Density overwrites of internal tumor volumes in intensity modulated proton therapy plans for mobile lung tumors. (30th January 2018) - Botas, Pablo; Grassberger, Clemens; Sharp, Gregory; Paganetti, Harald
Abstract: The purpose of this study was to investigate internal tumor volume density overwrite strategies to minimize intensity modulated proton therapy (IMPT) plan degradation of mobile lung tumors. Four planning paradigms were compared for nine lung cancer patients. Internal gross tumor volume (IGTV) and internal clinical target volume (ICTV) structures were defined encompassing their respective volumes in every 4DCT phase. The paradigms use different planning CT (pCT) created from the average intensity projection (AIP) of the 4DCT, overwriting the density within the IGTV to account for movement. The density overwrites were: (a) constant filling with 100 HU (C100) or (b) 50 HU (C50), (c) maximum intensity projection (MIP) across phases, and (d) water equivalent path length (WEPL) consideration from beam's-eye-view. Plans were created optimizing dose-influence matrices calculated with fast GPU Monte Carlo (MC) simulations in each pCT. Plans were evaluated with MC on the 4DCTs using a model of the beam delivery time structure. Dose accumulation was performed using deformable image registration. Interplay effect was addressed applying 10 times rescanning. Significantly less DVH metrics degradation occurred when using MIP and WEPL approaches. Target coverage ( D 99 ⩾ 70 Gy(RBE)) was fulfilled in most cases with MIP and WEPL ( D 99 W E P L = 69.2 ± 4.0 Gy (RBE)), keeping dose heterogeneity low ( D 5 − D 95 W E P L = 3.9 ± 2.0 Gy(RBE)). The mean lung dose was kept lowest by the WEPL strategy, as well as the maximum dose to organs at risk (OARs). The impact on dose levels in the heart, spinal cord and esophagus were patient specific. Overall, the WEPL strategy gives the best performance and should be preferred when using a 3D static geometry for lung cancer IMPT treatment planning. Newly available fast MC methods make it possible to handle long simulations based on 4D data sets to perform studies with high accuracy and efficiency, even prior to individual treatment planning.