Investigation of the optimum neutron energy spectrum for brain tumor boron neutron capture therapy using Monte Carlo N-Particle Transport Code

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Abdelfattah Y. Soliman
Essam Banoqitah
Ned Xoubi
Fathi Djouider

Abstract

Boron neutron capture therapy, a targeted technique for cancer treatment, is based on fission reaction of implanted boron-10 in tumor cells by thermal neutrons to yield alpha particles and recoiling lithium‐7 nuclei. The short range of these ionizing fission products induces damages to the cancer cells while sparing surrounding healthy tissues. A methodology to determine the optimum neutron energy according to the depth of the tumor in the brain is developed in this work. This methodology mainly depends on separately considering the different reaction types at discrete neutron energies using Monte Carlo N-Particle (MCNP) Transport Code and investigating their relative contribution to the absorbed dose in both the tumor and surrounding healthy tissues. For a certain tumor depth, the neutron energy that maximizes the neutron dose to the tumor and minimizes it in the surrounding healthy tissues is selected. The metrics to evaluate improvement in the optimization process are developed based on the ratio of the tumor dose rate density (Gy/cm3‧s) to that of the surrounding healthy tissues. The results showed a significant improvement when compared with those of the International Atomic Energy Agency (IAEA) recommended neutron energy ranges. For deep-seated tumors, the dose ratio was improved from 0.89 to 1.77 for tissues preceding the tumor and from 2.40 to 12.0 for tissues after the tumor. For the shallow-seated tumors, the dose ratio was improved from 2.48 to 2.64 for tissues preceding the tumor and from 8.63 to 18.8 for tissues after the tumor.

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Soliman, A. ., Banoqitah, E., Xoubi, N., & Djouider, F. . (2024). Investigation of the optimum neutron energy spectrum for brain tumor boron neutron capture therapy using Monte Carlo N-Particle Transport Code. Journal of King Abdulaziz University: Engineering Sciences, 34(1). Retrieved from https://journals.kau.edu.sa/index.php/JENGSCI/article/view/1977
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