An Innovative Stepwise C‐Means Clustering Approach for Classification of Adolescent Idiopathic Scoliosis

作者：Jie Gong, Zifang Zhang, Yunzhang Cheng, Liang Cheng, Yating Dong, Lin Sha, Qin Fan, Jian Chen, Chaomeng Wu, Wenyuan Sui, Yaqing Zhang, Fuyun Liu, Weiming Hu, Wenqing Wei, Junlin Yang · 发表于：Orthopaedic Surgery · 年份：2025 · DOI：10.1111/os.70042 · 被引用次数：1 · 研究领域：Scoliosis diagnosis and treatment、Medical Imaging and Analysis、Spinal Fractures and Fixation Techniques

OBJECTIVE: Existing 3D classification systems for scoliosis primarily guide surgical treatment, with limited application in conservative management. This study aims to establish a preliminary 3D classification system for moderate adolescent idiopathic scoliosis patients in China, providing a theoretical foundation for the standardization and automation of conservative treatment plans. METHODS: Data from 404 adolescent idiopathic scoliosis patients who did not undergo surgery were retrospectively collected from 2022 to 2025. EOS imaging technology was used to perform 3D reconstruction for each patient. The parameters included the 3D centroid coordinates of the vertebrae and vertebral angular displacement. A total of 102 features were extracted per model, and dimensionality reduction yielded 30 final features by the Stacked Autoencoder method. Fuzzy C-means clustering with two classification approaches is used: direct clustering and iterative clustering. Iterative clustering was performed based on coronal plane parameters for initial classification, followed by further clustering. Direct classification involved immediate clustering without further subdivision. RESULTS: Clustering identified 8 distinct 2D curve types, which were further subdivided into 13 3D subtypes. A comparison of the 13 clusters from direct classification with those obtained from iterative clustering was made using Euclidean and Mahalanobis distances between cluster centers and clinical data. The difference ...