Three-dimensional morphology study of surgical adolescent idiopathic scoliosis patient from encoded geometric models

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• 作者：William Thong ; Stefan Parent ; James Wu ; Carl-Eric Aubin…
• 关键词：Adolescent idiopathic scoliosis ; Spine ; Machine learning ; Morphology ; Cluster analysis
• 刊名：European Spine Journal
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：25
• 期：10
• 页码：3104-3113
• 全文大小：1,888 KB
• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Surgical Orthopedics
  Neurosurgery
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-0932
• 卷排序：25

文摘

PurposeThe classification of three-dimensional (3D) spinal deformities remains an open question in adolescent idiopathic scoliosis. Recent studies have investigated pattern classification based on explicit clinical parameters. An emerging trend however seeks to simplify complex spine geometries and capture the predominant modes of variability of the deformation. The objective of this study is to perform a 3D characterization and morphology analysis of the thoracic and thoraco/lumbar scoliotic spines (cross-sectional study). The presence of subgroups within all Lenke types will be investigated by analyzing a simplified representation of the geometric 3D reconstruction of a patient’s spine, and to establish the basis for a new classification approach based on a machine learning algorithm.