Toward Realistic Radiation Dosimetry Using Monte Carlo Method
通過蒙特卡羅方法邁向現實輻射劑量學
Student thesis: Doctoral Thesis
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| Award date | 3 Jul 2020 |
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| Permanent Link | https://scholars.cityu.edu.hk/en/theses/theses(99ee12bc-5c57-4cec-86d1-b4eaa887330c).html |
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Abstract
In our daily lives, we humans are continuously exposed to ionizing radiation; this exposure could either be from the natural radiation that is emitted from the earth or as a result of an accident such as Chernobyl and Fukushima. Generally, ionizing radiations can be broadly categorized into (1) directly and (2) indirectly ionizing radiations. Directly ionizing radiations (such as electrons, protons and other charged particles) are charged particles that will interact through Coulombic force with matter. Indirectly ionizing radiations (such as photons and neutrons) are uncharged particles that in fact set in motion charged particles to induce ionization with matter. The interaction of ionizing radiation with matter has a stochastic nature and therefore this property requires employment of Monte Carlo method for simulation of ionizing radiation. The interaction and transportation of these two categories of ionizing radiation can be carefully studied using the Monte Carlo method for applications in radiobiological experiments and in radiotherapy.
The present thesis was devoted to introducing and investigating realistic dosimetry upon interaction of ionizing radiations in radiobiological experiments and radiotherapy using Monte Carlo method. The thesis consists of 8 chapters.
Chapter 1 provided the introduction and basic concept of ionizing radiation and Monte Carlo method.
Chapter 2 described detailed Monte Carlo studies on photon interactions in radiobiological experiments. X-ray and γ-ray photons have been widely used for studying radiobiological effects of ionizing radiations. Photons are indirectly ionizing radiations, so they need to set in motion electrons (which are a directly ionizing radiation) to perform the ionizations. When the photon dose decreases to below a certain limit, the number of electrons set in motion will become so small that not all cells in an “exposed” cell population can get at least one electron hit. When some cells in a cell population are not hit by a directly ionizing radiation (in other words not irradiated), there will be rescue effect between the irradiated cells and non-irradiated cells, and the resultant radiobiological effect observed for the “exposed” cell population will be different. In the present chapter, the mechanisms underlying photon interactions in radiobiological experiments were studied using our developed NRUphoton computer code, which was benchmarked against the MCNP5 code by comparing the photon dose delivered to the cell layer underneath the water medium. The following conclusions were reached: (1) The interaction fractions decreased in the following order: 16O > 12C > 14N > 1H. Bulges in the interaction fractions (versus water medium thickness) were observed, which reflected changes in the energies of the propagating photons due to traversals of different amount of water medium as well as changes in the energy-dependent photon interaction cross-sections. (2) Photoelectric interaction and incoherent scattering dominated for lower-energy (10 keV) and high-energy (100 keV and 1 MeV) incident photons. (3) The fractions of electron ejection from different nuclei were mainly governed by the photoelectric effect cross-sections, and the fractions from the 1s subshell were the largest. (4) The penetration fractions in general decreased with increasing medium thickness, and increased with increasing incident photon energy, the latter being explained by the corresponding reduction in interaction cross-sections. (5) The areas under the angular distribution curves of photons exiting the medium layer and subsequently undergoing interactions within the cell layer became smaller for larger incident photon energies. (6) The number of cells suffering at least one electron hit increased with the administered dose. For larger incident photon energies, the numbers of cells suffering at least one electron hit became smaller, which was attributed to the reduction in the photon interaction cross-section. These results highlighted the importance of the administered dose in radiobiological experiments. In particular, the threshold administered doses at which all cells in the exposed cell array suffered at least one electron hit might provide hints on explaining the intriguing observation that radiation-induced cancers can be statistically detected only above the threshold value of ~100 mSv, and thus on reconciling controversies over the linear no-threshold model.
Chapter 3 described detailed Monte Carlo studies on neutron interactions in radiobiological experiments. The Monte Carlo method was used to study the characteristics of neutron interactions with cells underneath a water medium layer with varying thickness. The following results were obtained. (1) The fractions of neutron interaction with 1H, 12C, 14N and 16O nuclei in the cell layer were studied. The fraction with 1H increased with increasing medium thickness, while decreased for 12C, 14N and 16O nuclei. The bulges in the interaction fractions with 12C, 14N and 16O nuclei were explained by the resonance spikes in the interaction cross-section data. The interaction fraction decreased in the order: 1H > 16O > 12C > 14N. (2) In general, as the medium thickness increased, the number of “interacting neutrons” which exited the medium and then further interacted with the cell layer increased. (3) The area under the angular distributions for “interacting neutrons” decreased with increasing incident neutron energy. Such results would be useful for deciphering the reasons behind discrepancies among existing results in the literature.
