Calculation of the DNA damage yield and relative biological effectiveness in boron neutron capture therapy via the Monte Carlo track structure simulation.

Objective.Boron neutron capture therapy (BNCT) is an advanced cellular-level hadron therapy that has exhibited remarkable therapeutic efficacy in the treatment of locally invasive malignancies. Despite its clinical success, the intricate nature of relative biological effectiveness (RBE) and mechanisms responsible for DNA damage remains elusive. This work aims to quantify the RBE of compound particles (i.e. alpha and lithium) in BNCT based on the calculation of DNA damage yields via the Monte Carlo track structure (MCTS) simulation.Approach. The TOPAS-nBio toolkit was employed to conduct MCTS simulations. The calculations encompassed four steps: determination of the angle and energy spectra on the nuclear membrane, quantification of the database containing DNA damage yields for ions with specific angle and energy, accumulation of the database and spectra to obtain the DNA damage yields of compound particles, and calculation of the RBE by comparison yields of double-strand break (DSB) with the reference gamma-ray. Furthermore, the impact of cell size and microscopic boron distribution was thoroughly discussed.Main results. The DSB yields induced by compound particles in three types of spherical cells (radius equal to 10, 8, and 6µm) were found to be 13.28, 17.34, 22.15 Gy Gbp-1for boronophenylalanine (BPA), and 1.07, 3.45, 8.32 Gy Gbp-1for sodium borocaptate (BSH). The corresponding DSB-based RBE values were determined to be 1.90, 2.48, 3.16 for BPA and 0.15, 0.49, 1.19 for BSH. The calculated DSB-based RBE showed agreement with experimentally values of compound biological effectiveness for melanoma and gliosarcoma. Besides, the DNA damage yield and DSB-based RBE value exhibited an increasing trend as the cell radius decreased. The impact of the boron concentration ratio on RBE diminished once the drug enrichment surpasses a certain threshold.Significance. This work is potential to provide valuable guidance for accurate biological-weighted dose evaluation in BNCT.

Use of a neural network-based prediction method to calculate the therapeutic dose in boron neutron capture therapy of patients with glioblastoma.

BACKGROUND: Boron neutron capture therapy (BNCT) is a binary radiotherapy based on the 10 B(n, α)7 Li capture reaction. Nonradioactive isotope 10 B atoms which selectively concentrated in tumor cells will react with low energy neutrons (mainly thermal neutrons) to produce secondary particles with high linear energy transfer, thus depositing dose in tumor cells. In clinical practice, an appropriate treatment plan needs to be set on the basis of the treatment planning system (TPS). Existing BNCT TPSs usually use the Monte Carlo method to determine the three-dimensional (3D) therapeutic dose distribution, which often requires a lot of calculation time due to the complexity of simulating neutron transportation. PURPOSE: A neural network-based BNCT dose prediction method is proposed to achieve the rapid and accurate acquisition of BNCT 3D therapeutic dose distribution for patients with glioblastoma to solve the time-consuming problem of BNCT dose calculation in clinic. METHODS: The clinical data of 122 patients with glioblastoma are collected. Eighteen patients are used as a test set, and the rest are used as a training set. The 3D-UNET is constructed through the design optimization of input and output data sets based on radiation field information and patient CT information to enable the prediction of 3D dose distribution of BNCT. RESULTS: The average mean absolute error of the predicted and simulated equivalent doses of each organ are all less than 1 Gy. For the dose to 95% of the GTV volume (D95 ), the relative deviation between predicted and simulated results are all less than 2%. The average 2 mm/2% gamma index is 89.67%, and the average 3 mm/3% gamma index is 96.78%. The calculation takes about 6 h to simulate the 3D therapeutic dose distribution of a patient with glioblastoma by Monte Carlo method using Intel Xeon E5-2699 v4, whereas the time required by the method proposed in this study is almost less than 1 s using a Titan-V graphics card. CONCLUSIONS: This study proposes a 3D dose prediction method based on 3D-UNET architecture in BNCT, and the feasibility of this method is demonstrated. Results indicate that the method can remarkably reduce the time required for calculation and ensure the accuracy of the predicted 3D therapeutic dose-effect. This work is expected to promote the clinical development of BNCT in the future.

Radiopharmaceutical imaging based on 3D-CZT Compton camera with 3D-printed mouse phantom.

PURPOSE: The study proposes the use of three-dimensional CdZnTe Compton camera (3D-CZT CC) for radiopharmaceutical imaging and investigates the influence factors using a 3D-printed mouse phantom. METHODS: The event selection method and image reconstruction algorithm are optimized by Monte Carlo simulations and mouse phantom experiments. RESULTS: Simulation results show that the intrinsic energy resolution and spatial resolution of 3D-CZT cause a certain deviation in the calculated Compton scattering angle and Compton axis. Such deviation causes the imaging quality to deteriorate. By selecting events whose distance between Compton and photoelectronic interactions are larger than 10 mm, the mean deviation of the Compton axis could be reduced to less than 10%. Using the ordered origin ensemble algorithm with resolution recovery, the artifacts around organs where the radiopharmaceutical was placed are reduced, and the quality of the reconstruction results are improved compared to the results with simple back projection and origin ensembles algorithms. The phantom study shows that the 3D-CZT CC imaging device could visualize the radiopharmaceuticals distribution by 15 min detection. CONCLUSIONS: Through the analysis of this study, the feasibility of 3D-CZT CC for in-vivo distribution measurement of radiopharmaceuticals is demonstrated, and the quality of reconstruction result has been improved.