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The radiation pressure applied by an electromagnetic wave on a perfectly absorbing surface equals the energy density of the wave. The wave's momentum also gets transferred to the surface when an electromagnetic wave is entirely absorbed by it. The rate at which momentum is transmitted to an absorbing surface perpendicular to the propagation direction equals the force on the surface.
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Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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A unified path seeking algorithm for IMRT and IMPT beam orientation optimization.

Pavitra Ramesh1, Gilmer Valdes2, Daniel O'Connor3

  • 1Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA 90095, United States of America.

Physics in Medicine and Biology
|September 2, 2023
PubMed
Summary
This summary is machine-generated.

A new automated algorithm, PathGD, improves beam orientation optimization for intensity-modulated radiotherapy and proton therapy. It efficiently selects beams, enhancing plan quality and reducing radiation dose to healthy tissues.

Keywords:
beam selectiondose optimizationpath-seeking algorithms

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Area of Science:

  • Radiation Oncology
  • Medical Physics
  • Computational Imaging

Background:

  • Automated beam orientation optimization (BOO) is crucial for intensity-modulated radiotherapy (IMRT) and intensity-modulated proton therapy (IMPT) plan quality.
  • Current methods like group sparsity optimization require manual tuning to determine the optimal number of beams.
  • A need exists for faster, fully automated BOO methods that efficiently identify optimal beam configurations.

Purpose of the Study:

  • To introduce and evaluate a novel gradient descent-based path-seeking algorithm (PathGD) for automated BOO.
  • To compare the efficiency and dosimetric performance of PathGD against existing methods (GS-FISTA, manual selection).
  • To assess the dosimetric benefits of sequentially adding beams using PathGD for head-and-neck cancer patients.

Main Methods:

  • PathGD, a gradient descent-based path-seeking algorithm, was developed for fluence map optimization with sequentially added beams.
  • PathGD was used to select beam configurations (2-4 proton, 5-15 photon beams) for three head-and-neck patients.
  • Plans generated by PathGD were compared to those from group sparsity-FISTA (GS-FISTA) and manual selection (MAN) in terms of computational efficiency, dosimetry, and robustness (for proton plans).

Main Results:

  • PathGD demonstrated faster beam selection than GS-FISTA by an average of 35%.
  • PathGD matched the CTV coverage of GS-FISTA plans while significantly reducing OAR mean and maximum dose (average 13.6%).
  • PathGD improved CTV dose metrics and reduced worst-case OAR doses, highlighting the dosimetric benefits of its beam-by-beam approach.

Conclusions:

  • PathGD offers an efficient and dosimetrically superior alternative to existing BOO methods for IMRT and IMPT.
  • The algorithm's ability to analyze dosimetric cost per beam facilitates optimal plan selection.
  • PathGD's performance underscores the importance of beam arrangement optimization, particularly for IMPT.