Intensity modulated proton arc therapy via geometry-based energy selection for ependymoma
Wenhua Cao, Yupeng Li, Xiaodong Zhang, Falk Poenisch, Pablo Yepes,, Narayan Sahoo, David Grosshans, Susan McGovern, G. Brandon Gunn, Steven J., Frank, Xiaorong R. Zhu

TL;DR
This paper introduces a geometry-based energy selection method for intensity modulated proton arc therapy (IMPAT) that improves plan quality and dosimetric outcomes for ependymoma patients by efficiently selecting energy layers and optimizing scanning spots.
Contribution
The study presents a novel IMPAT planning approach using geometry-based energy selection, enhancing plan quality and dosimetric benefits over traditional IMPT methods.
Findings
IMPAT plans showed better homogeneity and conformity than IMPT.
IMPAT achieved higher RBE enhancement in target volumes.
The method demonstrated efficiency and potential clinical benefits.
Abstract
We developed a novel method of creating intensity modulated proton arc therapy (IMPAT) plans that uses computing resources efficiently and may offer a dosimetric benefit for patients with ependymoma or similar tumor geometries. Our IMPAT planning method consists of a geometry-based energy selection step with major scanning spot contributions as inputs computed using ray-tracing and single-Gaussian approximation of lateral spot profiles. Based on the geometric relation of scanning spots and dose voxels, our energy selection module selects a minimum set of energy layers at each gantry angle such that each target voxel is covered by sufficient scanning spots as specified by the planner, with dose contributions above the specified threshold. Finally, IMPAT plans are generated by robustly optimizing scanning spots of the selected energy layers using a commercial proton treatment planning…
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Taxonomy
TopicsRadiation Therapy and Dosimetry · Advanced Radiotherapy Techniques · Advanced Neural Network Applications
