学術雑誌論文 A robustness analysis method with fast estimation of dose uncertainty distributions for carbon-ion therapy treatment planning

坂間, 誠  ,  兼松, 伸幸  ,  稲庭, 拓

61pp.5818 - 5836 , 2016-07 , IOP Publishing
内容記述
A simple and efficient approach is needed for robustness evaluation andoptimization of treatment planning in routine clinical particle therapy. Herewe propose a robustness analysis method using dose standard deviation (SD)in possible scenarios such as the robustness indicator and a fast dose warpingmethod, i.e. deformation of dose distributions, taking into account the setupand range errors in carbon-ion therapy. The dose warping method is based onthe nominal dose distribution and the water-equivalent path length obtainedfrom planning computed tomography data with a clinically commissionedtreatment planning system (TPS). We compared, in a limited numberof scenarios at the extreme boundaries of the assumed error, the dose SDdistributions obtained by the warping method with those obtained using theTPS dose recalculations. The accuracy of the warping method was examinedby the standard-deviation-volume histograms (SDVHs) for varying degreesof setup and range errors for three different tumor sites. Furthermore, theinfluence of dose fractionation on the combined dose uncertainty, taking intoconsideration the correlation of setup and range errors between fractions, wasevaluated with simple equations using the SDVHs and the mean value of SDs inthe defined volume of interest. The results of the proposed method agreed wellwith those obtained with the dose recalculations in these comparisons, and theeffectiveness of dose SD evaluations at the extreme boundaries of given errorswas confirmed from the responsivity and DVH analysis of relative SD valuesfor each error. The combined dose uncertainties depended heavily on thenumber of fractions, assumed errors and tumor sites. The typical computationtime of the warping method is approximately 60 times less than that of the full dose calculation method using the TPS. The dose SD distributions andSDVHs with the fractionation effect will be useful indicators for robustnessanalysis in treatment planning, and the results of our comparative study showthat the proposed analysis method would be beneficial in routine clinical use.

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