Comparison of Integrated Radiation Transport Models with TEPC Measurements for the Average Quality Factors in Spaceflights

The purpose of this work is to test our theoretical model for the interpretation of radiation data measured in space. During the space missions astronauts are exposed to the complex field of radiation type and kinetic energies from galactic cosmic rays (GCR), trapped protons, and sometimes solar particle events (SPEs). The tissue equivalent proportional counter (TEPC) is a simple time-dependent approach for radiation monitoring for astronauts on board the International Space Station. Another and a newer approach to Microdosimetry is the use of silicon-on-insulator (SOI) technology launched on the MidSTAR-1 mission in low Earth orbit (LEO). In the radiation protection practice, the average quality factor of a radiation field is defined as a function of linear energy transfer (LET), Q(sub ave)(LET). However, TEPC measures the average quality factor as a function of the lineal energy y, Q(sub ave)(y), defined as the average energy deposition in a volume divided by the average chord length of the volume. Lineal energy, y, deviates from LET due to energy straggling, delta-ray escape or entry, and nuclear fragments produced in the detector volume. Monte Carlo track structure simulation was employed to obtain the response of a TEPC irradiated with charged particle for an equivalent site diameter of 1 micron of wall-less counter. The calculated data of the energy absorption in the wall-less counter were compiled for various y values for several ion types at various discrete projectile energy levels. For the simulation of TEPC response from the mixed radiation environments inside a spacecraft, such as, Space Shuttle and International Space Station, the complete microdosimetric TEPC response, f( y, E, Z), were calculated with the Monte Carlo theoretical results by using the first order Lagrangian interpolation for a monovariate function at a given y value (y = 0.1 keV/micron 5000 keV/micron) at any projectile energy level (E = 0.01 MeV/u to 50,000 MeV/u) of each specific radiation type (Z = 1 to 28). Because the anomalous response has been observed at large event sizes in the experiment due to the escape of energy out of sensitive volume by delta-rays and the entry of delta-rays from the high-density wall into the low-density gas-volume cavity, Monte Carlo simulation was also made for the response of a walled-TEPC with wall thickness 2 mm and density 1 g/cm(exp 3). The radius of cavity was set to 6.35 mm and a gas density 7.874 x 10(exp -5) g/cm(exp 3). The response of the walled- and the wall-less counters were compared. The average quality factor Q(sub ave)(y) for trapped protons on STS-89 demonstrated the good agreement between the model calculations and flight TEPC data as shown. Using an integrated space radiation model (this includes the transport codes HZETRN and BRYNTRN, the quantum nuclear interaction model QMSFRG) and the resultant response distribution functions of walled-TEPC from Monte-Carlo track simulations, we compared model calculations with walled-TEPC measurements from NASA missions in LEO and made predictions for the lunar and the Mars missions. The Q(sub ave)(y) values for the trapped or the solar protons ranged from 1.9-2.5. This over-estimates the Qave(LET) values which ranged from 1.4-1.6. Both quantities increase with shield thickness due to nuclear fragmentation. The Q(sub ave)(LET) for the complete GCR spectra was found to be 3.5-4.5, while flight TEPCs measured 2.9-3.4 for Q(sub ave)(y). The GCR values are decreasing with the shield thickness. Our analysis for a proper interpretation of data supports the use of TEPCs for monitoring space radiation environment

