A novel, easy-to-use scoring system for the diagnosis of extraforaminal stenosis of lumbosacral transition using X-ray and CT scan

Abstract

Background

The diagnosis of extraforaminal stenosis of the lumbosacral transition (ESLT) using conventional two-dimensional (2D) magnetic resonance imaging (MRI) (2D-MRI) is challenging, with some overlooking of ESLT. It is desirable to have criteria for determining whether patients require additional three-dimensional MRI (3D-MRI). In this study, we created a simple scoring system to screen for ESLT using X-rays and computed tomography (CT).

Methods

Ninety-two cases with unilateral L5 radiculopathy were recruited. We used 3D-MRI to determine the presence of ESLT. X-rays and CT were assessed by two examiners. X-rays were assessed for “vertebral inclination”, “lumbosacral overlap sign”, “lordosis angle”, “disc height”, and “vacuum phenomenon”. Axial CT slices were assessed for “transverse process drooping,” “nearthrosis” between transverse process and sacral ala, “osteosclerosis” of L5 endplate, and “osteophyte”. Correlation between ESLT and each radiological variable was assessed. Reproducible variables were defined as >0.6 for both intra- and interobserver agreement. Multivariate logistic regression analysis was performed using the radiological variables that were correlated with ESLT and judged to be reproducible. Finally, a score was assigned to each selected variable considering the odds ratio (OR), and a radiological index for screening the extraforaminal stenosis (RISE) score was established. The receiver operating characteristic (ROC) curve analysis was performed for external validation.

Results

Vertebral inclination (>3°) (OR: 4.8, p = 0.003), nearthrosis (OR: 10.2, p < 0.001), and osteophyte (OR: 5.2, p = 0.002) were selected. Considering the OR, 1 point was assigned to vertebral inclination and osteophyte, and 2 points were assigned to nearthrosis, obtaining RISE score (0–4 points). The area under the ROC curve was 0.91.

Conclusions

The RISE score accurately predicted the presence of ESLT, allowing aids in the selection of cases that require 3D-MRI.