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Comparison of different methods to define regions of interest for evaluation of regional lung ventilation by EIT

机译:通过EIT评估感兴趣区域以评估局部肺通气的不同方法的比较

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The measurement of regional lung ventilation by electrical impedance tomography (EIT) has been evaluated in many experimental studies. However, EIT is not routinely used in a clinical setting, which is attributable to the fact that a convenient concept for how to quantify the EIT data is missing. The definition of region of interest (ROI) is an essential point in the data analysis. To date, there are only limited data available on the different approaches to ROI definition to evaluate regional lung ventilation by EIT. For this survey we examined ten patients (mean age +/- SD: 60 +/- 10 years) under controlled ventilation. Regional tidal Volumes were quantified as pixel values of inspiratory-to-expiratory impedance differences and four types of ROIs were subsequently applied. The definition of ROI contours was based on the calculation of the pixel values of (1) standard deviation from each pixel set of impedance data and (2) the regression coefficient from linear regression equations between the individual local (pixel) and average (whole scan) impedance signals. Additionally, arbitrary ROIs (four quadrants and four anteroposterior segments of equal height) were used. Our results indicate that both approaches to ROI definition using statistical parameters are Suitable when impedance signals with high sensitivity to ventilation-related phenomena are to be analyzed. The definition of the ROI contour as 20-35% of the maximum standard deviation or regression coefficient is recommended. Simple segmental ROIs are less convenient because of the low ventilation-related signal component in the dorsal region.
机译:在许多实验研究中已经评估了通过电阻抗断层扫描(EIT)对局部肺通气的测量。但是,EIT在临床环境中并不是常规使用的,这是由于缺少用于量化EIT数据的方便概念的事实。感兴趣区域(ROI)的定义是数据分析的关键点。迄今为止,只有很少的数据可用以定义ROI的不同方法来评估EIT对区域肺通气的影响。在这项调查中,我们检查了十名在受控通气下的患者(平均年龄+/- SD:60 +/- 10岁)。区域潮气量被量化为吸气与呼气阻抗差异的像素值,随后应用了四种类型的ROI。 ROI轮廓的定义基于以下像素值的计算:(1)每个阻抗数据像素组的标准差;(2)各个局部(像素)和平均值(整个扫描)之间的线性回归方程式的回归系数)阻抗信号。另外,使用了任意的ROI(四个象限和四个高度相等的前后节)。我们的结果表明,当要分析对通风相关现象具有高灵敏度的阻抗信号时,两种使用统计参数定义ROI的方法均适用。建议将ROI轮廓的定义定义为最大标准偏差或回归系数的20-35%。由于背部区域中与通气相关的信号分量较低,因此简单的分段ROI不太方便。

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