Clinical implications of the implementation of advanced treatment planning algorithms for thoracic treatments

Abstract 

Background and Purpose

Radiotherapy treatment planning algorithms continue to develop and current planning systems typically offer simpler, but faster, algorithms, which may be 2, 2.5 or 3D in modelling scatter, but which do not model electron transport (type a) and more accurate algorithms which aim to be fully 3D, i.e. which model 3D scatter and also model electron transport (type b). A range of comparative planning studies and experiments indicate that the main situation where the changes are significant between the two types of algorithm is where lung tissue is involved. However, more generally, interface areas between materials of different electron density and composition are expected to show differences between the two types of algorithms. These are likely to pose potentially significant clinical consequences when a centre changes from using older simpler algorithms to more accurate fully 3D ones and require careful consideration.

Materials and Methods

Some modelling is presented using the different type algorithms for a recently available novel design of linear accelerator treatment head, as part of the commissioning of that machine and in preparing for a change in TPS algorithm. The TPS data are compared to measurements and to Monte Carlo calculations.

Results and Discussion

The results add to the evidence of other studies that 3D planning techniques and type b dose calculation algorithms lead to systematic changes in computation and delivery of radiotherapy dose and in dose distributions, as compared to simpler methods, and that these changes are more pronounced in treatments involving lung tissue. The type b algorithms agree well with Monte Carlo modelling.

Conclusions

Careful analysis of the changes is required before adopting new algorithms into clinical treatment planning practice. Discussion is needed between physicists and oncologists to fully understand the effects and potential consequences. These include changes in delivered dose to the reference point, to coverage of the PTV and to the dose distribution and also to dosimetric parameters used to constrain toxicity for lung, e.g. V20, and other tissues. There are consequences for assessment of dose–effect relationships and of parameters used in treatment planning decisions and this is an opportune time to re-evaluate this information.

Keywords: Dose calculation algorithms, Treatment planning, Clinical implication, Lung tissue, Radiation therapy