterior (AP) and transverse (RL) diameters, eccentricity, and solidity, were estimated from sagittal T2w magnetic resonance imaging (MRI) images using the Spinal Cord Toolbox (SCT). Normalized metrics were extracted from the C1 to C7 vertebral levels and compared between DCM patients and HC. Morphometric data at regions of maximum spinal cord compression (MSCC) were correlated with the clinical scores. A subset of participants underwent follow-up scans at 6 months to monitor longitudinal changes in spinal cord atrophy. RESULTS Spinal cord morphometric data were normalized against the healthy population morphometry (PAM50 database) and extracted for all participants. DCM patients showed a notable reduction in CSA, AP, and RL diameter across all vertebral levels compared to HC. MSCC metrics correlated significantly with clinical scores like dexterity, grip strength, and mJOA scores. Longitudinal analysis indicated a decrease in CSA and worsening clinical scores in DCM patients. CONCLUSION Our processing pipeline offers a reliable method for assessing spinal cord compression in DCM patients. Normalized spinal cord morphometrics, particularly the CSA could have potential for monitoring DCM disease severity and progression, guiding treatment decisions. Furthermore, to our knowledge our study is the first to apply the generic spinal cord acquisition protocol, ensuring consistent imaging across different MRI scanners and settings. Coupled with our semiautomated analysis pipeline, this protocol is key for the detailed morphometric characterization of compressed spinal cords in patients with DCM, a disease that is both complex and heterogenous. This study was funded by the National Institute of Neurological Disorders and Stroke (NINDS) (K23:NS091430) and (R01: NS129852-01A1).
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Affiliation(s)
- Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | - Kenneth A Weber
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, Palo Alto, CA, USA
| | - Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Lonnie Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Sanaa Hameed
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Kathyrn Gray
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Kathleen McGovern
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Michael Rohan
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Lei Ding
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Michael Van Hal
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Douglas Dickson
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mazin Al Tamimi
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Todd Parrish
- Department of Radiology, Fienberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Yasin Dhaher
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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Alvi MA, Pedro KM, Quddusi AI, Fehlings MG. Advances and Challenges in Spinal Cord Injury Treatments. J Clin Med 2024; 13:4101. [PMID: 39064141 PMCID: PMC11278467 DOI: 10.3390/jcm13144101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 07/03/2024] [Accepted: 07/05/2024] [Indexed: 07/28/2024] Open
Abstract
Spinal cord injury (SCI) is a debilitating condition that is associated with long-term physical and functional disability. Our understanding of the pathogenesis of SCI has evolved significantly over the past three decades. In parallel, significant advances have been made in optimizing the management of patients with SCI. Early surgical decompression, adequate bony decompression and expansile duraplasty are surgical strategies that may improve neurological and functional outcomes in patients with SCI. Furthermore, advances in the non-surgical management of SCI have been made, including optimization of hemodynamic management in the critical care setting. Several promising therapies have also been investigated in pre-clinical studies, with some being translated into clinical trials. Given the recent interest in advancing precision medicine, several investigations have been performed to delineate the role of imaging, cerebral spinal fluid (CSF) and serum biomarkers in predicting outcomes and curating individualized treatment plans for SCI patients. Finally, technological advancements in biomechanics and bioengineering have also found a role in SCI management in the form of neuromodulation and brain-computer interfaces.
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Affiliation(s)
- Mohammed Ali Alvi
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada; (M.A.A.); (K.M.P.); (A.I.Q.)
| | - Karlo M. Pedro
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada; (M.A.A.); (K.M.P.); (A.I.Q.)
- Department of Surgery and Spine Program, University of Toronto, Toronto, ON M5T 1P5, Canada
| | - Ayesha I. Quddusi
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada; (M.A.A.); (K.M.P.); (A.I.Q.)
| | - Michael G. Fehlings
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada; (M.A.A.); (K.M.P.); (A.I.Q.)
- Department of Surgery and Spine Program, University of Toronto, Toronto, ON M5T 1P5, Canada
- Division of Neurosurgery, Krembil Neuroscience Centre, Toronto Western Hospital, University Health Network, Toronto, ON M5T 2S8, Canada
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Chernysh AA, Loftus DH, Zheng B, Arditi J, Leary OP, Fridley JS. Utility of Diffusion Tensor Imaging for Prognosis and Management of Cervical Spondylotic Myelopathy: A PRISMA Review. World Neurosurg 2024; 190:88-98. [PMID: 38986943 DOI: 10.1016/j.wneu.2024.07.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 07/02/2024] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
OBJECTIVE As advances are made in quantitative magnetic resonance imaging, specifically diffusion tensor imaging, researchers have investigated its potential to serve as a biomarker of disease or prognosticator for postoperative recovery in the management of cervical spondylotic myelopathy. Here, we narratively review the current state of the emerging literature, describing areas of consensus and disagreement. METHODS In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, we queried 2 large databases for original manuscripts published in English and systematically produced a narrative review of the use of diffusion tensor imaging in the management of cervical spondylotic myelopathy. RESULTS Of the 437 manuscripts initially returned in our query, 29 met the final inclusion criteria, and data were extracted regarding diffusion tensor imaging indices and their relationships with clinical outcomes following surgery. Preoperative fractional anisotropy was most commonly found to correlate closely with postsurgical clinical outcomes, though results were mixed. CONCLUSIONS Preoperative fractional anisotropy most frequently and best correlates with functional outcomes following surgery for cervical spondylotic myelopathy, according to a review of the current literature. The findings were not universal and at times contradictory, highlighting the need for high-quality future investigations to better define the utility of diffusion tensor imaging in spinal disease.
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Affiliation(s)
- Alexander A Chernysh
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA.
| | - David H Loftus
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Bryan Zheng
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Jonathan Arditi
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Owen P Leary
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
| | - Jared S Fridley
- Warren Alpert Medical School of Brown University, Rhode Island Hospital, Department of Neurosurgery, Providence, Rhode Island, USA
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Smith AC, Ahmed RU, Weber KA, Negahdar M, Gibson D, Boakye M, Rejc E. Spinal cord lesion MRI and behavioral outcomes in a miniature pig model of spinal cord injury: exploring preclinical potential through an ad hoc comparison with human SCI. Spinal Cord Ser Cases 2024; 10:44. [PMID: 38977671 PMCID: PMC11231227 DOI: 10.1038/s41394-024-00658-x] [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: 01/22/2024] [Revised: 06/24/2024] [Accepted: 07/02/2024] [Indexed: 07/10/2024] Open
Abstract
STUDY DESIGN prospective case series of Yucatan miniature pig spinal cord contusion injury model with comparison to human cases of spinal cord injury (SCI). OBJECTIVES to describe magnetic resonance imaging (MRI) measures of spinal cord lesion severity along with estimates of lateral corticospinal tracts spared neural tissue in both a less severe and more severe contusion SCI model, as well as to describe their corresponding behavioral outcome changes. SETTING University laboratory setting. METHODS Following a more severe and less severe SCI, each pig underwent spinal cord MRI to measure lesion characteristics, along with locomotor and urodynamics outcomes testing. RESULTS In the pig with more severe SCI, locomotor and urodynamic outcomes were poor, and both the spinal cord lesion volume and damage estimates to the lateral corticospinal tracts were large. Conversely, in the pig with less severe SCI, locomotor and urodynamic outcomes were favorable, with the spinal cord lesion volume and damage estimates to the lateral corticospinal tracts being less pronounced. For two human cases matched on estimates of damage to the lateral corticospinal tract regions, the clinical presentations were similar to the pig outcomes, with more limited mobility and more limited bladder functional independence in the more severe case. CONCLUSIONS Our initial findings contribute valuable insights to the emergent field of MRI-based evaluation of spinal cord lesions in pig models, offering a promising avenue for understanding and potentially improving outcomes in spinal cord injuries.
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Affiliation(s)
- Andrew C Smith
- University of Colorado School of Medicine, Department of Physical Medicine and Rehabilitation, Aurora, CO, USA.
| | - Rakib Uddin Ahmed
- University of Louisville School of Medicine, Department of Neurosurgery, Louisville, KY, USA
| | - Kenneth A Weber
- Stanford University School of Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Palo Alto, CA, USA
| | - MohammadJavad Negahdar
- University of Louisville School of Medicine, Department of Radiology, Louisville, KY, USA
| | - Destiny Gibson
- University of Louisville School of Medicine, Department of Neurosurgery, Louisville, KY, USA
| | - Maxwell Boakye
- University of Louisville School of Medicine, Department of Neurosurgery, Louisville, KY, USA
| | - Enrico Rejc
- University of Udine, Department of Medicine, Udine, Italy
- Kessler Foundation, West Orange, NJ, USA
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Fan G, Li Y, Wang D, Zhang J, Du X, Liu H, Liao X. Automatic segmentation of dura for quantitative analysis of lumbar stenosis: A deep learning study with 518 CT myelograms. J Appl Clin Med Phys 2024; 25:e14378. [PMID: 38729652 PMCID: PMC11244674 DOI: 10.1002/acm2.14378] [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: 01/31/2024] [Revised: 04/01/2024] [Accepted: 04/18/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND The diagnosis of lumbar spinal stenosis (LSS) can be challenging because radicular pain is not often present in the culprit-level localization. Accurate segmentation and quantitative analysis of the lumbar dura on radiographic images are key to the accurate differential diagnosis of LSS. The aim of this study is to develop an automatic dura-contouring tool for radiographic quantification on computed tomography myelogram (CTM) for patients with LSS. METHODS A total of 518 CTM cases with or without lumbar stenosis were included in this study. A deep learning (DL) segmentation algorithm 3-dimensional (3D) U-Net was deployed. A total of 210 labeled cases were used to develop the dura-contouring tool, with the ratio of the training, independent testing, and external validation datasets being 150:30:30. The Dice score (DCS) was the primary measure to evaluate the segmentation performance of the 3D U-Net, which was subsequently developed as the dura-contouring tool to segment another unlabeled 308 CTM cases with LSS. Automatic masks of 446 slices on the stenotic levels were then meticulously reviewed and revised by human experts, and the cross-sectional area (CSA) of the dura was compared. RESULTS The mean DCS of the 3D U-Net were 0.905 ± 0.080, 0.933 ± 0.018, and 0.928 ± 0.034 in the five-fold cross-validation, the independent testing, and the external validation datasets, respectively. The segmentation performance of the dura-contouring tool was also comparable to that of the second observer (the human expert). With the dura-contouring tool, only 59.0% (263/446) of the automatic masks of the stenotic slices needed to be revised. In the revised cases, there were no significant differences in the dura CSA between automatic masks and corresponding revised masks (p = 0.652). Additionally, a strong correlation of dura CSA was found between the automatic masks and corresponding revised masks (r = 0.805). CONCLUSIONS A dura-contouring tool was developed that could automatically segment the dural sac on CTM, and it demonstrated high accuracy and generalization ability. Additionally, the dura-contouring tool has the potential to be applied in patients with LSS because it facilitates the quantification of the dural CSA on stenotic slices.
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Affiliation(s)
- Guoxin Fan
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
- Department of Spine Surgery, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yufeng Li
- Department of Sports Medicine, Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Dongdong Wang
- Department of Orthopaedics, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Jianjin Zhang
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Xiaokang Du
- Department of Orthopedics, The People's Hospital of Wenshang County, Wenshang, Shandong, China
| | - Huaqing Liu
- Artificial Intelligence Innovation Center, Research Institute of Tsinghua PearlRiverDelta, Guangzhou, China
| | - Xiang Liao
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
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10
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Cook SR, Vasamreddy K, Combes A, Vandekar S, Visagie M, Houston D, Wald L, Kumar A, McGrath M, McKnight CD, Bagnato F, Smith SA, O’Grady KP. Biological variation in cervical spinal cord MRI morphometry in healthy individuals and people with multiple sclerosis. J Neuroimaging 2024; 34:466-474. [PMID: 38858847 PMCID: PMC11236499 DOI: 10.1111/jon.13219] [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: 02/06/2024] [Revised: 05/06/2024] [Accepted: 05/24/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND AND PURPOSE Conclusions from prior literature regarding the impact of sex, age, and height on spinal cord (SC) MRI morphometrics are conflicting, while the effect of body weight on SC morphometrics has been found to be nonsignificant. The purpose of this case-control study is to assess the associations between cervical SC MRI morphometric parameters and age, sex, height, and weight to establish their potential role as confounding variables in a clinical study of people with multiple sclerosis (MS) compared to a cohort of healthy volunteers. METHODS Sixty-nine healthy volunteers and 31 people with MS underwent cervical SC MRI at 3 Tesla field strength. Images were centered at the C3/C4 intervertebral disc and processed using Spinal Cord Toolbox v.4.0.2. Mixed-effects linear regression models were used to evaluate the effects of biological variables and disease status on morphometric parameters. RESULTS Sex, age, and height had significant effects on cord and gray matter (GM) cross-sectional area (CSA) as well as the GM:cord CSA ratio. There were no significant effects of body weight on morphometric parameters. The effect of MS disease duration on cord CSA in the C4 level was significant when controlling for all other variables. CONCLUSIONS Studies of disease-related changes in SC morphometry should control for sex, age, and height to account for physiological variation.
