SU-F-T-680: Radiobiological Analysis of the Impact of Daily Patient Deformation and Setup Variations Through the Use of the Cone Beam CT and Deformable Image Registration in Lung Cancer IMRT.

PURPOSE To estimate the dose distributions delivered to the patient in each treatment fraction using deformable image registration (DIR) and assess the radiobiological impact of the inter-fraction variations due to patient deformation and setup. METHODS The work is based on the cone beam CT (CBCT) images and treatment plans of two lung cancer patients. Both patients were treated with intensity modulated radiation therapy (IMRT) to 66Gy in 2Gy/fraction. The treatment plans were exported from the treatment planning system (TPS) to the Velocity AI where DIR was performed and the same deformation matrix was used for the deformation of the planned dose distribution and organ contours to each CBCT dataset. A radiobiological analysis was performed based on the radiobiological parameters of the involved organs at risk (OARs) and planning target volume (PTV). Using the complication free tumor control probability (P+) index, differences in P+ were observed between each CBCT as well as between CBCT and planning dose distributions. RESULTS The optimal CBCT P? values ranged from 91.6 % to 94.8 % for patient #1 and from 88.8 % to 90.6 % for patient #2. At the dose level of the clinical prescription, the CBCT P+ values ranged from 80.3% to 80.7% for patient #1 and from 80.7% to 81.0% for the patient #2. The planning CT P+ values were 81.0% and 80.7% for the two patients, respectively. These differences emphasize the significance of using the radiobiological analysis when assessing changes in the dose distribution due to the tumor motion and lung deformations. CONCLUSION Daily setup variations yield to differences in the actual dose delivered versus the planned one. The observed differences were rather small when only looking at the dosimetric comparison of the dose distributions, however the radiobiology analysis was able to detect clinically relevant differences among the studied dose distributions.