Measuring regional lung ventilation/perfusion ratio using electrical impedance tomography

对于重症监护患者的急性呼吸窘迫综合征(ARDS)的治疗，仔细的机械通气指导是必不可少的。呼吸机治疗必须确保肺泡气体交换，同时避免任何进一步的呼吸机相关的肺损伤。电阻抗断层成像(EIT)是一种非侵入性的成像手段，能够以高时间分辨率实时监测床边的区域肺通气量(V)。然而，由于最佳的肺泡气体交换仅发生在充分通风和充分灌流的肺区，因此使用EIT也可以获得区域肺灌注量(Q)和区域通气量/灌注率(V/Q)。在之前的项目中，开发了一种基于模型的方法，利用EIT和造影剂(Indicator-Based Signal，IBS)来确定Q，并结合V在生理条件下与单光子发射计算机断层扫描(SPECT)进行了验证。此外，还对低剂量造影剂在患者身上的适用性进行了广泛的动物研究。拟议的后续项目侧重于使用IBS确定V/Q。此外，还将研究是否有可能从EIT的搏动性心脏相关信号(CRS)中确定Q。在一项动物研究中，来自EIT的生理和病理V/Q比率将与SPECT进行验证。同时，将开发一个耦合模拟模式来全面研究IBS的起源。基于实验和模拟数据，基于模型的方法将适应病理条件。为了使该方法更接近临床应用，接下来将测试是否也可以在不中断机械通气的情况下从IBS获得Q。为了获得V/Q，将研究是否可以使用机器学习(卷积神经网络，CNN)来优化EIT重构以针对特定问题的解进行优化。最后，以IBS为参照，考察CRS的Q值是否可以改进。

For the treatment of intensive care patients with acute respiratory distress syndrome (ARDS) careful guidance of mechanical ventilation is essential. Ventilation therapy must ensure alveolar gas exchange and at the same time avoid any further ventilator-associated lung damage. Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows real-time monitoring of regional lung ventilation (V) at bedside with high time resolution. However, since optimal alveolar gas exchange only takes place in lung regions that are both adequately ventilated and perfused, it would be highly beneficial to also obtain regional lung perfusion (Q) and regional ventilation to perfusion ratio (V/Q) using EIT. In the previous project, a model-based approach to determine Q using EIT with contrast-agents (indicator-based signal, IBS) was developed and validated in combination with V against single-photon emission computed tomography (SPECT) under physiological condition. In addition, extensive animal studies were performed on the suitability of low-dose contrast agents for use in patients. The proposed follow-up project focuses on the determination of V/Q using the IBS. In addition, it will be investigated whether it is possible to determine Q from the pulsatile, cardiac-related signal (CRS) of EIT. In an animal study, physiological and pathological V/Q ratios from EIT will be validated against SPECT. At the same time, a coupled simulation model will be developed to comprehensively investigate the origin of IBS. Based on experimental and simulation data, the model-based approach will be adapted to pathological conditions. In order to bring the method closer to clinical application, it will then be tested whether it is also possible to obtain Q from the IBS without interruption of mechanical ventilation. In order to obtain V/Q, it will be investigated whether EIT reconstruction can be optimized for problem specific solutions using machine learning (Convolutive Neural Networks, CNN). Finally, it will be examined whether Q from the CRS can be improved using the IBS as a reference.