Predicting pulmonary function using thoracic deformity parameters in early onset scoliosis patients

M Mattan R. Orbach P Patrick J. Cahill A Annalise Noelle Larson R Ron El-Hawary O Oscar H. Mayer S Sriram Balasubramanian

Abstract

Introduction 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. Methods 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. Results 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. Conclusion 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.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 7
Published July 31, 2025
Pages e0329199
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (6)

M

Mattan R. Orbach

P

Patrick J. Cahill

A

Annalise Noelle Larson

R

Ron El-Hawary

O

Oscar H. Mayer

S

Sriram Balasubramanian