Incorporating boron distribution variations in microdosimetric kinetic model-based relative biological effectiveness calculations for boron neutron capture therapy

Author:

Li Mingzhu12,Geng Changran12ORCID,Han Yang12,Guan Fada3,Liu Yuanhao124,Shu Diyun124,Tang Xiaobin12

Affiliation:

1. Nanjing University of Aeronautics and Astronautics Department of Nuclear Science and Technology, , Nanjing, 211106, China

2. Nanjing University of Aeronautics and Astronautics Joint International Research Laboratory on Advanced Particle Therapy, , Nanjing, 211100, China

3. Yale University School of Medicine Department of Therapeutic Radiology, , New Haven, Connecticut, 06530, United States

4. Neuboron Medtech Ltd. , Nanjing, Jiangsu, 211112, China

Abstract

Abstract This study introduces the MKM_B model, an approach derived from the MKM model, designed to evaluate the biological effectiveness of Boron Neutron Capture Therapy (BNCT) in the face of challenges from varying microscopic boron distributions. The model introduces a boron compensation factor, allowing for the assessment of compound Biological Effectiveness (CBE) values for different boron distributions. Utilizing the TOPAS simulation platform, the lineal energy spectrum of particles in BNCT was simulated, and the sensitivity of the MKM_B model to parameter variations and the influence of cell size on the model were thoroughly investigated. The CBE values for 10B-boronphenylalanine (BPA) and 10B-sodium (BSH) were determined to be 3.70 and 1.75, respectively. These calculations were based on using the nucleus radius of 2.5 μm and the cell radius of 5 μm while considering a 50% surviving fraction. It was observed that as cell size decreased, the CBE values for both BPA and BSH increased. Additionally, the model parameter rd was identified as having the most significant impact on CBE, with other parameters showing moderate effects. The development of the MKM_B model enables the accurate prediction of CBE under different boron distributions in BNCT. This model offers a promising approach to optimize treatment planning by providing increased accuracy in biological effectiveness.

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

National Key Research and Development Program

Publisher

Oxford University Press (OUP)

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