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Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma

Tumor Treating Fields (TTFields) therapy is an approved treatment that has known clinical efficacy against recurrent and newly diagnosed glioblastoma. However, the distribution of the electric fields and the corresponding pattern of energy deposition in the brain are poorly understood. To evaluate t...

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Autores principales: Lok, Edwin, San, Pyay, Hua, Van, Phung, Melissa, Wong, Eric T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5463092/
https://www.ncbi.nlm.nih.gov/pubmed/28544575
http://dx.doi.org/10.1002/cam4.1095
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author Lok, Edwin
San, Pyay
Hua, Van
Phung, Melissa
Wong, Eric T.
author_facet Lok, Edwin
San, Pyay
Hua, Van
Phung, Melissa
Wong, Eric T.
author_sort Lok, Edwin
collection PubMed
description Tumor Treating Fields (TTFields) therapy is an approved treatment that has known clinical efficacy against recurrent and newly diagnosed glioblastoma. However, the distribution of the electric fields and the corresponding pattern of energy deposition in the brain are poorly understood. To evaluate the physical parameters that may influence TTFields, postacquisition MP‐RAGE, T1 and T2 MRI sequences from a responder with a right parietal glioblastoma were anatomically segmented and then solved using finite‐element method to determine the distribution of the electric fields and rate of energy deposition at the gross tumor volume (GTV) and other intracranial structures. Electric field–volume histograms (EVH) and specific absorption rate–volume histograms (SARVH) were constructed to numerically evaluate the relative and/or absolute magnitude volumetric differences between models. The electric field parameters E(AUC), V(E) (150), E(95%), E(50%), and E(20%), as well as the SAR parameters SAR(AUC), V(SAR) (7.5), SAR (95%), SAR (50%), and SAR (20%), facilitated comparisons between models derived from various conditions. Specifically, TTFields at the GTV were influenced by the dielectric characteristics of the adjacent tissues as well as the GTV itself, particularly the presence or absence of a necrotic core. The thickness of the cerebrospinal fluid on the convexity of the brain and the geometry of the tumor were also relevant factors. Finally, the position of the arrays also influenced the electric field distribution and rate of energy deposition in the GTV. Using EVH and SARVH, a personalized approach for TTFields treatment can be developed when various patient‐related and tumor‐related factors are incorporated into the planning procedure.
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spelling pubmed-54630922017-06-09 Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma Lok, Edwin San, Pyay Hua, Van Phung, Melissa Wong, Eric T. Cancer Med Clinical Cancer Research Tumor Treating Fields (TTFields) therapy is an approved treatment that has known clinical efficacy against recurrent and newly diagnosed glioblastoma. However, the distribution of the electric fields and the corresponding pattern of energy deposition in the brain are poorly understood. To evaluate the physical parameters that may influence TTFields, postacquisition MP‐RAGE, T1 and T2 MRI sequences from a responder with a right parietal glioblastoma were anatomically segmented and then solved using finite‐element method to determine the distribution of the electric fields and rate of energy deposition at the gross tumor volume (GTV) and other intracranial structures. Electric field–volume histograms (EVH) and specific absorption rate–volume histograms (SARVH) were constructed to numerically evaluate the relative and/or absolute magnitude volumetric differences between models. The electric field parameters E(AUC), V(E) (150), E(95%), E(50%), and E(20%), as well as the SAR parameters SAR(AUC), V(SAR) (7.5), SAR (95%), SAR (50%), and SAR (20%), facilitated comparisons between models derived from various conditions. Specifically, TTFields at the GTV were influenced by the dielectric characteristics of the adjacent tissues as well as the GTV itself, particularly the presence or absence of a necrotic core. The thickness of the cerebrospinal fluid on the convexity of the brain and the geometry of the tumor were also relevant factors. Finally, the position of the arrays also influenced the electric field distribution and rate of energy deposition in the GTV. Using EVH and SARVH, a personalized approach for TTFields treatment can be developed when various patient‐related and tumor‐related factors are incorporated into the planning procedure. John Wiley and Sons Inc. 2017-05-23 /pmc/articles/PMC5463092/ /pubmed/28544575 http://dx.doi.org/10.1002/cam4.1095 Text en © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Cancer Research
Lok, Edwin
San, Pyay
Hua, Van
Phung, Melissa
Wong, Eric T.
Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma
title Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma
title_full Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma
title_fullStr Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma
title_full_unstemmed Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma
title_short Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma
title_sort analysis of physical characteristics of tumor treating fields for human glioblastoma
topic Clinical Cancer Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5463092/
https://www.ncbi.nlm.nih.gov/pubmed/28544575
http://dx.doi.org/10.1002/cam4.1095
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