Forsberg Daniel, Lundström Claes, Knutsson Hans
Sectra, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Sweden.
Department of Biomedical Engineering, Linköping University, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Sweden.
Comput Med Imaging Graph. 2014 Oct;38(7):549-57. doi: 10.1016/j.compmedimag.2014.06.011. Epub 2014 Jul 11.
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.
本文描述了特征脊柱的概念,该概念适用于确定对描述与青少年特发性脊柱侧弯相关的三维脊柱畸形有用的测量值的两两组合之间的相关性。所提出的数据分析方案基于主成分分析(PCA)和典型相关分析(CCA)的使用。PCA用于降低数据空间的维度,从而对测量值进行正则化,而CCA用于确定不同测量值的两两组合之间的线性相关性。通过分析46例青少年特发性脊柱侧弯患者的所有腰椎和胸椎的位置和旋转情况,证明了特征脊柱概念的实用性。分析表明,椎体的侧向位移和冠状面旋转之间存在最强的线性关系,并且椎体的冠状面旋转和轴面旋转之间存在较弱但仍然很强的相关性。这些结果与对特发性脊柱侧弯的一般理解一致。不过值得注意的是,前后位移和矢状面旋转之间的相关性不如预期的强,并且所获得的结果进一步表明,在表征不同类型的特发性脊柱侧弯时,需要将椎体的轴面旋转作为一项测量指标。除了分析不同测量值之间的两两相关性之外,该方法还被认为适用于找到一个能够最大程度描述特发性脊柱侧弯中脊柱畸形的低维测量值组合。