Frontiers in oncology
Relevance between patients' clinical factors and 4D-CT lung ventilation heterogeneity for evaluating the adoption of functional avoidance thoracic radiotherapy with a large patient database
By Deng G, Ying Y, Wang X and 5 others.
Abstract
Objective
Four-dimensional computed tomography (4D-CT)-guided functional-avoidance radiotherapy reduces radiation pneumonitis, but the lack of patient selection criteria limits its adoption. This study aimed to identify clinical predictors of lung ventilation heterogeneity and determine which patients derive the greatest dosimetric benefit from functional-avoidance planning.
Methods
We retrospectively analyzed 274 lung cancer patients. 4D-CT ventilation imaging was generated via deformable registration and a density-change algorithm, and the coefficient of variation (CoV) across six lung zones quantified heterogeneity. Clinical factors were assessed using Mann-Whitney U, Spearman, and multivariable logistic regression for three ventilation outcomes. Thirty-two patients were selected from CoV quartiles and re-planned with functional-avoidance plans; dosimetric parameters were compared using the Wilcoxon signed-rank test, with False Discovery Rate (FDR) correction applied to address multiple comparisons.