TUMOR TREATING FIELDS: MODELING AND A NUMERICAL ALGORITHM

被引:1
|
作者
Shen, Jun [1 ]
Gong, Rongfang [1 ]
Chen, Chunxiao [2 ]
Wang, Liang [2 ]
Lin, Zhe [2 ]
Lo, Catharine w. k. [3 ]
Lu, Ming [4 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Sch Math, Nanjing 211106, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Dept Biomed Engn, Nanjing 211106, Peoples R China
[3] City Univ Hong Kong, Dept Math, Hong Kong, Peoples R China
[4] GuiQian Int Gen Hosp, Dept Radiol, Guiyang 550018, Peoples R China
来源
COMMUNICATIONS ON ANALYSIS AND COMPUTATION | 2024年 / 2卷 / 02期
基金
中国国家自然科学基金;
关键词
Tumor Treating Fields; inverse problem; mathematical modeling; finite element method; particle swarm optimization algorithm; CELLS IN-VITRO; GLIOBLASTOMA; DISRUPTION; TTFIELDS;
D O I
10.3934/cac.2024008
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper investigates the optimal control problem generated in Tumor Treating Fields (TTFields). TTFields is an emerging cancer treatment method with several advantages including the convenience of treatment, fewer side effects, and a better quality of life for patients. Therefore, it holds significant promise for applications in cancer treatments and other fields. In view of such an immense potential, in this work, we are motivated to determine the optimal arrangement of electrodes for TTFields. The paper begins by presenting a comprehensive modeling process for TTFields, followed by the establishment of an optimal control problem that involves finding the optimal configuration of the electrode array. To solve this problem, the particle swarm optimization (PSO) algorithm, which is a type of intelligent algorithm, is employed, and is further improved on to address various situations. Finally, the model is validated and the effectiveness of the PSO algorithm is verified through numerical examples.
引用
收藏
页码:159 / 179
页数:21
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