Volume 18, Issue 4 (8-2018)
Modares Mechanical Engineering 2018, 18(4): 71-78 |
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Meghdadi N, Niroomand-Oscuii H, Soltani M. Investigation of mass effect and reaction terms on the prediction of brain tumor growth by using mathematical model based on MRIs. Modares Mechanical Engineering 2018; 18 (4) :71-78
URL: http://mme.modares.ac.ir/article-15-9564-en.html
URL: http://mme.modares.ac.ir/article-15-9564-en.html
1- Sahand University of Technology, PhD student
2- Sahand University of Technology
3- K. N. Toosi University of Technology
2- Sahand University of Technology
3- K. N. Toosi University of Technology
Abstract: (5668 Views)
Cancer is one of the main causes of mortality and morbidity worldwide. Using a single treatment plan for all of the patients is not efficient due to the biological heterogeneity in the individuals. In order to personalize the therapy plan, tumors behavior in each patient must be understood. For this purpose clinical information of the patients are used. Mathematical modeling has gained significant interest in tumor growth investigations, due to its higher flexibility than the other methods. Mass effect and the reaction terms are the key parameters that are investigated in this paper. This is the first time that the effects of these parameters are considered in brain tumor growth modeling and there are few researches that have used only MR images in this area. The mathematical models are used for predicting the growth of brain tumors based on personal MRIs and introducing intracellular fraction into the model. Results of the comparisons show that considering the mass effect in the growth model would improve the prediction. Furthermore, it is necessary to define the optimum formulation for reaction term according to patients' medical information, to be used in the personalized model of tumor growth prediction. The represented approach can be used as a basis for personalizing the therapy plan in patients with brain tumors.
Article Type: Research Article |
Subject:
Aerospace Structures
Received: 2018/01/6 | Accepted: 2018/02/18 | Published: 2018/03/3
Received: 2018/01/6 | Accepted: 2018/02/18 | Published: 2018/03/3
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