Quadratic Spline Fitting for Robust Measurement of Thoracic Kyphosis Using Key Vertebral Landmarks
<b>Objective:</b> The purpose of this study is to present a kyphosis measurement method based on quadratic spline fitting through three key vertebral landmarks: T12, T8 and T4. This approach aims to capture thoracic spine curvature more continuously and accurately than traditional methods such as the Cobb angle and circle fitting. <b>Methods:</b> A dataset of 560 lateral thoracic spine radiographs was retrospectively analyzed, including cases of postural kyphosis, Scheuermann's disease, osteoporosis-induced kyphosis and ankylosing spondylitis. Two trained raters independently performed three repeated landmark annotations per image. The kyphosis angle was computed using two methods: (1) a quadratic spline fitted through the three landmarks, with the angle derived from tangent vectors at T12 and T4; and (2) a least-squares circle fit with the angle subtended between T12 and T4. Agreement with reference Cobb angles was evaluated using Pearson correlation, MAE, RMSE, ROC analysis and Bland-Altman plots. Reliability was assessed using intraclass correlation coefficients (ICC). <b>Results:</b> Both methods showed excellent intra- and inter-rater reliability (ICC ≥ 0.967). The spline method achieved lower MAE (5.81°), lower RMSE (8.94°) and smaller bias compared to the circle method. Both methods showed strong correlation with Cobb angles (r ≥ 0.851) and excellent classification performance (AUC > 0.950). <b>Conclusions:</b> Spline-based kyphosis measurement is accurate, reliable and particularly robust in cases with severe spinal deformity. Significance: This method supports automated, reproducible kyphosis assessment and may enhance clinical evaluation of spinal curvature using artificial intelligence-driven image analysis.
Authors
- Nikola Kirilov (ORCID: https://orcid.org/0000-0001-7668-2448)
- Elena Kirilova (ORCID: https://orcid.org/0000-0003-1632-2920)
Institutions
- Prof. Assen Zlatarov University (BG)
- Medical University Pleven (BG)
Publication Details
- Journal
- Diagnostics
- Published
- 2025-10-25
- DOI
- https://doi.org/10.3390/diagnostics15212703
- Primary Topic
- Scoliosis diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00