Title :
Noninvasive Clinical Assessment of Trunk Deformities Associated With Scoliosis
Author :
Seoud, L. ; Dansereau, J. ; Labelle, H. ; Cheriet, Farida
Author_Institution :
Inst. of Biomed. Eng., Ecole Polytech. de Montreal, Montréal, QC, Canada
Abstract :
Besides the spinal deformity, scoliosis modifies notably the general appearance of the trunk resulting in trunk rotation, imbalance, and asymmetries that constitutes patients´ major concern. Existing classifications of scoliosis, based on the type of spinal curve as depicted on radiographs, are currently used to guide treatment strategies. Unfortunately, even though a perfect correction of the spinal curve is achieved, some trunk deformities remain, making patients dissatisfied with the treatment received. The purpose of this study is to identify possible shape patterns of trunk surface deformity associated with scoliosis. First, trunk surface is represented by a multivariate functional trunk shape descriptor based on 3-D clinical measurements computed on cross sections of the trunk. Then, the classical formulation of hierarchical clustering is adapted to the case of multivariate functional data and applied to a set of 236 trunk surface 3-D reconstructions. The highest internal validity is obtained when considering 11 clusters that explain up to 65% of the variance in our dataset. Our clustering result shows a concordance with the radiographic classification of spinal curves in 68% of the cases. As opposed to radiographic evaluation, the trunk descriptor is 3-D and its functional nature offers a compact and elegant description of not only the type, but also the severity and extent of the trunk surface deformity along the trunk length. In future work, new management strategies based on the resulting trunk shape patterns could be thought of in order to improve the esthetic outcome after treatment, and thus patients satisfaction.
Keywords :
biomechanics; bone; deformation; diagnostic radiography; image classification; image reconstruction; medical image processing; patient treatment; 3-D clinical measurements; hierarchical clustering; multivariate functional data; multivariate functional trunk shape; noninvasive clinical assessment; patient treatment; radiographic classification; radiographic evaluation; scoliosis; spinal curve; spinal deformity; trunk imbalance; trunk rotation; trunk shape patterns; trunk surface 3-D reconstructions; trunk surface deformity; Back; Biomedical measurements; Couplings; Shape; Splines (mathematics); Surface reconstruction; Surface treatment; Clustering; functional data analysis; scoliosis; shape analysis; Adolescent; Analysis of Variance; Child; Cluster Analysis; Databases, Factual; Female; Humans; Imaging, Three-Dimensional; Male; Reproducibility of Results; Scoliosis; Torso; Young Adult;
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
DOI :
10.1109/TITB.2012.2222425