The effect of planning algorithms in oesophageal radiotherapy in the context of the SCOPE 1 trial
Received 30 January 2009; received in revised form 21 August 2009; accepted 24 August 2009. published online 27 September 2009.
Abstract
Background and purpose
In radiotherapy clinical trials multiple centres contribute to patient recruitment. Depending on the calculation algorithm used, the reported dose distributions may differ significantly: broadly, the results for algorithms which do not model lateral electron transport (type a) give less accurate results than the more recently available algorithms that do (type b) when compared to Monte Carlo simulations and measurements. Clinical implementation studies for type b algorithms have yet to be reported for oesophageal radiotherapy. Furthermore, clinical trials must ensure an equivalent effect of the treatment regardless of calculation method. This retrospective planning study aims to define guidance for type b planning in a UK oesophageal clinical trial, to enable acceptable consistency of dose distributions regardless of algorithm, and allow for the improved calculation accuracy of type b to be incorporated into the optimization.
Materials and methods
Fifteen patient data sets were planned using a single type a algorithm. Plans were recalculated using a single type b algorithm and subsequently re-optimized with the type b in accordance with optimization rules. The changes in absolute dose at the point of prescription for type a were compared to the recalculated type b. Dose–volume data for organs at risk (OARs), and target volumes were compared, and the volume of the planning target volume (PTV) receiving 95% of the prescribed dose (V95%) was compared to the percentage of PTV overlapping with lung.
Results
Dose at the prescription point decreased by 0.69% on average (SD=0.71), p=0.0021, for type b compared to that for type a. For the re-optimized type b, the OAR doses corresponding to the trial dose–volume constraints were maintained within 1.0% of the type a levels on average. Reductions in the mean PTV V95% of 9.3% and 3.8% were observed for the recalculated and re-optimized type b plans, respectively, when compared to the mean PTV V95% for type a. For the re-optimized type b there is a correlation between PTV V95% and the percentage of PTV overlapping lung (R2=0.4979).
Conclusions
Plan optimization with the type b algorithm results in improved PTV V95%. Using our suggested optimization rules, equivalent OAR doses can be maintained with both types. For type b, this requires a measured level of compromise to PTV in low density tissue, quantified by the relationship between PTV V95% and the percentage of PTV in lung.
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