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Computed modeling of alternating electric fields therapy for recurrent glioblastoma

Tumor treating fields (TTFields) are alternating electric fields frequency tuned to 200 kHz for the treatment of recurrent glioblastoma. We report a patient treated with TTFields and determined the distribution of TTFields intracranially by computerized simulation using co-registered postgadolinium...

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Detalles Bibliográficos
Autores principales: Lok, Edwin, Hua, Van, Wong, Eric T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673996/
https://www.ncbi.nlm.nih.gov/pubmed/26311253
http://dx.doi.org/10.1002/cam4.519
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author Lok, Edwin
Hua, Van
Wong, Eric T
author_facet Lok, Edwin
Hua, Van
Wong, Eric T
author_sort Lok, Edwin
collection PubMed
description Tumor treating fields (TTFields) are alternating electric fields frequency tuned to 200 kHz for the treatment of recurrent glioblastoma. We report a patient treated with TTFields and determined the distribution of TTFields intracranially by computerized simulation using co-registered postgadolinium T1-weighted, T2, and MP RAGE images together with pre-specified conductivity and relative permittivity values for various cerebral structures. The distribution of the electric fields within the brain is inhomogeneous. Higher field intensities were aggregated near the ventricles, particularly at the frontal and occipital horns. The recurred tumor was found distant from the primary glioblastoma and it was located at a site of relatively lower electric field intensity. Future improvement in TTFields treatment may need to take into account the inhomogeneity of the electric field distribution within the brain.
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spelling pubmed-46739962015-12-16 Computed modeling of alternating electric fields therapy for recurrent glioblastoma Lok, Edwin Hua, Van Wong, Eric T Cancer Med Clinical Cancer Research Tumor treating fields (TTFields) are alternating electric fields frequency tuned to 200 kHz for the treatment of recurrent glioblastoma. We report a patient treated with TTFields and determined the distribution of TTFields intracranially by computerized simulation using co-registered postgadolinium T1-weighted, T2, and MP RAGE images together with pre-specified conductivity and relative permittivity values for various cerebral structures. The distribution of the electric fields within the brain is inhomogeneous. Higher field intensities were aggregated near the ventricles, particularly at the frontal and occipital horns. The recurred tumor was found distant from the primary glioblastoma and it was located at a site of relatively lower electric field intensity. Future improvement in TTFields treatment may need to take into account the inhomogeneity of the electric field distribution within the brain. John Wiley & Sons, Ltd 2015-11 2015-08-26 /pmc/articles/PMC4673996/ /pubmed/26311253 http://dx.doi.org/10.1002/cam4.519 Text en © 2015 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Cancer Research
Lok, Edwin
Hua, Van
Wong, Eric T
Computed modeling of alternating electric fields therapy for recurrent glioblastoma
title Computed modeling of alternating electric fields therapy for recurrent glioblastoma
title_full Computed modeling of alternating electric fields therapy for recurrent glioblastoma
title_fullStr Computed modeling of alternating electric fields therapy for recurrent glioblastoma
title_full_unstemmed Computed modeling of alternating electric fields therapy for recurrent glioblastoma
title_short Computed modeling of alternating electric fields therapy for recurrent glioblastoma
title_sort computed modeling of alternating electric fields therapy for recurrent glioblastoma
topic Clinical Cancer Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673996/
https://www.ncbi.nlm.nih.gov/pubmed/26311253
http://dx.doi.org/10.1002/cam4.519
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