Providing optimal personalized mechanical ventilation for patients with acute or chronic respiratory failure is still a challenge within a clinical setting for each case anew. In this article, we integrate electrical impedance tomography (EIT) monitoring into a powerful patient-specific computational lung model to create an approach for personalizing protective ventilatory treatment. The underlying computational lung model is based on a single computed tomography scan and able to predict global airflow quantities, as well as local tissue aeration and strains for any ventilation maneuver. For validation, a novel “virtual EIT” module is added to our computational lung model, allowing to simulate EIT images based on the patient's thorax geometry and the results of our numerically predicted tissue aeration. Clinically measured EIT images are not used to calibrate the computational model. Thus they provide an independent method to validate the computational predictions at high temporal resolution. The performance of this coupling approach has been tested in an example patient with acute respiratory distress syndrome. The method shows good agreement between computationally predicted and clinically measured airflow data and EIT images. These results imply that the proposed framework can be used for numerical prediction of patient-specific responses to certain therapeutic measures before applying them to an actual patient. In the long run, definition of patient-specific optimal ventilation protocols might be assisted by computational modeling. NEW & NOTEWORTHY In this work, we present a patient-specific computational lung model that is able to predict global and local ventilatory quantities for a given patient and any selected ventilation protocol. For the first time, such a predictive lung model is equipped with a virtual electrical impedance tomography module allowing real-time validation of the computed results with the patient measurements. First promising results obtained in an acute respiratory distress syndrome patient show the potential of this approach for personalized computationally guided optimization of mechanical ventilation in future.
Objective. In this paper, an automated stable tidal breathing period (STBP) identification method based on processing electrical impedance tomography (EIT) waveforms is proposed and the possibility of detecting and identifying such periods using EIT waveforms is analyzed. In wearable chest EIT, patients breathe spontaneously, and therefore, their breathing pattern might not be stable. Since most of the EIT feature extraction methods are applied to STBPs, this renders their automatic identification of central importance.Approach. The EIT frame sequence is reconstructed from the raw EIT recordings and the raw global impedance waveform (GIW) is computed. Next, the respiratory component of the raw GIW is extracted and processed for the automatic respiratory cycle (breath) extraction and their subsequent grouping into STBPs.Main results. We suggest three criteria for the identification of STBPs, namely, the coefficient of variation of (i) breath tidal volume, (ii) breath duration and (iii) end-expiratory impedance. The total number of true STBPs identified by the proposed method was 294 out of 318 identified by the expert corresponding to accuracy over 90%. Specific activities such as speaking, eating and arm elevation are identified as sources of false positives and their discrimination is discussed.Significance. Simple and computationally efficient STBP detection and identification is a highly desirable component in the EIT processing pipeline. Our study implies that it is feasible, however, the determination of its limits is necessary in order to consider the implementation of more advanced and computationally demanding approaches such as deep learning and fusion with data from other wearable sensors such as accelerometers and microphones.
Abstract Background Prone positioning (PP) improves oxygenation in awake patients with acute hypoxemic respiratory failure (AHRF). However, the underlying mechanisms remain unclear in patients with diverse lung morphology. We aimed to determine the short-term effects of awake prone positioning (APP) in AHRF patients with focal and non-focal lung morphology. Methods This is a prospective physiological study. Twenty-four non-intubated patients with PaO2/FiO2 ≤ 300 mm Hg were included. Gas exchange, ventilation and perfusion distribution, and hemodynamics variables were recorded in the supine position (SP1), 2 h after PP, and 1 h after re-supine (SP2). Lung morphology was classified as focal and non-focal patterns using computed tomography. Results Twelve of the included patients were classified to the focal group and 12 to the non-focal group. PaO2/FiO2 improved after PP in all patients (161 [137, 227] mmHg vs. 236 [202, 275] mmHg, p < 0.001). Ventilation-perfusion (V/Q) matching increased after PP in all patients (61.9 [53.9, 66.5] vs. 77.5 [68.3, 80.0], p < 0.001). Shunt exhibited a significant decrease in patients of the non-focal group (28.6 [22.5, 30.3] vs. 11.3 [9.0, 14.5], p < 0.001), whereas no difference was found in the focal group after PP. Dead space decreased significantly in patients of the focal group (25.6 [21.5, 28.4] vs. 12.0 [10.8, 14.1], p < 0.001), whereas no difference was found in the non-focal group after PP. Conclusions APP improves V/Q matching by decreasing dead space in patients with focal lung morphology, and by decreasing shunt in patients with non-focal lung morphology. Trial registration: The study is registered in ClinicalTrials.gov (NCT04754113).
