Feasibility Study of Planning Phase Optimization using Patient Geometry-driven information for Respi

来源 :The 15th Asia-Oceania Congress of Medical Physics (AOCMP2015 | 被引量 : 0次 | 上传用户:adunisrunning
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Purpose:End-of-exhale(EOE) phase is generally preferred for gating window because tumor position is more reproducible.However,other gating windows might be more appropriate for dose distribution perspective.In this pilot study,we proposed to utilize overlap volume histogram and normal tissue tolerance dose to search optimized gating window and demonstrated its feasibility.Methods:We acquired 4DCT of 10 phases for 4 lung.After structures were defined in every phase,the OVH of each OAR was generated to quantify the three dimensional spatial relationship between the PTV and OARs(bronchus,esophagus,heart and cord etc.) at each phase.For dose calculation,3D CRT plans were made for all phases under the same beam angles and objectives.After structures were defined in every phase,the overlap volume histogram(OVH) of each OAR was generated to quantify the three dimensional spatial relationship between the PTV and OARs(esophagus,heart and spinal cord etc.) at each phase.A simplified mathematical optimization function was made to achieve surrounding OARs dose-sparing.This function includes changed geometric relationship between tumor and surrounding OARs according to patients respiration and biological index of OARs.The gating window phase was ranked according to score function,and the relationship between score and dose distribution at each phase was evaluated by comparing the mean dose.Results:A simplified mathematical optimization function showed noticeable difference from phase to phase,implying it is possible to find optimal phases for gating window.We confirmed correlations between mean dose and optimization score in most cases tested.Conclusions:It is demonstrated that optimal phases(in dose distribution perspective) for gating window could exist and optimization score function could be a useful tool for determining such phases without performing dose optimization calculations in all phases.
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