SU-E-T-576: Dosimetric Evaluation of Collapsed Cone Convolution (CCC) Algorithm in Predicting Dose Beyond Air Gap

Abstract

Purpose: To investigate the effect of air gaps on depth dose calculations computed by collapsed cone convolution (CCC) algorithm Methods: A computed tomography scan of inhomogenous phantom (30×30×30 cm3) containing rectangular solid‐water blocks and two 5 cm air gaps was used for central axis dose calculations computed by CCC in Pinnacle treatment planning system. Central axis depth dose measurements were taken by a cylindrical ionization chamber for identical beam parameters and monitor units as in the depth dose computations. The calculated and the measured percent depth dose (PDDs) were then compared. The data presented in this study included 6 mega‐voltage (MV) X‐ray and field sizes of 3×3, 5×5, 10×10, and 15×15 cm2. Results: The results of CCC were within ±1.5% in the first water medium. However, upon traversing the first air gap and re‐entering the water medium, in comparison to the measurements, the CCC under‐predicted the dose, with difference ranged from 1.6 to 3.3% for 3×3 cm2, 2.4 to 4.2% for 5×5 cm2, 2.4 to 6.7% for 10×10 cm2, and 1.6 to 6.3% for 15×15 cm2. After the second air gap, the CCC continued to under‐predict the dose, and the difference ranged from 3.2 to 3.9% for 3×3 cm2, 2.4 to 5.6% for 5×5 cm2, 2.3 to 6.0% for 10×10 cm2, and 1.5 to 5.6% for 15×15 cm2. Conclusion: The CCC had good agreement with the measurements in the first water medium before the air gap. However, the CCC under‐predicted the dose in water‐medium after the photon beam traversed the air gap. These effects should be considered in treatment planning of lung cancer where lesion is at the center of the lung. Furthermore, special attention must be given during the patient set up since large air gaps between the patient body and immobilization devices are often encountered.