Abstract
BACKGROUD: The conventional magnetic resonance imaging (MRI) grading system for foraminal stenosis (FS), known as the Lee classification, was introduced in 2010 and is widely utilized in clinical practice. Previous studies have reported that the conventional grading system for FS lacks prediction ability for surgical treatment. The purpose of this study was to develop a novel MRI grading system for lumbar FS with improved prediction ability for surgical treatment by incorporating facet effusion to indicate segmental instability. METHODS: We retrospectively reviewed patients diagnosed with lumbar FS between 2011 and 2017 who had a follow-up period of at least 5 years. The FS severity was assessed using a conventional MRI grading system developed by Lee et al. We recorded whether the patient underwent surgical treatment for FS during the follow-up period and the time from the initial diagnosis to surgery. Survival analysis using a Kaplan-Meier curve and log-rank test was performed to verify the impact of FS severity on the surgical treatment. We performed additional survival analysis after modifying the grading system by incorporating the presence of excessive facet joint effusion assessed using axial MRI. We also compared the discrimination ability of the modified and conventional grading systems using Uno's concordance index (C-index). RESULTS: In total, 235 patients with a mean age of 63.7 years were included in this study. During the mean follow-up period of 8.1 years, 63 patients underwent surgical treatment for FS. The conventional grading system revealed no significant difference in survival between the grade 2 and 3 groups (p = 0.104). Conversely, the modified grading system revealed a significant difference in survival between the new grade 2 and 3 groups (p < 0.001). After modification, the discrimination ability, assessed using Uno's Cindex, significantly improved from 0.69 to 0.73. CONCLUSIONS: The Facet Effusion-Incorporating Grading System, which adds excessive facet joint effusion to the conventional MRI grading framework, demonstrated improved predictive value for surgical treatment and better discriminatory ability compared with the original system.