Purpose: An 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. Methods: Out-of-field dose distributions predicted by the collapsed cone convolution (CCC) and Monte Carlo (MC Monaco) 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 (MC EGSnrc). Three different irradiation scenarios are considered: (a) a 10 × 10 cm 2 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. Results: For the 10 × 10 cm 2 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. MC Monaco 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 MC Monaco and ≈60% for CCC, relative to MC EGSnrc simulations, were observed in mean dose to organs located beyond the 2% isodose. Conclusions: This 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.

Considering that cancer survival rates have been growing and that nearly two-thirds of those survivors were exposed to clinical radiation during its treatment, the study of long-term radiation effects, especially secondary cancer induction, has become increasingly important. To correctly assess this risk, knowing the dose to out-of-field organs is essential. As it has been reported, commercial treatment planning systems do not accurately calculate the dose far away from the border of the field; analytical dose estimation models may help this purpose. In this work, the development and validation of a new three-dimensional (3D) analytical model to assess the photon peripheral dose during radiotherapy is presented. It needs only two treatment-specific input parameter values, plus information about the linac-specific leakage, when available. It is easy to use and generates 3D whole-body dose distributions and, particularly, the dose to out-of-field organs (as dose–volume histograms) outside the 5% isodose for any isocentric treatment using coplanar beams [including intensity modulated radiotherapy and volumetric modulated arc therapy (VMAT)]. The model was configured with the corresponding Monte Carlo simulation of the peripheral absorbed dose for a 6 MV abdomen treatment on the International Comission on Radiological Protection (ICRP) 110 computational phantom. It was then validated with experimental measurements using thermoluminescent dosimeters in the male ATOM anthropomorphic phantom irradiated with a VMAT treatment for prostate cancer. Additionally, its performance was challenged by applying it to a lung radiotherapy treatment very different from the one used for training. The model agreed well with measurements and simulated dose values. A graphical user interface was developed as a first step to making this work more approachable to a daily clinical application.

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