Optimisation of delivery efficiency in prostate intensity modulated radiotherapy planning

[摘要] English: Evidence that supports dose escalation for prostate cancer is growing and with Intensity Modulated Radiation Therapy (IMRT) higher conformal target doses can be delivered. With more segments and higher monitor units (MU's), target conformity can be improved, however this results in longer delivery times, which makes it difficult to ensure accurate dose delivery, as intra-fractional as well as target movement plays an increasing role. Evidence from the literature indicates that secondary radiation-induced cancer risk is proportional to the beam-on time (thus the MU's). Improvements in IMRT delivery efficiency while maintaining plan quality can be achieved by reducing the complexity of an IMRT plan. This can be done by changing the optimization parameters during the optimization process. Less 'complex prostate IMRT plans will require fewer MU's by using less segments resulting in shorter delivery times and therefore reduced risk of secondary cancers. The goal of this study was to recommend a set of optimization parameter values that will improve the delivery efficiency of prostate IMRT treatment plan while maintaining plan quality.Fifteen clinical prostate IMRT plans (15 MV), already used for treatment, were re-optimized, using a XiO treatment planning system (TPS). Changes in total MU's and segments were evaluated for changes in some of the optimization parameter values. Eleven optimization parameters (some of them used more than once with different values) were used to generate 15 new IMRT combination plans (ICP's) for each patient for both 6 and 15 MV, resulting in 450 plans being assessed. One parameter was changed at a time while all other variables were kept constant. Plan quality was evaluated in terms of four variables: MU, number of segments, homogeneity index and conformity index while the delivery efficiency was evaluated in terms of delivery time. To our knowledge no time delivery model has been proposed for a Siemens® ARTISTETM Linear Accelerator (Linac). Using the principles given in the literature we derived such a time delivery model by adding the radio frequency wave component and Multi Leaf Collimator delay time. K-means clustering was then used to analyse the data in terms of the five variables and the top 10 ICP's in 3 patients in terms of a faster more conformal, delivered plan were identified.To confirm the delivery efficiency and accuracy, the fluences of these top 10 ICP's were measured on a Siemens® ARTISTETM Linac with the step and shoot method and compared to the treatment planning system's fluences. The evaluation criteria chosen were 3% and 3 mm, distance to agreement. A 3 dimensional dose volume histogram program was used to determine the percentage pass rates on the planned target volumes and the organs at risk.The optimization parameters such as the minimum MU's per segment, intensity level, minimum segment size and minimum segment area; demonstrated the greatest influence on the total number of segments, while the total MU's was most greatly influenced by the filters and intensity level optimization parameter. Controversy exists regarding which energy should be used, 6 MV or 15 MV, when treating prostate cancer. Both energies were considered here during the optimization process and it was concluded that the optimization parameters are not greatly influenced by the beam energy. However, it was seen that beam arrangement has an influence on optimization parameter behaviour. A limitation of this study is that the beam angle distribution was not investigated.Thus recommendations could be made in terms of which ICP demonstrated the most improved delivery efficiency of a prostate IMRT treatment plan while maintaining plan quality. The optimisation parameter which was introduced to the optimization process was a General High filter.Gaining knowledge about the behaviour of the optimization parameters during optimization makes it easier to advise and assist treatment planners preparing complex IMRT plans.

[发布机构] University of the Free State