de Castro Martins Thiago, Sato André Kubagawa, de Moura Fernando Silva, de Camargo Erick Dario León Bueno, Silva Olavo Luppi, Santos Talles Batista Rattis, Zhao Zhanqi, Möeller Knut, Amato Marcelo Brito Passos, Mueller Jennifer L, Lima Raul Gonzalez, de Sales Guerra Tsuzuki Marcos
Computational Geometry Laboratory, Escola Politécnica da Universidade de São Paulo, Brazil.
Universidade Federal do ABC, Center of Engineering, Modeling and Applied Social Sciences, Brazil.
Annu Rev Control. 2019;48:442-471. doi: 10.1016/j.arcontrol.2019.05.002. Epub 2019 May 17.
Electrical Impedance Tomography (EIT) is under fast development, the present paper is a review of some procedures that are contributing to improve spatial resolution and material properties accuracy, admitivitty or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative patients. The use of absolute EIT image may enable the assessment of absolute lung volume, which may significantly improve the clinical acceptance of EIT. The Control Theory, the State Observers more specifically, have a developed theory that can be used for the design and operation of EIT devices. Electrode placement, current injection strategy and electrode electric potential measurements strategy should maximize the number of observable and controllable directions of the state vector space. A non-linear stochastic state observer, the Unscented Kalman Filter, is used directly for the reconstruction of absolute EIT images. Historically, difference images were explored first since they are more stable in the presence of modelling errors. Absolute images require more detailed models of contact impedance, stray capacitance and properly refined finite element mesh where the electric potential gradient is high. Parallelization of the forward program computation is necessary since the solution of the inverse problem often requires frequent solutions of the forward problem. Several reconstruction algorithms benefit by the Bayesian inverse problem approach and the concept of prior information. Anatomic and physiologic information are used to form the prior information. An already tested methodology is presented to build the prior probability density function using an ensemble of CT scans and in vivo impedance measurements. Eight absolute EIT image algorithms are presented.
电阻抗断层成像（EIT）正在快速发展，本文回顾了一些有助于提高空间分辨率、材料特性精度、导纳或阻抗精度的方法。文中介绍了EIT在医学领域的应用，并将其分为三大类：急性呼吸窘迫综合征（ARDS）患者、阻塞性肺病患者和围手术期患者。使用绝对EIT图像可以评估绝对肺容积，这可能会显著提高EIT在临床上的接受度。控制理论，更具体地说是状态观测器，有一套成熟的理论可用于EIT设备的设计和操作。电极放置、电流注入策略和电极电位测量策略应使状态向量空间中可观测和可控方向的数量最大化。一种非线性随机状态观测器——无迹卡尔曼滤波器，直接用于绝对EIT图像的重建。从历史上看，首先探索的是差分图像，因为它们在存在建模误差时更稳定。绝对图像需要更详细的接触阻抗、杂散电容模型以及在电位梯度较高的地方进行适当细化的有限元网格。由于逆问题的求解通常需要频繁求解正问题，因此正问题计算的并行化是必要的。几种重建算法受益于贝叶斯逆问题方法和先验信息的概念。解剖学和生理学信息用于形成先验信息。文中提出了一种已经经过测试的方法，使用一组CT扫描和体内阻抗测量来构建先验概率密度函数。还介绍了八种绝对EIT图像算法。
