SU‐E‐T‐530: Knowledge‐Based Treatment Planning and Its Potential Role in the Transition Between Treatment Planning Systems

Abstract

Purpose:Commissioning a treatment planning system (TPS) involves many tasks, including making sure users have sufficient training and experience to create quality plans. We investigated the role that knowledge‐based planning (KBP) can play in aiding a clinic's transition to a new TPS.Methods:60 clinically treated prostate and prostate bed IMRT plans were exported from an in‐house TPS and used to create a KBP‐model in a newly introduced commercial TPS (Eclipse v13.5, Varian Medical Systems). To determine the benefit that KBP may have in a TPS transition, the model was tested on two groups. Group 1 consisted of the first 10 patients treated in the commercial TPS after the transition from the in‐house TPS, Group 2 consisted of 10 patients planned in the commercial TPS, but without the KBP model, after 8 months of clinical use. The KBP‐generated plan for each patient was compared to the clinically‐used plan in terms of quality and planning efficiency.Results:On average, the KBP‐generated plans provided better target coverage for group 1 than the clinical plans,and about equivalent coverage for group 2. The average absolute difference (KBP‐clinical) for D95 for the PTV was 0.48±0.49% and −0.11±0.48% for groups 1 and 2, respectively. For the OARs, the KBP‐generated plans produced lower doses for every normal tissue objective except the maximum dose to 0.1cc of rectum (0.50±0.27Gy and 0.22±0.17Gy for groups 1 and 2, respectively). The time needed for KBP‐generated plans ranged from 6– 15min compared to 30–150 and 15–60min for groups 1 and 2, respectively.Conclusion:Knowledge‐based planning is a promising tool to aid in transitions to new TPSs. Our study indicates that high‐quality treatment plans could have been generated in the new TPS more efficiently compared to not using KBP. Even after 8 months of clinical use, KBP still showed a quality and efficiency increase compared to manual planning.Partially supported by Varian Medical Systems