Abstract
PurposeAn accurate assessment of out‐of‐field dose is necessary to estimate the risk of second cancer after radiotherapy and the damage to the organs at risk surrounding the planning target volume. Although treatment planning systems (TPSs) calculate dose distributions outside the treatment field, little is known about the accuracy of these calculations. The aim of this work is to thoroughly compare the out‐of‐field dose distributions given by two algorithms implemented in the Monaco TPS, with measurements and full Monte Carlo simulations.MethodsOut‐of‐field dose distributions predicted by the collapsed cone convolution (CCC) and Monte Carlo (MCMonaco) algorithms, built into the commercially available Monaco version 5.11 TPS, are compared with measurements carried out on an Elekta Axesse linear accelerator. For the measurements, ion chambers, thermoluminescent dosimeters, and EBT3 film are used. The BEAMnrc code, built on the EGSnrc system, is used to create a model of the Elekta Axesse with the Agility collimation system, and the space phase file generated is scored by DOSXYZnrc to generate the dose distributions (MCEGSnrc). Three different irradiation scenarios are considered: (a) a 10 × 10 cm2 field, (b) an IMRT prostate plan, and (c) a three‐field lung plan. Monaco's calculations, experimental measurements, and Monte Carlo simulations are carried out in water and/or in an ICRP110 phantom.ResultsFor the 10 × 10 cm2 field case, CCC underestimated the dose, compared to ion chamber measurements, by 13% (differences relative to the algorithm) on average between the 5% and the ≈2% isodoses. MCMonaco underestimated the dose only from approximately the 2% isodose for this case. Qualitatively similar results were observed for the studied IMRT case when compared to film dosimetry. For the three‐field lung plan, dose underestimations of up to ≈90% for MCMonaco and ≈60% for CCC, relative to MCEGSnrc simulations, were observed in mean dose to organs located beyond the 2% isodose.ConclusionsThis work shows that Monaco underestimates out‐of‐field doses in almost all the cases considered. Thus, it does not describe dose distribution beyond the border of the field accurately. This is in agreement with previously published works reporting similar results for other TPSs. Analytical models for out‐of‐field dose assessment, MC simulations or experimental measurements may be an adequate alternative for this purpose.
Highlights
In recent decades, radiotherapy (RT) has undergone considerable development that has had a positive impact on long-term outcomes for cancer patients
This choice is motivated by three main reasons: (a) most treatment planning systems (TPSs) are typically commissioned using out-of-axis profiles covering up to these distances, (b) no CT information is usually available far beyond those limits, which poses a natural restriction to the calculations performed by TPSs, and (c) approximately 75% of all out-of-field second cancers lay within this region.[1]
The performance for out-of-field dose calculations of two algorithms implemented in a commercial TPS was thoroughly evaluated by comparison with experimental measurements and full Monte Carlo (MC) simulations
Summary
Radiotherapy (RT) has undergone considerable development that has had a positive impact on long-term outcomes for cancer patients. The concept of uncomplicated and cancer-free control probability (UCFCP) has been recently proposed.[2] This approach requires further knowledge about the carcinogenic potential and deterministic effects of the out-of-field radiation doses, which in turn has to be accurately assessed. This latter is a complex task,[3] and there is no established and reliable method to be currently used in the clinical routine, which poses unique challenges to clinical medical physicists.[4]
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