Background: Electrical impedance measurements have become an accepted tool for monitoring intracardiac radio frequency ablation. Recently, the long-established generator impedance was joined by novel local impedance measurement capabilities with all electrical circuit terminals being accommodated within the catheter. Objective: This work aims at in silico quantification of distinct influencing factors that have remained challenges due to the lack of ground truth knowledge and the superposition of effects in clinical settings. Methods: We introduced a highly detailed in silico model of two local impedance enabled catheters, namely IntellaNav MiFi OI and IntellaNav Stablepoint, embedded in a series of clinically relevant environments. Assigning material and frequency specific conductivities and subsequently calculating the spread of the electrical field with the finite element method yielded in silico local impedances. The in silico model was validated by comparison to in vitro measurements of standardized sodium chloride solutions. We then investigated the effect of the withdrawal of the catheter into the transseptal sheath, catheter-tissue interaction, insertion of the catheter into pulmonary veins, and catheter irrigation. Results: All simulated setups were in line with in vitro experiments and in human measurements and gave detailed insight into determinants of local impedance changes as well as the relation between values measured with two different devices. Conclusion: The in silico environment proved to be capable of resembling clinical scenarios and quantifying local impedance changes. Significance: The tool can assists the interpretation of measurements in humans and has the potential to support future catheter development.

BACKGROUND Variable ventilation recruits alveoli in atelectatic lungs, but it is unknown how it compares with conventional recruitment manoeuvres. OBJECTIVES To test whether mechanical ventilation with variable tidal volumes and conventional recruitment manoeuvres have comparable effects on lung function. DESIGN Randomised crossover study. SETTING University hospital research facility. ANIMALS Eleven juvenile mechanically ventilated pigs with atelectasis created by saline lung lavage. INTERVENTIONS Lung recruitment was performed using two strategies, both with an individualised optimal positive-end expiratory pressure (PEEP) associated with the best respiratory system elastance during a decremental PEEP trial: conventional recruitment manoeuvres (stepwise increase of PEEP) in pressure-controlled mode) followed by 50 min of volume-controlled ventilation (VCV) with constant tidal volume, and variable ventilation, consisting of 50 min of VCV with random variation in tidal volume. MAIN OUTCOME MEASURES Before and 50 min after each recruitment manoeuvre strategy, lung aeration was assessed by computed tomography, and relative lung perfusion and ventilation (0% = dorsal, 100% = ventral) were determined by electrical impedance tomography. RESULTS After 50 min, variable ventilation and stepwise recruitment manoeuvres decreased the relative mass of poorly and nonaerated lung tissue (percent lung mass: 35.3 ± 6.2 versus 34.2 ± 6.6, P = 0.303); reduced poorly aerated lung mass compared with baseline (−3.5 ± 4.0%, P = 0.016, and −5.2 ± 2.8%, P < 0.001, respectively), and reduced nonaerated lung mass compared with baseline (−7.2 ± 2.5%, P < 0.001; and −4.7 ± 2.8%, P < 0.001 respectively), while the distribution of relative perfusion was barely affected (variable ventilation: −0.8 ± 1.1%, P = 0.044; stepwise recruitment manoeuvres: −0.4 ± 0.9%, P = 0.167). Compared with baseline, variable ventilation and stepwise recruitment manoeuvres increased P aO2 (172 ± 85mmHg, P = 0.001; and 213 ± 73 mmHg, P < 0.001, respectively), reduced P aCO2 (−9.6 ± 8.1 mmHg, P = 0.003; and −6.7 ± 4.6 mmHg, P < 0.001, respectively), and decreased elastance (−11.4 ± 6.3 cmH2O, P < 0.001; and −14.1 ± 3.3 cmH2O, P < 0.001, respectively). Mean arterial pressure decreased during stepwise recruitment manoeuvres (−24 ± 8 mmHg, P = 0.006), but not variable ventilation. CONCLUSION In this model of lung atelectasis, variable ventilation and stepwise recruitment manoeuvres effectively recruited lungs, but only variable ventilation did not adversely affect haemodynamics. TRIAL REGISTRATION This study was registered and approved by Landesdirektion Dresden, Germany (DD24-5131/354/64).

