Adolescent idiopathic scoliosis (AIS) is associated with low bone mineral density, which could be related to its etiopathogenesis. Apart from bone density, bone micro-architectures are equally important for better understanding of disease initiation and progression in AIS. Quantitative assessment of bone quality is hampered by the invasive nature of investigations, until recently when the high-resolution pQCT (XtremeCT) became available for revolutionary in-vivo microimaging and derivation of bone micro-architectural parameters. Our objective was to use this powerful instrument to study bone qualities in AIS and compare findings with those from healthy controls. 48 girls with AIS and 84 sex-matched healthy controls were recruited. Cobb angle was measured with standing radiographs, and imaging of the non-dominant distal radius was captured with XtremeCT according to a standard protocol.Introduction
Methods
The main challenge in management of adolescent idiopathic scoliosis (AIS) is to predict which curve will progress so that appropriate treatment can be given. We previously reported that low bone mineral density (BMD) was one of the adverse prognostic factors for AIS. With advancement in imaging technology, quantitative ultrasound (QUS) becomes a useful method to assess bone density and bone quality. The objective of this study was to assess the role of QUS as a radiation-free method to predict curve progression in AIS. 294 girls with AIS were recruited at ages 11–16 years and followed up until skeletal maturity. 269 age-matched healthy girls were recruited as controls. They provided the normal reference for calculation of Z score for QUS parameters. QUS measurements, including BUA (broadband ultrasound attenuation), VOS (velocity of sound) and SI (stiffness index) of the calcaneum, BMD of femoral neck, menarche history, ages, and Cobb angle of the major curve were recorded at baseline as independent variables. The predictive outcome was curve progression defined as an increase of Cobb angle of 6° or more. Logistic regression model and the ROC curve were used for statistical analysis.Introduction
Methods
