German Cancer Research Center (DKFZ), Heidelberg, Germany.
Physiol Meas. 2013 Jun;34(6):579-93. doi: 10.1088/0967-3334/34/6/579. Epub 2013 May 29.
Electrical impedance tomography (EIT) estimates an image of conductivity change within a body from stimulation and measurement at body surface electrodes. There is significant interest in EIT for imaging the thorax, as a monitoring tool for lung ventilation. To be useful in this application, we require an understanding of if and when EIT images can produce inaccurate images. In this paper, we study the consequences of the homogeneous background assumption, frequently made in linear image reconstruction, which introduces a mismatch between the reference measurement and the linearization point. We show in simulation and experimental data that the resulting images may contain large and clinically significant errors. A 3D finite element model of thorax conductivity is used to simulate EIT measurements for different heart and lung conductivity, size and position, as well as different amounts of gravitational collapse and ventilation-associated conductivity change. Three common linear EIT reconstruction algorithms are studied. We find that the asymmetric position of the heart can cause EIT images of ventilation to show up to 60% undue bias towards the left lung and that the effect is particularly strong for a ventilation distribution typical of mechanically ventilated patients. The conductivity gradient associated with gravitational lung collapse causes conductivity changes in non-dependent lung to be overestimated by up to 100% with respect to the dependent lung. Eliminating the mismatch by using a realistic conductivity distribution in the forward model of the reconstruction algorithm strongly reduces these undesirable effects. We conclude that subject-specific anatomically accurate forward models should be used in lung EIT and extra care is required when analysing EIT images of subjects whose background conductivity distribution in the lungs is known to be heterogeneous or exhibiting large changes.
电阻抗断层成像（EIT）通过在体表电极处进行刺激和测量，来估计体内的电导率变化图像。EIT 对胸部成像具有重要的应用价值，可作为监测肺部通气的工具。为了在该应用中发挥作用，我们需要了解 EIT 图像是否以及何时会产生不准确的图像。在本文中，我们研究了线性图像重建中经常采用的均匀背景假设所带来的后果，该假设会导致参考测量值与线性化点之间不匹配。我们通过仿真和实验数据表明，由此产生的图像可能包含较大且具有临床意义的误差。我们使用胸部电导率的 3D 有限元模型来模拟不同心脏和肺电导率、大小和位置，以及不同程度的重力塌陷和与通气相关的电导率变化情况下的 EIT 测量。我们研究了三种常见的线性 EIT 重建算法。我们发现，心脏的不对称位置可能导致通气 EIT 图像出现高达 60%的左肺不必要的偏差，并且对于机械通气患者典型的通气分布，这种影响尤其强烈。与重力性肺塌陷相关的电导率梯度会导致非依赖肺的电导率变化相对于依赖肺被高估高达 100%。通过在重建算法的正向模型中使用实际的电导率分布来消除不匹配，可以大大减少这些不良影响。我们得出结论，应在肺部 EIT 中使用基于个体的解剖精确正向模型，并且当分析已知肺部背景电导率分布不均匀或发生较大变化的对象的 EIT 图像时，需要格外小心。
