3D VMAT Verification Based on Monte Carlo Log File Simulation with Experimental Feedback from Film Dosimetry.
A R BarbeiroA UrebaJ A BaezaR LinaresM PeruchaE Jiménez-OrtegaS VelázquezJ C MateosAntonio LealPublished in: PloS one (2016)
A model based on a specific phantom, called QuAArC, has been designed for the evaluation of planning and verification systems of complex radiotherapy treatments, such as volumetric modulated arc therapy (VMAT). This model uses the high accuracy provided by the Monte Carlo (MC) simulation of log files and allows the experimental feedback from the high spatial resolution of films hosted in QuAArC. This cylindrical phantom was specifically designed to host films rolled at different radial distances able to take into account the entrance fluence and the 3D dose distribution. Ionization chamber measurements are also included in the feedback process for absolute dose considerations. In this way, automated MC simulation of treatment log files is implemented to calculate the actual delivery geometries, while the monitor units are experimentally adjusted to reconstruct the dose-volume histogram (DVH) on the patient CT. Prostate and head and neck clinical cases, previously planned with Monaco and Pinnacle treatment planning systems and verified with two different commercial systems (Delta4 and COMPASS), were selected in order to test operational feasibility of the proposed model. The proper operation of the feedback procedure was proved through the achieved high agreement between reconstructed dose distributions and the film measurements (global gamma passing rates > 90% for the 2%/2 mm criteria). The necessary discretization level of the log file for dose calculation and the potential mismatching between calculated control points and detection grid in the verification process were discussed. Besides the effect of dose calculation accuracy of the analytic algorithm implemented in treatment planning systems for a dynamic technique, it was discussed the importance of the detection density level and its location in VMAT specific phantom to obtain a more reliable DVH in the patient CT. The proposed model also showed enough robustness and efficiency to be considered as a pre-treatment VMAT verification system.
Keyphrases
- monte carlo
- image quality
- dual energy
- room temperature
- prostate cancer
- computed tomography
- magnetic resonance imaging
- case report
- contrast enhanced
- early stage
- deep learning
- stem cells
- machine learning
- magnetic resonance
- positron emission tomography
- loop mediated isothermal amplification
- mesenchymal stem cells
- gold nanoparticles
- virtual reality
- real time pcr
- locally advanced
- simultaneous determination
- mass spectrometry