Identifying vertebral end plate lesions (schmorl's nodes) using a semi-automatic method

INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.