TWO NUMERICAL SOLUTIONS FOR SOLVING A MATHEMATICAL MODEL OF THE AVASCULAR TUMOR GROWTH

被引:0
|
作者
Korkut, Sila Ovgu [1 ,2 ]
Karabas, Neslisah Imamoglu [3 ]
Basbinar, Yasemin [2 ]
机构
[1] Izmir Katip Celebi Univ, Dept Appl Math & Stat, Izmir, Turkey
[2] Dokuz Eylul Univ, Inst Oncol, Dept Translat Oncol, Izmir, Turkey
[3] Izmir Inst High Technol, Dept Math, Izmir, Turkey
来源
关键词
Avascular tumor growth; numerical simulation; mathematical biology; three-stage strongly-stability preserving Runge-Kutta method; 4th-order Runge-Kutta Method;
D O I
10.30621/jbachs.957601
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective: Cancer which is one of the most challenging health problems overall the world is composed of various processes: tumorigenesis, angiogenesis, and metastasis. Attempting to understand the truth behind this complicated disease is one of the common objectives of many experts and researchers from different fields. To provide deeper insights any prognostic and/or diagnostic scientific contribution to this topic is so crucial. In this study, the avascular tumor growth model which is the earliest stage of tumor growth is taken into account from a mathematical point of view. The main aim is to solve the mathematical model of avascular tumor growth numerically. Methods: This study has focused on the numerical solution of the continuum mathematical model of the avascular tumor growth described by Sharrett and Chaplin. Unlike the existing recent literature, the study has focused on the methods for the temporal domain. To obtain the numerical schemes the central difference method has been used in the spatial coordinates. This discretization technique has reduced the main partial differential equation into an ordinary differential equation which will be solved successively by two alternative techniques: the 4th order Runge-Kutta method (RK4) and the three-stage strongly-stability preserving Runge-Kutta method (SSP-RK3). Results: The model has been solved by the proposed methods. The numerical results are discussed in both mathematical and biological angles. The biological compatibility of the methods is depicted in various figures. Besides biological outputs, the accuracies of the methods have been listed from a mathematical point of view. Furthermore, the rate of convergence of the proposed methods has also been discussed computationally. Conclusion: All recorded results are evidence that the proposed schemes are applicable for solving such models. Moreover, all exhibited figures have proved the biological compatibility of the methods. It is observed that the quiescent cells which are one of the most mysterious cells in clinics tend to become proliferative for the selected parameters.
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收藏
页码:156 / 164
页数:9
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