Scoliosis is a three-dimensional deformity affecting the orientation and position of the spine. Locally, the shape of the vertebra is also affected. The most common form is adolescent idiopathic scoliosis (AIS) with a prevalence of 1-3% affecting primarily young adolescent females. AIS can either be treated using a brace and in some cases necessitate surgical correction to prevent progressive deformity. Risk factors for progression include female gender, curve magnitude and location, skeletal maturity and growth velocity. However, these risk factors have been shown to be inconsistent in predicting curve progression. Over the past 6 years, the investigators have developed a predictive model of the final Cobb angle in AIS based on 3D spinal parameters. This analysis was based on a prospective cohort of 195 patients that were enrolled upon their initial visit and followed until maturity. This predictive model has a determination coefficient of 0.702. The proposed new study aims at refining and testing the external validity of this model in a larger cohort. The next step towards using the new model in the clinical setting is to redesign the model and to externally validate the model by measuring the agreement between the new method and the traditional Cobb angle at maturity in a larger multicenter study. The objective of this study is to characterize the risk of scoliosis progression based on local three-dimensional vertebral and pelvic measurements present on initial evaluation. Three-dimensional reconstructions will be derived from stereo-radiographs acquired with a new biplanar low-dose radiographic system installed in all 8 clinical sites (EOS system, EOS-Imaging, Paris). These calibrated radiographs will then be used to reconstruct the vertebrae and intervertebral disks at each level as well as the geometry of the pelvis. A series of local and regional parameters will then be calculated from these 3D reconstructions. Correlation analysis will help determine if intervertebral disk wedging, vertebral wedging, transverse plane rotation or pelvic geometry can be used as early predictors of curve progression in AIS. Identifying a new 3D measure of scoliosis associated with rapid curve progression could help predict which curves need early treatment to prevent further progression. The ultimate goal of this research project will be to validate this new predictive model and finally transfer this new predictive tool in the hands of clinicians treating AIS.