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Affiliation(s)
- Sarah R. Cook
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Yale University, New Haven, CT, United States
| | - Kritin Vasamreddy
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Anna Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mereze Visagie
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Delaney Houston
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lily Wald
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Ashwin Kumar
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Megan McGrath
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 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 Center, Nashville, TN, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Kristin P. O’Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
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11
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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 PMCID: PMC11234946 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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12
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Al-Shaari H, Heales CJ, Fulford J. Within-participants reliability and measurement error of magnetization transfer imaging determinations within the healthy cervical spinal cord. Radiography (Lond) 2024; 30:1085-1092. [PMID: 38772065 DOI: 10.1016/j.radi.2024.04.027] [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: 02/03/2024] [Revised: 04/15/2024] [Accepted: 04/28/2024] [Indexed: 05/23/2024]
Abstract
PURPOSE To assess the within-participant reliability and measurement error in the determination of MTR in the healthy human cervical spinal cord. METHODS AND MATERIALS A total of twenty healthy controls (10 male, mean ± sd age: 33.9 ± 3.5 years, 10 females, mean ± sd age: 47.5 ± 14.4 years), with no family history of any neurological disorders or a contraindication to MRI scanning were recruited over a period of two months. Each participant was scanned twice with a 3T MRI scanner using standard MTI sequences. Spinal Cord Toolbox (v5.4) was used for image post-processing. Data were first segmented and then registered to a template and then MTR was computed. The within-participant coefficients of variation (CV%), single and average within-participants intraclass correlation coefficients (ICC) and Bland-Altman plots were determined for MT values over the volume between the 2nd and 5th cervical vertebrae for the total WM and for specific WM regions: dorsal column (DC), ventral column (VC) and lateral column (LC). RESULTS MTR showed poor to excellent within-participant reliability for the total WM, DC, VC and LC with single/average ICC values of 0.03/0.06, 0.10/0.18, 0.39/0.75, and 0.001/0.002, respectively, and the CV% reported an acceptable variation with values less than 10%. The Bland-Altman plots showed good within-participant agreement between the scan-rescan values. CONCLUSION This study demonstrates that clinical trials using MTI technique are feasible and shows that quantitative MTI can monitor tissue changes in degenerative WM patients. IMPLICATIONS FOR PRACTICE MTI with its MTR index provide broad assessment of the integrity of white matter tissue and are being studied widely in brain as a diagnostic tool for the assessment of different neurological diseases.
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Affiliation(s)
- H Al-Shaari
- Faculty of Health and Life Sciences, Medical Imaging Department, University of Exeter, Exeter, UK; College of Applied Medical Sciences, Radiological Sciences Department, Najran University, Najran, 61441, Kingdom of Saudi Arabia.
| | - C J Heales
- Faculty of Health and Life Sciences, Medical Imaging Department, University of Exeter, Exeter, UK.
| | - J Fulford
- Faculty of Health and Life Sciences, Medical Imaging Department, University of Exeter, Exeter, UK.
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13
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Windsor R, Jamaludin A, Kadir T, Zisserman A. Automated detection, labelling and radiological grading of clinical spinal MRIs. Sci Rep 2024; 14:14993. [PMID: 38951574 PMCID: PMC11217300 DOI: 10.1038/s41598-024-64580-w] [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: 11/19/2023] [Accepted: 06/11/2024] [Indexed: 07/03/2024] Open
Abstract
Spinal magnetic resonance (MR) scans are a vital tool for diagnosing the cause of back pain for many diseases and conditions. However, interpreting clinically useful information from these scans can be challenging, time-consuming and hard to reproduce across different radiologists. In this paper, we alleviate these problems by introducing a multi-stage automated pipeline for analysing spinal MR scans. This pipeline first detects and labels vertebral bodies across several commonly used sequences (e.g. T1w, T2w and STIR) and fields of view (e.g. lumbar, cervical, whole spine). Using these detections it then performs automated diagnosis for several spinal disorders, including intervertebral disc degenerative changes in T1w and T2w lumbar scans, and spinal metastases, cord compression and vertebral fractures. To achieve this, we propose a new method of vertebrae detection and labelling, using vector fields to group together detected vertebral landmarks and a language-modelling inspired beam search to determine the corresponding levels of the detections. We also employ a new transformer-based architecture to perform radiological grading which incorporates context from multiple vertebrae and sequences, as a real radiologist would. The performance of each stage of the pipeline is tested in isolation on several clinical datasets, each consisting of 66 to 421 scans. The outputs are compared to manual annotations of expert radiologists, demonstrating accurate vertebrae detection across a range of scan parameters. Similarly, the model's grading predictions for various types of disc degeneration and detection of spinal metastases closely match those of an expert radiologist. To aid future research, our code and trained models are made publicly available.
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Affiliation(s)
- Rhydian Windsor
- Visual Geometry Group, Department of Engineering Science, University of Oxford, Oxford, UK.
| | - Amir Jamaludin
- Visual Geometry Group, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Timor Kadir
- Visual Geometry Group, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Andrew Zisserman
- Visual Geometry Group, Department of Engineering Science, University of Oxford, Oxford, UK
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14
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Freund P, Boller V, Emmenegger TM, Akbar M, Hupp M, Pfender N, Wheeler‐Kingshott CAMG, Cohen‐Adad J, Fehlings MG, Curt A, Seif M. Quantifying neurodegeneration of the cervical cord and brain in degenerative cervical myelopathy: A multicentre study using quantitative magnetic resonance imaging. Eur J Neurol 2024; 31:e16297. [PMID: 38713645 PMCID: PMC11235710 DOI: 10.1111/ene.16297] [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: 12/22/2023] [Revised: 03/06/2024] [Accepted: 03/21/2024] [Indexed: 05/09/2024]
Abstract
BACKGROUND AND PURPOSE Simultaneous assessment of neurodegeneration in both the cervical cord and brain across multiple centres can enhance the effectiveness of clinical trials. Thus, this study aims to simultaneously assess microstructural changes in the cervical cord and brain above the stenosis in degenerative cervical myelopathy (DCM) using quantitative magnetic resonance imaging (MRI) in a multicentre study. METHODS We applied voxelwise analysis with a probabilistic brain/spinal cord template embedded in statistical parametric mappin (SPM-BSC) to process multi parametric mapping (MPM) including effective transverse relaxation rate (R2*), longitudinal relaxation rate (R1), and magnetization transfer (MT), which are indirectly sensitive to iron and myelin content. Regression analysis was conducted to establish associations between neurodegeneration and clinical impairment. Thirty-eight DCM patients (mean age ± SD = 58.45 ± 11.47 years) and 38 healthy controls (mean age ± SD = 41.18 ± 12.75 years) were recruited at University Hospital Balgrist, Switzerland and Toronto Western Hospital, Canada. RESULTS Remote atrophy was observed in the cervical cord (p = 0.002) and in the left thalamus (0.026) of the DCM group. R1 was decreased in the periaqueductal grey matter (p = 0.014), thalamus (p = 0.001), corpus callosum (p = 0.0001), and cranial corticospinal tract (p = 0.03). R2* was increased in the primary somatosensory cortices (p = 0.008). Sensory impairments were associated with increased iron-sensitive R2* in the thalamus and periaqueductal grey matter in DCM. CONCLUSIONS Simultaneous assessment of the spinal cord and brain revealed DCM-induced demyelination, iron deposition, and atrophy. The extent of remote neurodegeneration was associated with sensory impairment, highlighting the intricate and expansive nature of microstructural neurodegeneration in DCM, reaching beyond the stenosis level.
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Affiliation(s)
- Patrick Freund
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Viveka Boller
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Tim M. Emmenegger
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Muhammad Akbar
- Spine Program Division of NeurosurgeryUniversity of Toronto and Toronto Western HospitalTorontoOntarioCanada
| | - Markus Hupp
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Nikolai Pfender
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Claudia Angela Michela Gandini Wheeler‐Kingshott
- NMR Research Unit, Queen Square MS CentreUniversity College London (UCL) Queen Square Institute of Neurology, Faculty of Brain SciencesLondonUK
- Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
- Digital Neuroscience Research UnitIRCCS Mondino FoundationPaviaItaly
| | - Julien Cohen‐Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique MontrealMontrealQuebecCanada
- Functional Neuroimaging Unit, CRIUGMUniversity of MontrealMontrealQuebecCanada
| | - Michael G. Fehlings
- Spine Program Division of NeurosurgeryUniversity of Toronto and Toronto Western HospitalTorontoOntarioCanada
| | - Armin Curt
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
| | - Maryam Seif
- Spinal Cord Injury CentreUniversity Hospital Balgrist, University of ZurichZurichSwitzerland
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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15
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Qi Q, Wang L, Yang B, Jia Y, Wang Y, Xin H, Zheng W, Chen X, Chen Q, Li F, Du J, Lu J, Chen N. The relationship between the structural changes in the cervical spinal cord and sensorimotor function of children with thoracolumbar spinal cord injury (TLSCI). Spinal Cord 2024; 62:414-420. [PMID: 38824252 PMCID: PMC11230908 DOI: 10.1038/s41393-024-01000-w] [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: 12/29/2023] [Revised: 05/15/2024] [Accepted: 05/23/2024] [Indexed: 06/03/2024]
Abstract
STUDY DESIGN Cross-sectional study. OBJECTIVES To study the relationship between the structural changes in the cervical spinal cord (C2/3 level) and the sensorimotor function of children with traumatic thoracolumbar spinal cord injury (TLSCI) and to discover objective imaging biomarkers to evaluate its functional status. SETTING Xuanwu Hospital, Capital Medical University, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, China. METHODS 30 children (age range 5-13 years) with TLSCI and 11 typically developing (TD) children (age range 6-12 years) were recruited in this study. Based on whether there is preserved motor function below the neurological level of injury (NLI), the children with TLSCI are divided into the AIS A/B group (motor complete) and the AIS C/D group (motor incomplete). A Siemens Verio 3.0 T MR scanner was used to acquire 3D high-resolution anatomic scans covering the head and upper cervical spinal cord. Morphologic parameters of the spinal cord at the C2/3 level, including cross-sectional area (CSA), anterior-posterior width (APW), and left-right width (LRW) were obtained using the spinal cord toolbox (SCT; https://www.nitrc.org/projects/sct ). Correlation analyses were performed to compare the morphologic spinal cord parameters and clinical scores determined by the International Standard for Neurological Classification of Spinal Cord Injuries (ISNCSCI) examination. RESULTS CSA and LRW in the AIS A/B group were significantly lower than those in the TD group and the AIS C/D group. LRW was the most sensitive imaging biomarker to differentiate the AIS A/B group from the AIS C/D group. Both CSA and APW were positively correlated with ISNCSCI sensory scores. CONCLUSIONS Quantitative measurement of the morphologic spinal cord parameters of the cervical spinal cord can be used as an objective imaging biomarker to evaluate the neurological function of children with TLSCI. Cervical spinal cord atrophy in children after TLSCI was correlated with clinical grading; CSA and APW can reflect sensory function. Meanwhile, LRW has the potential to be an objective imaging biomarker for evaluating motor function preservation.
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Affiliation(s)
- Qunya Qi
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Ling Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Beining Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Yulong Jia
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Yu Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Haotian Xin
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Weimin Zheng
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, 100020, Beijing, China
| | - Xin Chen
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, 100050, Beijing, China
| | - Fang Li
- Department of Rehabilitation Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
| | - Jubao Du
- Department of Rehabilitation Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China
| | - Nan Chen
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, 100053, Beijing, China.
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16
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Mobarak-Abadi M, Mahmoudi-Aznaveh A, Dehghani H, Zarei M, Vahdat S, Doyon J, Khatibi A. DeepRetroMoCo: deep neural network-based retrospective motion correction algorithm for spinal cord functional MRI. Front Psychiatry 2024; 15:1323109. [PMID: 39006826 PMCID: PMC11239515 DOI: 10.3389/fpsyt.2024.1323109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 05/21/2024] [Indexed: 07/16/2024] Open
Abstract
Background and purpose There are distinct challenges in the preprocessing of spinal cord fMRI data, particularly concerning the mitigation of voluntary or involuntary movement artifacts during image acquisition. Despite the notable progress in data processing techniques for movement detection and correction, applying motion correction algorithms developed for the brain cortex to the brainstem and spinal cord remains a challenging endeavor. Methods In this study, we employed a deep learning-based convolutional neural network (CNN) named DeepRetroMoCo, trained using an unsupervised learning algorithm. Our goal was to detect and rectify motion artifacts in axial T2*-weighted spinal cord data. The training dataset consisted of spinal cord fMRI data from 27 participants, comprising 135 runs for training and 81 runs for testing. Results To evaluate the efficacy of DeepRetroMoCo, we compared its performance against the sct_fmri_moco method implemented in the spinal cord toolbox. We assessed the motion-corrected images using two metrics: the average temporal signal-to-noise ratio (tSNR) and Delta Variation Signal (DVARS) for both raw and motion-corrected data. Notably, the average tSNR in the cervical cord was significantly higher when DeepRetroMoCo was utilized for motion correction, compared to the sct_fmri_moco method. Additionally, the average DVARS values were lower in images corrected by DeepRetroMoCo, indicating a superior reduction in motion artifacts. Moreover, DeepRetroMoCo exhibited a significantly shorter processing time compared to sct_fmri_moco. Conclusion Our findings strongly support the notion that DeepRetroMoCo represents a substantial improvement in motion correction procedures for fMRI data acquired from the cervical spinal cord. This novel deep learning-based approach showcases enhanced performance, offering a promising solution to address the challenges posed by motion artifacts in spinal cord fMRI data.
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Affiliation(s)
- Mahdi Mobarak-Abadi
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | | | - Hamed Dehghani
- Neuro Imaging and Analysis Group (NIAG), Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Shahabeddin Vahdat
- Department of Applied Physiology and Kinesiology (DAPK), University of Florida, Gainesville, FL, United States
| | - Julien Doyon
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Ali Khatibi
- Centre of Precision Rehabilitation for Spinal Pain, School of Sports Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
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17
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Dabbagh A, Horn U, Kaptan M, Mildner T, Müller R, Lepsien J, Weiskopf N, Brooks JCW, Finsterbusch J, Eippert F. Reliability of task-based fMRI in the dorsal horn of the human spinal cord. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.22.572825. [PMID: 38187724 PMCID: PMC10769329 DOI: 10.1101/2023.12.22.572825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across two consecutive days in 40 healthy volunteers. We assessed the test-retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat pain stimuli (1s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both β-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with fair reliability across days. Taken together, these results demonstrate that heat pain stimuli as short as one second are able to evoke a robust and spatially specific BOLD response, which is however strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.
