The Woodruff School

SUMMARY

This dissertation describes a Monte Carlo-based simulation study that integrates charged particle track structures and cell nucleus DNA organizations to quantify DNA and chromatin damage as well as the cell survival rate for various radiation types. Geant4-DNA, a detailed Monte Carlo code for particle track simulation at the nanometer scale, was employed for the production of charged particle tracks. The cell nucleus DNA organizations modeled in the study include chromatin domains, chromatin fibers, and chromosome territories. The positioning and orientation of these organizations in a cell nucleus are based on the Monte Carlo method. This study also includes a stochastic method for simulating the production of DNA double strand breaks (DSBs) and DSB misrejoining events, which can be used to generate chromosome aberrations and cell survival curves. In the presented work we are able to characterize differences in the spatial distribution pattern of DSBs produced by low-LET electrons, ultrasoft X-rays, protons, helium ions, and carbon ions. A core element of this Monte Carlo study is that subtle nuances of charged particle interactions and DNA damage are retained. The results include the unique spatial distributions of nanometer scale clusters of energy deposition events as well as the spatial distribution of DSBs for the different radiation types. The spatial distribution of DSBs, in turn, allows the estimate of the number of potential DSB misrejoining events, Chromosome aberrations, and cell survival probability. The stochastic nature of the simulation method allows the cell survival fraction to be estimated on the cell-by-cell basis, reflecting the true nature of radiation-induced cell killing effect. In the presented work we also show that the new radiobiological model may find applications in radiotherapy and radiation protection. In radiotherapy, it can be used to estimate the RBE values for radiotherapy that employs radiation types other than the conventional X-rays (e.g. protons, neutrons, and carbon ions). In radiation protection, it can be used to estimate the radiation weighting factors for the various radiation types.

SUBJECT:	Ph.D. Dissertation Defense

BY:	Brian Lee

TIME:	Thursday, July 20, 2017, 1:30 p.m.

PLACE:	Boggs, 3-47

TITLE:	A MONTE CARLO-BASED SIMULATION STUDY FOR ASSESSING RADIATION-INDUCED DNA DAMAGE AND CELL SURVIVAL

COMMITTEE:	Dr. Chris Wang, Chair (Nuclear and Radiological Engineering) Dr. Eric Elder (Nuclear and Radiological Engineering) Dr. Nolan Hertel (Nuclear and Radiological Engineering) Dr. Yuhong Fan (Biological Sciences) Dr. William Dynan (Biochemistry, Emory University)

SUMMARY This dissertation describes a Monte Carlo-based simulation study that integrates charged particle track structures and cell nucleus DNA organizations to quantify DNA and chromatin damage as well as the cell survival rate for various radiation types. Geant4-DNA, a detailed Monte Carlo code for particle track simulation at the nanometer scale, was employed for the production of charged particle tracks. The cell nucleus DNA organizations modeled in the study include chromatin domains, chromatin fibers, and chromosome territories. The positioning and orientation of these organizations in a cell nucleus are based on the Monte Carlo method. This study also includes a stochastic method for simulating the production of DNA double strand breaks (DSBs) and DSB misrejoining events, which can be used to generate chromosome aberrations and cell survival curves. In the presented work we are able to characterize differences in the spatial distribution pattern of DSBs produced by low-LET electrons, ultrasoft X-rays, protons, helium ions, and carbon ions. A core element of this Monte Carlo study is that subtle nuances of charged particle interactions and DNA damage are retained. The results include the unique spatial distributions of nanometer scale clusters of energy deposition events as well as the spatial distribution of DSBs for the different radiation types. The spatial distribution of DSBs, in turn, allows the estimate of the number of potential DSB misrejoining events, Chromosome aberrations, and cell survival probability. The stochastic nature of the simulation method allows the cell survival fraction to be estimated on the cell-by-cell basis, reflecting the true nature of radiation-induced cell killing effect. In the presented work we also show that the new radiobiological model may find applications in radiotherapy and radiation protection. In radiotherapy, it can be used to estimate the RBE values for radiotherapy that employs radiation types other than the conventional X-rays (e.g. protons, neutrons, and carbon ions). In radiation protection, it can be used to estimate the radiation weighting factors for the various radiation types.