TY - JOUR SN - 1748-717X CY - London SP - 1 A1 - Nwankwo, Obioma A1 - Mekdash, Hana A1 - Sihono, Dwi Seno Kuncoro A1 - Wenz, Frederik A1 - Glatting, Gerhard AV - public Y1 - 2015/// EP - 5 VL - 10 JF - Radiation oncology IS - 111 ID - heidok19433 TI - Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning UR - https://archiv.ub.uni-heidelberg.de/volltextserver/19433/ N2 - Background: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the judgment of the experienced planner. Methods: Thirty volumetric modulated arc therapy plans were randomly selected from a database of prostate plans that were generated by experienced planners (expert plans). The anatomical data (CT scan and delineation of organs) of these patients and the KBRT algorithm were given to a novice with no prior treatment planning experience. The inexperienced planner used the knowledge-based algorithm to predict the dose that the OARs receive based on their proximity to the treated volume. The population-based OAR constraints were changed to the predicted doses. A KBRT plan was subsequently generated. The KBRT and expert plans were compared for the achieved target coverage and OAR sparing. The target coverages were compared using the Uniformity Index (UI), while 5 dose-volume points (D10, D30, D50, D70 and D90) were used to compare the OARs (bladder and rectum) doses. Wilcoxon matched-pairs signed rank test was used to check for significant differences (p?