Evaluating tissue injury in cervical spondylotic myelopathy with spinal cord MRI: a systematic review

Khan, Ali Fahim; Mohammadi, Esmaeil; Haynes, Grace; Hameed, Sanaa; Rohan, Michael; Anderson, David B.; Weber, Kenneth A.; Muhammad, Fauziyya; Smith, Zachary A.

doi:10.1007/s00586-023-07990-0

Cited by 7 publications

(3 citation statements)

References 62 publications

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“…Some studies in the above analysis demonstrated the great usefulness of MRI in the diagnosis of CSM, but the authors pay special attention to the fact that other modal configurations can also be very useful in detailed diagnostics. This is one of the newest methods and is still in the development phase; therefore, researchers emphasize that it is important to conduct further research into the use of individual MRI elements in the spinal cord in the course of CSM [ 35 ]. In another recent report from December 2023, Atchut et al confirmed the role of diffusion tensor imaging (DTI) in the diagnosis of spinal stenosis.…”

Section: Discussionmentioning

confidence: 99%

Cervical Spondylotic Myelopathy—Diagnostics and Clinimetrics

Opara,

Odzimek

2024

Diagnostics

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Cervical myelopathy is referred to in many ways in the English literature, for example, as cervical spondylotic myelopathy (CSM), spondylotic radiculomyelopathy (SRM) or degenerative cervical myelopathy (DCM). In addition, more frequent occurrences are noted in older adults and to a greater extent in men. The causes of the effects of cervical myelopathy may be the appearance of lesions on the spinal cord, ischemia due to compression of the vertebral artery and repeated micro-injuries during maximal movements—hyperflexion or hyperextension. It is well known that lesions on the spinal cord may occur in a quarter of the population, and this problem is clearly noted in people over 60 years old. The symptoms of SCM develop insidiously, and their severity and side (unilateral or bilateral) are associated with the location and extent of spinal cord compression. Neurological examination most often diagnoses problems in the upper limbs (most often paresis with developing hand muscle atrophy), pyramidal paralysis in one or both lower limbs and disorders in the urinary system. To make a diagnosis of CSM, it is necessary to perform MRI and neurophysiological tests (such as EMG or sensory and/or motor-evoked potentials). The use of appropriately selected scales and specific tests in diagnostics is also crucial. This narrative review article describes the latest knowledge on the diagnosis and clinimetrics of cervical spondylotic myelopathy in adults and provides future directions.

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Section: Discussionmentioning

confidence: 99%

Cervical Spondylotic Myelopathy—Diagnostics and Clinimetrics

Opara,

Odzimek

2024

Diagnostics

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“…Cord compression following degenerative processes in cervical spine often leads to Degenerative Cervical Myelopathy (DCM) also known as cervical spondylotic myelopathy, a common cause of myelopathy in adults. It is associated with cervical spinal cord tissue injury [ 1 ] and functional changes in the brain [ 2 ]. DCM commonly presents with neurologic manifestations such as loss of dexterity and gait issues [ 3 ] and patients are typically screen using Magnetic Resonance Imaging [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Systematic review protocol for complications following surgical decompression of degenerative cervical myelopathy

Mohammadi,

Khan,

Villeneuve

et al. 2024

PLoS ONE

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Background Degenerative Cervical Myelopathy (DCM) is one of the most common degenerative disorders of cervical spine and sources of cord dysfunction in adults. It usually manifests with neurologic presentations such as loss of dexterity and gait issues. Treatment for moderate and severe cases of DCM is surgical decompression of the region. There are many approaches available for surgical intervention which could be categorized into anterior and posterior based on the side of neck where operation takes place. Additionally, for certain cases the hybridized anterior-posterior combined surgery is indicated. While there are many technical differences between these approaches with each having its own advantages, the complications and safety profiles of them are not fully disclosed. This protocol aims to systematically search for current reports on complications of surgical decompression methods of DCM and pool them for robust evidence generation. Method Search will be carried out in PubMed, Scopus, and Cochrane databases for retrospective and prospective surgical series, cohorts, or trials being performed for DCM with at least a sample size of 20 patients. Query strings will be designed to capture reports with details of complications with no year limit. Studies not being original (e.g., review articles, case reports, etc.), not in English, having patients younger than 18-years-old, and not reporting at least one complication will be excluded. Two independent reviewers will review the titles and abstracts for first round of screening. Full text of retrieved studies from previous round will be screened again by the same reviewers. In case of discrepancy, the third senior reviewer will be consulted. Eligible studies will then be examined for data extraction where data will be recorded into standardized form. Cumulative incidence and 95% confidence intervals of complication will be then pooled based on generalized linear mixed models with consideration of approach of surgery as subgroups. Heterogeneity tests will be performed for assessment of risk of bias. Discussion This systematic review is aimed at providing practical information for spine surgeons on the rates of complications of different surgical approaches of DCM decompression. Proper decision-making regarding the surgical approach in addition to informing patients could be facilitated through results of this investigation.

