A cluster analysis describing spine and torso shape in Lenke type 1 adolescent idiopathic scoliosis

Abstract

Purpose: The purpose of this work is to identify the variability and subtypes of the combined shape of the spine and torso in Lenke type 1 adolescent idiopathic scoliosis (AIS). Methods: Using ISIS2 surface topography, measures of coronal deformity, kyphosis and skin angulation (as a measure of torso asymmetry) in a series of children with Lenke 1 convex to the right AIS were analyzed using k-means clustering techniques to describe the combined variability of shape in the spine and torso. Following this, a k-nearest neighbor algorithm was used to measure the ability to automatically identify the correct cluster for any particular datum. Results: There were 1399 ISIS2 images from 691 individuals available for analysis. There were 5 clusters identified in the data representing the variability of the 3 measured parameters which included mild, moderate and marked coronal deformity, mild, moderate and marked asymmetry alongside normal and hypokyphosis. The k-nearest neighbor identification of the correct cluster had an accuracy of 93%. Conclusion: These clusters represent a new description of Lenke 1 AIS that comprises both coronal and sagittal measures of the spine combined with a measure of torso asymmetry. Automated identification of the clusters is accurate. The ability to identify subtypes of deformity, based on parameters that affect both the spine and the torso in AIS, leads to as better understanding of the totality of the deformity seen.