A simple method to account for skin dose enhancement during treatment planning of VMAT treatments of patients in contact with immobilization equipment. (22nd June 2018) - Rijken, James; Kairn, Tanya; Crowe, Scott; Muñoz, Luis; Trapp, Jamie
Abstract: Purpose: The ability to accurately predict skin doses and thereby design radiotherapy treatments that balance the likelihood of skin reactions against other treatment objectives is especially important when hypofractionated prescription regimes are used. However, calculations of skin dose provided by many commercial radiotherapy treatment planning systems are known to be inaccurate, especially if the presence of immobilization equipment is not accurately taken into account. This study proposes a simple method by which the accuracy of skin dose calculations can be substantially improved, to allow informed evaluation of volumetric modulated arc therapy (VMAT) treatment plans. Method: A simple method was developed whereby dose calculation is split into grid regions, each with a correction factor which determines MU scaling for skin dose calculation. Correction factors were derived from film measurements made using a geometrically simple phantom in partial contact with a vacuum immobilization device. This method was applied to two different test treatments, planned for delivery to a humanoid phantom with a hypofractionated stereotactic body radiotherapy technique, and results were verified using film measurements of surface dose. Results: Compared to the measured values, calculations of skin dose volumes corresponding to different grade tissue reactions were greatly improved through use of the method employed in this study. In some cases, the accuracy of skin dose evaluation improved by 76% and brought values to within 3% of those measured. Conclusion: The method of skin dose calculation in this study is simple, can be made as accurate as the user requires and is applicable for various immobilization systems. This concept has been verified through use on SBRT lung treatment plans and will aid clinicians in predicting skin response in patients.