Modeling of tumor growth: Preliminary developments

Abstract

The aim of this work is modeling the growth of three-dimensional tissue lesions, whose models and X-ray images are of crucial interest in research activities dedicated to improving diagnostic imaging of the mammary gland. The starting point is to model a section of a human tissue as composed of cells with anatomically true dimensions and location. The modelled healthy tissue is initially visualized and then the user triggers the lesion growth. The focus of the software application is the growing process of the tumor formation modelled as a process of gradually conversion of neighboring healthy cells to abnormal such. As a consequence, the healthy cells undergo transformations and change their properties to abnormal ones. The geometrical primitives used to model the cells are spheres. The sphere is a quadric surface and is easily visualized by exploiting the OpenGL library. The program is written in the C++ programming language and run under Windows platform. The application starts with the initialization of a tissue segment, approximated as a parallelepiped with a size, set by the user and filled with healthy cells with a specific radius (6 μm). One of these cells is then randomly sampled to become abnormal and the abnormal process begins. The cells when turning their properties to cancerous are also visualized in the three-dimensional space where they can be examined closely. The modeled tumor formations are intended for use in X-ray imaging research. Both, computational models and images are dedicated for developing of CAD applications for cancer detection and characterising, for development of machine learning algorithms to classify human breast tissues, as well as to speed up the development and optimization of new diagnostic procedures based on X-rays. Acknowledgements This research is supported by the Bulgarian National Science Fund under grant agreement DN17/2. This project also has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 692097.