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Affiliation(s)
- Alice Dabbagh
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ulrike Horn
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Merve Kaptan
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, CA, USA
| | - Toralf Mildner
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roland Müller
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jöran Lepsien
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
| | - Jonathan C W Brooks
- School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), Norwich, United Kingdom
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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18
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Rezende TJR, Adanyaguh I, Barsottini OGP, Bender B, Cendes F, Coutinho L, Deistung A, Dogan I, Durr A, Fernandez-Ruiz J, Göricke SL, Grisoli M, Hernandez-Castillo CR, Lenglet C, Mariotti C, Martinez ARM, Massuyama BK, Mochel F, Nanetti L, Nigri A, Ono SE, Öz G, Pedroso JL, Reetz K, Synofzik M, Teive H, Thomopoulos SI, Thompson PM, Timmann D, van de Warrenburg BPC, van Gaalen J, França MC, Harding IH. Genotype-specific spinal cord damage in spinocerebellar ataxias: an ENIGMA-Ataxia study. J Neurol Neurosurg Psychiatry 2024; 95:682-690. [PMID: 38383154 PMCID: PMC11187354 DOI: 10.1136/jnnp-2023-332696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/17/2024] [Indexed: 02/23/2024]
Abstract
BACKGROUND Spinal cord damage is a feature of many spinocerebellar ataxias (SCAs), but well-powered in vivo studies are lacking and links with disease severity and progression remain unclear. Here we characterise cervical spinal cord morphometric abnormalities in SCA1, SCA2, SCA3 and SCA6 using a large multisite MRI dataset. METHODS Upper spinal cord (vertebrae C1-C4) cross-sectional area (CSA) and eccentricity (flattening) were assessed using MRI data from nine sites within the ENIGMA-Ataxia consortium, including 364 people with ataxic SCA, 56 individuals with preataxic SCA and 394 nonataxic controls. Correlations and subgroup analyses within the SCA cohorts were undertaken based on disease duration and ataxia severity. RESULTS Individuals in the ataxic stage of SCA1, SCA2 and SCA3, relative to non-ataxic controls, had significantly reduced CSA and increased eccentricity at all examined levels. CSA showed large effect sizes (d>2.0) and correlated with ataxia severity (r<-0.43) and disease duration (r<-0.21). Eccentricity correlated only with ataxia severity in SCA2 (r=0.28). No significant spinal cord differences were evident in SCA6. In preataxic individuals, CSA was significantly reduced in SCA2 (d=1.6) and SCA3 (d=1.7), and the SCA2 group also showed increased eccentricity (d=1.1) relative to nonataxic controls. Subgroup analyses confirmed that CSA and eccentricity are abnormal in early disease stages in SCA1, SCA2 and SCA3. CSA declined with disease progression in all, whereas eccentricity progressed only in SCA2. CONCLUSIONS Spinal cord abnormalities are an early and progressive feature of SCA1, SCA2 and SCA3, but not SCA6, which can be captured using quantitative MRI.
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Affiliation(s)
- Thiago Junqueira Ribeiro Rezende
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Isaac Adanyaguh
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Fernando Cendes
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Leo Coutinho
- Graduate program of Internal Medicine, Internal Medicine Department, Hospital de Clínicas, Federal University of Paraná, Curitiba, Brazil
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), University Medicine Halle, Halle (Saale), Germany
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute (ICM), Pitié-Salpêtrière Hospital, AP-HP, INSERM, CNRS, University Hospital Pitié-Salpêtrière, Paris, France
| | - Juan Fernandez-Ruiz
- Neuropsychology Laboratory, Department of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Sophia L Göricke
- Institute of Diagnostic and Interventional Radiology and Neuroradiology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Marina Grisoli
- Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Caterina Mariotti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Alberto R M Martinez
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Breno K Massuyama
- Department of Neurology, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Fanny Mochel
- Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière University Hospital, Paris, France
| | - Lorenzo Nanetti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Anna Nigri
- Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Sergio E Ono
- Clínica DAPI - Diagnóstico Avançado Por Imagem, Curitiba, Brazil
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - José Luiz Pedroso
- Department of Neurology, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Helio Teive
- Graduate program of Internal Medicine, Internal Medicine Department, Hospital de Clínicas, Federal University of Paraná, Curitiba, Brazil
- Movement Disorders Unit, Neurology Service, Internal Medicine Department, Hospital de Clínicas, Federal University of Paraná, Curitiba, Brazil
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Bart P C van de Warrenburg
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - Judith van Gaalen
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - Marcondes C França
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Ian H Harding
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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19
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Wang J, Huang J, Cui B, Yang H, Tian D, Ma J, Duan W, Dong H, Chen Z, Lu J. Diffusion Tensor Imaging Identifies Cervical Spondylosis, Myelitis, and Spinal Cord Tumors. Diagnostics (Basel) 2024; 14:1225. [PMID: 38928642 PMCID: PMC11202471 DOI: 10.3390/diagnostics14121225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 05/30/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND Diffusion tensor imaging (DTI) has been increasingly recognized for its capability to study microstructural changes in the neuropathology of brain diseases. However, the optimal DTI metric and its diagnostic utility for a variety of spinal cord diseases are still under investigation. PURPOSE To evaluate the diagnostic efficacy of DTI metrics for differentiating between cervical spondylosis, myelitis, and spinal tumors. METHODS This retrospective study analyzed DTI scans from 68 patients (22 with cervical spondylosis, 23 with myelitis, and 23 with spinal tumors). DTI indicators, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), were calculated. The Kruskal-Wallis test was used to compare these indicators, followed by Receiver Operating Characteristic (ROC) curve analysis, to evaluate the diagnostic efficacy of each indicator across disease pairs. Additionally, we explored the correlations of DTI indicators with specific clinical measurements. RESULTS FA values were significantly lower in tumor patients compared to those with cervical spondylosis (p < 0.0001) and myelitis (p < 0.05). Additionally, tumor patients exhibited significantly elevated MD and RD values relative to the spondylosis and myelitis groups. ROC curve analysis underscored FA's superior discriminative performance, with an area under the curve (AUC) of 0.902 for differentiating tumors from cervical spondylosis, and an AUC of 0.748 for distinguishing cervical myelitis from spondylosis. Furthermore, a significant negative correlation was observed between FA values and Expanded Disability Status Scores (EDSSs) in myelitis patients (r = -0.62, p = 0.002), as well as between FA values and Ki-67 scores in tumor patients (r = -0.71, p = 0.0002). CONCLUSION DTI indicators, especially FA, have the potential in distinguishing spondylosis, myelitis, and spinal cord tumors. The significant correlation between FA values and clinical indicators highlights the value of FA in the clinical assessment and prognosis of spinal diseases and may be applied in diagnostic protocols in the future.
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Affiliation(s)
- Jiyuan Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
| | - Jing Huang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
| | - Defeng Tian
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
| | - Jie Ma
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
| | - Wanru Duan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (W.D.); (Z.C.)
| | - Huiqing Dong
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China;
| | - Zan Chen
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (W.D.); (Z.C.)
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (J.W.); (J.H.); (B.C.); (H.Y.); (D.T.); (J.M.)
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing 100053, China
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20
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Tan Y, Shao Z, Wu K, Zhou F, He L. Resting-state brain plasticity is associated with the severity in cervical spondylotic myelopathy. BMC Musculoskelet Disord 2024; 25:450. [PMID: 38844898 PMCID: PMC11155054 DOI: 10.1186/s12891-024-07539-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/23/2024] [Indexed: 06/10/2024] Open
Abstract
OBJECTIVE To investigate the brain mechanism of non-correspondence between imaging presentations and clinical symptoms in cervical spondylotic myelopathy (CSM) patients and to test the utility of brain imaging biomarkers for predicting prognosis of CSM. METHODS Forty patients with CSM (22 mild-moderate CSM, 18 severe CSM) and 25 healthy controls (HCs) were recruited for rs-fMRI and cervical spinal cord diffusion tensor imaging (DTI) scans. DTI at the spinal cord (level C2/3) with fractional anisotropy (FA) and degree centrality (DC) were recorded. Then one-way analysis of covariance (ANCOVA) was conducted to detect the group differences in the DC and FA values across the three groups. Pearson correlation analysis was then separately performed between JOA with FA and DC. RESULTS Among them, degree centrality value of left middle temporal gyrus exhibited a progressive increase in CSM groups compared with HCs, the DC value in severe CSM group was higher compared with mild-moderate CSM group. (P < 0.05), and the DC values of the right superior temporal gyrus and precuneus showed a decrease after increase. Among them, DC values in the area of precuneus in severe CSM group were significantly lower than those in mild-moderate CSM and HCs. (P < 0.05). The fractional anisotropy (FA) values of the level C2/3 showed a progressive decrease in different clinical stages, that severe CSM group was the lowest, significantly lower than those in mild-moderate CSM and HCs (P < 0.05). There was negative correlation between DC value of left middle temporal gyrus and JOA scores (P < 0.001), and the FA values of dorsal column in the level C2/3 positively correlated with the JOA scores (P < 0.001). CONCLUSION Structural and functional changes have taken place in the cervical spinal cord and brain of CSM patients. The Brain reorganization plays an important role in maintaining the symptoms and signs of CSM, aberrant DC values in the left middle temporal gyrus may be the possible mechanism of inconsistency between imaging findings and clinical symptoms. Degree centrality is a potentially useful prognostic functional biomarker in cervical spondylotic myelopathy.
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Affiliation(s)
- Yongming Tan
- Department of Radiology, First affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Clinical Research Center for Medical Imaging of Jiangxi Province, Nanchang, Jiangxi Province, China
| | - Ziwei Shao
- Department of Radiology, First affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Clinical Research Center for Medical Imaging of Jiangxi Province, Nanchang, Jiangxi Province, China
| | - Kaifu Wu
- Department of Radiology, Wuhan Central Hospital, Wuhan, China
| | - Fuqing Zhou
- Department of Radiology, First affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Clinical Research Center for Medical Imaging of Jiangxi Province, Nanchang, Jiangxi Province, China
| | - Laichang He
- Department of Radiology, First affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China.
- Clinical Research Center for Medical Imaging of Jiangxi Province, Nanchang, Jiangxi Province, China.
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21
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Al-Shaari H, Fulford J, Heales CJ. Diffusion tensor imaging within the healthy cervical spinal cord: Within- participants reliability and measurement error. Magn Reson Imaging 2024; 109:56-66. [PMID: 38458552 DOI: 10.1016/j.mri.2024.03.005] [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: 05/06/2023] [Revised: 03/05/2024] [Accepted: 03/05/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Diffusion tensor imaging (DTI) is a promising technique for the visualization of the cervical spinal cord (CSC) in vivo. It provides information about the tissue structure of axonal white matter, and it is thought to be more sensitive than other MR imaging techniques for the evaluation of damage to tracts in the spinal cord. AIM The purpose of this study was to determine the within-participants reliability and error magnitude of measurements of DTI metrics in healthy human CSC. METHODS A total of twenty healthy controls (10 male, mean age: 33.9 ± 3.5 years, 10 females, mean age: 47.5 ± 14.4 years), with no family history of any neurological disorders or a contraindication to MRI scanning were recruited over a period of two months. Each participant was scanned twice with an MRI 3 T scanner using standard DTI sequences. Spinal Cord Toolbox (SCT) software was used for image post-processing. Data were first corrected for motion artefact, then segmented, registered to a template, and then the DTI metrics were computed. The within-participants coefficients of variation (CV%), the single and average within-participants intraclass correlation coefficients (ICC) and Bland-Altman plots for WM, VC, DC and LC fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were determined for the cervical spinal cord (between the 2nd and 5th cervical vertebrae). RESULTS DTI metrics showed poor to excellent within-participants reliability for both single and average ICC and moderate to high reproducibility for CV%, all variation dependent on the location of the ROI. The BA plots showed good within-participants agreement between the scan-rescan values. CONCLUSION Results from this reliability study demonstrate that clinical trials using the DTI technique are feasible and that DTI, in particular regions of the cord is suitable for use for the monitoring of degenerative WM changes.
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Affiliation(s)
- Hussein Al-Shaari
- Diagnostic Radiology Department, College of Applied Medical Sciences, Najran University, Najran 61441, Saudi Arabia; Department of Medical Imaging, Faculty of Health and Life Sciences, The University of Exeter, South Cloisters, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, UK.
| | - Jon Fulford
- Department of Medical Imaging, Faculty of Health and Life Sciences, The University of Exeter, South Cloisters, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, UK.
| | - C J Heales
- Department of Medical Imaging, Faculty of Health and Life Sciences, The University of Exeter, South Cloisters, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, UK.
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22
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Öz G, Cocozza S, Henry PG, Lenglet C, Deistung A, Faber J, Schwarz AJ, Timmann D, Van Dijk KRA, Harding IH. MR Imaging in Ataxias: Consensus Recommendations by the Ataxia Global Initiative Working Group on MRI Biomarkers. CEREBELLUM (LONDON, ENGLAND) 2024; 23:931-945. [PMID: 37280482 PMCID: PMC11102392 DOI: 10.1007/s12311-023-01572-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/18/2023] [Indexed: 06/08/2023]
Abstract
With many viable strategies in the therapeutic pipeline, upcoming clinical trials in hereditary and sporadic degenerative ataxias will benefit from non-invasive MRI biomarkers for patient stratification and the evaluation of therapies. The MRI Biomarkers Working Group of the Ataxia Global Initiative therefore devised guidelines to facilitate harmonized MRI data acquisition in clinical research and trials in ataxias. Recommendations are provided for a basic structural MRI protocol that can be used for clinical care and for an advanced multi-modal MRI protocol relevant for research and trial settings. The advanced protocol consists of modalities with demonstrated utility for tracking brain changes in degenerative ataxias and includes structural MRI, magnetic resonance spectroscopy, diffusion MRI, quantitative susceptibility mapping, and resting-state functional MRI. Acceptable ranges of acquisition parameters are provided to accommodate diverse scanner hardware in research and clinical contexts while maintaining a minimum standard of data quality. Important technical considerations in setting up an advanced multi-modal protocol are outlined, including the order of pulse sequences, and example software packages commonly used for data analysis are provided. Outcome measures most relevant for ataxias are highlighted with use cases from recent ataxia literature. Finally, to facilitate access to the recommendations by the ataxia clinical and research community, examples of datasets collected with the recommended parameters are provided and platform-specific protocols are shared via the Open Science Framework.
