Dosimetric uncertainties impact on cell survival curve with low energy proton

2020 ◽  
Vol 76 ◽  
pp. 277-284
Author(s):  
Hong Qi Tan ◽  
Wei Yang Calvin Koh ◽  
Eugenia Li Ling Yeo ◽  
Khong Wei Ang ◽  
Dennis Jun Jie Poon ◽  
...  
Keyword(s):  
Cell Survival ◽  
Survival Curve ◽  
Low Energy ◽  
Energy Proton ◽  
Cell Survival Curve

scholarly journals A Boltzmann-Tsallis approach towards cell survival curve in Radiobiology

2019 ◽  
Vol 206 ◽  
pp. 09014
Author(s):  
B.W.Q. Tan ◽  
H.Q. Tan ◽  
A.H. Chan
Keyword(s):  
Statistical Mechanics ◽  
Cell Survival ◽  
Survival Curve ◽  
Phenomenological Approach ◽  
Physical Parameters ◽  
Chain Model ◽  
Nonextensive Statistical Mechanics ◽  
Cell Survival Curve ◽  
New Perspective ◽  
First Time

This paper outlines a phenomenological approach towards cell survival curve at low dose using tools of extensive Statistical Mechanics and nonextensive Statistical Mechanics. An Ising chain model is developed for the cell survival curve and the canonical ensemble formalism based on Boltzmann Gibbs statistic and Tsallis statistic is presented. The resulting cell survival curve shows excellent agreement with the experimental data and the physical parameters from our Tsallis model (N’, q) can be shown to provide clear classification between healthy and cancerous cells. In this paper, we also provides possible biophysical interpretation to the (N’, q) parameters where N’ is representative of the amount of repairable DNA content in the nucleus and q represents the degree of correlation in DNA damage. Overall, this is the first time a Statistical Mechanics approach is used in Radiobiology, and could present a new perspective.

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