BACKGROUND:Variable ventilation recruits alveoli in atelectatic lungs, but it is unknown how it compares with conventional recruitment manoeuvres.OBJECTIVES:To test whether mechanical ventilation with variable tidal volumes and conventional recruitment manoeuvres have comparable effects on lung function.DESIGN:Randomised crossover study.SETTING:University hospital research facility.ANIMALS:Eleven juvenile mechanically ventilated pigs with atelectasis created by saline lung lavage.INTERVENTIONS:Lung recruitment was performed using two strategies, both with an individualised optimal positive-end expiratory pressure (PEEP) associated with the best respiratory system elastance during a decremental PEEP trial: conventional recruitment manoeuvres (stepwise increase of PEEP) in pressure-controlled mode) followed by 50 min of volume-controlled ventilation (VCV) with constant tidal volume, and variable ventilation, consisting of 50 min of VCV with random variation in tidal volume.MAIN OUTCOME MEASURES:Before and 50 min after each recruitment manoeuvre strategy, lung aeration was assessed by computed tomography, and relative lung perfusion and ventilation (0% = dorsal, 100% = ventral) were determined by electrical impedance tomography.RESULTS:After 50 min, variable ventilation and stepwise recruitment manoeuvres decreased the relative mass of poorly and nonaerated lung tissue (percent lung mass: 35.3 ± 6.2 versus 34.2 ± 6.6, P  = 0.303); reduced poorly aerated lung mass compared with baseline (-3.5 ± 4.0%, P  = 0.016, and -5.2 ± 2.8%, P  < 0.001, respectively), and reduced nonaerated lung mass compared with baseline (-7.2 ± 2.5%, P  < 0.001; and -4.7 ± 2.8%, P  < 0.001 respectively), while the distribution of relative perfusion was barely affected (variable ventilation: -0.8 ± 1.1%, P  = 0.044; stepwise recruitment manoeuvres: -0.4 ± 0.9%, P  = 0.167). Compared with baseline, variable ventilation and stepwise recruitment manoeuvres increased Pa O 2 (172 ± 85mmHg, P  = 0.001; and 213 ± 73 mmHg, P  < 0.001, respectively), reduced Pa CO 2 (-9.6 ± 8.1 mmHg, P  = 0.003; and -6.7 ± 4.6 mmHg, P  < 0.001, respectively), and decreased elastance (-11.4 ± 6.3 cmH 2 O, P  < 0.001; and -14.1 ± 3.3 cmH 2 O, P  < 0.001, respectively). Mean arterial pressure decreased during stepwise recruitment manoeuvres (-24 ± 8 mmHg, P  = 0.006), but not variable ventilation.CONCLUSION:In this model of lung atelectasis, variable ventilation and stepwise recruitment manoeuvres effectively recruited lungs, but only variable ventilation did not adversely affect haemodynamics.TRIAL REGISTRATION:This study was registered and approved by Landesdirektion Dresden, Germany (DD24-5131/354/64).

Electrical impedance tomography is clinically used to trace ventilation related changes in electrical conductivity of lung tissue. Estimating regional pulmonary perfusion using electrical impedance tomography is still a matter of research. To support clinical decision making, reliable bedside information of pulmonary perfusion is needed. We introduce a method to robustly detect pulmonary perfusion based on indicator-enhanced electrical impedance tomography and validate it by dynamic multidetector computed tomography in two experimental models of acute respiratory distress syndrome. The acute injury was induced in a sublobar segment of the right lung by saline lavage or endotoxin instillation in eight anesthetized mechanically ventilated pigs. For electrical impedance tomography measurements, a conductive bolus (10% saline solution) was injected into the right ventricle during breath hold. Electrical impedance tomography perfusion images were reconstructed by linear and normalized Gauss-Newton reconstruction on a finite element mesh with subsequent element-wise signal and feature analysis. An iodinated contrast agent was used to compute pulmonary blood flow via dynamic multidetector computed tomography. Spatial perfusion was estimated based on first-pass indicator dilution for both electrical impedance and multidetector computed tomography and compared by Pearson correlation and Bland-Altman analysis. Strong correlation was found in dorsoventral (r = 0.92) and in right-to-left directions (r = 0.85) with good limits of agreement of 8.74% in eight lung segments. With a robust electrical impedance tomography perfusion estimation method, we found strong agreement between multidetector computed and electrical impedance tomography perfusion in healthy and regionally injured lungs and demonstrated feasibility of electrical impedance tomography perfusion imaging.

