The minimum knowledge base for predicting organ-at-risk dose-volume levels and plan-related complications in IMRT planning.
IMRT treatment planning requires consideration of two competing objectives: achieving the required amount of radiation for the planning target volume and minimizing the amount of radiation delivered to all other tissues. It is important for planners to understand the tradeoff between competing factors so that the time-consuming human interaction loop (plan-evaluate-modify) can be eliminated. Treatment-plan-surface models have been proposed as a decision support tool to aid treatment planners and clinicians in choosing between rival treatment plans in a multi-plan environment. In this paper, an empirical approach is introduced to determine the minimum number of treatment plans (minimum knowledge base) required to build accurate representations of the IMRT plan surface in order to predict organ-at-risk (OAR) dose-volume (DV) levels and complications as a function of input DV constraint settings corresponding to all involved OARs in the plan. We have tested our approach on five head and neck patients and five whole pelvis/prostate patients. Our results suggest that approximately 30 plans were sufficient to predict DV levels with less than 3% relative error in both head and neck and whole pelvis/prostate cases. In addition, approximately 30-60 plans were sufficient to predict saliva flow rate with less than 2% relative error and to classify rectal bleeding with an accuracy of 90%.
Zhang
Hao H
HH
Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA. hzhan001@umaryland.edu
Meyer
Robert R
RR
Shi
Leyuan
L
D'Souza
Warren D
WD
D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D009369:Neoplasms / Q000532:radiotherapy*; D011832:Radiation Injuries / Q000209:etiology / Q000517:prevention & control*; D011835:Radiation Protection / Q000379:methods*; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000009:adverse effects* / Q000379:methods