Chapter 4 introduced and described a calibration method for realistic neutron dosimetry in radiobiological experiments assisted by MCNP simulation. Many studies on biological effects of neutrons involve dose responses of neutrons, which rely on accurately determined absorbed doses in the irradiated cells or living organisms. Absorbed doses in the cells or living organisms are difficult to measure and are thus commonly surrogated by doses measured using separate radiation detectors. The present work described the determination of doses absorbed in the cell layer underneath a medium column (DA) and the doses absorbed in an ionization chamber (DE) from neutrons through computer simulations using the MCNP-5 code, and then determined the conversion coefficients R (= DA/DE). It was found that R in general decreased with the medium thickness, which was due to elastic and inelastic scattering. For 2-MeV neutrons, conspicuous bulges in R values were observed at medium thicknesses of about 1500, 3500 and 4500 µm, which were attributed to the presence of carbon, oxygen and nitrogen nuclei, and were reflections of the spikes in the neutron interaction cross sections with carbon, oxygen and nitrogen nuclei. For 0.1-MeV neutrons, no conspicuous bulges in R were observed (except one at about 2000 µm which was due to photon interactions), which was explained by the absence of prominent spikes in the interaction cross sections with carbon, oxygen and nitrogen nuclei for neutron energies < 0.1 MeV. The ratio R could be increased by ~50% for small medium thickness if the incident neutron energy was reduced from 2 MeV down to 0.1 MeV. As such, the absorbed doses in cells (DA) would be different for different incident neutron energies, even when the absorbed doses shown on the detector were the same.
Chapter 5 described a realistic dosimetry for studies on biological responses to X-rays and gamma-rays. A calibration coefficient R (= DA/DE) for photons was employed to characterize the photon dose in radiobiological experiments, where DA was the actual dose delivered to cells and DE was the dose recorded by an ionization chamber. R was determined using the Monte Carlo N-Particle version 5 (MCNP-5) code. Photons with (1) discrete energies, and (2) continuous-energy distributions under different beam conditioning were considered. The four studied mono-energetic photons had energies E = 0.01, 0.1, 1 and 2 MeV. Photons with E = 0.01 MeV gave R values significantly different from unity while those with E > 0.1 MeV gave R ≈ 1. Moreover, R decreased monotonically with increasing thickness of water medium above the cells for E = 0.01, 1 or 2 MeV due to energy loss of photons in the medium. For E = 0.1 MeV, the monotonic pattern no longer existed due to the dose delivered to the cells by electrons created through photoelectric effect close to the medium-cell boundary. The continuous-energy distributions from the X-Rad 320 Biological Irradiator (voltage = 150 kV) were also studied under three different beam conditioning: (a) F0: no filter used (b) F1: using a 2 mm-thick Al filter, and (c) F2: using a filter made of (1.5 mm Al + 0.25 mm Cu + 0.75 mm Sn), giving mean output photon energies of 47.4, 57.3 and 102 keV, respectively. R varied from ~1.04 to ~1.28 for F0, from ~1.13 to ~1.21 for F1, and was very close to unity for F2.
Chapter 6 described the medium-thickness-dependent proton dosimetry for radiobiological experiments. A calibration method was proposed in the present work to determine the medium-thickness-dependent proton doses absorbed in cellular components (i.e., cellular cytoplasm and nucleus) in radiobiological experiments. Consideration of the dependency on medium thickness was crucial as the linear energy transfer (LET) of protons could rise to a sharp peak (known as the Bragg peak) towards the end of their ranges. Relationships between the calibration coefficient R vs medium-layer thickness were obtained for incident proton energies of 10, 15, 20, 25, 30 and 35 MeV, and for various medium thicknesses up to 5000 µm, where R was defined as the ratio DA/DE, DA was the absorbed proton dose in cellular components, and DE was the absorbed proton dose in a separate radiation detector. In the present work, DA and DE were determined using the MCNPX (Monte Carlo N-Particle eXtended) code version 2.4.0. For lower incident proton energies (i.e., 10, 15 and 20 MeV), formation of Bragg-peak-like features were noticed in their R-vs-medium-layer-thickness relationships, and large R values of >7 and >6 were obtained for cytoplasm and nucleus of cells, respectively, which highlighted the importance of careful consideration of the medium thickness in radiobiological experiments.