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Affiliation(s)
- Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA.
| | - Sirio Cocozza
- UNINA Department of Advanced Biomedical Sciences, University of Naples Federico II , Naples, Italy
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 Sixth Street Southeast, Minneapolis, MN, 55455, USA
| | - Andreas Deistung
- Department for Radiation Medicine, University Clinic and Outpatient Clinic for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Jennifer Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Hospital Bonn, Bonn, Germany
| | | | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Koene R A Van Dijk
- Digital Sciences and Translational Imaging, Early Clinical Development, Pfizer, Inc., Cambridge, MA, USA
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Australia
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23
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Lee S, Schmit BD, Kurpad SN, Budde MD. Cervical spinal cord angiography and vessel-selective perfusion imaging in the rat. NMR IN BIOMEDICINE 2024; 37:e5115. [PMID: 38355219 PMCID: PMC11078600 DOI: 10.1002/nbm.5115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/04/2024] [Accepted: 01/15/2024] [Indexed: 02/16/2024]
Abstract
Arterial spin labeling (ASL) has been widely used to evaluate arterial blood and perfusion dynamics, particularly in the brain, but its application to the spinal cord has been limited. The purpose of this study was to optimize vessel-selective pseudocontinuous arterial spin labeling (pCASL) for angiographic and perfusion imaging of the rat cervical spinal cord. A pCASL preparation module was combined with a train of gradient echoes for dynamic angiography. The effects of the echo train flip angle, label duration, and a Cartesian or radial readout were compared to examine their effects on visualizing the segmental arteries and anterior spinal artery (ASA) that supply the spinal cord. Lastly, vessel-selective encoding with either vessel-encoded pCASL (VE-pCASL) or super-selective pCASL (SS-pCASL) were compared. Vascular territory maps were obtained with VE-pCASL perfusion imaging of the spinal cord, and the interanimal variability was evaluated. The results demonstrated that longer label durations (200 ms) resulted in greater signal-to-noise ratio in the vertebral arteries, improved the conspicuity of the ASA, and produced better quality maps of blood arrival times. Cartesian and radial readouts demonstrated similar image quality. Both VE-pCASL and SS-pCASL adequately labeled the right or left vertebral arteries, which revealed the interanimal variability in the segmental artery with variations in their location, number, and laterality. VE-pCASL also demonstrated unique interanimal variations in spinal cord perfusion with a right-sided dominance across the six animals. Vessel-selective pCASL successfully achieved visualization of the arterial inflow dynamics and corresponding perfusion territories of the spinal cord. These methodological developments provide unique insights into the interanimal variations in the arterial anatomy and dynamics of spinal cord perfusion.
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Affiliation(s)
- Seongtaek Lee
- Joint Department of Biomedical Engineering, Marquette University & Medical College of Wisconsin, Milwaukee, WI
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI
| | - Brian D Schmit
- Joint Department of Biomedical Engineering, Marquette University & Medical College of Wisconsin, Milwaukee, WI
| | - Shekar N Kurpad
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI
- Clement J. Zablocki Veterans Affairs Medical Center, Milwaukee, WI
| | - Matthew D Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI
- Clement J. Zablocki Veterans Affairs Medical Center, Milwaukee, WI
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24
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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] [Grants] [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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Wang J, Huang J, Sun Z, Dong H, Li K, Lu J. Structural changes in spinal cord following optic neuritis: Insights from quantitative spinal MRI. Brain Res 2024; 1831:148830. [PMID: 38408557 DOI: 10.1016/j.brainres.2024.148830] [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: 12/04/2023] [Revised: 02/16/2024] [Accepted: 02/23/2024] [Indexed: 02/28/2024]
Abstract
OBJECTIVES Previous studies have demonstrated that optic neuritis (ON) affects brain plasticity. However, whether ON affects the spinal cord remains unclear. We aimed to investigate the spinal cord changes in ON and their associations with disability. METHODS A total of 101 ON patients, and 41 healthy controls (HC) were retrospectively recruited. High-resolution imaging was conducted using a Magnetization Prepared Rapid Acquisition Gradient-Echo (MP-RAGE) sequence for T1-weighted images and an echo planar imaging (EPI) sequence for Diffusion Tensor Imaging (DTI) data collection. Additionally, patients' disability and cognitive impairment were evaluated using the Expanded Disability Status Scale (EDSS) and the Paced Auditory Serial Addition Test (PASAT), respectively. The quantitative spinal MRI was employed to examine the cross-sectional area (CSA) and diffusion indicators, with a specific focus on calculating the average values across the C2-C7 cervical spinal cord segments. CSA, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared between groups. Correlation analyses were performed between CSA, diffusion indicators, and clinical variables. RESULTS No significant differences were found in CSA between ON patients and HCs. MD (p = 0.007) and RD (p = 0.018) were increased in ON patients compared with HCs, and AD was decreased in ON (p = 0.013). The AD values of the ON patients were significantly positively correlated with PASAT scores (r = 0.37, p < 0.001). CONCLUSIONS This study provided imaging evidence for DTI abnormalities in patients with ON. Spinal cord DTI can improve our knowledge of the path physiology of ON, and clinical progression.
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Affiliation(s)
- Jiyuan Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Jing Huang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Zheng Sun
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Huiqing Dong
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kuncheng Li
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, 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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Kuang C, Zha Y. Neurodegeneration within the rostral spinal cord is associated with brain gray matter volume atrophy in the early stage of cervical spondylotic myelopathy. Spinal Cord 2024; 62:214-220. [PMID: 38454066 DOI: 10.1038/s41393-024-00971-0] [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: 09/29/2022] [Revised: 02/21/2024] [Accepted: 02/27/2024] [Indexed: 03/09/2024]
Abstract
STUDY DESIGN Case-control study. OBJECTIVES Investigating the association between neurodegeneration within rostral spinal cord and brain gray matter volume (GMV) and assessing the relationship between remote neurodegenerative changes and clinical outcomes at the early phase of Cervical Spondylotic Myelopathy (CSM). SETTING University/hospital. METHODS Using Spinal Cord Toolbox, spinal cord morphometrics (cross-sectional area [CSA], gray matter area [GMA], white matter area [WMA]) of 40 patients with CSM and 28 healthy controls (HCs) were computed and compared using two-sample t test. Brain GMV of the two groups was analyzed using voxel-based morphometry approach. Pearson's correlation between spinal cord morphometrics and altered brain GMV and Spearman's relationship between remote neurodegenerations and clinical outcomes were conducted in CSM group. RESULTS Compared to HCs, CSA and WMA at C2/3 and GMV in right postcentral gyrus (PoCG.R) and left supplementary motor area (SMA.L) were significantly decreased in patients with CSM. CSA and WMA at C2/3 were associated with GMV in SMA.L and MCG.R in patients with CSM. CSA at C2/3 and GMV in PoCG.R were related to modified Japanese Orthopedic Association score in patients with CSM. CONCLUSIONS The associations between CSA and WMA at C2/3 and GMV in SMA.L and MCG.R suggest a concordant change pattern and adaptive mechanisms for neuronal plasticity underlying remote neurodegeneration in early CSM. The atrophy of CSA at C2/3 and GMV loss in PoCG.R can serve as potential neuroimaging biomarkers of early structural changes within spinal cord and brain preceding marked clinical disabilities in patients with CSM.
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Affiliation(s)
- Cuili Kuang
- Department of Radiological, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Yunfei Zha
- Department of Radiological, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
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28
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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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29
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Cronin AE, Liebig P, Detombe SA, Duggal N, Bartha R. Reproducibility of 3D pH-weighted chemical exchange saturation transfer contrast in the healthy cervical spinal cord. NMR IN BIOMEDICINE 2024; 37:e5103. [PMID: 38243648 DOI: 10.1002/nbm.5103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 12/01/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024]
Abstract
Spinal cord ischemia and hypoxia can be caused by compression, injury, and vascular alterations. Measuring ischemia and hypoxia directly in the spinal cord noninvasively remains challenging. Ischemia and hypoxia alter tissue pH, providing a physiologic parameter that may be more directly related to tissue viability. Chemical exchange saturation transfer (CEST) is an MRI contrast mechanism that can be made sensitive to pH. More specifically, amine/amide concentration independent detection (AACID) is a recently developed endogenous CEST contrast that has demonstrated sensitivity to intracellular pH at 9.4 T. The goal of this study was to evaluate the reproducibility of AACID CEST measurements at different levels of the healthy cervical spinal cord at 3.0 T incorporating B1 correction. Using a 3.0 T MRI scanner, two 3D CEST scans (saturation pulse train followed by a 3D snapshot gradient-echo readout) were performed on 12 healthy subjects approximately 10 days apart, with the CEST volume centered at the C4 level for all subjects. Scan-rescan reproducibility was evaluated by examining between and within-subject coefficients of variation (CVs) and absolute AACID value differences. The C4 level of the spinal cord demonstrated the lowest within-subject CVs (4.1%-4.3%), between-subject CVs (5.6%-6.3%), and absolute AACID percent difference (5.8-6.1%). The B1 correction scheme significantly improved reproducibility (adjusted p-value = 0.002) compared with the noncorrected data, suggesting that implementing B1 corrections in the spinal cord is beneficial. It was concluded that pH-weighted AACID measurements, incorporating B1-inhomogeneity correction, were reproducible within subjects along the healthy cervical spinal cord and that optimal image quality was achieved at the center of the 3D CEST volume.
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Affiliation(s)
- Alicia E Cronin
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | | | - Sarah A Detombe
- Department of Clinical Neurological Sciences, London Health Sciences Centre, London, Ontario, Canada
| | - Neil Duggal
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Department of Clinical Neurological Sciences, London Health Sciences Centre, London, Ontario, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
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30
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Yu H, Liu Z, Pang M, Luo Q, Huang C, He W, Liu B, Rong L. Wallerian Degeneration Assessed by Multi-Modal Magnetic Resonance Imaging of Cervical Spinal Cord Is Associated With Neurological Impairment After Spinal Cord Injury. J Neurotrauma 2024; 41:1240-1252. [PMID: 38204213 DOI: 10.1089/neu.2023.0305] [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: 01/12/2024] Open
Abstract
While Wallerian degeneration (WD) is a crucial pathological process induced with spinal cord injury (SCI), its underlying mechanisms is still understudied. In this study, we aim to assess structural alterations and clinical significance of WD in the cervical cord following SCI using multi-modal magnetic resonance imaging (MRI), which combines T2*-weighted imaging and diffusion tensor imaging (DTI). T2*-weighted images allow segmentation of anatomical structures and the detection of WD on macrostructural level. DTI, on the other hand, can identify the reduction in neuroaxonal integrity by measuring the diffusion of water molecules on the microstructural level. In this prospective study, 35 SCI patients (19 paraplegic and 16 tetraplegic patients) and 12 healthy controls were recruited between July 2020 and May 2022. The hyperintensity voxels in the dorsal column was manually labeled as WD on T2*-weighted images. The mean cross-sectional area (CSA) and mean DTI indexes of WD at the C2 level were calculated and compared between groups. Correlation analysis was used to determine the associations of the magnitude of WD with lesion characteristics and clinical outcomes. Compared with controls, SCI patients showed evident hyperintensity (35/35) and decreased neuroaxonal integrity (p < 0.05) within the dorsal column at the C2 level. A higher neurological level of injury was associated with a larger mean CSA and reduction in neuroaxonal integrity within WD (p < 0.05). Smaller total and dorsal tissue bridges were related to greater mean CSA and lower fractional anisotropy values in WD (p < 0.05), respectively. Moreover, SCI participants with significantly larger CSAs and significantly lower microstructural integrity had worse sensory outcomes (p < 0.05). This comprehensive evaluation of WD can help us better understand the mechanisms of WD, monitor progression, and assess the effectiveness of therapeutic interventions after SCI.
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Affiliation(s)
- Haiyang Yu
- Department of Spine Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Department of Orthopedics, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhenzhen Liu
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Mao Pang
- Department of Spine Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Guangdong Provincial Center for Engineering and Technology Research of Minimally Invasive Spine Surgery, Guangzhou, Guangdong, China
| | - Qiuxia Luo
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Chong Huang
- Department of Spine Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Weijie He
- Department of Orthopedics, Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, Guangdong, China
| | - Bin Liu
- Department of Spine Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Guangdong Provincial Center for Engineering and Technology Research of Minimally Invasive Spine Surgery, Guangzhou, Guangdong, China
- Guangdong Provincial Center for Quality Control of Minimally Invasive Spine Surgery, Guangzhou, Guangdong, China
| | - Limin Rong
- Department of Spine Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Guangdong Provincial Center for Engineering and Technology Research of Minimally Invasive Spine Surgery, Guangzhou, Guangdong, China
- Guangdong Provincial Center for Quality Control of Minimally Invasive Spine Surgery, Guangzhou, Guangdong, China
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Labounek R, Bondy MT, Paulson AL, Bédard S, Abramovic M, Alonso-Ortiz E, Atcheson NT, Barlow LR, Barry RL, Barth M, Battiston M, Büchel C, Budde MD, Callot V, Combes A, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak AV, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Gandini Wheeler-Kingshott CAM, Germani G, Gilbert G, Giove F, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers JM, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler H, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Laganà MM, Laule C, Law CSW, Leutritz T, Liu Y, Llufriu S, Mackey S, Martin AR, Martinez-Heras E, Mattera L, O’Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley GW, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber KA, Weiskopf N, Wise RG, Wyss PO, Xu J, Cohen-Adad J, Lenglet C, Nestrašil I. Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591421. [PMID: 38746371 PMCID: PMC11092490 DOI: 10.1101/2024.04.29.591421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.
