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卵巢癌的肿瘤治疗电场:一项建模研究。

Tumor Treating Fields for Ovarian Carcinoma: A Modeling Study.

作者信息

Lok Edwin, San Pyay, White Victoria, Liang Olivia, Widick Page C, Reddy Sindhu Pisati, Wong Eric T

机构信息

Brain Tumor Center & Neuro-Oncology Unit, Beth Israel Deaconess Medical Center, Boston, Massachusetts.

Department of Radiation Oncology, US Oncology/Signature Healthcare of Brockton, Brockton, Massachusetts.

出版信息

Adv Radiat Oncol. 2021 May 17;6(4):100716. doi: 10.1016/j.adro.2021.100716. eCollection 2021 Jul-Aug.


DOI:10.1016/j.adro.2021.100716
PMID:34409211
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8361065/
Abstract

PURPOSE: Since the inception of tumor treating fields (TTFields) therapy as a Food and Drug Administration-approved treatment with known clinical efficacy against recurrent and newly diagnosed glioblastoma, various in silico modeling studies have been performed in an effort to better understand the distribution of applied electric fields throughout the human body for various malignancies or metastases. METHODS AND MATERIALS: Postacquisition attenuation-corrected positron emission tomography-computed tomography image data sets from 2 patients with ovarian carcinoma were used to fully segment various intrapelvic and intra-abdominal gross anatomic structures. A 3-dimensional finite element mesh model was generated and then solved for the distribution of applied electric fields, rate of energy deposition, and current density at the clinical target volumes (CTVs) and other intrapelvic and intra-abdominal structures. Electric field-volume histograms, specific absorption rate-volume histograms, and current density-volume histograms were generated, by which plan quality metrics were derived from and used to evaluate relative differences in field coverage between models under various conditions. RESULTS: TTFields therapy distribution throughout the pelvis and abdomen was largely heterogeneous, where specifically the field intensity at the CTV was heavily influenced by surrounding anatomic structures as well as its shape and location. The electric conductivity of the CTV had a direct effect on the field strength within itself, as did the position of the arrays on the surface of the pelvis and/or abdomen. CONCLUSION: The combined use of electric field-volume histograms, specific absorption rate-volume histograms, current density-volume histograms, and plan quality metrics enables a personalized method to dosimetrically evaluate patients receiving TTFields therapy for ovarian carcinoma when certain patient- and tumor-specific factors are integrated with the treatment plan.

摘要

目的:自肿瘤治疗电场(TTFields)疗法作为一种经美国食品药品监督管理局批准、对复发性和新诊断的胶质母细胞瘤具有已知临床疗效的治疗方法问世以来,已经进行了各种计算机模拟研究,以更好地了解在各种恶性肿瘤或转移瘤情况下施加的电场在整个人体内的分布情况。 方法和材料:使用来自2例卵巢癌患者的采集后经衰减校正的正电子发射断层扫描-计算机断层扫描图像数据集,对盆腔内和腹腔内的各种大体解剖结构进行完整分割。生成三维有限元网格模型,然后求解临床靶区(CTV)以及其他盆腔内和腹腔内结构处施加的电场分布、能量沉积速率和电流密度。生成电场-体积直方图、比吸收率-体积直方图和电流密度-体积直方图,并由此得出计划质量指标,用于评估不同条件下模型之间的场覆盖相对差异。 结果:TTFields疗法在整个骨盆和腹部的分布在很大程度上是不均匀的,具体而言,CTV处的场强受到周围解剖结构及其形状和位置的严重影响。CTV的电导率对其内部的场强有直接影响,骨盆和/或腹部表面阵列的位置也有同样的影响。 结论:当将某些患者和肿瘤特异性因素与治疗计划相结合时,电场-体积直方图、比吸收率-体积直方图、电流密度-体积直方图和计划质量指标的联合使用能够提供一种个性化方法,用于对接受TTFields疗法治疗卵巢癌的患者进行剂量学评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/88a87bb7d11c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/a6b13e4869a2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/62920c596c53/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/9226d9c012b6/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/88a87bb7d11c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/a6b13e4869a2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/62920c596c53/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/9226d9c012b6/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdb9/8361065/88a87bb7d11c/gr4.jpg

相似文献

[1]
Tumor Treating Fields for Ovarian Carcinoma: A Modeling Study.

