Reliability analysis of the epidural spinal cord compression scale. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: The evolution of imaging techniques, along with highly effective radiation options has changed the way metastatic epidural tumors are treated. While high-grade epidural spinal cord compression (ESCC) frequently serves as an indication for surgical decompression, no consensus exists in the literature about the precise definition of this term. The advancement of the treatment paradigms in patients with metastatic tumors for the spine requires a clear grading scheme of ESCC. The degree of ESCC often serves as a major determinant in the decision to operate or irradiate. The purpose of this study was to determine the reliability and validity of a 6-point, MR imaging-based grading system for ESCC. METHODS: To determine the reliability of the grading scale, a survey was distributed to 7 spine surgeons who participate in the Spine Oncology Study Group. The MR images of 25 cervical or thoracic spinal tumors were distributed consisting of 1 sagittal image and 3 axial images at the identical level including T1-weighted, T2-weighted, and Gd-enhanced T1-weighted images. The survey was administered 3 times at 2-week intervals. The inter- and intrarater reliability was assessed. RESULTS: The inter- and intrarater reliability ranged from good to excellent when surgeons were asked to rate the degree of spinal cord compression using T2-weighted axial images. The T2-weighted images were superior indicators of ESCC compared with T1-weighted images with and without Gd. CONCLUSIONS: The ESCC scale provides a valid and reliable instrument that may be used to describe the degree of ESCC based on T2-weighted MR images. This scale accounts for recent advances in the treatment of spinal metastases and may be used to provide an ESCC classification scheme for multicenter clinical trial and outcome studies.

authors

  • Bilsky, Mark H.
  • Laufer, Ilya
  • Fourney, Daryl R
  • Groff, Michael
  • Schmidt, Meic H
  • Varga, Peter Paul
  • Vrionis, Frank D
  • Yamada, Yoshiya
  • Gerszten, Peter C
  • Kuklo, Timothy R

publication date

  • September 1, 2010

Research

keywords

  • Diagnosis, Computer-Assisted
  • Magnetic Resonance Imaging
  • Spinal Cord Compression
  • Spinal Neoplasms

Identity

Scopus Document Identifier

  • 77956396943

Digital Object Identifier (DOI)

  • 10.3171/2010.3.SPINE09459

PubMed ID

  • 20809724

Additional Document Info

volume

  • 13

issue

  • 3