Chapter 7 described the conversion coefficients for determination of dispersed photon dose during radiotherapy: NRUrad input code for MCNP. Radiotherapy is a common cancer treatment module, where a certain amount of dose will be delivered to the targeted organ. This is achieved usually by photons generated by linear accelerator units. However, radiation scattering within the patient’s body and the surrounding environment will lead to dose dispersion to healthy tissues which are not targets of the primary radiation. Determination of the dispersed dose would be important for assessing the risk and biological consequences in different organs or tissues. In the present work, the concept of conversion coefficient (F) of the dispersed dose was developed, in which F = (Dd/Dt), where Dd was the dispersed dose in a non-targeted tissue and Dt is the absorbed dose in the targeted tissue. To quantify Dd and Dt, a comprehensive model was developed using the Monte Carlo N-Particle (MCNP) package to simulate the linear accelerator head, the human phantom, the treatment couch and the radiotherapy treatment room. The present work also demonstrated the feasibility and power of parallel computing through the use of the Message Passing Interface (MPI) version of MCNP5.
Chapter 8 gave the conclusion and some potential future works.
The present thesis was devoted to introducing and investigating realistic dosimetry upon interaction of ionizing radiations in radiobiological experiments and radiotherapy using Monte Carlo method. The thesis consists of 8 chapters.
Chapter 1 provided the introduction and basic concept of ionizing radiation and Monte Carlo method.
Chapter 2 described detailed Monte Carlo studies on photon interactions in radiobiological experiments. X-ray and γ-ray photons have been widely used for studying radiobiological effects of ionizing radiations. Photons are indirectly ionizing radiations, so they need to set in motion electrons (which are a directly ionizing radiation) to perform the ionizations. When the photon dose decreases to below a certain limit, the number of electrons set in motion will become so small that not all cells in an “exposed” cell population can get at least one electron hit. When some cells in a cell population are not hit by a directly ionizing radiation (in other words not irradiated), there will be rescue effect between the irradiated cells and non-irradiated cells, and the resultant radiobiological effect observed for the “exposed” cell population will be different. In the present chapter, the mechanisms underlying photon interactions in radiobiological experiments were studied using our developed NRUphoton computer code, which was benchmarked against the MCNP5 code by comparing the photon dose delivered to the cell layer underneath the water medium. The following conclusions were reached: (1) The interaction fractions decreased in the following order: 16O > 12C > 14N > 1H. Bulges in the interaction fractions (versus water medium thickness) were observed, which reflected changes in the energies of the propagating photons due to traversals of different amount of water medium as well as changes in the energy-dependent photon interaction cross-sections. (2) Photoelectric interaction and incoherent scattering dominated for lower-energy (10 keV) and high-energy (100 keV and 1 MeV) incident photons. (3) The fractions of electron ejection from different nuclei were mainly governed by the photoelectric effect cross-sections, and the fractions from the 1s subshell were the largest. (4) The penetration fractions in general decreased with increasing medium thickness, and increased with increasing incident photon energy, the latter being explained by the corresponding reduction in interaction cross-sections. (5) The areas under the angular distribution curves of photons exiting the medium layer and subsequently undergoing interactions within the cell layer became smaller for larger incident photon energies. (6) The number of cells suffering at least one electron hit increased with the administered dose. For larger incident photon energies, the numbers of cells suffering at least one electron hit became smaller, which was attributed to the reduction in the photon interaction cross-section. These results highlighted the importance of the administered dose in radiobiological experiments. In particular, the threshold administered doses at which all cells in the exposed cell array suffered at least one electron hit might provide hints on explaining the intriguing observation that radiation-induced cancers can be statistically detected only above the threshold value of ~100 mSv, and thus on reconciling controversies over the linear no-threshold model.
Chapter 3 described detailed Monte Carlo studies on neutron interactions in radiobiological experiments. The Monte Carlo method was used to study the characteristics of neutron interactions with cells underneath a water medium layer with varying thickness. The following results were obtained. (1) The fractions of neutron interaction with 1H, 12C, 14N and 16O nuclei in the cell layer were studied. The fraction with 1H increased with increasing medium thickness, while decreased for 12C, 14N and 16O nuclei. The bulges in the interaction fractions with 12C, 14N and 16O nuclei were explained by the resonance spikes in the interaction cross-section data. The interaction fraction decreased in the order: 1H > 16O > 12C > 14N. (2) In general, as the medium thickness increased, the number of “interacting neutrons” which exited the medium and then further interacted with the cell layer increased. (3) The area under the angular distributions for “interacting neutrons” decreased with increasing incident neutron energy. Such results would be useful for deciphering the reasons behind discrepancies among existing results in the literature.
