Quantitative versus qualitative MRI criteria for cervical spinal canal stenosis and cord compression: a comparative analysis and their relationship with clinical symptoms

Abstract Cervical spinal canal stenosis (CSCS) and spinal cord compression are important causes of neurological dysfunction, yet the correlation between imaging findings and clinical symptoms is variable. This study aimed to compare quantitative and qualitative MRI criteria for CSCS and cord compression and evaluate their relationship with clinical manifestations. In this prospective cross-sectional study, 1,084 patients referred for cervical spine MRI were screened, with 296 patients demonstrating stenosis included in the analysis. Clinical severity was assessed using the Modified Japanese Orthopaedic Association (mJOA) score. MRI evaluations included five quantitative parameters—Maximum Canal Compression (MCC), Maximum Spinal Cord Compression (MSCC), Spinal Cord Occupation Ratio (SCOR), Compression Ratio (CR), and Transverse Area (TA)—and a four-grade qualitative grading system based on the degree of subarachnoid space obliteration and spinal cord impingement. Statistical analyses assessed correlations between imaging metrics and clinical scores, agreement between quantitative and qualitative assessments, and the ability of MRI parameters to discriminate neurological deficits. MCC, MSCC, and CR showed strong agreement with qualitative grades and significantly differentiated stenosis severity ( p < 0.001), whereas SCOR and TA were less discriminative. Quantitative metrics correlated with clinical deficits, including upper limb motor and sensory impairments and sphincter dysfunction, but correlations with overall mJOA scores were modest. Patients with cord signal changes exhibited higher MCC and MSCC and lower CR and TA. Quantitative MRI metrics provide an objective and reproducible assessment of cervical stenosis and complement qualitative grading. While these measures are associated with specific neurological deficits, imaging alone cannot fully predict overall clinical severity. Integrating quantitative and qualitative evaluations may enhance diagnostic accuracy and inform patient management.