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TUMOR TREATING FIELDS: MODELING AND A NUMERICAL ALGORITHM

  • Jun SHEN
  • , Rongfang GONG
  • , Chunxiao CHEN*
  • , Liang WANG
  • , Zhe LIN
  • , Catharine W. K. LO*
  • , Ming LU*
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

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.
Original languageEnglish
Pages (from-to)159-179
JournalCommunications on Analysis and Computation
Volume2
Issue number2
Online publishedMay 2024
DOIs
Publication statusPublished - Jun 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • Tumor Treating Fields
  • inverse problem
  • mathematical modeling
  • finite element method
  • particle swarm optimization algorithm

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