Interpretation of TEPC Measurements in Space Flights for Radiation Monitoring

For the proper interpretation of radiation data measured in space, the results of integrated radiation transport models were compared with the tissue equivalent proportional counter (TEPC) measurements. TEPC is a simple, time-dependent approach to radiation monitoring for astronauts on board the International Space Station. Another and a newer approach to microdosimetry is the use of silicon-on-insulator (SOI) technology launched on the MidSTAR-1 mission in low Earth orbit (LEO). In the radiation protection practice, the average quality factor of a radiation field is defined as a function of linear energy transfer (LET), Qave(LET). However, TEPC measures the average quality factor as a function of the lineal energy y, Qave(y), defined as the average energy deposition in a volume divided by the average chord length of the volume. The deviation of y from LET is caused by energy straggling, delta-ray escape or entry, and nuclear fragments produced in the detector volume. The response distribution functions of the wall-less and walled TEPCs were calculated from Monte-Carlo track simulations. Using an integrated space radiation model (which includes the transport codes HZETRN and BRYNTRN, and the quantum nuclear interaction model QMSFRG) and the resultant response distribution functions from Monte-Carlo track simulations, we compared model calculations with the walled-TEPC measurements from NASA missions in LEO and made predictions for the lunar and the Mars missions. Good agreement was found for Qave(y) between the model and measured spectra from past NASA missions. The Qave(y) values for the trapped or the solar protons ranged from 1.9-2.5. This over-estimates the Qave(LET) values which ranged from 1.4-1.6. Both quantities increase with shield thickness due to nuclear fragmentation. The Qave(LET) for the complete GCR spectra was found to be 3.5-4.5, while flight TEPCs measured 2.9-3.4 for Qave(y). The GCR values are decreasing with the shield thickness. Our analysis of the measurements of TEPCs can be used for a proper interpretation of observed data of monitoring the space radiation environment

Microdosimetry simulations of solar protons within a spacecraft

The microdosimetric spectra derived by silicon microdosimeter in a proton radiation field traversing heterogeneous structures were simulated using the GEANT4 toolkit

Solid State Microdosimetry With Heavy Ions for Space Applications

This work provides information pertaining to the performance of Silicon-On-Insulator (SOI) microdosimeters in heavy ion radiation fields. SOI microdosimeters have been previously tested in light ion radiation fields for both space and therapeutic applications, however their response has not been established in high energy, heavy ion radiation fields which are experienced in space. Irradiations were completed at the NASA Space Radiation Laboratory at BNL using 0.6 GeV/u Fe and 1.0 GeV/u Ti ions. Energy deposition and lineal energy spectra were obtained with this device at various depths within a Lucite phantom along the central axis of the beam. The response of which was compared with existing proportional counter data to assess the applicability of SOI microdosimeters to future deployments in space missions

Tumor Response to Radiotherapy is Dependent on Genotype-Associated Mechanisms in vitro and in vivo

Background: We have previously shown that in vitro radiosensitivity of human tumor cells segregate non-randomly into a limited number of groups. Each group associates with a specific genotype. However we have also shown that abrogation of a single gene (p21) in a human tumor cell unexpectedly sensitized xenograft tumors comprised of these cells to radiotherapy while not affecting in vitro cellular radiosensitivity. Therefore in vitro assays alone cannot predict tumor response to radiotherapy. In the current work, we measure in vitro radiosensitivity and in vivo response of their xenograft tumors in a series of human tumor lines that represent the range of radiosensitivity observed in human tumor cells. We also measure response of their xenograft tumors to different radiotherapy protocols. We reduce these data into a simple analytical structure that defines the relationship between tumor response and total dose based on two coefficients that are specific to tumor cell genotype, fraction size and total dose. Methods: We assayed in vitro survival patterns in eight tumor cell lines that vary in cellular radiosensitivity and genotype. We also measured response of their xenograft tumors to four radiotherapy protocols: 8 × 2 Gy; 2 × 5Gy, 1 × 7.5 Gy and 1 × 15 Gy. We analyze these data to derive coefficients that describe both in vitro and in vivo responses. Results: Response of xenografts comprised of human tumor cells to different radiotherapy protocols can be reduced to only two coefficients that represent 1) total cells killed as measured in vitro 2) additional response in vivo not predicted by cell killing. These coefficients segregate with specific genotypes including those most frequently observed in human tumors in the clinic. Coefficients that describe in vitro and in vivo mechanisms can predict tumor response to any radiation protocol based on tumor cell genotype, fraction-size and total dose. Conclusions: We establish an analytical structure that predicts tumor response to radiotherapy based on coefficients that represent in vitro and in vivo responses. Both coefficients are dependent on tumor cell genotype and fraction-size. We identify a novel previously unreported mechanism that sensitizes tumors in vivo; this sensitization varies with tumor cell genotype and fraction size

