Orbach Mattan R, Cahill Patrick J, Larson Annalise Noelle, El-Hawary Ron, Mayer Oscar H, Balasubramanian Sriram
Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.
School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2025 Jul 31;20(7):e0329199. doi: 10.1371/journal.pone.0329199. eCollection 2025.
Thoracospinal deformities in early onset scoliosis (EOS) patients often lead to thoracic insufficiency syndrome, in which respiration or lung growth is impaired. Pulmonary function tests (PFTs) are used to assess pulmonary deficits but are challenging to comply with for EOS patients, who typically are between 5 and 10 years old. Thus, the objective was to predict PFT values in EOS patients directly from deformity parameters measured on routine radiographs.
Corresponding preoperative radiographs and PFT values were retrospectively obtained from 47 EOS patients (13M/34F; mean age: 9.8 ± 3.0 years), and 19 literature-based deformity parameters were measured. Multiple linear regression (MLR) analyses using an exhaustive search feature selection method were used to estimate percent predicted forced vital capacity (%FVC) and forced expiratory volume in one second (%FEV1). Ten percent of the dataset was set aside to validate the predictive accuracy of the MLR models.
The additive contributions of multiple thoracospinal deformity parameters successfully yielded significant (p < 0.001) MLR models that predicted %FVC (R2 = 0.54) and %FEV1 (R2 = 0.59) in EOS patients. For the validation test, no significant differences (p > 0.05) in prediction error magnitudes were found.
The developed MLR models provide the highest reported precision for predicting PFT values in EOS patients from radiographic deformity parameters. Additionally, a key subset of deformity parameters was identified, and their relative contributions to predicting PFT values provide quantitative metrics to guide surgical treatment.
早发性脊柱侧弯(EOS)患者的胸段脊柱畸形常导致胸廓发育不全综合征,即呼吸或肺生长受到损害。肺功能测试(PFTs)用于评估肺部缺陷,但对于通常年龄在5至10岁的EOS患者来说,很难配合完成。因此,目标是直接根据常规X线片上测量的畸形参数预测EOS患者的PFT值。
回顾性收集了47例EOS患者(13例男性/34例女性;平均年龄:9.8±3.0岁)术前相应的X线片和PFT值,并测量了19个基于文献的畸形参数。使用穷举搜索特征选择方法进行多元线性回归(MLR)分析,以估计预测的用力肺活量百分比(%FVC)和一秒用力呼气量百分比(%FEV1)。留出10%的数据集以验证MLR模型的预测准确性。
多个胸段脊柱畸形参数的累加贡献成功得出了显著(p<0.001)的MLR模型,可预测EOS患者的%FVC(R2=0.54)和%FEV1(R2=0.59)。对于验证测试,未发现预测误差幅度有显著差异(p>0.05)。
所建立的MLR模型在根据X线畸形参数预测EOS患者的PFT值方面具有目前报道的最高精度。此外,还确定了畸形参数的关键子集,它们对预测PFT值的相对贡献提供了定量指标,以指导手术治疗。