@article{QIMS27448,
author = {Hoda Sharifi and Gary C. McDonald and Joon Kyu Lee and Munther I. Ajlouni and Indrin J. Chetty and Hualiang Zhong},
title = {Four-dimensional computed tomography-based biomechanical measurements of pulmonary function and their correlation with clinical outcome for lung stereotactic body radiation therapy patients},
journal = {Quantitative Imaging in Medicine and Surgery},
volume = {9},
number = {7},
year = {2019},
keywords = {},
abstract = {Background: Functional image guided radiotherapy allows for the delivery of an equivalent dose to tumor targets while sparing high ventilation lung tissues. In this study, we investigate whether radiation dose to functional lung is associated with clinical outcome for stereotactic body radiation therapy (SBRT) patients.
Methods: Four-dimensional computed tomography (4DCT) images were used to assess lung function. Deformable image registration (DIR) was performed from the end-inhale phase to the end-exhale phase with resultant displacement vectors used to calculate ventilation maps. In addition to the Jacobian-based ventilation we introduce a volumetric variation method (Rv) based on a biomechanical finite element method (FEM), to assess lung ventilation. Thirty NSCLC patients, treated with SBRT, were evaluated in this study. 4DCT images were used to calculate both Jacobian and Rv-based ventilation images. Areas under the receiver operating characteristic curve (AUC) were used to assess the predictive power of functional metrics. Metrics were calculated over the whole lung as well as high and low ventilated regions.
Results: Ventilation in dose regions between 1 and 5 Gy had higher AUC values compared to other dose regions. Rv based ventilation imaging method also showed to be less spatially variant and less heterogeneous, and the resultant Rv metrics had higher AUC values for predicting grade 2+ dyspnea.
Conclusions: Low dose delivered to high ventilation areas may also increase the risk of compromised pulmonary function. Rv based ventilation images could be useful for the prediction of clinical toxicity for lung SBRT patients.},
issn = {2223-4306}, url = {https://qims.amegroups.org/article/view/27448}
}