Four-dimensional computed tomography-based ventilation imaging in intensity-modulated radiation therapy treatment planning for pulmonary functional avoidance
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS(2023)
Abstract
PurposeTo incorporate four-dimensional computed tomography (4DCT)-based ventilation imaging into intensity-modulated radiation therapy (IMRT) treatment planning for pulmonary functional avoidance. Methods and MaterialsNineteen locally advanced lung cancer patients are retrospectively studied. 4DCT images are employed to create ventilation maps for each patient via a density-change-based algorithm with mass correction. The regional ventilation is directly incorporated into the mathematical formulation of a direct aperture optimization model in IMRT treatment planning to achieve functional avoidance and a voxel-based treatment plan. The proposed functional avoidance planning and voxel-based planning are compared to the conventional treatment planning approach purely based on the anatomy of patients. Paired sample t-tests are conducted to see whether dosimetric differences among the three approaches are significant. ResultsSimilar planning target volume (PTV) coverage is achieved by anatomical, functional avoidance, and voxel-based approaches. The voxel-based treatment planning performs better than both functional avoidance and anatomical planning to the lung. For a total lung, the average volume reductions in a functional avoidance plan from an anatomical plan, a voxel-based plan from an anatomical plan, and a voxel-based plan from a functional avoidance plan are 7.0% , 16.8%, and 10.6%, respectively for V-40; and 0.4%, 6.4%, and 6.0%, respectively for mean Lung Dose (MLD). For a functional lung, the reductions are 8.8% , 17.2%, and 9.2%, respectively, for fV(40); and 1.1%, 6.2%, and 5.2%, respectively, for functional mean lung dose (fMLD). These reductions are obtained without significantly increasing doses to other organs-at-risk. All the pairwise treatment planning comparisons for both total lung and functional lung are statistically significant (p-value alpha=0.05$> \\alpha =0.05$ . From these results, we can conclude that voxel-based treatment planning outperforms both anatomical and functional-avoidance planning. ConclusionsWe propose a treatment planning framework that directly utilizes functional images and compares voxel-based treatment planning with functional avoidance and anatomical treatment planning.
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Key words
voxel based treatment,column generation algorithm,lung cancer optimization
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