PO-0822: An evolutionary model improvement strategy for knowledge-based planning
Y. Zhang, F. Jiang, H. Yue, Sijia Li, Qing He Hu, M. Wang, Hao Wu · Radiotherapy and Oncology · 2017
Purpose or ObjectiveTo develop and evaluate a new concept for automatic replanning of VMAT plans as failure concept for solitary treatment machines, e.g.MR-Linac.In contrast to previously published automatic planning approaches which replicate the planned dose distribution, we propose an automatic re-planning concept which uses constrained optimization to generate Pareto-optimal VMAT plans for different treatment machines.The scheme interprets a treatment plan as a point on the corresponding Pareto front, and creates the re-planned one by projecting this point onto the substitute´s Pareto front.Thereby, comparable biological effect and hence clinical outcome can be guaranteed. Material and MethodsIn this automatic re-planning study, n=16 prostate cancer and n=19 head and neck cancer (HNC) cases were included.All patients had previously planned clinical VMAT plans created with in-house TPS Hyperion.Hyperion uses constrained optimization where a Lagrange multiplier λi is associated to each cost-function constraint Ci, rating the effect of each organ-at-risk (OAR) constraint on the target objective.Automatic re-planning starts from the initially reached optimal constraints Ci for PTVs and OARs and adapted machine parameters.A full optimization was executed automatically, in order to generate a comparable Paretooptimal plan.For prostate cases, Elekta BeamModulator plans were re-planned for Elekta Agility, whereas for HNC, Elekta Agility plans were re-planned for Elekta MLCi.For prostate cases we identified rectum and bladder as main OARs and for HNC contralateral parotid gland and spinal cord.For PTV we evaluated variations in EUD, DMean, D2% and D98% and for OARs EUD and D2%. ResultsAutomatic re-planning using constrained optimization was successful in all cases.Auto-optimized plans never corrupted OAR constraints, in some cases re-planning even improved OAR sparing.The mean deviation (range) in rectum EUD was 0,30% (-1,04 --0,27%), bladder EUD 0,44% (-1,08 --0,13%), parotid EUD -0,34% (-14,79 -8,23%) and spinal cord EUD -0,02% (-0,49 -0,31%).For the prostate cases the mean EUD deviation in PTV was -0,15% (-0,57 -0,56%) and for the HNC cases -0,60% for PTV_60 (-2,58 --0,08%) and -0,79% (-3,44 -0,20%) for PTV_54, respectively.Except of 3 HNC cases, all evaluated parameters for targets showed variations within ±1%.For 3 HN cases the target EUD is reduced by up to 3.44%, indicated by λ > 10 * λavg.Consequently, if all λ < 10* λavg, the original and the re-planned plan comply with the given constraints and therefore represent the same optimal point on the Pareto-front, which means they are equal in terms of biological effect for targets and OAR. ConclusionThis study showed that fully automatic re-planning by taking a prescription list from previously optimized VMAT plans is feasible and successful in terms of equal plan quality.Furthermore this approach enables the identification of problematic plans beforehand.