Related Experiment Video
Updated: Aug 18, 2025
Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
Published on: February 6, 2019
Knowledge-based DVH estimation and optimization for breast VMAT plans with and without avoidance sectors
Antonella Fogliata1, Sara Parabicoli2, Lucia Paganini2
1Radiotherapy and Radiosurgery Department, Humanitas Research Hospital IRCCS, Milan-Rozzano, Italy. antonella.fogliata@humanitas.it.
Background:
To analyze RapidPlan knowledge-based models for DVH estimation of organs at risk from breast cancer VMAT plans presenting arc sectors en-face to the breast with zero dose rate, feature imposed during the optimization phase (avoidance sectors AS).
Methods:
CT datasets of twenty left breast patients in deep-inspiration breath-hold were selected. Two VMAT plans, PartArc and AvoidArc, were manually generated with double arcs from ~ 300 to ~ 160°, with the second having an AS en-face to the breast to avoid contralateral breast and lung direct irradiation. Two RapidPlan models were generated from the two plan sets. The two models were evaluated in a closed loop to assess the model performance on plans where the AS were selected or not in the optimization.
Results:
The PartArc plans model estimated DVHs comparable with the original plans. The AvoidArc plans model estimated a DVH pattern with two steps for the contralateral structures when the plan does not contain the AS selected in the optimization phase. This feature produced mean doses of the contralateral breast, averaged over all patients, of 0.4 ± 0.1 Gy, 0.6 ± 0.2 Gy, and 1.1 ± 0.2 Gy for the AvoidArc plan, AvoidArc model estimation, RapidPlan generated plan, respectively. The same figures for the contralateral lung were 0.3 ± 0.1 Gy, 1.6 ± 0.6 Gy, and 1.2 ± 0.5 Gy. The reason was found in the possible incorrect information extracted from the model training plans due to the lack of knowledge about the AS. Conversely, in the case of plans with AS set in the optimization generated with the same AvoidArc model, the estimated and resulting DVHs were comparable. Whenever the AvoidArc model was used to generate DVH estimation for a plan with AS, while the optimization was made on the plan without the AS, the optimizer evidentiated the limitation of a minimum dose rate of 0.2 MU/°, resulting in an increased dose to the contralateral structures respect to the estimation.
Conclusions:
The RapidPlan models for breast planning with VMAT can properly estimate organ at risk DVH. Attention has to be paid to the plan selection and usage for model training in the presence of avoidance sectors.
