Lew Si-Hyung, Jeong Ye-Jin, Roh Ye-Ri, Kang Dong-Ho
College of Medicine, Seoul National University, Seoul 03080, Republic of Korea.
ALLIV Healthcare Co., Seoul 05070, Republic of Korea.
Medicina (Kaunas). 2025 May 19;61(5):916. doi: 10.3390/medicina61050916.
: Degenerative cervical myelopathy (DCM), a major subtype of degenerative cervical disorders, presents with diverse sagittal alignment patterns. However, radiography-based phenotyping remains underexplored. This study aimed to identify distinct cervical alignment subgroups using unsupervised clustering analysis and to explore their potential clinical relevance. : We analyzed 1371 lateral cervical radiographs of patients with DCM. C3-C7 sagittal vertical axis (SVA), lordosis, vertical length, and curved length were determined. K-means clustering was applied, and the optimal cluster number was determined using the elbow method and silhouette analysis. Clustering validity was assessed using the Calinski-Harabasz and Davies-Bouldin indices. : The final clustering solution was validated with a high Calinski-Harabasz index (1171.70) and an acceptable Davies-Bouldin index (0.99) at k = 3, confirming the stability and robustness of the classification. Cluster 1 (forward-head type) exhibited low lordosis (8.3° ± 4.7°), moderate SVA (95.9 ± 60.2 mm), and a compact cervical structure, consistent with kyphotic alignment and forward-head displacement. Cluster 2 (normal) showed the highest lordosis (24.1° ± 6.8°), moderate SVA (70.6 ± 50.2 mm), and balanced sagittal alignment, indicating a biomechanically stable cervical posture. Cluster 3 (long-neck type) displayed the highest SVA (135.6 ± 76.7 mm), the longest vertical and curved lengths, and moderate lordosis, suggesting a structurally elongated cervical spine with anterior head displacement. Significant differences ( < 0.01) were observed across all clusters, confirming distinct phenotypic patterns in cervical sagittal alignment. : This exploratory clustering analysis identified three distinct radiographic phenotypes of DCM, reflecting biomechanical heterogeneity. Although prospective studies linking these phenotypes to clinical outcomes are warranted, our findings provide a framework for personalized spinal care in the future.
退行性颈椎脊髓病（DCM）是退行性颈椎疾病的一种主要亚型，呈现出多样的矢状位排列模式。然而，基于X线摄影的表型分析仍未得到充分探索。本研究旨在通过无监督聚类分析确定不同的颈椎排列亚组，并探讨它们潜在的临床相关性。
我们分析了1371例DCM患者的颈椎侧位X线片。测定了C3 - C7矢状垂直轴（SVA）、前凸、垂直长度和曲度长度。应用K均值聚类法，并使用肘部法和轮廓分析确定最佳聚类数。使用Calinski - Harabasz指数和Davies - Bouldin指数评估聚类有效性。
最终聚类结果在k = 3时，通过高Calinski - Harabasz指数（1171.70）和可接受的Davies - Bouldin指数（0.99）得到验证，证实了分类的稳定性和稳健性。第1组（头部前倾型）前凸较低（8.3°±4.7°），SVA适中（95.9±60.2 mm），颈椎结构紧凑，与后凸排列和头部前倾移位一致。第2组（正常型）前凸最高（24.1°±6.8°），SVA适中（70.6±50.2 mm），矢状位排列平衡，表明颈椎姿势在生物力学上稳定。第3组（长颈型）SVA最高（135.6±76.7 mm），垂直和曲度长度最长，前凸适中，提示颈椎结构拉长且头部向前移位。在所有聚类组间均观察到显著差异（<0.01），证实了颈椎矢状位排列存在不同的表型模式。
这项探索性聚类分析确定了DCM的三种不同的影像学表型，反映了生物力学异质性。尽管有必要进行前瞻性研究将这些表型与临床结果联系起来，但我们的发现为未来的个性化脊柱护理提供了一个框架。
