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Updated: Jun 29, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
Published on: February 6, 2019
Deterministic photon kerma distribution based on the Boltzmann equation for external beam radiation therapy
Jiankui Yuan1, David Jette, Weimin Chen
1ICT Radiotherapy, Livingston, New Jersey 07039, USA. jiankui.yuan@gmail.com
A new photon transport algorithm using discrete ordinates (SN) was developed for 3D radiotherapy planning. This optimized algorithm accurately calculates photon flux distributions, showing good agreement with Monte Carlo methods.
Area of Science:
- Medical Physics
- Computational Physics
- Radiotherapy Technology
Background:
- Accurate photon transport simulation is crucial for effective radiotherapy treatment planning.
- Existing discrete ordinates (SN) codes are often general-purpose and not optimized for medical applications.
Purpose of the Study:
- To develop and validate a novel, optimized photon transport algorithm for fully three-dimensional radiotherapy treatment planning.
- To improve the accuracy and efficiency of radiation dose calculations in cancer treatment.
Main Methods:
- Developed a photon transport algorithm based on the discrete ordinates (SN) solution of the Boltzmann equation.
- Employed orthogonal adaptive meshes and spherical harmonic expansion for flux evaluation.
- Utilized spatial, energy, and angular discretization with the first-collision source method to mitigate ray effects.
Main Results:
- The developed algorithm accurately calculates photon flux distributions in three dimensions.
- Numerical results demonstrate good agreement with established Monte Carlo (EGSnrc) calculations.
- The code is optimized specifically for medical radiation transport, outperforming general-purpose SN codes.
Conclusions:
- The novel SN algorithm provides an accurate and efficient method for photon transport in radiotherapy planning.
- This optimization for medical applications enhances the reliability of treatment planning systems.
- The validated algorithm represents a significant advancement in computational methods for radiation oncology.
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