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肿瘤位置、电导率分布和组织均匀性对人脑肿瘤治疗场分布的影响:一项计算机建模研究。

Impact of tumor position, conductivity distribution and tissue homogeneity on the distribution of tumor treating fields in a human brain: A computer modeling study.

作者信息

Korshoej Anders Rosendal, Hansen Frederik Lundgaard, Thielscher Axel, von Oettingen Gorm Burckhardt, Sørensen Jens Christian Hedemann

机构信息

Aarhus University Hospital, Department of Neurosurgery, Nørrebrogade 44, Aarhus C, Denmark.

Aarhus University, Department of Clinical Medicine, Palle Juul-Jensens Boulevard 100, Aarhus N, Denmark.

出版信息

PLoS One. 2017 Jun 12;12(6):e0179214. doi: 10.1371/journal.pone.0179214. eCollection 2017.


DOI:10.1371/journal.pone.0179214
PMID:28604803
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5467909/
Abstract

BACKGROUND: Tumor treating fields (TTFields) are increasingly used in the treatment of glioblastoma. TTFields inhibit cancer growth through induction of alternating electrical fields. To optimize TTFields efficacy, it is necessary to understand the factors determining the strength and distribution of TTFields. In this study, we provide simple guiding principles for clinicians to assess the distribution and the local efficacy of TTFields in various clinical scenarios. METHODS: We calculated the TTFields distribution using finite element methods applied to a realistic head model. Dielectric property estimates were taken from the literature. Twentyfour tumors were virtually introduced at locations systematically varied relative to the applied field. In addition, we investigated the impact of central tumor necrosis on the induced field. RESULTS: Local field "hot spots" occurred at the sulcal fundi and in deep tumors embedded in white matter. The field strength was not higher for tumors close to the active electrode. Left/right field directions were generally superior to anterior/posterior directions. Central necrosis focally enhanced the field near tumor boundaries perpendicular to the applied field and introduced significant field non-uniformity within the tumor. CONCLUSIONS: The TTFields distribution is largely determined by local conductivity differences. The well conducting tumor tissue creates a preferred pathway for current flow, which increases the field intensity in the tumor boundaries and surrounding regions perpendicular to the applied field. The cerebrospinal fluid plays a significant role in shaping the current pathways and funnels currents through the ventricles and sulci towards deeper regions, which thereby experience higher fields. Clinicians may apply these principles to better understand how TTFields will affect individual patients and possibly predict where local recurrence may occur. Accurate predictions should, however, be based on patient specific models. Future work is needed to assess the robustness of the presented results towards variations in conductivity.

摘要

背景:肿瘤治疗电场(TTFields)在胶质母细胞瘤治疗中的应用日益广泛。TTFields通过诱导交变电场抑制肿瘤生长。为优化TTFields疗效,有必要了解决定TTFields强度和分布的因素。在本研究中,我们为临床医生提供了简单的指导原则,以评估TTFields在各种临床场景中的分布和局部疗效。 方法:我们使用有限元方法对逼真的头部模型计算TTFields分布。介电特性估计取自文献。在相对于施加电场系统变化的位置虚拟植入24个肿瘤。此外,我们研究了中心肿瘤坏死对感应电场的影响。 结果:局部电场“热点”出现在脑沟底部以及白质中包埋的深部肿瘤处。靠近有源电极的肿瘤处电场强度并不更高。左右电场方向通常优于前后方向。中心坏死在垂直于施加电场的肿瘤边界附近局部增强了电场,并在肿瘤内引入了显著的电场不均匀性。 结论:TTFields分布在很大程度上由局部电导率差异决定。导电性良好的肿瘤组织为电流形成了优先路径,这增加了肿瘤边界及垂直于施加电场的周围区域的场强。脑脊液在塑造电流路径以及将电流通过脑室和脑沟导向更深区域方面发挥着重要作用,从而使这些区域经历更高的电场。临床医生可应用这些原则更好地理解TTFields将如何影响个体患者,并可能预测局部复发可能发生的位置。然而,准确的预测应基于患者特异性模型。未来需要开展工作来评估所呈现结果对电导率变化的稳健性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35ca/5467909/1da390dccec6/pone.0179214.g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35ca/5467909/1da390dccec6/pone.0179214.g009.jpg

相似文献

[1]
Impact of tumor position, conductivity distribution and tissue homogeneity on the distribution of tumor treating fields in a human brain: A computer modeling study.

