Voxel-by-voxel correlation between radiologically radiation induced lung injury and dose after image-guided, intensity modulated radiotherapy for lung tumors.

PURPOSE: To correlate radiation dose to the risk of severe radiologically-evident radiation-induced lung injury (RRLI) using voxel-by-voxel analysis of the follow-up computed tomography (CT) of patients treated for lung cancer with hypofractionated helical Tomotherapy.

METHODS AND MATERIALS: The follow-up CT scans from 32 lung cancer patients treated with various regimens (5, 8, and 25 fractions) were registered to pre-treatment CT using deformable image registration (DIR). The change in density was calculated for each voxel within the combined lungs minus the planning target volume (PTV). Parameters of a Probit formula were derived by fitting the occurrences of changes of density in voxels greater than 0.361gcm-3 to the radiation dose. The model's predictive capability was assessed using the area under receiver operating characteristic curve (AUC), the Kolmogorov-Smirnov test for goodness-of-fit, and the permutation test (Ptest ).

RESULTS: The best-fit parameters for prediction of RRLI 6months post RT were D50 of 73.0 (95% CI 59.2.4-85.3.7)Gy, and m of 0.41 (0.39-0.46) for hypofractionated (5 and 8 fractions) and D50 of 96.8 (76.9-123.9)Gy, and m of 0.36 (0.34-0.39) for 25 fractions RT. According to the goodness-of-fit test the null hypothesis of modeled and observed occurrence of RRLI coming from the same distribution could not be rejected. The AUC was 0.581 (0.575-0.583) for fractionated and 0.579 (0.577-0.581) for hypofractionated patients. The predictive models had AUC>upper 95% band of the Ptest .

CONCLUSIONS: The correlation of voxel-by-voxel density increase with dose can be used as a support tool for differential diagnosis of tumor from benign changes in the follow-up of lung IMRT patients.