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Affiliation(s)
- René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Monica T. Bondy
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Amy L. Paulson
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Sandrine Bédard
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
| | - Nicole T Atcheson
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | - Laura R. Barlow
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, Massachusetts, USA
| | - Markus Barth
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Christian Büchel
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew D. Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
- Clement J. Zablocki Veteran’s Affairs Medical Center, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna Combes
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | | | - Marek Dostál
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Adam V. Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Jürgen Finsterbusch
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Claudia A. M. Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - GianCarlo Germani
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Neuroimaging Laboratory, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Francesco Grussu
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
- Department of Neurology, University Hospital Brno, Brno, Czech Republic
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 1-2-1, Hongo, Bunkyo, Tokyo 113-8421, Japan
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James M. Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Haleh Karbasforoushan
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, University Hospital Brno and Masaryk University, Czech Republic
| | - Ali Khatibi
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), University of Birmingham, Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - 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, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Nawal Kinany
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Hagen Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Science, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Petr Kudlička
- Multimodal and Functional Imaging Laboratory, Central European Institute of Technology, Brno, Czech Republic
- First Department of Neurology, St. Anne’s University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Nyoman D. Kurniawan
- Centre for Advanced Imaging, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Australia
| | | | | | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, Canada
| | | | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, China
| | - Sara Llufriu
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Allan R. Martin
- Department of Neurological Surgery, University of California, Davis, CA, USA
| | - Eloy Martinez-Heras
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Geneva, Genève, Switzerland
| | - 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
| | - Nico Papinutto
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Todd B. Parrish
- Department of Radiology, Northwestern University, Chicago, IL 60611, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Artificial Intelligence Center, Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
- Centre for Medical Image Computing, University College London, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain
| | - Marc J. Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, Australia
| | - Rebecca S. Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Giovanni Savini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20072, Pieve Emanuele (MI), Italy
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089, Rozzano (MI), Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 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, USA
| | - Alex K. Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN USA
| | - Zachary A. Smith
- Department of Neurosurgery, University of Oklahoma, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Neuroimmunology and Multiple Sclerosis Unit, Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-IDIBAPS and Universitat de Barcelona. Barcelona, Spain
| | - Yuichi Suzuki
- The University of Tokyo Hospital, Radiology Center, Tokyo, Japan
| | - George W Tackley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
| | - Alexandra Tinnermann
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - 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, Czech Republic
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
| | - Marios C. Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Kenneth A. Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Nikolaus Weiskopf
- Wellcome Trust Centre for Neuroimaging, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
| | - Richard G. Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, UK
- Department of Neurosciences, Imaging, and Clinical Sciences, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies, ‘G. D’Annunzio’ University of Chieti-Pescara, Chieti, Italy
| | - Patrik O. Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas, USA
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Igor Nestrašil
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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Renton AI, Dao TT, Johnstone T, Civier O, Sullivan RP, White DJ, Lyons P, Slade BM, Abbott DF, Amos TJ, Bollmann S, Botting A, Campbell MEJ, Chang J, Close TG, Dörig M, Eckstein K, Egan GF, Evas S, Flandin G, Garner KG, Garrido MI, Ghosh SS, Grignard M, Halchenko YO, Hannan AJ, Heinsfeld AS, Huber L, Hughes ME, Kaczmarzyk JR, Kasper L, Kuhlmann L, Lou K, Mantilla-Ramos YJ, Mattingley JB, Meier ML, Morris J, Narayanan A, Pestilli F, Puce A, Ribeiro FL, Rogasch NC, Rorden C, Schira MM, Shaw TB, Sowman PF, Spitz G, Stewart AW, Ye X, Zhu JD, Narayanan A, Bollmann S. Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging. Nat Methods 2024; 21:804-808. [PMID: 38191935 PMCID: PMC11180540 DOI: 10.1038/s41592-023-02145-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 11/27/2023] [Indexed: 01/10/2024]
Abstract
Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.
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Affiliation(s)
- Angela I Renton
- The University of Queensland, Queensland Brain Institute, St Lucia, Brisbane, Queensland, Australia.
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia.
| | - Thuy T Dao
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Tom Johnstone
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Oren Civier
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Ryan P Sullivan
- The University of Sydney, School of Biomedical Engineering, Sydney, New South Wales, Australia
| | - David J White
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Paris Lyons
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Benjamin M Slade
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - David F Abbott
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Toluwani J Amos
- School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, China
| | - Saskia Bollmann
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Andy Botting
- Australian Research Data Commons (ARDC), Sydney, New South Wales, Australia
| | - Megan E J Campbell
- School of Psychological Sciences, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute Imaging Centre, Newcastle, New South Wales, Australia
| | - Jeryn Chang
- The University of Queensland, School of Biomedical Sciences, St Lucia, Brisbane, Queensland, Australia
| | - Thomas G Close
- The University of Sydney, School of Biomedical Engineering, Sydney, New South Wales, Australia
| | - Monika Dörig
- Integrative Spinal Research, Department of Chiropractic Medicine, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Korbinian Eckstein
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Gary F Egan
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Stefanie Evas
- School of Psychology, University of Adelaide, Adelaide, South Australia, Australia
- Human Health, Health & Biosecurity, CSIRO, Adelaide, South Australia, Australia
| | - Guillaume Flandin
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Kelly G Garner
- School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
- The University of Queensland, School of Psychology, St Lucia, Brisbane, Queensland, Australia
| | - Marta I Garrido
- Melbourne School of Psychological Sciences, he University of Melbourne, Melbourne, Victoria, Australia
- Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
| | - Satrajit S Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| | - Martin Grignard
- GIGA CRC In-Vivo Imaging, University of Liège, Liège, Belgium
| | - Yaroslav O Halchenko
- Center for Open Neuroscience, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Anthony J Hannan
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Anibal S Heinsfeld
- Department of Psychology, Center for Perceptual Systems, Institute for Neuroscience, Center For Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Laurentius Huber
- National Institute of Mental Health (NIMH), National Institutes Health, Bethesda, MD, USA
| | - Matthew E Hughes
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Jakub R Kaczmarzyk
- Department of Biomedical Informatics, Stony Brook University, New York, NY, USA
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, New York, NY, USA
| | - Lars Kasper
- BRAIN-TO Lab, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Levin Kuhlmann
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia
| | - Kexin Lou
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yorguin-Jose Mantilla-Ramos
- Grupo Neuropsicología y Conducta (GRUNECO), Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Jason B Mattingley
- The University of Queensland, Queensland Brain Institute, St Lucia, Brisbane, Queensland, Australia
- The University of Queensland, School of Psychology, St Lucia, Brisbane, Queensland, Australia
| | - Michael L Meier
- Integrative Spinal Research, Department of Chiropractic Medicine, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Jo Morris
- Australian Research Data Commons (ARDC), Sydney, New South Wales, Australia
| | - Akshaiy Narayanan
- School of Computer Science, The University of Auckland, Auckland, New Zealand
| | - Franco Pestilli
- Department of Psychology, Center for Perceptual Systems, Institute for Neuroscience, Center For Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Aina Puce
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Fernanda L Ribeiro
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Nigel C Rogasch
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
- Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
| | - Chris Rorden
- McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Mark M Schira
- School of Psychology, University of Wollongong, Wollongong, New South Wales, Australia
| | - Thomas B Shaw
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Paul F Sowman
- Macquarie University, School of Psychological Sciences, Sydney, New South Wales, Australia
| | - Gershon Spitz
- Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Ashley W Stewart
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
| | - Xincheng Ye
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Judy D Zhu
- Macquarie University, School of Psychological Sciences, Sydney, New South Wales, Australia
| | - Aswin Narayanan
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia
| | - Steffen Bollmann
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia.
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia.
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia.
- Queensland Digital Health Centre, The University of Queensland, Brisbane, Queensland, Australia.
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33
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Al-Shawwa A, Ost K, Anderson D, Cho N, Evaniew N, Jacobs WB, Martin AR, Gaekwad R, Tripathy S, Bouchard J, Casha S, Cho R, duPlessis S, Lewkonia P, Nicholls F, Salo PT, Soroceanu A, Swamy G, Thomas KC, Yang MMH, Cohen-Adad J, Cadotte DW. Advanced MRI metrics improve the prediction of baseline disease severity for individuals with degenerative cervical myelopathy. Spine J 2024:S1529-9430(24)00193-1. [PMID: 38679077 DOI: 10.1016/j.spinee.2024.04.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/05/2024] [Accepted: 04/23/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND CONTEXT Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Degeneration of spinal discs, bony osteophyte growth and ligament pathology results in physical compression of the spinal cord contributing to damage of white matter tracts and grey matter cellular populations. This results in an insidious neurological and functional decline in patients which can lead to paralysis. Magnetic resonance imaging (MRI) confirms the diagnosis of DCM and is a prerequisite to surgical intervention, the only known treatment for this disorder. Unfortunately, there is a weak correlation between features of current commonly acquired MRI scans ("community MRI, cMRI") and the degree of disability experienced by a patient. PURPOSE This study examines the predictive ability of current MRI sequences relative to "advanced MRI" (aMRI) metrics designed to detect evidence of spinal cord injury secondary to degenerative myelopathy. We hypothesize that the utilization of higher fidelity aMRI scans will increase the effectiveness of machine learning models predicting DCM severity and may ultimately lead to a more efficient protocol for identifying patients in need of surgical intervention. STUDY DESIGN/SETTING Single institution analysis of imaging registry of patients with DCM. PATIENT SAMPLE A total of 296 patients in the cMRI group and 228 patients in the aMRI group. OUTCOME MEASURES Physiologic measures: accuracy of machine learning algorithms to detect severity of DCM assessed clinically based on the modified Japanese Orthopedic Association (mJOA) scale. METHODS Patients enrolled in the Canadian Spine Outcomes Research Network registry with DCM were screened and 296 cervical spine MRIs acquired in cMRI were compared with 228 aMRI acquisitions. aMRI acquisitions consisted of diffusion tensor imaging, magnetization transfer, T2-weighted, and T2*-weighted images. The cMRI group consisted of only T2-weighted MRI scans. Various machine learning models were applied to both MRI groups to assess accuracy of prediction of baseline disease severity assessed clinically using the mJOA scale for cervical myelopathy. RESULTS Through the utilization of Random Forest Classifiers, disease severity was predicted with 41.8% accuracy in cMRI scans and 73.3% in the aMRI scans. Across different predictive model variations tested, the aMRI scans consistently produced higher prediction accuracies compared to the cMRI counterparts. CONCLUSIONS aMRI metrics perform better in machine learning models at predicting disease severity of patients with DCM. Continued work is needed to refine these models and address DCM severity class imbalance concerns, ultimately improving model confidence for clinical implementation.
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Affiliation(s)
- Abdul Al-Shawwa
- Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, T2N4N1, Canada
| | - Kalum Ost
- Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, T2N4N1, Canada
| | - David Anderson
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, HMRB 231, 3330 Hospital Drive NW, Calgary, Alberta, T2N4N1, Canada
| | - Newton Cho
- Department of Neurosurgery, University of Toronto,149 College Street, 5th Floor, Toronto, Ontario, M5T1P5, Canada
| | - Nathan Evaniew
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - W Bradley Jacobs
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Department of Clinical Neurosciences, Section of Neurosurgery, Cumming School of Medicine, University of Calgary, 1403 29th Street NW, Calgary, Alberta, T2N2T9, Canada
| | - Allan R Martin
- Department of Neurological Surgery, University of California - Davis, 3301 C Street, Suite 1500, Sacramento, CA, 95816, USA
| | - Ranjeet Gaekwad
- Department of Clinical Neurosciences, Section of Neurosurgery, Cumming School of Medicine, University of Calgary, 1403 29th Street NW, Calgary, Alberta, T2N2T9, Canada
| | - Saswati Tripathy
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada
| | - Jacques Bouchard
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Steve Casha
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Department of Clinical Neurosciences, Section of Neurosurgery, Cumming School of Medicine, University of Calgary, 1403 29th Street NW, Calgary, Alberta, T2N2T9, Canada
| | - Roger Cho
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Stephen duPlessis
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Department of Clinical Neurosciences, Section of Neurosurgery, Cumming School of Medicine, University of Calgary, 1403 29th Street NW, Calgary, Alberta, T2N2T9, Canada
| | - Peter Lewkonia
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Fred Nicholls
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Paul T Salo
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Alex Soroceanu
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Ganesh Swamy
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Kenneth C Thomas
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Section of Orthopaedic Surgery, Department of Surgery, University of Calgary, 1403 29 Street NW, T2N2T9, Calgary, Alberta, T2N2T9, Canada
| | - Michael M H Yang
- Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Department of Clinical Neurosciences, Section of Neurosurgery, Cumming School of Medicine, University of Calgary, 1403 29th Street NW, Calgary, Alberta, T2N2T9, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Pavillon Lassonde 2700 Ch de la Tour, Montreal, Quebec, H3T1N8, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, 4565 Queen Mary Rd, Montreal, Quebec, H3W1W5, Canada; Mila - Quebec AI Institute, 6666 Saint-Urbain Street, #200, Montreal, Quebec, H2S3H1, Canada
| | - David W Cadotte
- Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, T2N4N1, Canada; Combined Orthopedic and Neurosurgery Spine Program, University of Calgary, 1409 29 Street NW, Calgary, Alberta, T2N2T9, Canada; Department of Clinical Neurosciences, Section of Neurosurgery, Cumming School of Medicine, University of Calgary, 1403 29th Street NW, Calgary, Alberta, T2N2T9, Canada.
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Karthik EN, Valosek J, Smith AC, Pfyffer D, Schading-Sassenhausen S, Farner L, Weber KA, Freund P, Cohen-Adad J. SCIseg: Automatic Segmentation of T2-weighted Intramedullary Lesions in Spinal Cord Injury. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.03.24300794. [PMID: 38699309 PMCID: PMC11065035 DOI: 10.1101/2024.01.03.24300794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Purpose To develop a deep learning tool for the automatic segmentation of T2-weighted intramedullary lesions in spinal cord injury (SCI). Material and Methods This retrospective study included a cohort of SCI patients from three sites enrolled between July 2002 and February 2023. A deep learning model, SCIseg, was trained in a three-phase process involving active learning for the automatic segmentation of intramedullary SCI lesions and the spinal cord. The data consisted of T2-weighted MRI acquired using different scanner manufacturers with heterogeneous image resolutions (isotropic/anisotropic), orientations (axial/sagittal), lesion etiologies (traumatic/ischemic/hemorrhagic) and lesions spread across the cervical, thoracic and lumbar spine. The segmentations from the proposed model were visually and quantitatively compared with other open-source baselines. Wilcoxon signed-rank test was used to compare quantitative MRI biomarkers (lesion volume, lesion length, and maximal axial damage ratio) computed from manual lesion masks and those obtained automatically with SCIseg predictions. Results MRI data from 191 SCI patients (mean age, 48.1 years ± 17.9 [SD]; 142 males) were used for model training and evaluation. SCIseg achieved the best segmentation performance for both the cord and lesions. There was no statistically significant difference between lesion length and maximal axial damage ratio computed from manually annotated lesions and those obtained using SCIseg. Conclusion Automatic segmentation of intramedullary lesions commonly seen in SCI replaces the tedious manual annotation process and enables the extraction of relevant lesion morphometrics in large cohorts. The proposed model segments lesions across different etiologies, scanner manufacturers, and heterogeneous image resolutions. SCIseg is open-source and accessible through the Spinal Cord Toolbox.
