A New Model for Dose-Response Relations in Hadron Therapy: a Statistical Analysis of Hadron Therapy Data
Date
2021
Authors
Mcintyre, Melissa Anne
Editors
Advisors
Kizilersu, Ayse
Thomas, Anthony
Thomas, Anthony
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Abstract
In recent years, hadron therapy has become an increasingly popular cancer treatment
alternative to conventional photon-based radiation. The distinct advantage
of using proton or heavy ion radiation over other treatment modalities (x-rays) is
the depositing of the desired dose directly onto a targeted tumour. This treatment
avoids delivering lethal doses of radiation to the surrounding healthy and potentially
radiation-sensitive tissues. The tissue sparing e ect of hadron therapy signi cantly
improves the quality of life and minimises long-term health side-e ects in cancer
patients from excessive radiation exposure.
Understanding the response of a eukaryotic cell to ionising radiation is of vital
importance in the eld. Many models have been developed to explain the response
of a cell to ionising radiation, all of which are based on the Poisson count process.
The most widely used model in the literature, the Linear-Quadratic model, is no exception.
However, despite its wide use, the Linear-Quadratic model presents serious
problems under statistical analysis and explaining the mid to high linear-energytransfer
(LET) region of experimental data.
In this study, we rst make use of rigorous statistical analyses of experimental
world hadron therapy dose-response data to test the validity range of the Linear-
Quadratic model under di erent radiation exposure and biological conditions. Our
statistical analysis showed that it has a limited range of applicability and is restricted
to the low to mid-LET region. Moreover, we demonstrated that it exhibits
discrepancies under the considered regression analysis.
To understand and explain these discrepancies, we make use of the TOPAS and
Geant4 software toolkits to carry out a series of numerical simulations to study the
dose-response relations by radiating V79 Chinese Hamster cells with a proton beam
for a range of LET.
Our analysis of the simulated data shows that the distribution of lethal damages
per cell is overdispersed in the mid to high-LET range, violating the equidispersion
condition of the Poisson process. However as the LET decreases, an overdispersed
distribution of lethal damages approach to an equidispersed distribution, satisfying the Poisson condition.
To explain the experimental and simulated data better, we proposed a new
stochastic model based on a fractional Poisson count process which converges to
the Poisson count process in the low-LET region. We rigorously tested our newly
proposed model against the experimental and our simulated dose-response data and
found that they are in excellent agreement.
We showed that the distribution of lethal damages can be explained by a fractional
Poisson process signi cantly better than the Poisson count process. The cell
survival dose-response results exhibit a superior agreement with the Mittag-Le er
distribution which corresponds to zero count events of the fractional Poisson process
in all LET ranges for di erent cell lines and radiation types. The Mittag-Le er
distribution predicts the DNA damage yield and therefore the relative biological
e ectiveness extremely accurately. Compared with the Linear-Quadratic model, we
demonstrated that our proposed model is superior.
School/Discipline
School of Physical Sciences
Dissertation Note
Thesis (MPhil) -- University of Adelaide, School of Physical Sciences, 2021
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