Three-dimensional classification of the Lenke 1 adolescent idiopathic scoliosis using coronal and lateral spinal radiographs

利用冠状位和侧位脊柱X线片对Lenke 1型青少年特发性脊柱侧弯进行三维分类

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Abstract

BACKGROUND: Classification of the spinal deformity in adolescent idiopathic scoliosis (AIS) remains two-dimensional (2D) as the spinal radiographs remain the mainstay in clinical evaluation of the disease. 3D classification systems are proposed, however are time consuming. We here aim to evaluate the clinical application of a 3D classification system by the use of only posterior-anterior and lateral radiographs in Lenke 1 adolescent idiopathic scoliosis (AIS). METHODS: Forty Lenke 1 AIS were classified by five observers following a three-step flowchart, developed based on our previous 3D classification system. This 3D classification characterizes the curve in the frontal and sagittal views and infers the third dimension with rules based on prior data to determine the 3D subtypes of the curve. Repeated rating was performed for 20 randomly selected patients in the same cohort. In addition to the classification by the raters, the 3D model of the spines were generated to determine the actual curve subtype based on the algorithm that was originally used to develop the 3D classification system. The interobserver and intraobserver reliability and the classification accuracy were determined for both 3D and axial classifications of the cohort. RESULTS: The interobserver reliability was moderate to strong with a kappa value between 0.61-0.89 for 3D and axial classifications. Comparing the mathematical classification and the raters' classification, the classification accuracy among all raters ranged between 56 and 89%. CONCLUSION: We evaluated the reliability of a previously developed 3D classification system for Lenke 1 AIS patients when only two-view spinal radiographs are available. Radiologists and orthopedic surgeons were able to identify the 3D subtypes of Lenke 1 AIS from the patients' radiographs with moderate to strong reliability. The new 3D classification has the potential to identify the subtypes of the Lenke 1 AIS without a need for quantitative 3D image post-processing.

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