Background In acute respiratory distress syndrome (ARDS), non-ventilated perfused regions coexist with non-perfused ventilated regions within lungs. The number of unmatched regions might reflect ARDS severity and affect the risk of ventilation-induced lung injury. Despite pathophysiological relevance, unmatched ventilation and perfusion are not routinely assessed at the bedside. The aims of this study were to quantify unmatched ventilation and perfusion at the bedside by electrical impedance tomography (EIT) investigating their association with mortality in patients with ARDS and to explore the effects of positive end-expiratory pressure (PEEP) on unmatched ventilation and perfusion in subgroups of patients with different ARDS severity based on PaO 2 /FiO 2 and compliance. Methods Prospective observational study in 50 patients with mild (36%), moderate (46%), and severe (18%) ARDS under clinical ventilation settings. EIT was applied to measure the regional distribution of ventilation and perfusion using central venous bolus of saline 5% during end-inspiratory pause. We defined unmatched units as the percentage of only ventilated units plus the percentage of only perfused units. Results Percentage of unmatched units was significantly higher in non-survivors compared to survivors (32[27–47]% vs. 21[17–27]%, p < 0.001). Percentage of unmatched units was an independent predictor of mortality (OR 1.22, 95% CI 1.07–1.39, p = 0.004) with an area under the ROC curve of 0.88 (95% CI 0.79–0.97, p < 0.001). The percentage of ventilation to the ventral region of the lung was higher than the percentage of ventilation to the dorsal region (32 [27–38]% vs. 18 [13–21]%, p < 0.001), while the opposite was true for perfusion (28 [22–38]% vs. 36 [32–44]%, p < 0.001). Higher percentage of only perfused units was correlated with lower dorsal ventilation ( r = − 0.486, p < 0.001) and with lower PaO 2 /FiO 2 ratio ( r = − 0.293, p = 0.039). Conclusions EIT allows bedside assessment of unmatched ventilation and perfusion in mechanically ventilated patients with ARDS. Measurement of unmatched units could identify patients at higher risk of death and could guide personalized treatment.

Abstract The indicator dilution method (IDM) is one approach to measure pulmonary perfusion using Electrical Impedance Tomography (EIT). To be able to calculate perfusion parameters and to increase robustnes, it is necessary to approximate and then to separate the components of the measured signals. The component referring to the passage of the injected bolus through the pixels can be modeled as a gamma variate function, its parameters are often determined using nonlinear optimization algorithms. In this paper, we introduce a linear approach that enables higher robustnes and faster computation, and compare the linear and nonlinear fitting approach on data of an animal study.

Abstract Electrical Impedance Tomography (EIT) is a clinically used tool for bed-side monitoring of ventilation. Previous work also showed a high potential for lung perfusion monitoring with indicator-enhanced EIT. However, many research questions have yet to be answered before it can be broadly applied in clinical everyday life. The goal of this work is to evaluate a new method to improve EIT perfusion measurements. Pulmonary hemodynamic transfer functions were estimated using regularized deconvolution with Tikhonov regularization to estimate spatial perfusion parameters. The final comparison between EIT images and PET scans showed a median correlation of 0.897 for the images which were reconstructed using the regularized deconvolution. In comparison the previously used maximum slope method led to a median correlation of 0.868.

In this study a physiological closed-loop system for arterial CO2 partial pressure control was designed and comprehensively tested using a set of models of the respiratory CO2 gas exchange. The underlying preclinical data were collected from 12 pigs in presence of severe changes in hemodynamic and pulmonary condition. A minimally complex nonlinear state space model of CO2 gas exchange was identified post hoc in different lung conditions. The control variable was measured noninvasively using the endtidal CO2 partial pressure. For the simulation study the output signal of the controller was defined as the alveolar minute volume set value of an underlying adaptive lung protective ventilation mode. A linearisation of the two-compartment CO2 gas exchange model was used for the design of a model predictive controller (MPC). It was augmented by a tube based controller suppressing prediction errors due to model uncertainties. The controller was subject to comparative testing in interaction with each of the CO2 gas exchange models previously identified on the preclinical study data. The performance was evaluated for the system response towards the following five tests in comparison to a PID controller: recruitment maneuver, PEEP titration maneuver, stepwise change in the CO2 production, breath-hold maneuver and a step in the reference signal. A root mean square error of 2.69 mmHg between arterial CO2 partial pressure and the reference signal was achieved throughout the trial. The reference-variable response of the model predictive controller was superior regarding overshoot and settling time.

