Chapter 7: Biomathematical engineering of cell renewal systems: Modeling of radiogenic responses induced by fractionated irradiation in malignant and normal tissue

Abstract

The aim of this contribution is to outline how methods of system analysis, control theory and computer science can be applied to simulate malignant and normal cell growth and to optimize cancer treatment. Based on biological observations and cell kinetic data, our group has constructed three types of computer models: 1) A cell cycle model describing the spatial (3D) and temporal growth of tumor spheroids; 2) A compartment model describing the growth of rapidly proliferating normal cells; 3) A compartment model simulating slowly proliferating normal tissues. These growth models have been extended by an irradiation model based on the linear-quadratic survival function. Different clinical fractionation schemes (standard-, super-, hyperfractionation and weekly high single dose) have been applied to the tissues mentioned above. The simulation results show that in the case of irradiating a rapidly growing tumor spheroid the hyperfractionation (3 x 1-1.5 Gy per day) leads to a particularly good anti-tumor effectiveness. On the other hand, the radiogenic response of rapidly growing normal tissue to a hyperfractionated treatment schedule is severe. The same result is observed when simulating the late reaction on slowly growing parenchymal tissue. Therefore, this therapeutic modality is ensured only if the overall dose is reduced from DTOTAL = 60 Gy to DTOTAL = 50 Gy.(ABSTRACT TRUNCATED AT 250 WORDS)

A four-dimensional simulation model of tumour response to radiotherapy in vivo: parametric validation considering radiosensitivity, genetic profile and fractionation

“…An exception is the Wasserman et al (1996) model, but this was a two-dimensional model of untreated tumour growth mainly focused on the material properties of the tumour and normal tissue. In addition, only in the in vitro models developed by Duechting et al (1992Duechting et al ( , 1995 is there an explicit passage of the cells through the subsequent phases of the cell cycle. This is of particular importance when considering the effect of radiation therapy (or chemotherapy) on the ultimate fate of cells, since this effect is considered to be phasespecific.…”

“…The developed models involved small tumour spheroids with a diameter of about 1 mm and a single-cell cubic lattice was used. In the papers Stamatakos et al (1998Stamatakos et al ( , 2000Stamatakos et al ( , 2001b the authors presented substantial advances in the approach of Duechting et al (1995), including high performance computing and virtual reality techniques in order to visualize both the external surface and the internal structure of a dynamic tumour. Qi et al (1993) proposed a two-dimensional (2D) cellular automaton tumour growth model that reproduced the Gompertzian growth of a tumour.…”

“…In the following paragraphs some representative modelling efforts of particular interest are presented. Duechting et al (1992Duechting et al ( , 1995 developed 3D simulation models of in vitro tumour growth and response to radiation therapy by combining system analysis, control theory, and cellular automata techniques. These approaches used a control model describing the passage of tumour cells through the successive phases of the cell cycle and the linear-quadratic model to compute the number of cells hit by irradiation.…”

Low-Dose Hypersensitivity and Bystander Effect are Not Mutually Exclusive in A549 Lung Carcinoma Cells after Irradiation with Charged Particles

“…Some simplified cell cycle models, involving no checkpoint and assuming constant phase duration were used in some tumour models (Dionysiou et al, ,2006Duchting et al, 1995;Duchting and Vogelsaenger, 1985); these works focused on tumour growth and tumour response to therapy. Some tumour models of tumour interaction with the environment included the quiescent state (Alarcon et al, 2004;Antipas et al, 2004).…”

Monte Carlo radiotherapy simulations of accelerated repopulation and reoxygenation for hypoxic head and neck cancer

“…Stochastic computer tumour models were first developed in the early 1980s and 1990s by groups Donaghey et al, Duechting and Vogelsaenger, Smolle and Stettner, and Kocher [16][17][18][19][20]. These were the first models to peruse individual (or grouped) cell division using Monte Carlo methods, to grow a tumour and simulate radiotherapy, and in some cases start to implement oxygenation-related parameters.…”