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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; 24:1605-1614. [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] [MESH Headings] [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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Baker AK, Park SH, Weber KA, Martucci KT. Reduced Spinal Cord Gray Matter in Patients with Fibromyalgia Using Opioids Long-term. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.02.23289401. [PMID: 37205383 PMCID: PMC10187444 DOI: 10.1101/2023.05.02.23289401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Objective Chronic pain involves alterations in brain gray matter volume (GMV). Moreover, opioid medications are known to reduce GMV in numerous brain regions involved in pain processing. However, no research has evaluated (1) chronic pain-related GMV alterations in the spinal cord or (2) the effect of opioids on spinal cord GMV. Accordingly, this study evaluated spinal cord GMV in health controls and patients with fibromyalgia who were using and not using opioids long-term. Methods We analyzed average C5 - C7 GMV of the spinal cord dorsal and ventral horns in separate female cohorts of healthy controls (HC, n = 30), fibromyalgia patients not using opioids (FMN, n = 31), and fibromyalgia patients using opioids long-term (FMO, n = 27). To assess the effect of group on average dorsal and ventral horn GMV, we conducted a one-way multivariate analysis of covariance. Results After controlling for age, we observed a significant effect of group on ventral horn GMV (p = 0.03, η2 = 0.09), and on dorsal horn GMV (p = 0.05, η2 = 0.08). Tukey's posthoc comparisons showed that, compared to HC participants, FMOs had significantly lower ventral (p = 0.01) and dorsal (p = 0.02) GMVs. Among FMOs only, ventral horn GMV was significantly positively associated with pain severity and interference, and both dorsal and ventral GMVs were significantly positively associated with cold pain tolerance. Conclusion Long-term opioid use may impact sensory processing in fibromyalgia via gray matter changes within the cervical spinal cord.
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Affiliation(s)
- Anne K. Baker
- Human Affect and Pain Neuroscience Laboratory, Department of Anesthesiology, Duke University School of Medicine, Durham NC 27710
- Center for Translational Pain Medicine, Duke University Medical Center, Durham NC 27710
| | - Su Hyoun Park
- Human Affect and Pain Neuroscience Laboratory, Department of Anesthesiology, Duke University School of Medicine, Durham NC 27710
- Center for Translational Pain Medicine, Duke University Medical Center, Durham NC 27710
| | - Kenneth A. Weber
- Systems Neuroscience and Pain Lab, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School fo Medicine, Palo Alto, CA 94304
| | - Katherine T. Martucci
- Human Affect and Pain Neuroscience Laboratory, Department of Anesthesiology, Duke University School of Medicine, Durham NC 27710
- Center for Translational Pain Medicine, Duke University Medical Center, Durham NC 27710
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Paliwal M, Weber KA, Smith AC, Elliott JM, Muhammad F, Dahdaleh NS, Bodurka J, Dhaher Y, Parrish TB, Mackey S, Smith ZA. Fatty infiltration in cervical flexors and extensors in patients with degenerative cervical myelopathy using a multi-muscle segmentation model. PLoS One 2021; 16:e0253863. [PMID: 34170961 PMCID: PMC8232539 DOI: 10.1371/journal.pone.0253863] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 06/14/2021] [Indexed: 12/27/2022] Open
Abstract
Background In patients with degenerative cervical myelopathy (DCM) that have spinal cord compression and sensorimotor deficits, surgical decompression is often performed. However, there is heterogeneity in clinical presentation and post-surgical functional recovery. Objectives Primary: a) to assess differences in muscle fat infiltration (MFI) in patients with DCM versus controls, b) to assess association between MFI and clinical disability. Secondary: to assess association between MFI pre-surgery and post-surgical functional recovery. Study design Cross-sectional case control study. Methods Eighteen patients with DCM (58.6 ± 14.2 years, 10 M/8F) and 25 controls (52.6 ± 11.8 years, 13M/12 F) underwent 3D Dixon fat-water imaging. A convolutional neural network (CNN) was used to segment cervical muscles (MFSS- multifidus and semispinalis cervicis, LC- longus capitis/colli) and quantify MFI. Modified Japanese Orthopedic Association (mJOA) and Nurick were collected. Results Patients with DCM had significantly higher MFI in MFSS (20.63 ± 5.43 vs 17.04 ± 5.24, p = 0.043) and LC (18.74 ± 6.7 vs 13.66 ± 4.91, p = 0.021) than controls. Patients with increased MFI in LC and MFSS had higher disability (LC: Nurick (Spearman’s ρ = 0.436, p = 0.003) and mJOA (ρ = -0.399, p = 0.008)). Increased MFI in LC pre-surgery was associated with post-surgical improvement in Nurick (ρ = -0.664, p = 0.026) and mJOA (ρ = -0.603, p = 0.049). Conclusion In DCM, increased muscle adiposity is significantly associated with sensorimotor deficits, clinical disability, and functional recovery after surgery. Accurate and time efficient evaluation of fat infiltration in cervical muscles may be conducted through implementation of CNN models.
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Affiliation(s)
- Monica Paliwal
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- * E-mail:
| | - Kenneth A. Weber
- Department of Anesthesiology, Systems Neuroscience and Pain Laboratory, Perioperative and Pain Medicine, Stanford University, Palo Alto, California, United States of America
| | - Andrew C. Smith
- Department of Physical Medicine and Rehabilitation, School of Medicine, Physical Therapy Program, Aurora, Colorado, United States of America
| | - James M. Elliott
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
- Faculty of Medicine and Health, University of Sydney, Kolling Institute of Medical Research, St. Leonards, New South Wales, Australia
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Nader S. Dahdaleh
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, Oklahoma, United States of America
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Yasin Dhaher
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Todd B. Parrish
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Sean Mackey
- Department of Anesthesiology, Systems Neuroscience and Pain Laboratory, Perioperative and Pain Medicine, Stanford University, Palo Alto, California, United States of America
| | - Zachary A. Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
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