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Idiopathic scoliosis is the most common pediatric musculoskeletal disorder that causes a three-dimensional deformity of the spine. Early detection of this progressive aliment is essential. The aim of this study is to determine outcomes using a newly developed automated asymmetry-evaluation system for the surface of the human back using a three-dimensional depth sensor. Seventy-six human subjects suspected to have idiopathic scoliosis were included in this study. Outcome measures include patient demographics, radiographic measurements, and asymmetry indexes defined in the automated asymmetry-recognition system. The mean time from scanning to analysis was 1.5 seconds. For predicting idiopathic scoliosis of greater than 25°, the area under the curve was 0.96, sensitivity was 0.97, and specificity was 0.88. The coefficient of variation for repeatability analyses using phantom models was 1–4%. The intraclass correlation coefficient obtained for intra-observer repeatability for human subjects was 0.995. The system three-dimensionally scans multiple points on the back, enabling an automated evaluation of the back’s asymmetry in a few seconds. This study demonstrated discriminative ability in determining whether an examinee requires an additional x-ray to confirm diagnosis.

Automated noninvasive detection of idiopathic scoliosis in children and adolescents: A principle validation study