ArticleSpine deformity2026
AI-derived versus surgeon-performed instrumentation in adolescent idiopathic scoliosis: a biomechanical simulation analysis.
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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Abstract
purposePosterior spinal fusion (PSF) with pedicle screws is the standard treatment for adolescent idiopathic scoliosis (AIS) with curves > 45°, yet significant variability in instrumentation strategies persists. Current planning guidelines lack patient-specific detail and 3D optimization. This study aimed to biomechanically evaluate the simulated 3D spinal correction and implant forces of artificial intelligence (AI)-derived instrumentation strategies compared with surgeon-performed instrumentation in AIS patients undergoing PSF.
methodsThirty-five AIS patients (Lenke 1-2, aged 12-19) treated with PSF were included, with data obtained from the MIMO Clinical Trial and affiliated hospitals. Patient-specific 3D biomechanical models were reconstructed from preoperative radiographs using validated geometric algorithms and multibody dynamics. For each patient, nine instrumentation strategies (AI-generated or surgeon-performed) were simulated with standardized surgical steps. Screw positions were assigned using predefined rule-based patterns derived from neural network-based multi-task learning model (NNML)-predicted parameters. Outcome measures included main thoracic Cobb angle, thoracic kyphosis, apical vertebral rotation, screw pullout forces, number of screws, and fused levels. Statistical comparisons were performed using repeated-measures ANOVA and Friedman tests. All reported outcomes represent simulated biomechanical results rather than clinical follow-up data.
resultsSurgeon-performed instrumentations achieved slightly greater simulated Cobb angle correction (≈4°, p < 0.001) but required more screws and fused levels. AI-generated strategies produced higher thoracic kyphosis (≈4°, p = 0.008) and, when optimized, matched or exceeded overall correction in 77% of patients. Best-AI configurations reduced screw count modestly (≈1 screw, p = 0.048) without compromising simulated 3D correction.
conclusionsBiomechanical modeling suggests that AI-derived plans can achieve comparable simulated 3D correction with fewer implants. These findings reflect simulated performance and require clinical validation, but indicate potential value of AI-assisted 3D modeling for future AIS preoperative planning.
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