Tumor response to radiotherapy is dependent on genotype-associated mechanisms in vitro and in vivo

<p>Abstract</p> <p>Background</p> <p>We have previously shown that in vitro radiosensitivity of human tumor cells segregate non-randomly into a limited number of groups. Each group associates with a specific genotype. However we have also shown that abrogation of a single gene (p21) in a human tumor cell unexpectedly sensitized xenograft tumors comprised of these cells to radiotherapy while not affecting in vitro cellular radiosensitivity. Therefore in vitro assays alone cannot predict tumor response to radiotherapy.</p> <p>In the current work, we measure in vitro radiosensitivity and in vivo response of their xenograft tumors in a series of human tumor lines that represent the range of radiosensitivity observed in human tumor cells. We also measure response of their xenograft tumors to different radiotherapy protocols. We reduce these data into a simple analytical structure that defines the relationship between tumor response and total dose based on two coefficients that are specific to tumor cell genotype, fraction size and total dose.</p> <p>Methods</p> <p>We assayed in vitro survival patterns in eight tumor cell lines that vary in cellular radiosensitivity and genotype. We also measured response of their xenograft tumors to four radiotherapy protocols: 8 × 2 Gy; 2 × 5Gy, 1 × 7.5 Gy and 1 × 15 Gy. We analyze these data to derive coefficients that describe both in vitro and in vivo responses.</p> <p>Results</p> <p>Response of xenografts comprised of human tumor cells to different radiotherapy protocols can be reduced to only two coefficients that represent 1) total cells killed as measured in vitro 2) additional response in vivo not predicted by cell killing. These coefficients segregate with specific genotypes including those most frequently observed in human tumors in the clinic. Coefficients that describe in vitro and in vivo mechanisms can predict tumor response to any radiation protocol based on tumor cell genotype, fraction-size and total dose.</p> <p>Conclusions</p> <p>We establish an analytical structure that predicts tumor response to radiotherapy based on coefficients that represent in vitro and in vivo responses. Both coefficients are dependent on tumor cell genotype and fraction-size. We identify a novel previously unreported mechanism that sensitizes tumors in vivo; this sensitization varies with tumor cell genotype and fraction size.</p

On The Development of Biophysical Models for Space Radiation Risk Assessment

Experimental techniques in molecular biology are being applied to study biological risks from space radiation. The use of molecular assays presents a challenge to biophysical models which in the past have relied on descriptions of energy deposition and phenomenological treatments of repair. We describe a biochemical kinetics model of cell cycle control and DNA damage response proteins in order to model cellular responses to radiation exposures. Using models of cyclin-cdk, pRB, E2F's, p53, and GI inhibitors we show that simulations of cell cycle populations and GI arrest can be described by our biochemical approach. We consider radiation damaged DNA as a substrate for signal transduction processes and consider a dose and dose-rate reduction effectiveness factor (DDREF) for protein expression

The Role of Non-Targeted Effects as Mediators in the Biological Effects of Proton Irradiation

In recent years, the hypothesis that non-DNA targets are primary initiators and mediators of the biological effects of ionizing radiation, such as proton beams and heavy ions, has gained much interest. These phenomena have been denoted as non-targeted or bystander effects to distinguish them from the more traditionally studied model that focuses on direct damage to DNA causing chromosomal rearrangements and mutations as causative of most biological endpoints such as cell killing, tissue damage, and cancer. We review cellular and extra-cellular structures and signal transduction pathways that have been implemented in these recent studies. Non-targeted effects of interest include oxidative damage to the cytoplasm and mitochondria, disruption of the extra-cellular matrix, and modification of cytokine signaling including TGF-beta, and gap junction communication. We present an introduction to these targets and pathways, and contrast there role with DNA damage pathways