Characterising intensity-modulated radiation therapy (IMRT) software following upgrades in a commercial treatment planning system

Abstract

AbstractWhen upgrading treatment planning software, it is important to understand and characterise any changes that may have been made to the system. This includes inverse treatment planning and dose optimisation software used for intensity-modulated radiation therapy (IMRT). A systematic and practical approach to characterising dose optimisation software following upgrades is presented based on a planning study of six IMRT prostate cases using the commercial treatment planning system Oncentra Masterplan (OMP). Upgrades included general changes in the fluence to multileaf collimator (MLC) segmentation algorithm, a change from a two-step to a one-step optimisation method and an upgrade of the dose calculation algorithm. Post upgrade changes in plan parameters such as calculation times, monitor units, segments and target doses were analysed. A 32% reduction in total calculated monitor units was observed following the general software upgrade. A smaller 12% reduction was observed when using the optional one-step optimisation method rather than a two-step process using a classic dose calculation algorithm. An increase in monitor units of approximately 12% was observed when changing to an enhanced dose calculation algorithm. The enhanced dose calculation algorithm accounted for MLC type, leakage and source size unlike the previous classic dose calculation algorithm. Differences in dose to volumes between fluence segmentation and final dose calculation varied between versions. These differences were found to be minimal for the most recent treatment planning system version. Repeatability tests revealed a more effective use of the system. The characterisation of the effects of treatment planning software upgrades allowed a better appreciation of IMRT planning and delivery attributes. Although this work is based on one commercial inverse treatment planning system, it would be easily transferable to other systems as the underlying system principles are the same.