We present a novel computational model for the dynamics of alveolar recruitment/derecruitment (RD), which reproduces the underlying characteristics typically observed in injured lungs. The basic idea is a pressure- and time-dependent variation of the stress-free reference volume in reduced dimensional viscoelastic elements representing the acinar tissue. We choose a variable reference volume triggered by critical opening and closing pressures in a time-dependent manner from a straightforward mechanical point of view. In the case of (partially and progressively) collapsing alveolar structures, the volume available for expansion during breathing reduces and vice versa, eventually enabling consideration of alveolar collapse and reopening in our model. We further introduce a method for patient-specific determination of the underlying critical parameters of the new alveolar RD dynamics when integrated into the tissue elements, referred to as terminal units, of a spatially resolved physics-based lung model that simulates the human respiratory system in an anatomically correct manner. Relevant patient-specific parameters of the terminal units are herein determined based on medical image data and the macromechanical behavior of the lung during artificial ventilation. We test the whole modeling approach for a real-life scenario by applying it to the clinical data of a mechanically ventilated patient. The generated lung model is capable of reproducing clinical measurements such as tidal volume and pleural pressure during various ventilation maneuvers. We conclude that this new model is an important step toward personalized treatment of ARDS patients by considering potentially harmful mechanisms - such as cyclic RD and overdistension - and might help in the development of relevant protective ventilation strategies to reduce ventilator-induced lung injury (VILI).
Respiratory muscle endurance training is beneficial for patients with chronic spinal cord injury.This study measured the effects of respiratory muscle endurance training on lung function and patient-reported outcomes.Eighteen patients with spinal cord injury who were > 24 months post-injury were randomly assigned to either a studied or a control group.The results showed that endurance training may reduce the incidence of respiratory symptoms, improve lung function and quality of life, and reduce depression in patients with chronic spinal cord injury, regardless of their neurological level of injury, even at more than 24 months after injury. Objective: To investigate the effects of normocapnic hyperpnoea training on pulmonary function and patient-reported outcomes in chronic spinal cord injury.Design: Single-centre randomized controlled trial.Patients: Eighteen patients with spinal cord injury > 24 months post-injury and without regular respiratory muscle training prior to the study were included prospectively.Methods: Patients were randomly assigned to either normocapnic hyperpnoea or control groups.The normocapnic hyperpnoea group patients performed training 15-20 min per day, 5 times a week for 4 weeks.The patients hyperventilated through partial re-breathing of ventilated air.The control group received no respiratory muscle training.Other rehabilitative programmes were performed identically in both groups.Lung function testing was performed in the sitting position prior to and after the study.Patient-reported outcomes were assessed using the Patient Health Questionnaire-9, St George's Respiratory Questionnaire, Chronic Obstructive Pulmonary Disease Assessment Test and Borg scores.Results: Significant differences were found in the improvement ratio between the normocapnic hyperpnoea and control groups for all investigated parameters, except total lung capacity and diffusing capacity of the lung for carbon monoxide.Conclusion: Normocapnic hyperpnoea training may reduce the incidence of respiratory symptoms, improve pulmonary function and quality of life, and reduce depression in patients with chronic spinal cord injury, regardless of their neurological level of injury, even at more than 24 months after injury.
