Tidal volume monitoring by electrical impedance tomography (EIT) using different regions of interest (ROI): Calibration equations

Abstract

a b s t r a c t A set of calibration equations was previously obtained to transform the lung impedance changes obtained by electrical impedance tomography (EIT), using all frame's elements, into a measurable volume signal. In order to study the goodness of the use of regions of interest (ROI) for lung ventilation monitoring, we considered 6 different ROI to obtain a calibration equation for each area. Our aim was to compare the results, determined by these areas, and those obtained by using all EIT image elements. Two ROI's were defined by those pixels with an impedance change higher than 30% and 70% of the maximum change value. These areas were called P30 and P70, respectively. Two other ROI were defined by bounding two areas by mouse, resembling P30 and P70 regions, which were called M30 and M70, respectively. The remainder was defined by two elliptical areas with an eccentricity of 0.8, and 25 and 32 pixels of mayor axis (E25p and E32p, respectively). Twenty healthy males and 24 chronic obstructive pulmonary disease (COPD) patients were considered. For small region (P30 and M30) we obtained a large dispersion in volume measurement, concluding that small regions are not suitable for monitoring the tidal changes in lung volume even for healthy subjects. The results obtained by the remainder areas, and by using EIT image were similar. Even a slight improvement in data dispersion was obtained by using some ROI. These optimal results, for healthy people, were those corresponding to P70 and M70 (volume dispersion improved from 12% with the whole EIT image to 9% using ROI), and for COPD patients improves volume dispersion from 32% using the whole EIT image to 27% by using E25p. Using not so small ROI, it is possible to estimate the total lung ventilation. IntroductionIn clinical environment, there is nothing good enough to measure and monitor in a non-invasive manner the breathing pattern (BP), especially during large periods of time. The BP monitoring provides information about neuromuscular alterations suffered by patients and assesses organs that regulate breathing [1,2]. The reference method aimed to monitor the BP is the pneumotachometer. However, this device spontaneously modifies the behavior of respiration between 15% and 35% due to the essential use of a mouthpiece and clip-nose [3][4][5][6]. The pneumotachometer is mainly used in exercise stress testing in order to assess the pulmonary functional capacity during exercise. Other alternative method to monitor BP is the respiratory inductance plethysmography (RIP). This equipment is used to estimate lung volume by detecting respiratory movements of chest and abdominal wall. This method has been almost completely abandoned due to calibration problems [7][8][9]. Nowadays, this technique is used to monitor qualitatively respiration in patients with obstructive sleep apnea/hypopnea syndrome. A new experimental method used in clinical environment is the electrical impedance tomography (EIT). EIT is used to image regional impedance distribution in a cross-sectional...

Effects of PEEP on the relationship between tidal volume and total impedance change measured via electrical impedance tomography (EIT)

“…The electrical current flows either side of the electrode plane creating an image area of the lung up to 10 cm in both directions from the electrode plane [5,7]. Impedance change (△Z) has been shown to have a direct relationship with tidal volume (VT) measured via spirometry in healthy people, pigs, small ruminants, dogs and horses with no positive end-tidal expiratory pressures (PEEP) applied [3,[7][8][9][10][11][12][13][14]. This relationship has not been established in cattle and has yet to be challenged with alterations in lung state via the application of PEEP.…”

Optimising mechanical ventilation through model-based methods and automation

“…Real-time information would provide clinicians with immediate indicators of patient-specific condition evolution and how they are responding to treatment, beyond the current, static, snapshot of information available from a ventilator. Incorporation of emerging, non-invasive imaging techniques such as EIT (Balleza-Ordaz, Perez-Alday, Vargas-Luna, & Riu, 2015;Bodenstein, David, & Markstaller, 2009;Gong et al, 2015;Heizmann, Baumgärtner, Zhao, & Möller, 2014;Karsten et al, 2013;Mezidi et al, 2018;Spaeth, Daume, Goebel, Wirth, & Schumann, 2016;Zhao, Fischer, Frerichs, Müller-Lisse, & Möller, 2012;Zhao, Steinmann, Frerichs, Guttmann, & Möller, 2010), into predictive lung models would ensure the localised effects of many lung diseases could be better seen, and treatment could be adjusted accordingly to further optimise patient care. Currently, the most insightful imaging techniques are not available at the bedside due to physical limitations (Chase et al, 2014), which means pulmonary care and outcome is often determined solely based on limited insight from pressure-flow data available from the ventilator.…”

Effects of electrical impedance measuring methods on two-dimensional tomogram recovery of biological tissues

“…Webster, але воно не було томографічним. Із 1990-х років електроімпедансна томографія інтенсивно розвивається (Kim et al, 2004;Balleza-Ordaz et al, 2015;Zhao et al, 2014). Значних успіхів у розробленні медичних застосувань досягнуто в галузі неонатології, пульмонології, онкології, нейрофізіології, а також фізіології рослин.…”