Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy
Background Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Clinical guidelines regarding surgery for patients with mild DCM and minimal symptoms remain uncertain. This study aims to identify imaging and clinical predictors of neurological det...
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BMJ Publishing Group
2025-01-01
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| Series: | BMJ Neurology Open |
| Online Access: | https://neurologyopen.bmj.com/content/7/1/e000940.full |
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| author | Jefferson R Wilson David Anderson Stephan Duplessis Julien Cohen-Adad David W Cadotte Nathan Evaniew Jacques Bouchard Michael Craig Abdul Al-Shawwa Kalum Ost Steve Casha W Bradley Jacobs Saswati Tripathy Peter Lewkonia Fred Nicholls Alex Soroceanu Ganesh Swamy Kenneth C Thomas Michael MH Yang Nicholas Dea |
| author_facet | Jefferson R Wilson David Anderson Stephan Duplessis Julien Cohen-Adad David W Cadotte Nathan Evaniew Jacques Bouchard Michael Craig Abdul Al-Shawwa Kalum Ost Steve Casha W Bradley Jacobs Saswati Tripathy Peter Lewkonia Fred Nicholls Alex Soroceanu Ganesh Swamy Kenneth C Thomas Michael MH Yang Nicholas Dea |
| author_sort | Jefferson R Wilson |
| collection | DOAJ |
| description | Background Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Clinical guidelines regarding surgery for patients with mild DCM and minimal symptoms remain uncertain. This study aims to identify imaging and clinical predictors of neurological deterioration in mild DCM and explore pathophysiological correlates to guide clinical decision-making.Methods Patients with mild DCM underwent advanced MRI scans that included T2-weighted, diffusion tensor imaging and magnetisation transfer (MT) sequences, along with clinical outcome measures at baseline and 6-month intervals after enrolment. Quantitative MRI (qMRI) metrics were derived above and below maximally compressed cervical levels (MCCLs). Various machine learning (ML) models were trained to predict 6 month neurological deterioration, followed by global and local model interpretation to assess feature importance.Results A total of 49 patients were followed for a maximum of 2 years, contributing 110 6-month data entries. Neurological deterioration occurred in 38% of cases. The best-performing ML model, combining clinical and qMRI metrics, achieved a balanced accuracy of 83%, and an area under curve-receiver operating characteristic of 0.87. Key predictors included MT ratio (demyelination) above the MCCL in the dorsal and ventral funiculi and moderate tingling in the arm, shoulder or hand. qMRI metrics significantly improved predictive performance compared to models using only clinical (bal. acc=68.1%) or imaging data (bal. acc=57.4%).Conclusions Reduced myelin content in the dorsal and ventral funiculi above the site of compression, combined with sensory deficits in the hands and gait/balance disturbances, predicts 6-month neurological deterioration in mild DCM and may warrant early surgical intervention. |
| format | Article |
| id | doaj-art-e4477746cee04643b7910577935440ab |
| institution | Kabale University |
| issn | 2632-6140 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Neurology Open |
| spelling | doaj-art-e4477746cee04643b7910577935440ab2025-02-01T02:00:13ZengBMJ Publishing GroupBMJ Neurology Open2632-61402025-01-017110.1136/bmjno-2024-000940Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathyJefferson R Wilson0David Anderson1Stephan Duplessis2Julien Cohen-Adad3David W Cadotte4Nathan Evaniew5Jacques Bouchard6Michael Craig7Abdul Al-Shawwa8Kalum Ost9Steve Casha10W Bradley Jacobs11Saswati Tripathy12Peter Lewkonia13Fred Nicholls14Alex Soroceanu15Ganesh Swamy16Kenneth C Thomas17Michael MH Yang18Nicholas Dea197 Department of Neurosurgery, Toronto Western Hospital, Toronto, UK9 Faculty of Medicine and Health, School of Health Sciences, The University of Sydney, Sydney, New South Wales, Australia2 Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada2 Institute of Biomedical Engineering, École Polytechnique de Montréal, Montréal, Québec, Canada3 Department of Neurosurgery, University of Calgary, Calgary, Alberta, Canada2Department of Surgery, McMaster University, Hamilton, Ontario, CanadaUniversity of Calgary Orthopaedic Surgery Residency Training Program, Head, Spine Section, Bone and Joint Health Program, University of Calgary, Calgary, Alberta, Canada5 Department of Psychology, Northumbria University, Newcastle upon Tyne, UKHotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, Alberta, CanadaHotchkiss Brain Institute, University of Calgary Cumming School of Medicine, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaSection of Orthopaedic Surgery, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Orthopaedic and Neurosurgery Spine Program, University of Calgary Department of Surgery, Calgary, Alberta, CanadaCombined Neurosurgical and Orthopaedic Spine Program, The University of British Columbia Department of Surgery, Vancouver, British Columbia, CanadaBackground Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Clinical guidelines regarding surgery for patients with mild DCM and minimal symptoms remain uncertain. This study aims to identify imaging and clinical predictors of neurological deterioration in mild DCM and explore pathophysiological correlates to guide clinical decision-making.Methods Patients with mild DCM underwent advanced MRI scans that included T2-weighted, diffusion tensor imaging and magnetisation transfer (MT) sequences, along with clinical outcome measures at baseline and 6-month intervals after enrolment. Quantitative MRI (qMRI) metrics were derived above and below maximally compressed cervical levels (MCCLs). Various machine learning (ML) models were trained to predict 6 month neurological deterioration, followed by global and local model interpretation to assess feature importance.Results A total of 49 patients were followed for a maximum of 2 years, contributing 110 6-month data entries. Neurological deterioration occurred in 38% of cases. The best-performing ML model, combining clinical and qMRI metrics, achieved a balanced accuracy of 83%, and an area under curve-receiver operating characteristic of 0.87. Key predictors included MT ratio (demyelination) above the MCCL in the dorsal and ventral funiculi and moderate tingling in the arm, shoulder or hand. qMRI metrics significantly improved predictive performance compared to models using only clinical (bal. acc=68.1%) or imaging data (bal. acc=57.4%).Conclusions Reduced myelin content in the dorsal and ventral funiculi above the site of compression, combined with sensory deficits in the hands and gait/balance disturbances, predicts 6-month neurological deterioration in mild DCM and may warrant early surgical intervention.https://neurologyopen.bmj.com/content/7/1/e000940.full |
| spellingShingle | Jefferson R Wilson David Anderson Stephan Duplessis Julien Cohen-Adad David W Cadotte Nathan Evaniew Jacques Bouchard Michael Craig Abdul Al-Shawwa Kalum Ost Steve Casha W Bradley Jacobs Saswati Tripathy Peter Lewkonia Fred Nicholls Alex Soroceanu Ganesh Swamy Kenneth C Thomas Michael MH Yang Nicholas Dea Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy BMJ Neurology Open |
| title | Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy |
| title_full | Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy |
| title_fullStr | Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy |
| title_full_unstemmed | Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy |
| title_short | Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy |
| title_sort | spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy |
| url | https://neurologyopen.bmj.com/content/7/1/e000940.full |
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