Abstract
The paper summarizes the analytic and stochastic approaches to radiation induced carcinogenesis among generic cells population. Many important effects were taken into consideration, like chromosomal aberrations induction, bystander effect, adaptive response effect, etc. The results can be simulated in analytical or Monte Carlo forms that show, e.g., a general probability function for a single cell’s cancer transformation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
“BEIR VII Report (Biological Effects of Ionizing Radiation committee). Health risks from exposure to low levels of ionizing radiation”, Board on Radiation Effects Research, Commision on Life Sciences, National Research Council, National Academy Press, Washington (2006).
“Cytogenetic dosimetry: applications in preparedness for and response to radiation emergencies”, IAEA (International Atomic Energy Agency), Safety Standards, Vienna (2011).
M. Avrami, “Kinetics of phase change. II. Transformation-time relations for random distribution of nuclei”, Journal of Chemical Physics 8(2) (1940), 212–224.
M. Avrami, “Kinetics of phase change. III. Granulation, phase change, and microstructure”, Journal of Chemical Physics 9(2) (1941), 177–184.
L.E. Feinendegen, “Low doses of ionizing radiation: relationship between biological benefit and damage induction. A synapsis”, World Journal of Nuclear Medicine 4 (2005).
L.E. Feinendegen, V.P. Bond, and C.A. Sondhaus, “The dual response to low-dose irradiation: induction versus prevention of DNA damage”, in “Biological Effects of Low Dose Radiation”, Elsevier (2000), 3–17.
K.W. Fornalski, “Mechanistic model of the cells irradiation using the stochastic biophysical input”, International Journal of Low Radiation 9(5/6) (2014), 370–395.
K.W. Fornalski, “Biophysical Monte Carlo modelling of irradiated cells”, presentation during LD-RadStats – DoReMi Workshop, CRM, Barcelona, Spain (2015), available at http://www.doremi-noe.net/pdf/events/radstats15/DoReMiRadstats2015_Fornalski.pdf.
K.W. Fornalski, L. Dobrzyński, and M.K. Janiak, “A stochastic Markov model of cellular response to radiation”, Dose-Response 9(4) (2011), 477–496.
S. Gaillard, D. Pusset, S.M. de Toledo, M. Fromm, and E.I. Azzam, “Propagation distance of the \(\propto \)-particle-induced bystander effect: the role of nuclear traversal and gap junction communication”, Radiat Res. 171(5) (2009), 513–520.
A. Knudson, “Mutation and cancer: statistical study of retinoblastoma”, Proc. Natl. Acad. Sci. USA 68(4) (1971), 820–823.
B.E. Leonard, “A review: development of a microdose model for analysis of adaptive response and bystander dose response behavior”, Dose-Response 6 (2008), 113–183.
C. Nordling, “A new theory on cancer-inducing mechanism”, British Journal of Cancer 7(1) (1953), 68–72.
K.M. Prise, M. Folkard, and B.D. Michael, “A review of the bystander effect and its implications for low-dose exposure”, Radiation Protection Dosimetry 104(4) (2003), 347–355.
M.S. Sasaki, “Chromosomal biodosimetry by unfolding a mixed Poisson distribution: a generalized model”, Int. J. Radiat. Biol. 79(2) (2003), 83–97.
K. Sasaki, K. Waku, K. Tsutsumi, A. Itoh, and H. Date, “A simulation study of the radiation-induced bystander effect: modeling with stochastically defined signal reemission”, Computational and Mathematical Methods in Medicine 2012 (2012), 389095.
R.D. Schreiber, J.O. Lloyd, and M.J. Smyth, “Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion”, Science 331 (2011), 1565–1570.
B.R. Scott, J. Hutt, Y. Lin, M.T. Padilla, K.M. Gott, and C.A. Potter, “Biological microdosimetry based on radiation cytotoxicity data”, Radiation Protection Dosimetry 153(4) (2013), 417–424.
M. Stark, “The sandpile model: optimal stress and hormesis”, Dose-Response 10(1) (2012), 66–74.
M. Szłuińska, A.A. Edwards, and D.C. Lloyd, “Statistical methods for biological dosimetry”, Health Protection Agency/Public Health England report no. HPA-RPD-011 (2005).
E.C. Zeeman, “Catastrophe Theory”, Selected Papers 1972–1977. Addison-Wesley Publ. Co. (1977).
Acknowledgements
The authors wish to thank Dr. Yehoshua Socol and Prof. Marek K. Janiak for stimulating discussions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Fornalski, K.W., Dobrzyński, L., Reszczyńska, J. (2017). Modelling of the Radiation Carcinogenesis: The Analytic and Stochastic Approaches. In: Ainsbury, E., Calle, M., Cardis, E., Einbeck, J., Gómez, G., Puig, P. (eds) Extended Abstracts Fall 2015. Trends in Mathematics(), vol 7. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-55639-0_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-55639-0_16
Published:
Publisher Name: Birkhäuser, Cham
Print ISBN: 978-3-319-55638-3
Online ISBN: 978-3-319-55639-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)