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Affiliation(s)
- Enamundram Naga Karthik
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila - Quebec AI Institute, Montreal, QC, Canada
| | - Jan Valosek
- 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
| | - Andrew C Smith
- Department of Physical Medicine and Rehabilitation Physical Therapy Program, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Dario Pfyffer
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | | | - Lynn Farner
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Kenneth A Weber
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - 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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Stuart CM, Varatharaj A, Zou Y, Darekar A, Domjan J, Gandini Wheeler-Kingshott CAM, Perry VH, Galea I. Systemic inflammation associates with and precedes cord atrophy in progressive multiple sclerosis. Brain Commun 2024; 6:fcae143. [PMID: 38712323 PMCID: PMC11073756 DOI: 10.1093/braincomms/fcae143] [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: 11/13/2023] [Revised: 02/05/2024] [Accepted: 04/17/2024] [Indexed: 05/08/2024] Open
Abstract
In preclinical models of multiple sclerosis, systemic inflammation has an impact on the compartmentalized inflammatory process within the central nervous system and results in axonal loss. It remains to be shown whether this is the case in humans, specifically whether systemic inflammation contributes to spinal cord or brain atrophy in multiple sclerosis. Hence, an observational longitudinal study was conducted to delineate the relationship between systemic inflammation and atrophy using magnetic resonance imaging: the SIMS (Systemic Inflammation in Multiple Sclerosis) study. Systemic inflammation and progression were assessed in people with progressive multiple sclerosis (n = 50) over two and a half years. Eligibility criteria included: (i) primary or secondary progressive multiple sclerosis; (ii) age ≤ 70; and (iii) Expanded Disability Status Scale ≤ 6.5. First morning urine was collected weekly to quantify systemic inflammation by measuring the urinary neopterin-to-creatinine ratio using a validated ultra-performance liquid chromatography mass spectrometry technique. The urinary neopterin-to-creatinine ratio temporal profile was characterized by short-term responses overlaid on a background level of inflammation, so these two distinct processes were considered as separate variables: background inflammation and inflammatory response. Participants underwent MRI at the start and end of the study, to measure cervical spinal cord and brain atrophy. Brain and cervical cord atrophy occurred on the study, but the most striking change was seen in the cervical spinal cord, in keeping with the corticospinal tract involvement that is typical of progressive disease. Systemic inflammation predicted cervical cord atrophy. An association with brain atrophy was not observed in this cohort. A time lag between systemic inflammation and cord atrophy was evident, suggesting but not proving causation. The association of the inflammatory response with cord atrophy depended on the level of background inflammation, in keeping with experimental data in preclinical models where the effects of a systemic inflammatory challenge on tissue injury depended on prior exposure to inflammation. A higher inflammatory response was associated with accelerated cord atrophy in the presence of background systemic inflammation below the median for the study population. Higher background inflammation, while associated with cervical cord atrophy itself, subdued the association of the inflammatory response with cord atrophy. Findings were robust to sensitivity analyses adjusting for potential confounders and excluding cases with new lesion formation. In conclusion, systemic inflammation associates with, and precedes, multiple sclerosis progression. Further work is needed to prove causation since targeting systemic inflammation may offer novel treatment strategies for slowing neurodegeneration in multiple sclerosis.
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Affiliation(s)
- Charlotte M Stuart
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
| | - Aravinthan Varatharaj
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Yukai Zou
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
- Department of Medical Physics, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Angela Darekar
- Department of Medical Physics, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Janine Domjan
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- Department of Neuroinflammation, Faculty of Brain Sciences, NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
| | - V Hugh Perry
- School of Biological Sciences, University of Southampton, Southampton SO16 6YD, UK
| | - Ian Galea
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK
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Büeler S, Freund P, Kessler TM, Liechti MD, David G. Improved inter-subject alignment of the lumbosacral cord for group-level in vivo gray and white matter assessments: A scan-rescan MRI study at 3T. PLoS One 2024; 19:e0301449. [PMID: 38626171 PMCID: PMC11020367 DOI: 10.1371/journal.pone.0301449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 03/15/2024] [Indexed: 04/18/2024] Open
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) enables the investigation of pathological changes in gray and white matter at the lumbosacral enlargement (LSE) and conus medullaris (CM). However, conducting group-level analyses of MRI metrics in the lumbosacral spinal cord is challenging due to variability in CM length, lack of established image-based landmarks, and unknown scan-rescan reliability. This study aimed to improve inter-subject alignment of the lumbosacral cord to facilitate group-level analyses of MRI metrics. Additionally, we evaluated the scan-rescan reliability of MRI-based cross-sectional area (CSA) measurements and diffusion tensor imaging (DTI) metrics. METHODS Fifteen participants (10 healthy volunteers and 5 patients with spinal cord injury) underwent axial T2*-weighted and diffusion MRI at 3T. We assessed the reliability of spinal cord and gray matter-based landmarks for inter-subject alignment of the lumbosacral cord, the inter-subject variability of MRI metrics before and after adjusting for the CM length, the intra- and inter-rater reliability of CSA measurements, and the scan-rescan reliability of CSA measurements and DTI metrics. RESULTS The slice with the largest gray matter CSA as an LSE landmark exhibited the highest reliability, both within and across raters. Adjusting for the CM length greatly reduced the inter-subject variability of MRI metrics. The intra-rater, inter-rater, and scan-rescan reliability of MRI metrics were the highest at and around the LSE (scan-rescan coefficient of variation <3% for CSA measurements and <7% for DTI metrics within the white matter) and decreased considerably caudal to it. CONCLUSIONS To facilitate group-level analyses, we recommend using the slice with the largest gray matter CSA as a reliable LSE landmark, along with an adjustment for the CM length. We also stress the significance of the anatomical location within the lumbosacral cord in relation to the reliability of MRI metrics. The scan-rescan reliability values serve as valuable guides for power and sample size calculations in future longitudinal studies.
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Affiliation(s)
- Silvan Büeler
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- UCL Queen Square Institute of Neurology, Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Thomas M. Kessler
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Martina D. Liechti
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
| | - Gergely David
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zürich, Switzerland
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Koch KM, Nencka AS, Kurpad S, Budde MD. Diffusion Weighted Magnetic Resonance Imaging of Spinal Cord Injuries After Instrumented Fusion Stabilization. J Neurotrauma 2024. [PMID: 38251658 DOI: 10.1089/neu.2023.0591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising technique for assessing spinal cord injury (SCI) that has historically been challenged by the presence of metallic stabilization hardware. This study leverages recent advances in metal-artifact resistant multi-spectral DW-MRI to enable diffusion quantification throughout the spinal cord even after fusion stabilization. Twelve participants with cervical spinal cord injuries treated with fusion stabilization and 49 asymptomatic able-bodied control participants underwent multi-spectral DW-MRI evaluation. Apparent diffusion coefficient (ADC) values were calculated in axial cord sections. Statistical modeling assessed ADC differences across cohorts and within distinct cord regions of the SCI participants (at, above, or below injured level). Computed models accounted for subject demographics and injury characteristics. ADC was found to be elevated at injured levels compared with non-injured levels (z = 3.2, p = 0.001), with ADC at injured levels decreasing over time since injury (z = -9.2, p < 0.001). Below the injury level, ADC was reduced relative to controls (z = -4.4, p < 0.001), with greater reductions after more severe injuries that correlated with lower extremity motor scores (z = 2.56, p = 0.012). No statistically significant differences in ADC above the level of injury were identified. By enabling diffusion analysis near fusion hardware, the multi-spectral DW-MRI technique allowed intuitive quantification of cord diffusion changes after SCI both at and away from injured levels. This demonstrates the approach's potential for assessing post-surgical spinal cord integrity throughout stabilized regions.
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Affiliation(s)
- Kevin M Koch
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Andrew S Nencka
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Shekar Kurpad
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Matthew D Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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Tur C, Battiston M, Yiannakas MC, Collorone S, Calvi A, Prados F, Kanber B, Grussu F, Ricciardi A, Pajak P, Martinelli D, Schneider T, Ciccarelli O, Samson RS, Wheeler-Kingshott CAG. What contributes to disability in progressive MS? A brain and cervical cord-matched quantitative MRI study. Mult Scler 2024; 30:516-534. [PMID: 38372019 DOI: 10.1177/13524585241229969] [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: 02/20/2024]
Abstract
BACKGROUND We assessed the ability of a brain-and-cord-matched quantitative magnetic resonance imaging (qMRI) protocol to differentiate patients with progressive multiple sclerosis (PMS) from controls, in terms of normal-appearing (NA) tissue abnormalities, and explain disability. METHODS A total of 27 patients and 16 controls were assessed on the Expanded Disability Status Scale (EDSS), 25-foot timed walk (TWT), 9-hole peg (9HPT) and symbol digit modalities (SDMT) tests. All underwent 3T brain and (C2-C3) cord structural imaging and qMRI (relaxometry, quantitative magnetisation transfer, multi-shell diffusion-weighted imaging), using a fast brain-and-cord-matched protocol with brain-and-cord-unified imaging readouts. Lesion and NA-tissue volumes and qMRI metrics reflecting demyelination and axonal loss were obtained. Random forest analyses identified the most relevant volumetric/qMRI measures to clinical outcomes. Confounder-adjusted linear regression estimated the actual MRI-clinical associations. RESULTS Several qMRI/volumetric differences between patients and controls were observed (p < 0.01). Higher NA-deep grey matter quantitative-T1 (EDSS: beta = 7.96, p = 0.006; 9HPT: beta = -0.09, p = 0.004), higher NA-white matter orientation dispersion index (TWT: beta = -3.21, p = 0.005; SDMT: beta = -847.10, p < 0.001), lower whole-cord bound pool fraction (9HPT: beta = 0.79, p = 0.001) and higher NA-cortical grey matter quantitative-T1 (SDMT = -94.31, p < 0.001) emerged as particularly relevant predictors of greater disability. CONCLUSION Fast brain-and-cord-matched qMRI protocols are feasible and identify demyelination - combined with other mechanisms - as key for disability accumulation in PMS.
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Affiliation(s)
- Carmen Tur
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Multiple Sclerosis Centre of Catalonia (Cemcat). Vall d'Hebron Institute of Research. Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Marco Battiston
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sara Collorone
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Alberto Calvi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Fundació de Recerca Clínic Barcelona-Institut d'Investigacions Biomèdiques August Pi i Sunyer, Hospital Clinic, Barcelona, Spain
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- eHealth Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Francesco Grussu
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square 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
| | - Antonio Ricciardi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Patrizia Pajak
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Daniele Martinelli
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | | | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- NIHR UCLH Biomedical Research Centre, London, UK
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Claudia Am Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, UCL (University College London) Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy; Brain Connectivity Research Center, IRCCS Mondino Foundation, Pavia, Italy
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Meng Y, Wang S, Zhu W, Wang T, Liu D, Wang M, Pi J, Liu Y, Zhuo Z, Pan Y, Wang Y. Association of Mean Upper Cervical Spinal Cord Cross-Sectional Area With Cerebral Small Vessel Disease: A Community-Based Cohort Study. Stroke 2024; 55:687-695. [PMID: 38269540 DOI: 10.1161/strokeaha.123.044666] [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: 07/29/2023] [Accepted: 12/13/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND The purpose of this study was to investigate the association between the mean upper cervical spinal cord cross-sectional area (MUCCA) and the risk and severity of cerebral small vessel disease (CSVD). METHODS Community-dwelling residents in Lishui City, China, from the cross-sectional survey in the PRECISE cohort study (Polyvascular Evaluation for Cognitive Impairment and Vascular Events) conducted from 2017 to 2019. We included 1644 of 3067 community-dwelling adults in the PRECISE study after excluding those with incorrect, incomplete, insufficient, or missing clinical or imaging data. Total and modified total CSVD scores, as well as magnetic resonance imaging features, including white matter hyperintensity, lacunes, cerebral microbleeds, enlarged perivascular spaces, and brain atrophy, were assessed at the baseline. The Spinal Cord Toolbox was used to measure the upper cervical spinal cord cross-sectional area of the C1 to C3 segments of the spinal cord and its average value was taken as MUCCA. Participants were divided into 4 groups according to quartiles of MUCCA. Associations were analyzed using linear regression models adjusted for age, sex, current smoking and drinking, medical history, intracranial volume, and total cortical volume. RESULTS The means±SD age of the participants was 61.4±6.5 years, and 635 of 1644 participants (38.6%) were men. The MUCCA was smaller in patients with CSVD than those without CSVD. Using the total CSVD score as a criterion, the MUCCA was 61.78±6.12 cm2 in 504 of 1644 participants with CSVD and 62.74±5.94 cm2 in 1140 of 1644 participants without CSVD. Using the modified total CSVD score, the MUCCA was 61.81±6.04 cm2 in 699 of 1644 participants with CSVD and 62.91±5.94 cm2 in 945 of 1644 without CSVD. There were statistical differences between the 2 groups after adjusting for covariates in 3 models. The MUCCA was negatively associated with the total and modified total CSVD scores (adjusted β value, -0.009 [95% CI, -0.01 to -0.003] and -0.007 [95% CI, -0.01 to -0.0006]) after adjustment for covariates. Furthermore, the MUCCA was negatively associated with the white matter hyperintensity burden (adjusted β value, -0.01 [95% CI, -0.02 to -0.003]), enlarged perivascular spaces in the basal ganglia (adjusted β value, -0.005 [95% CI, -0.009 to -0.001]), lacunes (adjusted β value, -0.004 [95% CI, -0.007 to -0.0007]), and brain atrophy (adjusted β value, -0.009 [95% CI, -0.01 to -0.004]). CONCLUSIONS The MUCCA and CSVD were correlated. Spinal cord atrophy may serve as an imaging marker for CSVD; thus, small vessel disease may involve the spinal cord in addition to being intracranial.
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Affiliation(s)
- Yufei Meng
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
- Dongzhimen Hospital, Beijing University of Chinese Medicine, China (Y.M.)
| | - Suying Wang
- Department of Neurology and Cerebrovascular Research Laboratory, Lishui Central Hospital and Fifth Affiliated Hospital of Wenzhou Medical University, Zhejiang, China (S.W.)
| | - Wanlin Zhu
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
| | - Tingting Wang
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
- China National Clinical Research Center for Neurological Diseases, Beijing (T.W., D.L., M.W., Y.P., Y.W.)
| | - Dandan Liu
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
- China National Clinical Research Center for Neurological Diseases, Beijing (T.W., D.L., M.W., Y.P., Y.W.)
| | - Mengxing Wang
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
- China National Clinical Research Center for Neurological Diseases, Beijing (T.W., D.L., M.W., Y.P., Y.W.)
| | - Jingtao Pi
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
| | - Yaou Liu
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
| | - Zhizheng Zhuo
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
- China National Clinical Research Center for Neurological Diseases, Beijing (T.W., D.L., M.W., Y.P., Y.W.)
