Paper
17 March 2008 Preliminary investigation of the inhibitory effects of mechanical stress in tumor growth
Author Affiliations +
Abstract
In the past years different models have been formulated to explain the growth of gliomas in the brain. The most accepted model is based on a reaction-diffusion equation that describes the growth of the tumor as two separate components- a proliferative component and an invasive component. While many improvements have been made to this basic model, the work exploring the factors that naturally inhibit growth is insufficient. It is known that stress fields affect the growth of normal tissue. Due to the rigid skull surrounding the brain, mechanical stress might be an important factor in inhibiting the growth of gliomas. A realistic model of glioma growth would have to take that inhibitory effect into account. In this work a mathematical model based on the reaction-diffusion equation was used to describe tumor growth, and the affect of mechanical stresses caused by the mass effect of tumor cells was studied. An initial tumor cell concentration with a Gaussian distribution was assumed and tumor growth was simulated for two cases- one where growth was solely governed by the reaction-diffusion equation and second where mechanical stress inhibits growth by affecting the diffusivity. All the simulations were performed using the finite difference method. The results of simulations show that the proposed mechanism of inhibition could have a significant affect on tumor growth predictions. This could have implications for varied applications in the imaging field that use growth models, such as registration and model updated surgery.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ishita Garg and Michael I. Miga "Preliminary investigation of the inhibitory effects of mechanical stress in tumor growth", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69182L (17 March 2008); https://doi.org/10.1117/12.773376
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Cited by 17 scholarly publications.
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KEYWORDS
Tumors

Mathematical modeling

Diffusion

Brain

In vitro testing

Tissues

Animal model studies

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