Abstract

Purpose: Measurement of global spinal alignment (GSA) is an important aspect of diagnosis and treatment evaluation for spinal deformity but is subject to a high level of inter-reader variability. Approach: Two methods for automatic GSA measurement are proposed to mitigate such variability and reduce the burden of manual measurements. Both approaches use vertebral labels in spine computed tomography (CT) as input: the first (EndSeg) segments vertebral endplates using input labels as seed points; and the second (SpNorm) computes a two-dimensional curvilinear fit to the input labels. Studies were performed to characterize the performance of EndSeg and SpNorm in comparison to manual GSA measurement by five clinicians, including measurements of proximal thoracic kyphosis, main thoracic kyphosis, and lumbar lordosis. Results: For the automatic methods, 93.8% of endplate angle estimates were within the inter-reader 95% confidence interval ( CI 95 ). All GSA measurements for the automatic methods were within the inter-reader CI 95 , and there was no statistically significant difference between automatic and manual methods. The SpNorm method appears particularly robust as it operates without segmentation. Conclusions: Such methods could improve the reproducibility and reliability of GSA measurements and are potentially suitable to applications in large datasets-e.g., for outcome assessment in surgical data science.

View details for DOI 10.1117/1.JMI.7.3.035001

View details for PubMedID 32411814

View details for PubMedCentralID PMC7218103