多电极结构与机器学习在电穿孔治疗中的肿瘤定位。
Tumor location on electroporation therapies by means of multi-electrode structures and machine learning.
发表日期：2023 Jul 22
作者：
P Briz, B López-Alonso, H Sarnago, J M Burdío, O Lucía
来源：
BIOELECTROCHEMISTRY
摘要：
电穿孔是细胞膜暴露于高脉冲电场下产生的现象，它增加了细胞膜的渗透性。在其他应用领域中，这个现象可以在临床环境中用于肿瘤消融疗法。在此背景下，为了达到最佳效果，方便起见，应将治疗重点放在肿瘤组织上，以最小化副作用。本文开发了一种预处理肿瘤定位方法，目的是能够精确地定位治疗。这通过利用多输出电穿孔发生器和多电极结构进行不同的阻抗测量来实现。数据通过一组独立的人工神经网络进行处理，这些网络通过模拟数据进行训练和测试，并且通过幻影凝胶进行验证。尽管电极数量较标准电阻抗层析成像设备的电极数量较少，但该算法证明了其提供适当的准确度。版权所有 © 2023 作者。由 Elsevier B.V. 发布。保留所有权利。
Electroporation is a phenomenon produced in the cell membrane when it is exposed to high pulsed electric fields that increases its permeability. Among other application fields, this phenomenon can be exploited in a clinical environment for tumor ablation therapies. In this context to achieve optimum results, it is convenient to focus the treatment on the tumor tissue to minimize side effects. In this work, a pre-treatment tumor location method is developed, with the purpose of being able to precisely target the therapy. This is done by taking different impedance measurements with a multi-output electroporation generator in conjunction with a multi-electrode structure. Data are processed by means of a vector of independent artificial neural networks, trained and tested with simulation data, and validated with phantom gels. This algorithm proved to provide suitable accuracy in spite of the low electrode count compared to the number of electrodes of a standard electrical impedance tomography device.Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.