Simulation of Spread-Out Bragg Peak for Proton Therapy in Prostate Cancer Treatment Using MATLAB Linear Least Squares Method

Authors

  • Rizki Budiman Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Semarang, Indonesia Author
  • Pandji Triadyaksa Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Semarang, Indonesia Author
  • Heri Sutanto Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Semarang, Indonesia Author

DOI:

https://doi.org/10.32628/IJSRST2512119

Keywords:

Geant4, MATLAB lsqlin, Prostate Cancer, Proton Therapy, Spread-Out Bragg Peak

Abstract

Delivering an accurate dose to the target in radiotherapy is crucial for maximizing the effectiveness of prostate cancer treatment while minimizing side effects. Proton therapy offers significant potential advantages over conventional radiotherapy due to its unique physical properties, particularly the ability to precisely deposit energy at a specific depth using the Spread-Out Bragg Peak (SOBP) technique. The SOBP ensures a uniform dose distribution across the tumor, sparing surrounding healthy tissues. However, challenges remain in designing an optimal SOBP that achieves precise dose delivery, especially given the complex interplay of proton energies and target depths. This study addresses these challenges by utilizing Geant4 simulations to model SOBP generation through the use of multiple proton pencil beam energies. Additionally, the MATLAB Linear Least Squares (lsqlin) optimization tool was employed to determine optimal beam weighting configurations for achieving desired dose distributions. The results demonstrate that an optimized SOBP can be successfully achieved, offering a promising foundation for enhancing proton therapy in prostate cancer treatment.

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References

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Published

20-01-2025

Issue

Section

Research Articles

How to Cite

Simulation of Spread-Out Bragg Peak for Proton Therapy in Prostate Cancer Treatment Using MATLAB Linear Least Squares Method. (2025). International Journal of Scientific Research in Science and Technology, 12(1), 126-131. https://doi.org/10.32628/IJSRST2512119

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