Page 43 - 2014 Printable Abstract Book
P. 43
To model the effects of particle linear energy transfer (LET) and hypoxia on cell survival, we used the
Monte Carlo Damage Simulation (MCDS) to estimate the DSB (Σ) and the frequency-mean specific energy
(zF) for human kidney T1 cells exposed to deuterons (2H+) with LET from 5.6-20 keV/μm and to α particles
(4He2+) with LETs from 24.6-200 keV/μm. Estimates of the other three cell-specific RMF model
parameters, which are independent of dose, dose rate and oxygen concentration were obtained from fits
to the cell survival data for 200-250 kVp x-rays. The predictive power of the combined MCDS + RMF models
were then tested against the survival data for the higher LET radiations with no additional fitting of the
measured data. Distributions of absolute error between the low dose and exact RMF model predictions
are not statistically different (paired t-test p > 0.9), suggesting that within this dose and LET range up to
200 keV/mm, the low dose LQ approximation to the RMF model provides equal predictive value.
(S602) Models, Mechanisms and Sources of Uncertainty in the Determination of Particle Relative
Biological Effectiveness. Robert D. Stewart, PhD, University of Washington, Seattle, WA
Particle relative biological effectiveness (RBE) is defined as the ratio of the absorbed dose of a
reference radiation needed to produce the same biological effect as another radiation, such as a high
linear energy transfer (LET) particle. Uncertainties in the quantification of the biological effect (endpoint)
of interest as well as uncertainties associated with the dosimetry of the reference radiation and particle
of interest all have an impact on the determination of particle RBE. Because biological responses are often
a non-linear function of dose and dose rate, particle RBE also depends on the dose and dose rate
(temporal pattern of radiation delivery). Moreover, dose-response functions at the molecular and cellular
levels may differ qualitatively as well as quantitatively from dose-response functions at the multi-cellular
and tissue levels. Is it reasonable to use estimates of particle RBE from in vitro molecular and cellular
experiments to guide the determination of particle RBE for clinical endpoints relevant radiation therapy?
To gain insight into these issues, we'll examine how the fine details of the cell culture geometry impact
(e.g., dose buildup near an air-water interface) on the accurate determination of dose and biological
response. Uncertainties in particle dosimetry associated with physical and biological factors, such as the
size and location of critical cellular and sub-cellular targets, will also be examined as a potential
explanation for some counter-intuitive reports in the literature of an RBE that tends to decrease with
increasing LET above 100 to 150 keV/um. As a test of the hypothesis that particle RBE at the cellular and
tissue levels arise from track structure effects at the molecular level, estimates of fast neutron RBE for 29
clinical endpoints and tissues will be compared to estimates of the neutron RBE derived from
measurements of cell survival in vitro and to estimates of the RBE for double strand break (DSB) induction
from first principle Monte Carlo simulations.
(S603) From Radiobiological Models and Patient-Specific Models of Tumor Growth to Optimized Dosing
Strategies for Each Patient. Kristin Swanson, University of Washington, Seattle, WA
Translating radiation dose into biological effect an. d quantifying the resulting tumor response on
a patient-specific basis in a clinically meaningful way is a challenge in contemporary radiation oncology.
Although dose fields are made patient-specific to limit exposure to organs at risk, the total dose and
fractionation scheme generally are not. Further contributing to this problem, clinical trials do not take into
account differential radiation sensitivity between patients, and may be unintentionally selecting patients
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Monte Carlo Damage Simulation (MCDS) to estimate the DSB (Σ) and the frequency-mean specific energy
(zF) for human kidney T1 cells exposed to deuterons (2H+) with LET from 5.6-20 keV/μm and to α particles
(4He2+) with LETs from 24.6-200 keV/μm. Estimates of the other three cell-specific RMF model
parameters, which are independent of dose, dose rate and oxygen concentration were obtained from fits
to the cell survival data for 200-250 kVp x-rays. The predictive power of the combined MCDS + RMF models
were then tested against the survival data for the higher LET radiations with no additional fitting of the
measured data. Distributions of absolute error between the low dose and exact RMF model predictions
are not statistically different (paired t-test p > 0.9), suggesting that within this dose and LET range up to
200 keV/mm, the low dose LQ approximation to the RMF model provides equal predictive value.
(S602) Models, Mechanisms and Sources of Uncertainty in the Determination of Particle Relative
Biological Effectiveness. Robert D. Stewart, PhD, University of Washington, Seattle, WA
Particle relative biological effectiveness (RBE) is defined as the ratio of the absorbed dose of a
reference radiation needed to produce the same biological effect as another radiation, such as a high
linear energy transfer (LET) particle. Uncertainties in the quantification of the biological effect (endpoint)
of interest as well as uncertainties associated with the dosimetry of the reference radiation and particle
of interest all have an impact on the determination of particle RBE. Because biological responses are often
a non-linear function of dose and dose rate, particle RBE also depends on the dose and dose rate
(temporal pattern of radiation delivery). Moreover, dose-response functions at the molecular and cellular
levels may differ qualitatively as well as quantitatively from dose-response functions at the multi-cellular
and tissue levels. Is it reasonable to use estimates of particle RBE from in vitro molecular and cellular
experiments to guide the determination of particle RBE for clinical endpoints relevant radiation therapy?
To gain insight into these issues, we'll examine how the fine details of the cell culture geometry impact
(e.g., dose buildup near an air-water interface) on the accurate determination of dose and biological
response. Uncertainties in particle dosimetry associated with physical and biological factors, such as the
size and location of critical cellular and sub-cellular targets, will also be examined as a potential
explanation for some counter-intuitive reports in the literature of an RBE that tends to decrease with
increasing LET above 100 to 150 keV/um. As a test of the hypothesis that particle RBE at the cellular and
tissue levels arise from track structure effects at the molecular level, estimates of fast neutron RBE for 29
clinical endpoints and tissues will be compared to estimates of the neutron RBE derived from
measurements of cell survival in vitro and to estimates of the RBE for double strand break (DSB) induction
from first principle Monte Carlo simulations.
(S603) From Radiobiological Models and Patient-Specific Models of Tumor Growth to Optimized Dosing
Strategies for Each Patient. Kristin Swanson, University of Washington, Seattle, WA
Translating radiation dose into biological effect an. d quantifying the resulting tumor response on
a patient-specific basis in a clinically meaningful way is a challenge in contemporary radiation oncology.
Although dose fields are made patient-specific to limit exposure to organs at risk, the total dose and
fractionation scheme generally are not. Further contributing to this problem, clinical trials do not take into
account differential radiation sensitivity between patients, and may be unintentionally selecting patients
41 | P a g e