Chapter 4 introduced and described a calibration method for realistic neutron dosimetry in radiobiological experiments assisted by MCNP simulation. Many studies on biological effects of neutrons involve dose responses of neutrons, which rely on accurately determined absorbed doses in the irradiated cells or living organisms. Absorbed doses in the cells or living organisms are difficult to measure and are thus commonly surrogated by doses measured using separate radiation detectors. The present work described the determination of doses absorbed in the cell layer underneath a medium column (DA) and the doses absorbed in an ionization chamber (DE) from neutrons through computer simulations using the MCNP-5 code, and then determined the conversion coefficients R (= DA/DE). It was found that R in general decreased with the medium thickness, which was due to elastic and inelastic scattering. For 2-MeV neutrons, conspicuous bulges in R values were observed at medium thicknesses of about 1500, 3500 and 4500 µm, which were attributed to the presence of carbon, oxygen and nitrogen nuclei, and were reflections of the spikes in the neutron interaction cross sections with carbon, oxygen and nitrogen nuclei. For 0.1-MeV neutrons, no conspicuous bulges in R were observed (except one at about 2000 µm which was due to photon interactions), which was explained by the absence of prominent spikes in the interaction cross sections with carbon, oxygen and nitrogen nuclei for neutron energies < 0.1 MeV. The ratio R could be increased by ~50% for small medium thickness if the incident neutron energy was reduced from 2 MeV down to 0.1 MeV. As such, the absorbed doses in cells (DA) would be different for different incident neutron energies, even when the absorbed doses shown on the detector were the same.
Chapter 5 described a realistic dosimetry for studies on biological responses to X-rays and gamma-rays. A calibration coefficient R (= DA/DE) for photons was employed to characterize the photon dose in radiobiological experiments, where DA was the actual dose delivered to cells and DE was the dose recorded by an ionization chamber. R was determined using the Monte Carlo N-Particle version 5 (MCNP-5) code. Photons with (1) discrete energies, and (2) continuous-energy distributions under different beam conditioning were considered. The four studied mono-energetic photons had energies E = 0.01, 0.1, 1 and 2 MeV. Photons with E = 0.01 MeV gave R values significantly different from unity while those with E > 0.1 MeV gave R ≈ 1. Moreover, R decreased monotonically with increasing thickness of water medium above the cells for E = 0.01, 1 or 2 MeV due to energy loss of photons in the medium. For E = 0.1 MeV, the monotonic pattern no longer existed due to the dose delivered to the cells by electrons created through photoelectric effect close to the medium-cell boundary. The continuous-energy distributions from the X-Rad 320 Biological Irradiator (voltage = 150 kV) were also studied under three different beam conditioning: (a) F0: no filter used (b) F1: using a 2 mm-thick Al filter, and (c) F2: using a filter made of (1.5 mm Al + 0.25 mm Cu + 0.75 mm Sn), giving mean output photon energies of 47.4, 57.3 and 102 keV, respectively. R varied from ~1.04 to ~1.28 for F0, from ~1.13 to ~1.21 for F1, and was very close to unity for F2.
Chapter 6 described the medium-thickness-dependent proton dosimetry for radiobiological experiments. A calibration method was proposed in the present work to determine the medium-thickness-dependent proton doses absorbed in cellular components (i.e., cellular cytoplasm and nucleus) in radiobiological experiments. Consideration of the dependency on medium thickness was crucial as the linear energy transfer (LET) of protons could rise to a sharp peak (known as the Bragg peak) towards the end of their ranges. Relationships between the calibration coefficient R vs medium-layer thickness were obtained for incident proton energies of 10, 15, 20, 25, 30 and 35 MeV, and for various medium thicknesses up to 5000 µm, where R was defined as the ratio DA/DE, DA was the absorbed proton dose in cellular components, and DE was the absorbed proton dose in a separate radiation detector. In the present work, DA and DE were determined using the MCNPX (Monte Carlo N-Particle eXtended) code version 2.4.0. For lower incident proton energies (i.e., 10, 15 and 20 MeV), formation of Bragg-peak-like features were noticed in their R-vs-medium-layer-thickness relationships, and large R values of >7 and >6 were obtained for cytoplasm and nucleus of cells, respectively, which highlighted the importance of careful consideration of the medium thickness in radiobiological experiments.
Chapter 7 described the conversion coefficients for determination of dispersed photon dose during radiotherapy: NRUrad input code for MCNP. Radiotherapy is a common cancer treatment module, where a certain amount of dose will be delivered to the targeted organ. This is achieved usually by photons generated by linear accelerator units. However, radiation scattering within the patient’s body and the surrounding environment will lead to dose dispersion to healthy tissues which are not targets of the primary radiation. Determination of the dispersed dose would be important for assessing the risk and biological consequences in different organs or tissues. In the present work, the concept of conversion coefficient (F) of the dispersed dose was developed, in which F = (Dd/Dt), where Dd was the dispersed dose in a non-targeted tissue and Dt is the absorbed dose in the targeted tissue. To quantify Dd and Dt, a comprehensive model was developed using the Monte Carlo N-Particle (MCNP) package to simulate the linear accelerator head, the human phantom, the treatment couch and the radiotherapy treatment room. The present work also demonstrated the feasibility and power of parallel computing through the use of the Message Passing Interface (MPI) version of MCNP5.
Chapter 8 gave the conclusion and some potential future works.