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital (Y.M., W.Z., T.W., D.L., M.W., J.P., Y.L., Z.Z., Y.P., Y.W.), Capital Medical University, China
- Advanced Innovation Center for Human Brain Protection (Y.W.), Capital Medical University, China
- Beijing Laboratory of Oral Health (Y.W.), Capital Medical University, China
- Chinese Institute for Brain Research, Beijing, China (Y.W.)
- National Center for Neurological Diseases, Beijing, China (Y.W.)
- China National Clinical Research Center for Neurological Diseases, Beijing (T.W., D.L., M.W., Y.P., Y.W.)
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Khamaysa M, Lefort M, Pélégrini-Issac M, Lackmy-Vallée A, Mendili MME, Preuilh A, Devos D, Bruneteau G, Salachas F, Lenglet T, Amador MM, Le Forestier N, Hesters A, Gonzalez J, Rolland AS, Desnuelle C, Chupin M, Querin G, Georges M, Morelot-Panzini C, Marchand-Pauvert V, Pradat PF. Quantitative brainstem and spinal MRI in amyotrophic lateral sclerosis: implications for predicting noninvasive ventilation needs. J Neurol 2024; 271:1235-1246. [PMID: 37910250 DOI: 10.1007/s00415-023-12045-x] [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: 08/23/2023] [Revised: 10/01/2023] [Accepted: 10/03/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Respiratory complications resulting from motor neurons degeneration are the primary cause of death in amyotrophic lateral sclerosis (ALS). Predicting the need for non-invasive ventilation (NIV) in ALS is important for advance care planning and clinical trial design. The aim of this study was to assess the potential of quantitative MRI at the brainstem and spinal cord levels to predict the need for NIV during the first six months after diagnosis. METHODS Forty-one ALS patients underwent MRI and spirometry shortly after diagnosis. The need for NIV was monitored according to French health guidelines for 6 months. The performance of four regression models based on: clinical variables, brainstem structures volumes, cervical spinal measurements, and combined variables were compared to predict the need for NIV within this period. RESULTS Both the clinical model (R2 = 0.28, AUC = 0.85, AICc = 42.67, BIC = 49.8) and the brainstem structures' volumes model (R2 = 0.30, AUC = 0.85, AICc = 40.13, BIC = 46.99) demonstrated good predictive performance. In addition, cervical spinal cord measurements model similar performance (R2 = 0.338, AUC = 0.87, AICc = 37.99, BIC = 44.49). Notably, the combined model incorporating predictors from all three models yielded the best performance (R2 = 0.60, AUC = 0.959, AICc = 36.38, BIC = 44.8). These findings are supported by observed positive correlations between brainstem volumes, cervical (C4/C7) cross-sectional area, and spirometry-measured lung volumes. CONCLUSIONS Our study shows that brainstem volumes and spinal cord area are promising measures to predict respiratory intervention needs in ALS.
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Affiliation(s)
- M Khamaysa
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - M Lefort
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - M Pélégrini-Issac
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - A Lackmy-Vallée
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - M M El Mendili
- APHM, Hôpital Timone, CEMEREM, Marseille, France
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
| | - A Preuilh
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - D Devos
- Département de Neurologie, Centre Référent SLA, CHU de Lille, Centre LICEND COEN, ACT4-ALS-MND network, Lille, France
- Départment de Pharmacologie Médicale, Université de Lille, INSERM UMRS_1172 LilNCog, CHU de Lille, Centre LICEND COEN, ACT4-ALS-MND network, Lille, France
| | - G Bruneteau
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France
| | - F Salachas
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France
| | - T Lenglet
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France
- Faculté de Médecine de Nice, Département de Neurologie, Université Cote d'Azur, Nice, France
- Département de Neurophysiologie, APHP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Md M Amador
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France
| | - N Le Forestier
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France
- Département de Recherche en Éthique, EA 1610: Etudes des Sciences et Techniques, Université Paris Sud/Paris Saclay, Paris, France
| | - A Hesters
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France
| | - J Gonzalez
- Neurophysiologie Respiratoire Expérimentale et Clinique, INSERM UMRS1158, Sorbonne Université, Paris, France
| | - A-S Rolland
- Départment de Pharmacologie Médicale, Université de Lille, INSERM UMRS_1172 LilNCog, CHU de Lille, Centre LICEND COEN, ACT4-ALS-MND network, Lille, France
| | - C Desnuelle
- Faculté de Médecine de Nice, Département de Neurologie, Université Cote d'Azur, Nice, France
| | - M Chupin
- CATI, Plateforme d'Imagerie Neurologique Multicentrique, Paris, France
| | - G Querin
- APHP, Service de Neuromyologie, Hôpital Pitié-Salpêtrière, Centre Référent Pour les Maladies Neuromusculaires Rares, Paris, France
- Institut de Myologie, Plateforme d'essais cliniques I-Motion, Hôpital Pitié-Salpêtrière, Paris, France
| | - M Georges
- Département des Maladies Respiratoires et Soins Intensifs, Centre de Référence pour les Maladies Pulmonaires Rares, Hôpital Universitaire de Dijon-Bourgogne, Dijon, France
- Université de Bourgogne Franche-Comté, Dijon, France
- Centre des Sciences du Goût et de l'Alimentation, UMR 6265 CNRS 1234 INRA, Université de Bourgogne Franche-Comté, Dijon, France
| | - C Morelot-Panzini
- Neurophysiologie Respiratoire Expérimentale et Clinique, INSERM UMRS1158, Sorbonne Université, Paris, France
- Service de Pneumologie (Département R3S), Groupe Hospitalier Pitié-Salpêtrière, AP-HP, Paris, France
| | - V Marchand-Pauvert
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France
| | - P-F Pradat
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France.
- APHP, Département de Neurologie, Hôpital Pitié-Salpêtrière, Centre Référent SLA, Paris, France.
- Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute Ulster University, C-TRIC, Altnagelvin Hospital, Derry, Londonderry, UK.
- Institut pour la Recherche sur la Moelle Epinière et l'encephale (IRME), 15 rue Duranton, 75015, Paris, France.
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Fang Y, Li S, Wang J, Zhang Z, Jiang W, Wang C, Jiang Y, Guo H, Han X, Tian W. Diagnostic efficacy of tract-specific diffusion tensor imaging in cervical spondylotic myelopathy with electrophysiological examination validation. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2024; 33:1230-1244. [PMID: 38286908 DOI: 10.1007/s00586-023-08111-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 11/02/2023] [Accepted: 12/17/2023] [Indexed: 01/31/2024]
Abstract
PURPOSE This study aimed to investigate the effectiveness of tract-specific diffusion tensor imaging (DTI) metrics in identifying the responsible segments for neurological dysfunction in cervical spondylotic myelopathy (CSM). METHODS The study encompassed nineteen participants diagnosed with CSM, including 10 males and 9 females. Additionally, a control group consisting of ten healthy caregivers (5 males and 5 females) were recruited with no symptoms and no compressions on magnetic resonance imaging (MRI). All participants underwent a comprehensive physical examination, MRI assessment, and DTI examination conducted by a senior chief physician. Several parameters were collected from the MR images, including the aspect ratio (defined as the anteroposterior diameter / the transverse diameter of the corresponding segment's spinal cord), transverse ratio (defined as the transverse diameter of the corresponding segment's spinal cord / the transverse diameter of the spinal cord at C2/3), and T2 high signal of the spinal cord. Furthermore, quantitative DTI metrics, such as axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA), were calculated using automatic region-of-interest (ROI) analysis for both whole spinal cord column and dorsal column. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic efficacy of the aspect ratio, transverse ratio, and DTI parameters. The area under the curve (AUC), sensitivity, and specificity were calculated. Intraoperative spinal cord electrophysiological examination was performed as the objective measure of spinal cord function during surgery. RESULTS As determined by electrophysiological examination, neurological dysfunction was found in 2 patients due to C3/4 compression, in 10 patients due to C4/5 compression, in 6 patients due to C5/6 compression, and in 1 patient due to C6/7 compression. The modified Japanese Orthopedic Association scale (mJOA) was 12.71 ± 1.55 in the CSM group, with 4.87 ± 0.72 for sensory nerve function and 5.05 ± 1.35 for motor nerve function. For the control group, none of the volunteers had neurological dysfunction. T2 high signal was found at the most stenotic segment in 13 patients of the CSM group. Considering all the cervical segments, the aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) was more capable of determining the responsible segment than transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). AD, MD, and RD were significantly higher while FA was significantly lower in the responsible segment than in the irresponsible segment (P < 0.05). The AUC of DTI-Dorsal column parameters (AD, MD, RD, FA) was larger than the corresponding parameters of the DTI (Whole spinal cord). AD of DTI-Dorsal Column possessed the greatest efficacy (AUC = 0.823, sensitivity = 84.21%, specificity = 77.32%) to determine the responsible segment, larger than AD of DTI-Whole spinal cord (AUC = 0.822, P = 0.001, Sensitivity = 89.47%, Specificity = 77.32%), aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) and transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). Subgroup analysis revealed that the diagnostic efficacy of DTI and MRI parameters was influenced by cervical spine segment. CONCLUSIONS When considering all cervical segments, AD from the DTI-Dorsal Column exhibited the most significant potential in identifying responsible segments. This potential was found to be superior to that of DTI-Whole spinal cord, aspect ratio, the most stenotic segment, T2 high signals, transverse ratio, motor nerve dysfunction, and sensory nerve dysfunction. The diagnostic effectiveness of both DTI and MRI parameters was notably influenced by the specific cervical spine segment.
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Affiliation(s)
- Yanming Fang
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
- Spine Department, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Sisi Li
- Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Jinchao Wang
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
- Spine Department, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Zhenzhen Zhang
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
- Department of Neurological Electrophysiology, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Wen Jiang
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
- Radiology Department, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Chao Wang
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
- Beijing Research Institute of Traumatology and Orthopaedics, Beijing, China
| | - Yuancheng Jiang
- Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Hua Guo
- Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Xiao Han
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
- Spine Department, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
- Beijing Research Institute of Traumatology and Orthopaedics, Beijing, China.
| | - Wei Tian
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
- Spine Department, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
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Bharadwaj UU, Chin CT, Majumdar S. Practical Applications of Artificial Intelligence in Spine Imaging: A Review. Radiol Clin North Am 2024; 62:355-370. [PMID: 38272627 DOI: 10.1016/j.rcl.2023.10.005] [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: 01/27/2024]
Abstract
Artificial intelligence (AI), a transformative technology with unprecedented potential in medical imaging, can be applied to various spinal pathologies. AI-based approaches may improve imaging efficiency, diagnostic accuracy, and interpretation, which is essential for positive patient outcomes. This review explores AI algorithms, techniques, and applications in spine imaging, highlighting diagnostic impact and challenges with future directions for integrating AI into spine imaging workflow.
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Affiliation(s)
- Upasana Upadhyay Bharadwaj
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, Byers Hall, Suite 203, Room 203D, San Francisco, CA 94158, USA
| | - Cynthia T Chin
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143, USA.
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, Byers Hall, Suite 203, Room 203D, San Francisco, CA 94158, USA
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Hemmerling KJ, Hoggarth MA, Sandhu MS, Parrish TB, Bright MG. MRI mapping of hemodynamics in the human spinal cord. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.22.581606. [PMID: 38464194 PMCID: PMC10925078 DOI: 10.1101/2024.02.22.581606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Impaired spinal cord vascular function contributes to numerous neurological pathologies, making it important to be able to noninvasively characterize these changes. Here, we propose a functional magnetic resonance imaging (fMRI)-based method to map spinal cord vascular reactivity (SCVR). We used a hypercapnic breath-holding task, monitored with end-tidal CO2 (PETCO2), to evoke a systemic vasodilatory response during concurrent blood oxygenation level-dependent (BOLD) fMRI. SCVR amplitude and hemodynamic delay were mapped at the group level in 27 healthy participants as proof-of-concept of the approach, and then in two highly-sampled participants to probe feasibility/stability of individual SCVR mapping. Across the group and the highly-sampled individuals, a strong ventral SCVR amplitude was initially observed without accounting for local regional variation in the timing of the vasodilatory response. Shifted breathing traces (PETCO2) were used to account for temporal differences in the vasodilatory response across the spinal cord, producing maps of SCVR delay. These delay maps reveal an earlier ventral and later dorsal response and demonstrate distinct gray matter regions concordant with territories of arterial supply. The SCVR fMRI methods described here enable robust mapping of spatiotemporal hemodynamic properties of the human spinal cord. This noninvasive approach has exciting potential to provide early insight into pathology-driven vascular changes in the cord, which may precede and predict future irreversible tissue damage and guide the treatment of several neurological pathologies involving the spine.
