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.
ABSTRACT
OBJECTIVE: The technique of lateral mass fixation restores the posterior tension band and provides effective stabilization in patients with many types of traumatic injuries. However, postoperative wound pain is not uncommon. The objective of this work is to describe a modified technique of minimally invasive lateral mass plating for cervical spine trauma. METHODS: Patient 1 was a 64-year-old woman who had been in a motor vehicle accident and sustained bilateral C5-C6 facet dislocation with posterior C5-C6 distraction. She was otherwise neurologically intact, and attempts at closed reduction were not successful. Patient 2 was a 16-year-old girl who had also been in a motor vehicle accident but had an incomplete spinal cord injury. She had an unstable burst fracture of C7 with posterior C5-C6 distraction. Both patients underwent anterior cervical fusion followed by staged minimally invasive posterior fusion with good results. A dilator tubular retractor system (METRX) was used to access the bilateral lateral masses through a small midline incision under fluoroscopic guidance. Lateral mass screws were then placed by using a modified Magerl technique, securing two-hole plates on each side onto the lateral masses, performed through the METRX system. We also successfully performed four-level lateral mass plating in a cadaveric cervical spine using a 2-cm skin incision. CONCLUSIONS: We describe successful placement of lateral mass screw and plate constructs with the use of a minimally invasive approach by means of a tubular dilator retractor system. This approach preserves the integrity of the muscles and ligaments that maintain the posterior tension band of the cervical spine.
