Benefits of robust optimization in comparison with PTV‐based planning approach to overcome beam positioning uncertainties in spot‐scanning proton therapy

TL;DR

This study compares two planning methods in proton therapy to handle beam positioning uncertainties, finding that robust optimization performs better than the PTV-based approach.

Contribution

The paper demonstrates that robust optimization is more effective than PTV-based planning for handling beam positioning uncertainties in proton therapy.

Findings

Robust optimization showed better results than PTV-based planning in most uncertainty scenarios.

The robust approach fully encompassed the CTV with 100% dose and improved dose conformity.

Facility-specific beam uncertainties of 1 mm should be considered during treatment planning.

Abstract

The inherent uncertainties associated with proton therapy (PT) may present a challenge to the optimal clinical utilization of this radiotherapy modality. The possibility to overcome the uncertainties associated with temporal fluctuations in some parameters of the PT system by selecting an additional clinical target volume to planning parget volume (CTV‐PTV) margin or by modifying the planning approach was suggested. The objective of this work was to verify the sufficiency of the calculated additional margin for overcoming beam positioning uncertainties in spot‐scanning PT.

Treatment plans for eight patients were calculated using two methods (robust optimization and PTV‐based approaches) and evaluated with regard to dose‐volume histogram (DVH)‐based dosimetric metrics. The robustness of each plan was evaluated under six scenarios in linear directions ±4 mm and two scenarios with a ±3.5% range uncertainty. A comparison between robust optimization and PTV‐based approaches was performed in the context of additional 1‐mm setup uncertainty associated with facility‐specific beam uncertainties.

No statistically significant difference was identified between the initial plans of the PTV‐based and robust approaches with regard to investigated dosimetric metrics. But robust optimization shows better results in comparison to PTV approach in majority of investigated scenarios. CTV was fully encompassed by the 100% dose in the plans created using the robust optimization approach. The Robust approach demonstrated superior dose conformity to the CTV, both for the 100% and 95% prescribed doses. Although both the PTV and Robust approaches permitted homogeneity in all scenarios, the superiority of the Robust approach was evident.

It is necessary to consider the facility‐specific beam uncertainty as additional margin during treatment planning in PT. It was demonstrated that the robust optimization approach is an effective method for eliminating beam‐related facility‐specific uncertainties order of 1 mm in comparison to the PTV planning approach.

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