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Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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GPU-accelerated FREDopt package for simultaneous dose and LETd proton radiotherapy plan optimization via

Damian Borys1,2, Jan Gajewski2, Tobias Becher3,4,5

  • 1Silesian University of Technology, Department of Systems Biology and Engineering, Gliwice, Poland.

Arxiv
|October 3, 2025
PubMed
Summary
This summary is machine-generated.

FREDopt, a new GPU-accelerated software, optimizes proton therapy plans for dose and dose-averaged Linear Energy Transfer (LETd). It significantly reduces LETd in organs at risk while maintaining target coverage, offering clinical potential.

Keywords:
feasibility seekinglinear energy transfer (LET)proton therapyradiation therapysuperiorizationtreatment plan optimization

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Area of Science:

  • Medical Physics
  • Computational Biology
  • Radiotherapy Research

Background:

  • Proton therapy offers precise dose delivery but optimizing for both dose and Linear Energy Transfer (LET) remains challenging.
  • Improving treatment planning systems is crucial for maximizing therapeutic benefit and minimizing side effects in proton therapy.

Purpose of the Study:

  • To introduce FREDopt, an open-source, GPU-accelerated software for simultaneous optimization of proton dose and dose-averaged LET (LETd) in Intensity Modulated Proton Therapy (IMPT).
  • To evaluate the efficacy of FREDopt in reducing dose and LETd in organs at risk (OARs) while preserving target dose conformity.

Main Methods:

  • FREDopt was developed in Python, utilizing CuPy for GPU acceleration and integrating fast Monte Carlo (MC) simulations.
  • A novel superiorization of feasibility-seeking algorithms was employed to efficiently find optimal treatment plans.
  • The software's performance was validated on clinical patient treatment plans, comparing pre-optimization and re-optimization results.

Main Results:

  • Simultaneous dose and LETd optimization using FREDopt resulted in significant reductions in LETd and the product of dose and LETd within OARs.
  • Target dose conformity was successfully preserved during the re-optimization process.
  • Computational times ranged from 14 to 50 minutes, demonstrating suitability for clinical and research use.

Conclusions:

  • FREDopt provides an efficient and effective solution for simultaneous dose and LETd optimization in IMPT.
  • The software's open-source nature and GPU acceleration facilitate further development and clinical adoption.
  • This approach holds promise for enhancing treatment efficacy and patient outcomes in proton therapy.