Adv Radiat Oncol. 2021-5-17

[2]
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Adv Radiat Oncol. 2022-8-6

[3]
Computational Analysis of Tumor Treating Fields for Non-Small Cell Lung Cancer in Full Thoracic Models.

Adv Radiat Oncol. 2023-2-26

[4]
Analysis of physical characteristics of Tumor Treating Fields for human glioblastoma.

Cancer Med. 2017-5-23

[5]
Insights from Computer Modeling: Analysis of Physical Characteristics of Glioblastoma in Patients Treated with Tumor-Treating Fields

2019

[6]
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

[7]
Combined radiotherapy and concurrent tumor treating fields (TTFields) for glioblastoma: Dosimetric consequences on non-coplanar IMRT as initial results from a phase I trial.

Radiat Oncol. 2020-4-19

[8]
Finite element analysis of Tumor Treating Fields in a patient with posterior fossa glioblastoma.

J Neurooncol. 2020-1-27

[9]
End-to-end workflow for finite element analysis of tumor treating fields in glioblastomas.

Phys Med Biol. 2017-10-12

[10]
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

引用本文的文献

[1]
Catalytic Degradation of Organic Dyes Indicates Anti-Proliferative Effects of Magnetoelectric Nanoparticles.

J Electron Mater. 2025

[2]
Hydrogel and scalp/skin conductivities impact dose from tumor treating fields.

Front Bioeng Biotechnol. 2025-2-24

[3]
Tumor treating fields suppress tumor cell growth and neurologic decline in models of spinal metastases.

JCI Insight. 2024-3-21

[4]
Tumor treating fields (TTFields) for spinal metastasis-The case for bone removal and spinal implants as waveguides to enhance field strength at the target.

Neurooncol Adv. 2024-1-3

[5]
Body Fluids Modulate Propagation of Tumor Treating Fields.

Adv Radiat Oncol. 2023-7-22

[6]
Nanotechnology and Cancer Bioelectricity: Bridging the Gap Between Biology and Translational Medicine.

Adv Sci (Weinh). 2024-1

[7]
A review of tumor treating fields (TTFields): advancements in clinical applications and mechanistic insights.

Radiol Oncol. 2023-9-1

本文引用的文献

[1]
EVALUATION OF SPECIFIC ABSORPTION RATE IN THE FAR-FIELD, NEAR-TO-FAR FIELD AND NEAR-FIELD REGIONS FOR INTEGRATIVE RADIOFREQUENCY EXPOSURE ASSESSMENT.

Radiat Prot Dosimetry. 2020-10-16

[2]
Olaparib Versus Nonplatinum Chemotherapy in Patients With Platinum-Sensitive Relapsed Ovarian Cancer and a Germline BRCA1/2 Mutation (SOLO3): A Randomized Phase III Trial.

J Clin Oncol. 2020-2-19

[3]
Niraparib in Patients with Newly Diagnosed Advanced Ovarian Cancer.

N Engl J Med. 2019-9-28

[4]
Correlation of Tumor Treating Fields Dosimetry to Survival Outcomes in Newly Diagnosed Glioblastoma: A Large-Scale Numerical Simulation-Based Analysis of Data from the Phase 3 EF-14 Randomized Trial.

Int J Radiat Oncol Biol Phys. 2019-4-23

[5]
Niraparib monotherapy for late-line treatment of ovarian cancer (QUADRA): a multicentre, open-label, single-arm, phase 2 trial.

Lancet Oncol. 2019-4-1

[6]
Maintenance Olaparib in Patients with Newly Diagnosed Advanced Ovarian Cancer.

N Engl J Med. 2018-10-21

[7]
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

[8]
Tumor Treating Fields in combination with paclitaxel in recurrent ovarian carcinoma: Results of the INNOVATE pilot study.

Gynecol Oncol. 2018-7-27

[9]
Effect of Tumor-Treating Fields Plus Maintenance Temozolomide vs Maintenance Temozolomide Alone on Survival in Patients With Glioblastoma: A Randomized Clinical Trial.

JAMA. 2017-12-19

[10]
Development of Peritoneal Carcinomatosis in Epithelial Ovarian Cancer: A Review.

J Histochem Cytochem. 2017-11-22

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