TY - JOUR
T1 - Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts
T2 - Validation of a KBRT algorithm for prostate cancer treatment planning
AU - Nwankwo, Obioma
AU - Mekdash, Hana
AU - Sihono, Dwi Seno Kuncoro
AU - Wenz, Frederik
AU - Glatting, Gerhard
N1 - Publisher Copyright:
© 2015 Nwankwo et al.
PY - 2015/5/10
Y1 - 2015/5/10
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 < 0.05) between both datasets. Results: The KBRT and expert plans achieved mean UI values of 1.10 ± 0.03 and 1.10 ± 0.04, respectively. The Wilcoxon test showed no statistically significant difference between both results. The D90, D70, D50, D30 and D10 values of the two planning strategies, and the Wilcoxon test results suggests that the KBRT plans achieved a statistically significant lower bladder dose (at D30), while the expert plans achieved a statistically significant lower rectal dose (at D10 and D30). Conclusions: The results of this study show that the KBRT treatment planning approach is a promising method to objectively incorporate patient anatomical variations in radiotherapy treatment planning.
AB - 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 < 0.05) between both datasets. Results: The KBRT and expert plans achieved mean UI values of 1.10 ± 0.03 and 1.10 ± 0.04, respectively. The Wilcoxon test showed no statistically significant difference between both results. The D90, D70, D50, D30 and D10 values of the two planning strategies, and the Wilcoxon test results suggests that the KBRT plans achieved a statistically significant lower bladder dose (at D30), while the expert plans achieved a statistically significant lower rectal dose (at D10 and D30). Conclusions: The results of this study show that the KBRT treatment planning approach is a promising method to objectively incorporate patient anatomical variations in radiotherapy treatment planning.
KW - Dose prediction algorithm
KW - Knowledge-based radiation therapy (KBRT) treatment planning
KW - Normal tissue sparing
KW - Personalized radiotherapy treatment planning
KW - Treatment plan optimization
UR - http://www.scopus.com/inward/record.url?scp=84930211229&partnerID=8YFLogxK
U2 - 10.1186/s13014-015-0416-6
DO - 10.1186/s13014-015-0416-6
M3 - Article
C2 - 25957871
AN - SCOPUS:84930211229
SN - 1748-717X
VL - 10
JO - Radiation Oncology
JF - Radiation Oncology
IS - 1
M1 - 111
ER -
