Optimizing Assessment Method For Pulmonary Ventilation And Perfusion Under Mechanical Ventilation With Electrical Impedance Tomography

The lung is the organ for gas exchange,and an abundant gas exchange requires adequate pulmonary ventilation and perfusion.So doctors need to keep a close eye on the situation of the lung ventilation and perfusion of critically ill patients in the process of mechanical ventilation treatment.The traditional imaging methods can meet the needs of diagnosis and evaluation,but they are not suitable for the bedside monitoring and evaluation of ventilated patients because of the radiation and bulkiness.Electriacl impedance tomography(EIT)is a portable,non-invasive,non-radiative and real-time imaging method,it images the distribution or variation of electrical impedance inside organisms,and as a result EIT can be suitable for the bedside evaluation of pulmonary ventilation and perfusion under mechanical ventilation.This thesis focused on the optimization of EIT assessment method for pulmonary ventilation and perfusion under mechanical ventilation.The main contents are as follows:Firstly,an EIT method for evaluating the purmonary ventilation region based on impedance compliance is optimized by avoiding calculating the impedance compliance by single platform fressure value.Then the EIT data of 6 piglets with acute respiratory distress syndrome model were processed by the original and optimized method.The corresponding results were compared with data obtained with computed tomography(CT).The relative error of overdistension ratio is reduced by 24.36±18.29% and that of collapse ratio is reduced by 16.41±19.18% after optimization,which indicated that the optimization in this thesis for the commonly used method based on impedance compliance is effective relatively.Secondly,two EIT methods for evaluating purmonary perfusion distribution were optimized.The method based on maximum slope calculates the slope of impedance decreases after saline injection,instead of fitting the gamma curve.The method based on non-negative matrix factorization automatically selects the initial base vector for iteration,instead of manually selection.EIT data of 7 postoperative patients with pulmonary embolism and 7 postoperative patients with healthy lung were processed by two original methods and two optimized methods.The results from two optimized methods are similar to the results from two original methods respectively.Optimization of the method in this thesis based on maximum slope and non-negative matrix factorization was relatively effective because the two optimized methods reduce the calculation time and manual processes obviously.Thirdly,the concept of EIT pulmonary ventilation / perfusion matching distribution image and the index of over-ventilation and over-perfusion ratio are proposed in this paper to evaluate the spatial matching of pulmonary ventilation and perfusion.The average overventilation and over-perfusion ratio was 29.00 ± 7.31% and 25.21 ± 8.80% in 7 patients with pulmonary embolism.That in 7 patients with healthy lung was 12.44 ± 9.86% and 13.01 ± 8.18%(over-ventilation and over-perfusion ratio,respectively).Over-ventilation and overperfusion ratio was significantly higher in pulmonary embolism group(P < 0.05),which suggested that these two indices proposed in this paper can be used to calculate the spatial matching of pulmonary ventilation / perfusion.