Evaluation of dose prediction error and optimization convergence error in four-dimensional inverse planning of robotic stereotactic lung radiotherapy.

ABSTRACT: Inverse optimization of robotic stereotactic lung radiotherapy is typically performed using relatively simple dose calculation algorithm on a single instance of breathing geometry. Variations of patient geometry and tissue density during respiration could reduce the dose accuracy of these 3D optimized plans. To quantify the potential benefits of direct four-dimensional (4D) optimization in robotic lung radiosurgery, 4D optimizations using 1) ray-tracing algorithm with equivalent path-length heterogeneity correction (4EPL(opt)), and 2) Monte Carlo (MC) algorithm (4MC(opt)), were performed in 25 patients. The 4EPL(opt) plans were recalculated using MC algorithm (4MC(recal)) to quantify the dose prediction errors (DPEs). Optimization convergence errors (OCEs) were evaluated by comparing the 4

SUBMITTER: Chan MK 

PROVIDER: S-EPMC5714544 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature