Assessment of the unilateral pulmonary function by means of electrical impedance tomography using a reduced electrode set

2004 ◽  
Vol 25 (4) ◽  
pp. 803-813 ◽  
Author(s):  
Roberto E Serrano ◽  
Pere J Riu ◽  
Bruno de Lema ◽  
Pere Casan
2018 ◽  
Vol 63 (6) ◽  
pp. 673-681 ◽  
Author(s):  
Chuong Ngo ◽  
Sarah Spagnesi ◽  
Carlos Munoz ◽  
Sylvia Lehmann ◽  
Thomas Vollmer ◽  
...  

Abstract There is a lack of noninvasive pulmonary function tests which can assess regional information of the lungs. Electrical impedance tomography (EIT) is a radiation-free, non-invasive real-time imaging that provides regional information of ventilation volume regarding the measurement of electrical impedance distribution. Forced oscillation technique (FOT) is a pulmonary function test which is based on the measurement of respiratory mechanical impedance over a frequency range. In this article, we introduce a new measurement approach by combining FOT and EIT, named the oscillatory electrical impedance tomography (oEIT). Our oEIT measurement system consists of a valve-based FOT device, an EIT device, pressure and flow sensors, and a computer fusing the data streams. Measurements were performed on five healthy volunteers at the frequencies 3, 4, 5, 6, 7, 8, 10, 15, and 20 Hz. The measurements suggest that the combination of FOT and EIT is a promising approach. High frequency responses are visible in the derivative of the global impedance index $\Delta {Z_{{\text{eit}}}}(t,{f_{{\text{os}}}}).$ The oEIT signals consist of three main components: forced oscillation, spontaneous breathing, and heart activity. The amplitude of the oscillation component decreases with increasing frequency. The band-pass filtered oEIT signal might be a new tool in regional lung function diagnostics, since local responses to high frequency perturbation could be distinguished between different lung regions.


2002 ◽  
Vol 23 (1) ◽  
pp. 211-220 ◽  
Author(s):  
Roberto E Serrano ◽  
Bruno de Lema ◽  
Oscar Casas ◽  
Teresa Feixas ◽  
Nuria Calaf ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chen Zhu ◽  
Bin Wang ◽  
Lei Li ◽  
Tianzuo Li

This research aimed to study the application of CT images based on deep learning in pulmonary function assessment of patients who underwent laparoscopic surgery under the guidance of electrical impedance tomography (EIT). Sixty patients undergoing laparoscopic surgery were taken as the research subjects, who were randomly labelled as control group and experimental group. Based on deep learning, the empty convolution-combined fully convolutional neural network optimization algorithm (ECFCNN) was proposed, which was adopted to evaluate the pulmonary function of 60 patients and was compared with convolutional neural network (CNN) algorithm. The clarity of the edge contour of the image segmented by ECFCNN was better than that segmented by CNN. Average arterial pressure (MAP) and heart rate (HR) were recorded before induction (T1), 10 min before pneumoperitoneum (T2), 10 min after pneumoperitoneum (T3), 10 min before extubation (T4), and 10 min after extubation (T5), respectively. Oxygenation index (PaO2/FiO2), alveolary-arterial partial pressure of oxygen (A-ADO2), and respiratory index (RI) were recorded. The sharpness of the segmentation image edge contour of the algorithm model in this study was higher than that of the convolutional neural network. Compared with T1, T2-T4 MAP in 2 groups was decreased ( P < 0.05 ). Compared with T1, T2-T5 HR was significantly decreased ( P < 0.05 ). Compared with T2, T5 PaO2/FiO2 in control group was significantly decreased ( P < 0.05 ). Compared with the control group, T5 A-aDO2 was decreased ( P < 0.05 ). To sum up, EIT-guided lung protective ventilation can assess the pulmonary function of patients who underwent laparoscopic surgery, reduce the incidence of atelectasis, and improve postoperative lung oxygenation.


Author(s):  
Bruno Furtado de Moura ◽  
francisco sepulveda ◽  
Jorge Luis Jorge Acevedo ◽  
Wellington Betencurte da Silva ◽  
Rogerio Ramos ◽  
...  

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