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

Authors


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

Ancillary