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Conference paper ยท Journal article

Estimating the Intensity and Anisotropy of Tumor Treating Fields Jsing Singular Value Decomposition. Towards a More Comprehensive Estimation of Anti-tumor Efficacy

From

Aarhus University1

Department of Electrical Engineering, Technical University of Denmark2

Center for Magnetic Resonance, Department of Electrical Engineering, Technical University of Denmark3

Tumor treating fields (TTFields) is an anticancer treatment that inhibits tumor growth with alternating electrical fields. Finite element (FE) methods have been used to estimate the TTFields intensity as a measure of treatment 'dose'. However, TTFields efficacy also depends on field direction and exposure time.

Here we propose a new FE based approach, which uses all these parameters to quantify the average field intensity and the amount of unwanted directional field correlation (fractional anisotropy, FA). The method is based on principal component decomposition of the sequential TTFields over one duty cycle.

Using a realistic head model of a glioblastoma patient, we observed significant unwanted FA in many regions of the brain, which may potentially affect therapeutic efficacy. FA varied between different array layouts and indicated a different order of array performance than predicted from the field intensity.

Tumor resection nullified differences in field distributions between layouts and increased FA considerably. Our results question the rationale for the use of macroscopically orthogonal array layouts to reduce field correlation and rather indicate that arrays should be placed to maximize pathology coverage and field intensity.

The proposed calculation framework has several potential applications, incl. improved treatment planning, technology development, and accurate prognostication models. Future studies are required to validate the method.

Language: English
Publisher: IEEE
Year: 2018
Pages: 4897-4900
Proceedings: 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
ISBN: 1538636468 , 1538636476 , 9781538636466 , 9781538636473 , 153863645X and 9781538636459
ISSN: 15584615 , 1094687x , 26940604 and 1557170x
Types: Conference paper and Journal article
DOI: 10.1109/EMBC.2018.8513440
ORCIDs: Thielscher, Axel and 0000-0003-4285-8171

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