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“…Cervical spondylotic myelopathy (CSM) is a common degenerative neurological condition that occurs when the spinal cord is compressed due to degenerative changes or traumatic injury to the cervical spine [ 1 , 2 ]. If left untreated, 20–60% of patients with CSM may experience neurological deterioration [ 3 , 4 ]. Treatment options for CSM include anterior and/or posterior approaches to the spine [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing the predictive capability of machine learning models in determining clinical outcomes for patients with cervical spondylotic myelopathy treated with laminectomy and posterior spinal fusion

Alimohammadi,

Fatahi,

Abdi

et al. 2024

Patient Saf Surg

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Background Cervical spondylotic myelopathy (CSM) is a prevalent degenerative condition resulting from spinal cord compression and injury. Laminectomy with posterior spinal fusion (LPSF) is a commonly employed treatment approach for CSM patients. This study aimed to assess the effectiveness of machine learning models (MLMs) in predicting clinical outcomes in CSM patients undergoing LPSF. Methods A retrospective analysis was conducted on 329 CSM patients who underwent LPSF at our institution from Jul 2017 to Jul 2023. Neurological outcomes were evaluated using the modified Japanese Orthopaedic Association (mJOA) scale preoperatively and at the final follow-up. Patients were categorized into two groups based on clinical outcomes: the favorable group (recovery rates ≥ 52.8%) and the unfavorable group (recovery rates < 52.8%). Potential predictors for poor clinical outcomes were compared between the groups. Four MLMs—random forest (RF), logistic regression (LR), support vector machine (SVM), and k-nearest neighborhood (k-NN)—were utilized to predict clinical outcome. RF model was also employed to identify factors associated with poor clinical outcome. Results Out of the 329 patients, 185 were male (56.2%) and 144 were female (43.4%), with an average follow-up period of 17.86 ± 1.74 months. Among them, 267 patients (81.2%) had favorable clinical outcomes, while 62 patients (18.8%) did not achieve favorable results. Analysis using binary logistic regression indicated that age, preoperative mJOA scale, and symptom duration (p < 0.05) were independent predictors of unfavorable clinical outcomes. All models performed satisfactorily, with RF achieving the highest accuracy of 0.922. RF also displayed superior sensitivity and specificity (sensitivity = 0.851, specificity = 0.944). The Area under the Curve (AUC) values for RF, Logistic LR, SVM, and k-NN were 0.905, 0.827, 0.851, and 0.883, respectively. The RF model identified preoperative mJOA scale, age, symptom duration, and MRI signal changes as the most significant variables associated with poor clinical outcomes in descending order. Conclusions This study highlighted the effectiveness of machine learning models in predicting the clinical outcomes of CSM patients undergoing LPSF. These models have the potential to forecast clinical outcomes in this patient population, providing valuable prognostic insights for preoperative counseling and postoperative management.

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Evaluating tissue injury in cervical spondylotic myelopathy with spinal cord MRI: a systematic review

Cited by 7 publications

References 62 publications

Cervical Spondylotic Myelopathy—Diagnostics and Clinimetrics

Cervical Spondylotic Myelopathy—Diagnostics and Clinimetrics

Systematic review protocol for complications following surgical decompression of degenerative cervical myelopathy

Assessing the predictive capability of machine learning models in determining clinical outcomes for patients with cervical spondylotic myelopathy treated with laminectomy and posterior spinal fusion

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