MR Classification System Based on Axial Images for Cervical Compressive Myelopathy

Area of Science:

• Radiology
• Neurology
• Orthopedics

Background:

• Cervical compressive myelopathy (CCM) diagnosis relies on imaging.
• Standardized classification systems are needed for better assessment and outcome prediction.

Purpose of the Study:

• Propose a novel magnetic resonance (MR) classification system (Ax-CCM) using axial images for CCM.
• Assess interobserver agreement for the Ax-CCM system.
• Evaluate the correlation between Ax-CCM patterns, baseline CCM severity, and surgical outcomes.

Main Methods:

• Retrospective analysis of 202 CCM patients who underwent surgery.
• Ax-CCM classification based on intramedullary hyperintensity on axial T2-weighted MR images (Type 0-3).
• Interobserver variability assessed using intraclass correlation coefficient; modified Japanese Orthopedic Association (JOA) scores and surgical outcomes analyzed.

Main Results:

• The Ax-CCM system demonstrated good interobserver agreement (Intraclass Correlation Coefficient = 0.83).
• Ax-CCM patterns significantly correlated with preoperative JOA scores (P < .05).
• Type 2 pattern was associated with the worst preoperative JOA scores and a significantly lower proportion of good postoperative improvement (37% vs 52%, P = .034).

Conclusions:

• The proposed Ax-CCM system is reliable and reproducible among observers.
• Ax-CCM Type 2 pattern is a significant predictor of poorer preoperative neurologic status and reduced surgical recovery in CCM patients.