PLoS One. 2017-6-12

[2]
Importance of electrode position for the distribution of tumor treating fields (TTFields) in a human brain. Identification of effective layouts through systematic analysis of array positions for multiple tumor locations.

PLoS One. 2018-8-22

[3]
The electric field distribution in the brain during TTFields therapy and its dependence on tissue dielectric properties and anatomy: a computational study.

Phys Med Biol. 2015-9-21

[4]
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[5]
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Int J Radiat Oncol Biol Phys. 2015-12-14

[6]
A Review on Tumor-Treating Fields (TTFields): Clinical Implications Inferred From Computational Modeling.

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[7]
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[8]
Simplified realistic human head model for simulating Tumor Treating Fields (TTFields).

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[9]
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[10]
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引用本文的文献

[1]
Survival of a patient with glioblastoma multiforme after undergoing bone flap surgery followed by chemoradiotherapy to maintain tumor-treating fields: A case report.

J Int Med Res. 2025-6

[2]
Tumor Treating Fields and Combination Therapy in Management of Brain Oncology.

Cancers (Basel). 2025-4-2

[3]
A Leadfield-Free Optimization Framework for Transcranially Applied Electric Currents.

bioRxiv. 2024-12-20

[4]
A theoretical study on evaluating brain tumor changes in tumor treating fields therapy by impedance detection.

Front Oncol. 2024-9-4

[5]
Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning.

Sci Rep. 2024-8-21

[6]
Disrupting glioblastoma networks with tumor treating fields (TTFields) in in vitro models.

J Neurooncol. 2024-10

[7]
[Simulation model of tumor-treating fields].

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024-4-25

[8]
Tumor-treating fields dosimetry in glioblastoma: Insights into treatment planning, optimization, and dose-response relationships.

Neurooncol Adv. 2024-3-2

[9]
Body Fluids Modulate Propagation of Tumor Treating Fields.

Adv Radiat Oncol. 2023-7-22

[10]
Modeling of intracranial tumor treating fields for the treatment of complex high-grade gliomas.

Sci Rep. 2023-1-30

本文引用的文献

[1]
Using computational phantoms to improve delivery of Tumor Treating Fields (TTFields) to patients.

Annu Int Conf IEEE Eng Med Biol Soc. 2016-8

[2]
Critical review of the addition of tumor treating fields (TTFields) to the existing standard of care for newly diagnosed glioblastoma patients.

Crit Rev Oncol Hematol. 2017-1-22

[3]
Enhancing Predicted Efficacy of Tumor Treating Fields Therapy of Glioblastoma Using Targeted Surgical Craniectomy: A Computer Modeling Study.

PLoS One. 2016-10-3

[4]
Improving Tumor Treating Fields Treatment Efficacy in Patients With Glioblastoma Using Personalized Array Layouts.

Int J Radiat Oncol Biol Phys. 2015-12-14

[5]
Maintenance Therapy With Tumor-Treating Fields Plus Temozolomide vs Temozolomide Alone for Glioblastoma: A Randomized Clinical Trial.

JAMA. 2015-12-15

[6]
Mitotic Spindle Disruption by Alternating Electric Fields Leads to Improper Chromosome Segregation and Mitotic Catastrophe in Cancer Cells.

Sci Rep. 2015-12-11

[7]
Tumor treating fields: a new standard treatment for glioblastoma?

Curr Opin Neurol. 2015-12

[8]
Tumor treating fields therapy device for glioblastoma: physics and clinical practice considerations.

Expert Rev Med Devices. 2015

[9]
The electric field distribution in the brain during TTFields therapy and its dependence on tissue dielectric properties and anatomy: a computational study.

Phys Med Biol. 2015-9-21

[10]
Computed modeling of alternating electric fields therapy for recurrent glioblastoma.

Cancer Med. 2015-11

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