title: Eigenspine: computing the correlation between measures describing vertebral pose for patients with adolescent idiopathic scoliosis.
abstract: This paper describes the concept of eigenspine, a concept applicable for determining the correlation between pair-wise combinations of measures useful for describing the three-dimensional spinal deformities associated with adolescent idiopathic scoliosis. The proposed data analysis scheme is based upon the use of principal component analysis (PCA) and canonical correlation analysis (CCA). PCA is employed to reduce the dimensionality of the data space, thereby providing a regularization of the measurements, and CCA is employed to determine the linear dependence between pair-wise combinations of different measures. The usefulness of the eigenspine concept is demonstrated by analyzing the position and the rotation of all lumbar and thoracic vertebrae as obtained from 46 patients suffering from adolescent idiopathic scoliosis. The analysis showed that the strongest linear relationship is found between the lateral displacement and the coronal rotation of the vertebrae, and that a somewhat weaker but still strong correlation is found between the coronal rotation and the axial rotation of the vertebrae. These results are well in-line with the general understanding of idiopathic scoliosis. Noteworthy though is that the correlation between the anterior-posterior displacement and the sagittal rotation was not as strong as expected and that the obtained results further indicate the need for including the axial vertebral rotation as a measure when characterizing different types of idiopathic scoliosis. Apart from analyzing pair-wise correlations between different measures, the method is believed to be suitable for finding a maximally descriptive low-dimensional combination of measures describing spinal deformities in idiopathic scoliosis.
authors: Sectra, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Sweden. Electronic address: daniel.forsberg@sectra.se.
authors: Daniel
authors: D
authors: Forsberg
authors: Sectra, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Sweden. Electronic address: claes.lundstrom@sectra.se.
authors: Claes
authors: C
authors: Lundström
authors: Department of Biomedical Engineering, Linköping University, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Sweden. Electronic address: hans.knutsson@liu.se.
authors: Hans
authors: H
authors: Knutsson
mesh_terms: D000293:Adolescent; D000465:Algorithms; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008159:Lumbar Vertebrae / Q000000981:diagnostic imaging*; D008297:Male; D009716:Numerical Analysis, Computer-Assisted; D056888:Patient Positioning / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012399:Rotation; D012600:Scoliosis / Q000000981:diagnostic imaging*; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D013904:Thoracic Vertebrae / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Canonical correlation analysis; Idiopathic scoliosis; Pose estimation; Principial component analysis; Spine imaging