A semiautomatic method to identify vertebral end plate lesions (Schmorl's nodes)

Nicolas Newell, Caroline A. Grant, Maree T. Izatt, J. Paige Little, Mark J. Pearcy, Clayton J. Adam

There are differences in definitions of end plate lesions (EPLs), often referred to as Schmorl's nodes, that may, to some extent, account for the large range of reported prevalence (3.8 - 76%). To develop a technique to measure the size, prevalence and location of EPLs in a consistent manner. This study proposed a method using a detection algorithm which was applied to five adolescent females (average age 15.1 years, range 13.0 to 19.2 years) with idiopathic scoliosis (average major Cobb angle 60°, range 55 to 67°). Existing low-dose, computed tomography (CT) scans were segmented semi-automatically to extract 3D morphology of each vertebral endplate. Any remaining attachments to the posterior elements of adjacent vertebrae or endplates were then manually sectioned. An automatic algorithm was used to determine the presence and position of EPLs. EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 11/15 of the EPLs were seen in the lumbar spine. The algorithm was found to be most sensitive to changes in the minimum EPL gradient at the edges of the EPL. This study describes an imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs. The technique can be used to analyse large populations without observer errors in EPL definitions.