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Objective <p>Previous 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).</p> Study design <p>Retrospective analysis of&#xa0;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 (<i>n</i> = 34) were followed for at least two years.</p> Methods <p>Surgical 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.</p> Results <p>At 2-year follow-up, in the overall cohort, median TK gain was 9.3° vs. preoperative [IQR: −1.9, 20.5] (<i>p</i> = .003) and 4.9° vs. planned [− 1.6, 10.8] (<i>p</i> &lt; .001). Median differences of postoperative vs. predicted in LL and PT were − 3.8° [IQR: − 10.4, 1.4] (<i>p</i> = .006) and − 0.1° [IQR: − 3.7, 3.3] (<i>p</i> = .555), respectively. At 2-year follow-up in the hypokyphotic subgroup (TK &lt; 20°) (<i>n</i> = 12), median TK gain was 22.4° vs. preoperative [IQR: 15.6, 21.2] (<i>p</i> = .002) and 2.1° vs. planned [IQR: − 2.1, 8.1] (<i>p</i> = .239). Median differences of postoperative vs. predicted in LL and PT were − 3.4 [− 9.7, 0.4] (<i>p</i> = .083) and 0.5 [IQR: − 2.0, 2.7] (<i>p</i> = .262), respectively.</p> Conclusion <p>The 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. </p>

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Use of machine learning predictive models in sagittal alignment planning in adolescent idiopathic scoliosis surgery

  • 期刊论文

  • 发表日期：

    2025年10月15日

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  • John Ngo,
  • Kiran Athreya,
  • Brandon Ehrlich,
  • Lois Sayrs,
  • Tricia Morphew,
  • Steven Halvorson,
  • Afshin Aminian

摘要

Objective

Previous 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 design

Retrospective 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.

Methods

Surgical 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.

Results

At 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.

Conclusion

The 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.