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Affiliation(s)
- Kimberly J. Hemmerling
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Mark A. Hoggarth
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Physical Therapy, North Central College, Naperville, IL, United States
| | - Milap S. Sandhu
- Shirley Ryan Ability Lab, Chicago, IL, United States
- Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Todd B. Parrish
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Molly G. Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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Seifert AC, Xu J, Kong Y, Eippert F, Miller KL, Tracey I, Vannesjo SJ. Thermal stimulus task fMRI in the cervical spinal cord at 7 Tesla. Hum Brain Mapp 2024; 45:e26597. [PMID: 38375948 PMCID: PMC10877664 DOI: 10.1002/hbm.26597] [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: 04/24/2023] [Revised: 12/15/2023] [Accepted: 01/04/2024] [Indexed: 02/21/2024] Open
Abstract
Although functional magnetic resonance imaging (fMRI) is widely applied in the brain, fMRI of the spinal cord is more technically demanding. Proximity to the vertebral column and lungs results in strong spatial inhomogeneity and temporal fluctuations in B0 . Increasing field strength enables higher spatial resolution and improved sensitivity to blood oxygenation level-dependent (BOLD) signal, but amplifies the effects of B0 inhomogeneity. In this work, we present the first task fMRI in the spinal cord at 7 T. Further, we compare the performance of single-shot and multi-shot 2D echo-planar imaging (EPI) protocols, which differ in sensitivity to spatial and temporal B0 inhomogeneity. The cervical spinal cords of 11 healthy volunteers were scanned at 7 T using single-shot 2D EPI at 0.75 mm in-plane resolution and multi-shot 2D EPI at 0.75 and 0.6 mm in-plane resolutions. All protocols used 3 mm slice thickness. For each protocol, the BOLD response to 13 10-s noxious thermal stimuli applied to the right thumb was acquired in a 10-min fMRI run. Image quality, temporal signal to noise ratio (SNR), and BOLD activation (percent signal change and z-stat) at both individual- and group-level were evaluated between the protocols. Temporal SNR was highest in single-shot and multi-shot 0.75 mm protocols. In group-level analyses, activation clusters appeared in all protocols in the ipsilateral dorsal quadrant at the expected C6 neurological level. In individual-level analyses, activation clusters at the expected level were detected in some, but not all subjects and protocols. Single-shot 0.75 mm generally produced the highest mean z-statistic, while multi-shot 0.60 mm produced the best-localized activation clusters and the least geometric distortion. Larger than expected within-subject segmental variation of BOLD activation along the cord was observed. Group-level sensory task fMRI of the cervical spinal cord is feasible at 7 T with single-shot or multi-shot EPI. The best choice of protocol will likely depend on the relative importance of sensitivity to activation versus spatial localization of activation for a given experiment. PRACTITIONER POINTS: First stimulus task fMRI results in the spinal cord at 7 T. Single-shot 0.75 mm 2D EPI produced the highest mean z-statistic. Multi-shot 0.60 mm 2D EPI provided the best-localized activation and least distortion.
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Affiliation(s)
- Alan C. Seifert
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Diagnostic, Molecular, and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Graduate School of Biomedical SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Junqian Xu
- Department of RadiologyBaylor College of MedicineHoustonTexasUSA
- Department of PsychiatryBaylor College of MedicineHoustonTexasUSA
| | - Yazhuo Kong
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
- Institute of PsychologyChinese Academy of SciencesBeijingChina
| | - Falk Eippert
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
- Max Planck Research Group Pain PerceptionMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Irene Tracey
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - S. Johanna Vannesjo
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
- Department of PhysicsNorwegian University of Science and Technology (NTNU)TrondheimNorway
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Oquita R, Cuello V, Uppati S, Mannuru S, Salinas D, Dobbs M, Potter-Baker KA. Moving toward elucidating alternative motor pathway structures post-stroke: the value of spinal cord neuroimaging. Front Neurol 2024; 15:1282685. [PMID: 38419695 PMCID: PMC10899520 DOI: 10.3389/fneur.2024.1282685] [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: 08/25/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024] Open
Abstract
Stroke results in varying levels of motor and sensory disability that have been linked to the neurodegeneration and neuroinflammation that occur in the infarct and peri-infarct regions within the brain. Specifically, previous research has identified a key role of the corticospinal tract in motor dysfunction and motor recovery post-stroke. Of note, neuroimaging studies have utilized magnetic resonance imaging (MRI) of the brain to describe the timeline of neurodegeneration of the corticospinal tract in tandem with motor function following a stroke. However, research has suggested that alternate motor pathways may also underlie disease progression and the degree of functional recovery post-stroke. Here, we assert that expanding neuroimaging techniques beyond the brain could expand our knowledge of alternate motor pathway structure post-stroke. In the present work, we will highlight findings that suggest that alternate motor pathways contribute to post-stroke motor dysfunction and recovery, such as the reticulospinal and rubrospinal tract. Then we review imaging and electrophysiological techniques that evaluate alternate motor pathways in populations of stroke and other neurodegenerative disorders. We will then outline and describe spinal cord neuroimaging techniques being used in other neurodegenerative disorders that may provide insight into alternate motor pathways post-stroke.
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Affiliation(s)
- Ramiro Oquita
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Victoria Cuello
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Sarvani Uppati
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Sravani Mannuru
- School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Daniel Salinas
- Department of Neuroscience, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
| | - Michael Dobbs
- Department of Clinical Neurosciences, College of Medicine, Florida Atlantic University, Boca Raton, FL, United States
| | - Kelsey A. Potter-Baker
- Department of Neuroscience, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, United States
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Bouyagoub S. A glimpse into the future: perfusion and diffusion MRI techniques for the assessment of cervical spondylotic myelopathy. Eur Radiol 2024; 34:1346-1348. [PMID: 37973634 DOI: 10.1007/s00330-023-10451-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/24/2023] [Accepted: 10/28/2023] [Indexed: 11/19/2023]
Affiliation(s)
- Samira Bouyagoub
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, BN1 9RR, UK.
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47
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Kowalczyk OS, Medina S, Tsivaka D, McMahon SB, Williams SCR, Brooks JCW, Lythgoe DJ, Howard MA. Spinal fMRI demonstrates segmental organisation of functionally connected networks in the cervical spinal cord: A test-retest reliability study. Hum Brain Mapp 2024; 45:e26600. [PMID: 38339896 PMCID: PMC10831202 DOI: 10.1002/hbm.26600] [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: 07/07/2023] [Revised: 12/21/2023] [Accepted: 01/04/2024] [Indexed: 02/12/2024] Open
Abstract
Resting functional magnetic resonance imaging (fMRI) studies have identified intrinsic spinal cord activity, which forms organised motor (ventral) and sensory (dorsal) resting-state networks. However, to facilitate the use of spinal fMRI in, for example, clinical studies, it is crucial to first assess the reliability of the method, particularly given the unique anatomical, physiological, and methodological challenges associated with acquiring the data. Here, we characterise functional connectivity relationships in the cervical cord and assess their between-session test-retest reliability in 23 young healthy volunteers. Resting-state networks were estimated in two ways (1) by estimating seed-to-voxel connectivity maps and (2) by calculating seed-to-seed correlations. Seed regions corresponded to the four grey matter horns (ventral/dorsal and left/right) of C5-C8 segmental levels. Test-retest reliability was assessed using the intraclass correlation coefficient. Spatial overlap of clusters derived from seed-to-voxel analysis between sessions was examined using Dice coefficients. Following seed-to-voxel analysis, we observed distinct unilateral dorsal and ventral organisation of cervical spinal resting-state networks that was largely confined in the rostro-caudal extent to each spinal segmental level, with more sparse connections observed between segments. Additionally, strongest correlations were observed between within-segment ipsilateral dorsal-ventral connections, followed by within-segment dorso-dorsal and ventro-ventral connections. Test-retest reliability of these networks was mixed. Reliability was poor when assessed on a voxelwise level, with more promising indications of reliability when examining the average signal within clusters. Reliability of correlation strength between seeds was highly variable, with the highest reliability achieved in ipsilateral dorsal-ventral and dorso-dorsal/ventro-ventral connectivity. However, the spatial overlap of networks between sessions was excellent. We demonstrate that while test-retest reliability of cervical spinal resting-state networks is mixed, their spatial extent is similar across sessions, suggesting that these networks are characterised by a consistent spatial representation over time.
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Affiliation(s)
- Olivia S. Kowalczyk
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
- The Wellcome Centre for Human Neuroimaging, Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Sonia Medina
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| | - Dimitra Tsivaka
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
- Medical Physics Department, Medical SchoolUniversity of ThessalyLarisaGreece
| | | | - Steven C. R. Williams
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| | | | - David J. Lythgoe
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| | - Matthew A. Howard
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
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Wang C, Han X, Ma X, Jiang W, Wang J, Li S, Guo H, Tian W, Chen H. Spinal cord perfusion is associated with microstructural damage in cervical spondylotic myelopathy patients who underwent cervical laminoplasty. Eur Radiol 2024; 34:1349-1357. [PMID: 37581664 DOI: 10.1007/s00330-023-10011-9] [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: 05/17/2022] [Revised: 05/01/2023] [Accepted: 06/08/2023] [Indexed: 08/16/2023]
Abstract
OBJECTIVES To investigate the association between spinal cord perfusion and microstructural damage in CSM patients who underwent cervical laminoplasty using MR dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) techniques. METHODS A follow-up cohort study was conducted with 53 consecutively recruited CSM patients who had undergone cervical laminoplasty 12-14 months after the surgery from April 2016 to December 2016. Twenty-one aged-matched healthy volunteers were recruited as controls. For each patient, decompressed spinal cord levels were imaged on a 3.0-T MRI scanner by diffusion and DSC sequences to quantify the degrees of microstructural damage and perfusion conditions, respectively. The diffusion data were analyzed by DTI and NODDI models to produce diffusion metrics. Classic indicator dilution model was used to quantify the DSC metrics. Mann-Whitney U test was performed for comparison of diffusion metrics between patients and healthy controls. Pearson correlation was used to explore the associations between the metrics of spinal cord perfusion and microstructural damage. RESULTS DTI metrics, neurite density, and isotropic volume fraction had significant differences between postoperative patients and healthy controls. Pearson correlation test showed that SCBV was significantly positively correlated with RD, MD, and ODI, and negatively correlated with FA and NDI. SCBF was found to be significantly positively correlated with RD and MD, and negatively correlated with FA. CONCLUSIONS Increased spinal cord perfusion quantified by DSC is associated with microstructural damage assessed by diffusion MRI in CSM patients who underwent cervical laminoplasty. CLINICAL RELEVANCE STATEMENT This study found that the spinal cord perfusion is associated with microstructural damage in postoperative cervical spondylotic myelopathy patients, indicating that high perfusion may play a role in the pathophysiological process of cervical spondylotic myelopathy and deserves more attention. KEY POINTS • Spinal cord microstructural damage can be persistent despite the compression had been relieved 12-14 months after the cervical laminoplasty in cervical spondylotic myelopathy (CSM) patients. • Spinal cord perfusion is associated with microstructural damage in CSM patients after the cervical laminoplasty. • Inflammation in the decompressed spinal cord may be a cause of increased perfusion and is associated with microstructural damage during the recovery period of CSM.
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Affiliation(s)
- Chunyao Wang
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiao Han
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
- Beijing Research Institute of Traumatology and Orthopaedics, Beijing, China
| | - Xiaodong Ma
- Center for Magnetic Resonance Research, Radiology, Medical School of the University of Minnesota, Minnesota, USA
| | - Wen Jiang
- Department of Radiology, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Jinchao Wang
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China
| | - Sisi Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Wei Tian
- Department of Spine Surgery, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
| | - Huijun Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
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Zhao J, Sun L, Sun Z, Zhou X, Si H, Zhang D. MSEF-Net: Multi-scale edge fusion network for lumbosacral plexus segmentation with MR image. Artif Intell Med 2024; 148:102771. [PMID: 38325928 DOI: 10.1016/j.artmed.2024.102771] [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: 12/24/2022] [Revised: 12/08/2023] [Accepted: 01/14/2024] [Indexed: 02/09/2024]
Abstract
Nerve damage of spine areas is a common cause of disability and paralysis. The lumbosacral plexus segmentation from magnetic resonance imaging (MRI) scans plays an important role in many computer-aided diagnoses and surgery of spinal nerve lesions. Due to the complex structure and low contrast of the lumbosacral plexus, it is difficult to delineate the regions of edges accurately. To address this issue, we propose a Multi-Scale Edge Fusion Network (MSEF-Net) to fully enhance the edge feature in the encoder and adaptively fuse multi-scale features in the decoder. Specifically, to highlight the edge structure feature, we propose an edge feature fusion module (EFFM) by combining the Sobel operator edge detection and the edge-guided attention module (EAM), respectively. To adaptively fuse the multi-scale feature map in the decoder, we introduce an adaptive multi-scale fusion module (AMSF). Our proposed MSEF-Net method was evaluated on the collected spinal MRI dataset with 89 patients (a total of 2848 MR images). Experimental results demonstrate that our MSEF-Net is effective for lumbosacral plexus segmentation with MR images, when compared with several state-of-the-art segmentation methods.
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Affiliation(s)
- Junyong Zhao
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing 211106, China
| | - Liang Sun
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing 211106, China; Nanjing University of Aeronautics and Astronautics Shenzhen Research Institute, Shenzhen 518063, China.
| | - Zhi Sun
- Department of Medical Imaging, Shandong Provincial Hospital, Jinan 250021, China
| | - Xin Zhou
- Department of Orthopedics, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Haipeng Si
- Department of Orthopedics, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
| | - Daoqiang Zhang
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing 211106, China; Nanjing University of Aeronautics and Astronautics Shenzhen Research Institute, Shenzhen 518063, China.
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50
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Vahdat S, Landelle C, Lungu O, De Leener B, Doyon J, Baniasad F. FASB: an integrated processing pipeline for Functional Analysis of simultaneous Spinal cord-Brain fMRI. RESEARCH SQUARE 2024:rs.3.rs-3889284. [PMID: 38352433 PMCID: PMC10862948 DOI: 10.21203/rs.3.rs-3889284/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Simultaneous functional magnetic resonance imaging (fMRI) of the spinal cord and brain represents a powerful method for examining both ascending sensory and descending motor pathways in humans in vivo . However, its image acquisition protocols, and processing pipeline are less well established. This limitation is mainly due to technical difficulties related to spinal cord fMRI, and problems with the logistics stemming from a large field of view covering both brain and cervical cord. Here, we propose an acquisition protocol optimized for both anatomical and functional images, as well as an optimized integrated image processing pipeline, which consists of a novel approach for automatic modeling and mitigating the negative impact of spinal voxels with low temporal signal to noise ratio (tSNR). We validate our integrated pipeline, named FASB, using simultaneous fMRI data acquired during the performance of a motor task, as well as during resting-state conditions. We demonstrate that FASB outperforms the current spinal fMRI processing methods in three domains, including motion correction, registration to the spinal cord template, and improved detection power of the group-level analysis by removing the effects of participant-specific low tSNR voxels, typically observed at the disk level. Using FASB, we identify significant task-based activations in the expected sensorimotor network associated with a unilateral handgrip force production task across the entire central nervous system, including the contralateral sensorimotor cortex, thalamus, striatum, cerebellum, brainstem, as well as ipsilateral ventral horn at C5-C8 cervical levels. Additionally, our results show significant task-based functional connectivity between the key sensory and motor brain areas and the dorsal and ventral horns of the cervical cord. Overall, our proposed acquisition protocol and processing pipeline provide a robust method for characterizing the activation and functional connectivity of distinct cortical, subcortical, brainstem and spinal cord regions in humans.
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