A beamlet-free approach to proton therapy treatment planning : reducing computational costs by combining Monte Carlo dose calculation and spot weight optimization in a single algorithm
(2025)
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- Abstract
- Proton therapy is able to deliver highly conformal dose distributions with a significant reduction in dose to healthy tissue compared to conventional radiotherapy. To turn these theoretical advantages into clinical reality, however, a complex time- and resource-intensive treatment planning process is needed, including highly accurate Monte Carlo dose calculations and robust optimization. Robust optimization can already be challenging for clinics due to the long runtime and high memory usage that often require a reduction of plan complexity. These issues are amplified in novel treatment techniques such as adaptive proton therapy and proton arc therapy, which are highly dependent on fast, memory-efficient treatment planning tools. This work seeks to address these challenges by proposing a deviation from the conventional treatment planning workflow. Over the course of this thesis this new method is developed, refined, extended and validated. This cumulates in a novel robust optimization method for proton therapy that addresses current issues and opens new pathways for even more elaborate treatment modalities.
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Citations
Pross, D. (2025). A beamlet-free approach to proton therapy treatment planning : reducing computational costs by combining Monte Carlo dose calculation and spot weight optimization in a single algorithm. https://hdl.handle.net/2078.5/248634