ArticleSpine deformity2026
Predicting pulmonary function in adolescent idiopathic scoliosis: is a simple 2D radiograph still the winner?
Article in Spine deformity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
purposeWhile 3D radiographic parameters are increasingly used to assess adolescent idiopathic scoliosis (AIS), barriers to 3D imaging limit their routine use. 2D-to-3D prediction algorithms have been proposed as a substitute. This study sought to determine if a predicted 3D kyphosis, derived from 2D images, is a more robust predictor of FEV1 in patients with AIS than a traditional 2D analysis.
methodsA retrospective, cross-sectional review of 259 AIS patients with surgical-range thoracic curves (> 40°) was performed. We built two multivariate linear regression models to predict FEV1. Due to structural multicollinearity, the deformity measures were tested separately. Model A included Main Thoracic Cobb, BMI, and Age. Model B included Predicted 3D T5-T12 Kyphosis, BMI, and Age. The models were compared using the Akaike Information Criterion (AIC) and adjusted.
resultsThe cohort (87% female, mean age 15.7 ± 3.3 years) presented with severe deformities (mean Main Thoracic Cobb 68.4° ± 16.5°) and widespread restrictive impairment (71%). Multivariate Analysis revealed that Model A, (2D Main Thoracic Cobb) was statistically superior to Model B (Predicted 3D T5 - T12 Kyphosis) with a lower AIC (-292.5 vs. -265.9) and a higher adjusted R
conclusionThe predicted 3D-based model was not superior, while a parsimonious 2D-based multivariate model including Main Thoracic Cobb, BMI, and Age explained a significantly larger proportion of the variance in FEV1. This specific 2D-to-3D prediction algorithm is an imperfect proxy and is not a valid substitute for true 3D imaging in predicting pulmonary risk.
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