Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study
<i>Background and Objectives</i>: 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 al...
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2025-05-01
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| author | Si-Hyung Lew Ye-Jin Jeong Ye-Ri Roh Dong-Ho Kang |
| author_facet | Si-Hyung Lew Ye-Jin Jeong Ye-Ri Roh Dong-Ho Kang |
| author_sort | Si-Hyung Lew |
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| description | <i>Background and Objectives</i>: 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. <i>Materials and Methods</i>: 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. <i>Results</i>: 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 (<i>p</i> < 0.01) were observed across all clusters, confirming distinct phenotypic patterns in cervical sagittal alignment. <i>Conclusions</i>: 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. |
| format | Article |
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| institution | OA Journals |
| issn | 1010-660X 1648-9144 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Medicina |
| spelling | doaj-art-74881dc07a634cb9a3e671be5ab055fc2025-08-20T02:33:58ZengMDPI AGMedicina1010-660X1648-91442025-05-0161591610.3390/medicina61050916Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective StudySi-Hyung Lew0Ye-Jin Jeong1Ye-Ri Roh2Dong-Ho Kang3College of Medicine, Seoul National University, Seoul 03080, Republic of KoreaALLIV Healthcare Co., Seoul 05070, Republic of KoreaALLIV Healthcare Co., Seoul 05070, Republic of KoreaCollege of Medicine, Seoul National University, Seoul 03080, Republic of Korea<i>Background and Objectives</i>: 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. <i>Materials and Methods</i>: 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. <i>Results</i>: 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 (<i>p</i> < 0.01) were observed across all clusters, confirming distinct phenotypic patterns in cervical sagittal alignment. <i>Conclusions</i>: 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.https://www.mdpi.com/1648-9144/61/5/916degenerative cervical disordercervical sagittal alignmentclustering analysisphenotypingk-means clusteringcervical spine morphology |
| spellingShingle | Si-Hyung Lew Ye-Jin Jeong Ye-Ri Roh Dong-Ho Kang Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study Medicina degenerative cervical disorder cervical sagittal alignment clustering analysis phenotyping k-means clustering cervical spine morphology |
| title | Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study |
| title_full | Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study |
| title_fullStr | Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study |
| title_full_unstemmed | Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study |
| title_short | Exploratory Cluster-Based Radiographic Phenotyping of Degenerative Cervical Disorder: A Retrospective Study |
| title_sort | exploratory cluster based radiographic phenotyping of degenerative cervical disorder a retrospective study |
| topic | degenerative cervical disorder cervical sagittal alignment clustering analysis phenotyping k-means clustering cervical spine morphology |
| url | https://www.mdpi.com/1648-9144/61/5/916 |
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