Electrical impedance tomography is an accepted and validated tool to analyze and support mechanical ventilation at the bedside. In the future it could furthermore clinically provide information of the pulmonary perfusion and other blood volume changes within the thorax by exploiting a cardiosynchronous EIT component. In the presented study, the spatial forward sensitivity against different background lung tissue distributions was analyzed. Spheres with a 10% change of the background conductivity were introduced in the lungs and in the heart. The cranio-caudal distribution of sensitivity had a bell shape and was similar between all simulated scenarios, varying only in magnitude. If the background tissue conductivity within the lungs was chosen to be the one of deflated tissue, the overall sensitivity was 46% smaller compared to the overall sensitivity against inflated lung tissue conductivity. Within the heart region, the sensitivity was increased for fully deflated lung tissue conductivity (23% relative to the sensitivity in the lungs) compared to a homogeneous distribution of inflated lung tissue conductivity (10% relative to the sensitivity in the lungs).

Heart rate variability (HRV) plays an important role in medicine and psychology because it is used to quantify imbalances of the autonomic nervous system (ANS). An important manifestations of the ANS on HRV is also directly related to respiration and it is called respiratory sinus arrhythmia (RSA). This is a controlled phenomenon that leads to a synchronized coupling between respiration and, instantaneous heart rate. Thus, the portion of HRV that is not related to respiration, and could potentially contain undiscovered diagnostic value, is overlapped and remains hidden in a standard HRV analysis. In such cases, a decoupling procedure would deliver a discriminated HRV analysis and possible new insights about the regulation of the cardiovascular system. In this work, we propose an algorithm based on Granger's causality to measure coupling between respiration and HRV. In the case of significant coupling, we estimate and cancel the respiration driven HRV component using a linear filtering approach. We tested the method using synthetic signals and prove it to deliver a reliable coupling measurement in 96.3% of the cases and reconstruct respiration free signals with a median correlation coefficient of 0.992. Afterwards, we applied our method to signals recorded during paced respiration and during natural breathing. We demonstrated that coupling is dependent on respiratory frequency and that it maximizes at 0.3 Hz. Furthermore, the HRV parameters measured during paced respiration tend to level among subjects after decoupling. The intersubject variability of HRV parameter is also decreased after the separation process. During natural breathing, coupling is notoriously lower to non-existing and decoupling has little impact on HRV. We conclude that the method proposed here can be used to investigate the diagnostic value of respiration independent HRV parameters. (C) 2016 Elsevier Ltd. All rights reserved.

Radiofrequency ablation is the gold standard for treating cardiac arrhythmias. However, the success rate of this procedure depends on numerous parameters. Wet lab experiments provide the opportunity to investigate cardiac electrophysiology under reproducible conditions. To evaluate the electrophysiological changes of ablated myocardium in these studies it is necessary to consider the three-dimensional (3D) geometry of the lesions. For this purpose, we investigated the usage of different magnetic resonance imaging (MRI) sequences as well as an image processing procedure to analyze in-vitro preparations. To differentiate signal intensities between nonablated and ablated tissue we evaluated FISP (fast imaging with steady-state precession; delivering dominantly T1-weighted images) and RARE (rapid acquisition with relaxation enhancement; delivering dominantly T2-weighted images). After image processing, the ablated tissue was segmented in each image slice forming a 3D volume. The geometry of the lesion was modeled by the boundary of this volume. It was generally feasible to distinguish between healthy myocardium and ablated tissue as well as to determine lesion transmurality. The analysis of the reconstructed lesion geometries from FISP and RARE MRI showed a high agreement, however T2-weighted sequences showed larger lesion volumes as well as higher variations in segmentation compared to T1- mapping. FISP with higher quality may be used to reconstruct the 3D geometry of the ablation lesions.

Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC) as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96).

Abstract Heart Rate Variability studies are a known measure for the autonomous control of the heart rate. In special situations, its interpretation can be ambiguous, since the respiration has a major influence on the heart rate variability. For this reason it has often been proposed to measure Heart Rate Variability, while the subjects are breathing at a constant respiration rate. That way the spectral influence of the respiration is known. In this work we propose to remove this constant respiratory influence from the heart rate and the Heart Rate Variability parameters to gain respiration free autonomous controlled heart rate signal. The spectral respiratory component in the heart rate signal is detected and characterized. Subsequently the respiratory effect on Heart Rate Variability is removed using spectral filtering approaches, such as the Notch filter or the Raised Cosine filter. As a result new decoupled Heart Variability parameters are gained, which could lead to new additional interpretations of the autonomous control of the heart rate.