New calculations of neutron kerma coefficients and dose equivalent

Liu, Zhenzhou; Chen, Jinxiang

doi:10.1088/0952-4746/28/2/002

Cited by 8 publications

(9 citation statements)

References 20 publications

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“…In the case of the (n, nα) and (n, 2α) channels for the n + 12 C reaction, the residual nuclei 8 Be and 5 He are very unstable and proceed spontaneously via two-body separation into m 3 and M 3 from the E k 2 level; for example, 8 Be→ α + α and 5 He→ n + α. The average energies of m 1 and m 2 expressed as Eqs.…”

Section: A For the N + 12 C Reactionmentioning

confidence: 99%

“…A special case is the residual nucleus 8 Be in the reaction channel (n, n2α) which decays via two-body separation into two α particles with Q 3 = 0.092 MeV as mentioned above in the case of the E k 3 energy level. Here, the average energies carried by two α particles (denoted by m 4 ) can be expressed as (see Appendix B3)…”

Section: B For the N + 16 O Reactionmentioning

confidence: 99%

“…Specially, for the 12 C(n, 5 He) 8 Be channel, the 5 He nucleus (denoted by m 1 ) separates spontaneously into m a and m b with Q 2 = 0.894 MeV; and 8 Be (denoted by M 1 ) does the same, into M a and M b with Q 3 = 0.092 MeV. The average energy carried by m a,b and M a,b can be obtained through an analogous method to that in Appendix B2.…”

Section: Appendix B: Kinematics Of the Neutron-inducedmentioning

confidence: 99%

“…After secondary-particle emission, the residual nuclide M 2 is unstable and can separate spontaneously [as in the 12 C(n, nα) 8 Be and 12 C(n, 2α) 5 He channels] or emit two particles (such as in the 18th-21st channels in Table II). The emitted energies of m 3 and M 3 in the residual nuclear coordinate are expressed as…”

Section: Appendix B: Kinematics Of the Neutron-inducedmentioning

confidence: 99%

“…Evaluation kerma coefficients below 20 MeV were derived from ENDF/B-VI format libraries using such data processing codes as NJOY [6], MAZE [7], and MCNP [8]. These codes take advantage of the fact that many evaluations give explicit energy distributions for the emitted neutrons and photons.…”

Section: Introductionmentioning

confidence: 99%

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New calculation method of neutron kerma coefficients for carbon and oxygen below 30 MeV

Sun

Duan

et al. 2008

Phys. Rev. C

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On the basis of the statistical theory of a neutron-induced light nucleus reaction, a new kerma coefficient calculation formula, expressed as k = N ij k E ij k (E n )σ ij k (E n ), is developed in this paper. In an analysis of the n + 12 C and n + 16 O reactions below 30 MeV, the average energies E ij k of emitted particles of all kinds in the laboratory frame are derived in detail for different channels, allowing an exact energy balance. The optical model parameters of neutron and charged particles, which had reproduced very well the outgoing neutron double-differential cross sections in our early works, are used to obtain the cross sections σ ij k . The calculated partial, elastic recoil, and total kerma coefficients for carbon and oxygen are consistent with existing experimental kerma coefficient data. The elastic cross sections and the first Legendre coefficients of elastic angular distribution derived from EBDF/B-VIIb3 are used in this paper to improve significantly the elastic recoil and total kerma coefficients.

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Section: A For the N + 12 C Reactionmentioning

confidence: 99%

Section: B For the N + 16 O Reactionmentioning

confidence: 99%

Section: Appendix B: Kinematics Of the Neutron-inducedmentioning

confidence: 99%

Section: Appendix B: Kinematics Of the Neutron-inducedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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New calculation method of neutron kerma coefficients for carbon and oxygen below 30 MeV

Sun

Duan

et al. 2008

Phys. Rev. C

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

et al. 2023

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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 (D 95 ), 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.

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Ionizing and non-ionizing kerma factors in silicon for China Spallation Neutron Source neutron spectrum

Jin

Liu

et al. 2019

NUCL SCI TECH

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New calculations of neutron kerma coefficients and dose equivalent

Cited by 8 publications

References 20 publications

New calculation method of neutron kerma coefficients for carbon and oxygen below 30 MeV

New calculation method of neutron kerma coefficients for carbon and oxygen below 30 MeV

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

Ionizing and non-ionizing kerma factors in silicon for China Spallation Neutron Source neutron spectrum

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