NYMC Faculty Publications

Understanding Radiographic Parameters in Cervical Deformity

Author Type(s)

Student

DOI

10.1097/BSD.0000000000001897

Journal Title

Clinical Spine Surgery

Document Type

Article

Publication Date

1-1-2025

Keywords

Ames classification, cervical sagittal vertical axis (cSVA), cervical spine deformity, Neck Disability Index (NDI), Passias classification, radiographic parameters, spinal alignment, surgical planning, T1 slope, upper cervical extension reserve (UER)

Disciplines

Medicine and Health Sciences

Abstract

Study Design: Narrative review. Objective: To synthesize current knowledge on radiographic parameters, classification systems, and compensatory mechanisms essential to the diagnosis and surgical planning of cervical spine deformity (CD) correction. Summary of Background Data: CD encompasses a heterogeneous set of conditions associated with neurological impairment and impaired health-related quality of life. Surgical outcomes are closely linked to radiographic alignment, yet no framework exists that integrates all relevant metrics. Methods: This review evaluates contemporary literature to outline major cervical and global alignment parameters, classification systems, and compensatory mechanisms relevant to surgical planning. Results: Key parameters such as T1S-CL mismatch and cSVA remain essential for assessing sagittal imbalance in CD. However, cervical alignment is often influenced by global compensation, highlighting the need for full-spine evaluation. Classification systems offer structured, outcome-driven frameworks, while morphologic subtypes further guide surgical approach. Despite these tools, revision rates remain relatively high. Emerging metrics, such as upper cervical extension reserve (UER), may offer additional insight into patient-specific alignment capacity, serving as valuable adjuncts to better predict outcomes. Conclusions: Optimal surgical planning in CD requires a comprehensive approach that integrates regional and global alignment parameters, individualized modifiers, and morphologic considerations. Incorporating emerging metrics may improve long-term clinical outcomes.

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