Biological Computer Modeling / Biological Computer Simulation
Seyed Hojat Sabzpoushan; Fateme Pourhasanzade
Volume 11, Issue 1 , May 2017, , Pages 1-18
Abstract
In this paper, a new method is proposed for slowing down avascular tumor growth. Our method is established on an agent based avascular tumor growth model (ABM). The model is based on biological assumptions with regard to the immune system interactions. The model parameters are fitted in compatability ...
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In this paper, a new method is proposed for slowing down avascular tumor growth. Our method is established on an agent based avascular tumor growth model (ABM). The model is based on biological assumptions with regard to the immune system interactions. The model parameters are fitted in compatability with cancer biology using in vivo expremental data. The immune cells recruitment, which usually occur after that tumor cells are identified, are also considered in ABM model. The results show that the proposed model not only is able to simulate the tumor growth graphically, but also the in vivo tumor growth quantitatively and qualitatively. Besides, the model proposes a new idea for slowing down the tumor growth considering two types of prolaiferative tumor cells, i.e. the tumor will grow slowly if the division probability of the proliferative tumor cells depends on the microenvironmental conditions. The proposed idea has been validated using an in silico simulation.
Biological Computer Modeling / Biological Computer Simulation
Fateme Pourhasan Zade; Seyed Hojat Sabzpoushan; Ali Mohammad Alizade; Ebrahim Esmati
Volume 10, Issue 2 , August 2016, , Pages 99-112
Abstract
Cancer is the third leading cause of death in Iran after cardiac diseases and car accidents. Mathematical and computational models are great help to better understand cancer related phenomena. It may even improve common therapies or introduce new therapies. In this paper, a new multiscale cellular automata ...
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Cancer is the third leading cause of death in Iran after cardiac diseases and car accidents. Mathematical and computational models are great help to better understand cancer related phenomena. It may even improve common therapies or introduce new therapies. In this paper, a new multiscale cellular automata model of tumor growth based on the tumor micro-environment is introduced. Two separate square lattices are presumed for metabolic and cellular spaces. One of the following four states can be devoted to each cell in the cellular lattice: proliferating cancer, non- proliferating cancer, necrotic, and normal cells. Changing the cell's state and tumor growth is discussed in this lattice. However, production/consumption, and the diffusion of nutrients (oxygen and glucose) and also waste products including lactic acid are studied in the metabolic lattice. In this study, we determined the stochastic rules of altering the states of each cell based on the concentration rates of nutrients and lactic acid. The growth fraction and necrotic fraction were used as output parameters beside a 2-D graphical display of growth. The changes in the level of nutrients in the metabolic lattice and the effect of acidity on the growth of tumor have been reported in this paper. Our simulations faithfully reproduce the in vivo experimental observations reported for cholangiocarcinoma.
