ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026
Use of machine learning predictive models in sagittal alignment planning in adolescent idiopathic scoliosis surgery.
Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Algorithmic fairness reporting in artificial intelligence for spinal deformity: a systematic review.Spine deformity · 2026Review
- State-of-the-art review in AI and digital technologies for spine deformity.Spine deformity · 2026Review
- Improved immediate postoperative T4-L1 hip axis with use of pre-contoured patient-specific rods versus surgeon-contoured rods in adolescent idiopathic scoliosis.Journal of spine surgery (Hong Kong) · 2026Article
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7 authors.
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Abstract
objectivePrevious research has shown that predictive models can optimize surgical planning. This study investigates whether predictive models can be used to accurately predict compensatory changes in sagittal spinopelvic parameters after all-posterior spinal fusion (PSF) in patients with adolescent idiopathic scoliosis (AIS). STUDY
designRetrospective analysis of medical records was performed to identify pediatric patients with Lenke class 1-4 AIS who underwent PSF with implantation of patient-specific rods (PSR) during the period from July 2018 to December 2020. All included patients (n = 34) were followed for at least two years.
methodsSurgical strategies were simulated on preoperative radiographs to achieve desired thoracic kyphosis (TK) for sagittal planning. Previously validated predictive models were used to predict postoperative lumbar lordosis (LL) and pelvic tilt (PT). Pre-contoured patient specific titanium rods were utilized during corrective surgery. Standard radiographic measurements were obtained preoperatively, along with one and two years postoperatively.
resultsAt 2-year follow-up, in the overall cohort, median TK gain was 9.3° vs. preoperative [IQR: -1.9, 20.5] (p = .003) and 4.9° vs. planned [- 1.6, 10.8] (p < .001). Median differences of postoperative vs. predicted in LL and PT were - 3.8° [IQR: - 10.4, 1.4] (p = .006) and - 0.1° [IQR: - 3.7, 3.3] (p = .555), respectively. At 2-year follow-up in the hypokyphotic subgroup (TK < 20°) (n = 12), median TK gain was 22.4° vs. preoperative [IQR: 15.6, 21.2] (p = .002) and 2.1° vs. planned [IQR: - 2.1, 8.1] (p = .239). Median differences of postoperative vs. predicted in LL and PT were - 3.4 [- 9.7, 0.4] (p = .083) and 0.5 [IQR: - 2.0, 2.7] (p = .262), respectively.
conclusionThe predictive models accurately predicted compensatory changes in the spinopelvic parameters of unfused segments after AIS surgery in the hypokyphotic subset of patients up to two years post op, and up to one year post-operatively in our entire cohort.
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