Zhao Zhanqi, Frerichs Inéz, Pulletz Sven, Müller-Lisse Ullrich, Möller Knut
Institute of Technical Medicine, Furtwangen University, Jakob-Kienzle Straße 17, D-78054 VS-Schwenningen, Germany. Department of Radiology, University of Munich, Ziemssenstrasse 1, D-80336 Munich, Germany.
Physiol Meas. 2014 Jun;35(6):1083-93. doi: 10.1088/0967-3334/35/6/1083. Epub 2014 May 20.
Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.
研究了基于不同重建算法的电阻抗断层成像(EIT)图像分析方法。对8例患有急性呼吸窘迫综合征的机械通气患者进行了EIT测量。进行了气道压力逐步增加的操作。EIT原始数据使用以下方法离线重建:(1)滤波反投影(BP);(2)基于线性化牛顿-拉夫逊的德尔格算法(DR);(3)具有圆形正向模型的GREIT(用于EIT的格拉茨共识重建算法)重建算法(GR(C))和(4)具有个体胸廓几何形状的GREIT(GR(T))。根据常规计算机断层扫描图像自动确定个体胸廓轮廓。分别在所得的EIT图像上计算五个指标:(a)潮气与深吸气阻抗变化的比值;(b)左右肺的潮气阻抗变化;(c)重心;(d)全局不均匀性指数;(e)背中部区域的通气延迟。四种重建算法在所有检查指标上均未发现显著差异(p>0.2,Kruskal-Wallis检验)。用于EIT图像重建的检查算法不会影响从EIT图像分析得出的选定指标。用一种重建算法验证的图像指标对其他重建算法也有效。