Evaluation of Lung Toxicity Risk with Computed Tomography Ventilation Functional Image for Lung Stereotactic Body Radiation Therapy and Three-Dimensional Conformal Radiation Therapy

Abstract

Ventilated regions using 4D-CT ventilation may reduce lung toxicity after radiation therapy. This study evaluated clinical correlations between 4D-CT ventilation-based dosimetric parameters and clinical outcomes. Pre-treatment 4D-CT data were used to compute ventilation images for 40 lung cancer patients. Ventilation images were calculated from 4D-CT data using a DIR and Jacobian-based algorithm. We normalized each ventilation map by converting it to percentile images. Ventilation-based dosimetric parameters (Mean Dose, V5, and V20 in highly and poorly ventilated regions) were calculated. To test whether the ventilation-based dosimetric parameters can be used for prediction of radiation pneumonitis of ≥Grade 2, the area under the curve (AUC) was determined from receiver operating characteristic analysis. For Mean Dose, poorly ventilated lung regions in the 0–30% observed the highest AUC value (0.809) (95% confidence interval (CI), 0.663 to 0.955). For V20, poorly ventilated lung regions in the 0–20% had the highest AUC value (0.774)(95% CI, 0.598 to 0.915). For V5, poorly ventilated lung regions in the 0–30% observed the highest AUC value (0.843)(95% CI, 0.732 to 0.954). These results showed that the highest AUC values for Mean Dose, V20, and V5 were obseved in poorly ventilated regions (0-20%, 0-30%). Our results showed that poorly ventilated lung regions had higher AUC values than highly ventilated regions, suggesting that 4D-CT ventilation-based functional planning may reduce the lung toxicity risk after radiation therapy.