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Application of the Taguchi method to explore a robust condition of tumor-treating field treatment
Tumor-treating fields have potential as minimally invasive cancer treatment. This study aimed to explore the optimum tumor-treating field conditions that minimize unpredicted variations in therapeutic outcomes resulting from differences in cell size and electrical properties. The electric field conc...
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Published in: | PloS one 2022-01, Vol.17 (1), p.e0262133-e0262133 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Tumor-treating fields have potential as minimally invasive cancer treatment. This study aimed to explore the optimum tumor-treating field conditions that minimize unpredicted variations in therapeutic outcomes resulting from differences in cell size and electrical properties. The electric field concentration that induces a dielectrophoretic force near the division plane of a mitotic cell was calculated by finite element analysis for 144 cases, based on different combinations of six noise factors associated with cells and four controllable factors including frequency, as determined by the Taguchi method. Changing the frequency from 200 to 400 kHz strongly increased robustness in producing a dielectrophoretic force, irrespective of noise factors. However, this frequency change reduced the force magnitude, which can be increased by simply applying a higher voltage. Based on additional simulations that considered this trade-off effect, a frequency of 300 kHz is recommended for a robust TTF treatment with allowable variations. The dielectrophoretic force was almost independent of the angle of applied electric field deviated from the most effective direction by ±20 degrees. Furthermore, increased robustness was observed for extracellular fluid with higher conductivity and permittivity. The Taguchi method was useful for identifying robust tumor-treating field therapy conditions from a considerably small number of replicated simulations. |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0262133 |