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  A review on Tumor Treating Fields (TTFields): Clinical implications inferred from computational modeling

Wenger, C., Miranda, P., Salvador, R., Thielscher, A., & Bomzon, Z. (2019). A review on Tumor Treating Fields (TTFields): Clinical implications inferred from computational modeling. IEEE Reviews in Biomedical Engineering, 11, 195-207. doi:10.1109/RBME.2017.2765282.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-7CFC-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0002-B9FE-0
Genre: Journal Article

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Wenger, C, Author
Miranda, P, Author
Salvador, R, Author
Thielscher, A1, 2, Author              
Bomzon, Z, Author
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Tumor Treating Fields (TTFields) are a cancer treatment modality that uses alternating electric fields of intermediate frequency (~100-500 kHz) and low intensity (1-3 V/cm) to disrupt cell division. TTFields are delivered by transducer arrays placed on the skin close to the tumor and act regionally and non-invasively to inhibit tumor growth. TTFields therapy is FDA approved for the treatment of glioblastoma multiforme, the most common and aggressive primary human brain cancer. Clinical trials testing the safety and efficacy of TTFields for other solid tumor types are underway. The objective of this article is to review computational approaches used to characterize TTFields. The review covers studies of the macroscopic spatial distribution of TTFields generated in the human head, and of the microscopic field distribution in tumor cells. In addition, pre-clinical and clinical findings related to TTFields and principles of its operation are summarized. Particular emphasis is put on outlining the potential clinical value inferred from computational modeling.

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 Dates: 2018-022019-01
 Publication Status: Published in print
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 Rev. Method: -
 Identifiers: DOI: 10.1109/RBME.2017.2765282
BibTex Citekey: WengerMSTB2018
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Title: IEEE Reviews in Biomedical Engineering
Source Genre: Journal
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Pages: - Volume / Issue: 11 Sequence Number: - Start / End Page: 195 - 207 Identifier: -