Regional differences in lung volume have been described in adults with acute respiratory distress syndrome, but it remains unclear to what extent they occur in children. To quantify regional alveolar collapse that occurred during mechanical ventilation during a standardized suctioning maneuver, we evaluated regional and global relative impedance changes (relative DeltaZ) in children with acute respiratory distress syndrome using electrical impedance tomography.Prospective observational trial.A 30-bed pediatric intensive care unit.Six children with acute respiratory distress syndrome.Standardized suctioning maneuver.By comparing layers from nondependent (layers 1 and 2) to dependent lung areas (layers 3 and 4), it was demonstrated that the middle layers (2 and 3) had the greatest ventilation-induced change in relative DeltaZ; layer 4 showed the least ventilation-induced change in relative DeltaZ. During suctioning, layers 1, 2, and 3 showed a negative change in relative DeltaZ, whereas layer 4 showed no significant change in relative DeltaZ. The derecruitment-induced change in relative DeltaZ representing the lung-volume loss was -9.8 (-3.0 mL/kg) during the first suctioning maneuver, -16.1 (-5.4 mL/kg) during the second, and -21.7 (-7.4 mL/kg) during the third. The ventilation-induced change in relative DeltaZ during mechanical ventilation remained unchanged after suctioning (mean change in relative DeltaZ before vs. after suctioning, 40.1 +/- 9.1 vs. 41.4 +/- 10.8; p = .30). Dynamic compliance was 11.8 +/- 6.1 mL.cm H2O before and 11.8 +/- 6.9 mL.cm H2O after the suctioning sequence (p = .90).Considerable regional heterogeneity was present during ventilation and a derecruitment maneuver. Significantly lower change in relative DeltaZ in the most dependent lung regions suggests alveolar collapse during ventilation before suctioning.
Introduction: Although automated weaning systems have shown to be safe and more efficient than a conventional approach, it is unknown whether they influence health-related quality of life (HRQOL). Objective: We hypothesized that automated weaning with SmartCare/PS compared with a standardized weaning protocol has a positive effect on HRQOL. Methods: Patients were systematically followed-up one year after participation in a randomized controlled trial investigating the effect of automated versus protocol-driven weaning from mechanical ventilation (ASOPI-trial; clinicaltrials.gov ID 00445289). Quality of life was assessed using QLQ C-30 3.0 questionnaire. Mean differences of equal or more than 10 score points were considered to be clinically relevant. Results: 300 patients were initially included, 232 patients were alive one year later. We were able to get into contact with 143 patients, 127 patients gave consent to fill out the questionnaire. 81 questionnaires were sent back and included into this analysis. Regarding the function-related scales we found clinically significant higher mean score values for “emotion” and “global health status” in the automated weaning group (Figure 1, Panel A). Symptom-related scales like “fatique” and “diarrhoea” were clinically significant lower in the SmartCare/PS-group (Figure 1, Panel B). Conclusions: This study shows an improved HRQOL in the automated weaning group.
The electrical impedance tomography (EIT)-based global inhomogeneity (GI) index was introduced to quantify tidal volume distribution within the lung. Up to now, the GI index was evaluated for plausibility but the analysis of how it is influenced by various physiological factors is still missing. The aim of our study was to evaluate the influence of proportion of open lung regions measured by EIT on the GI index. A constant low-flow inflation maneuver was performed in 18 acute respiratory distress syndrome (ARDS) patients (58 ± 14 years, mean age ± SD) and 8 lung-healthy patients (41 ± 12 years) under controlled mechanical ventilation. EIT raw data were acquired at 25 scans/s and reconstructed offline. Recruited lung regions were identified as those image pixels of the lung regions within the EIT scans where local impedance amplitudes exceeded 10% of the maximum amplitude during the maneuver. A series of GI indices was calculated during mechanical lung inflation, based on the differential images obtained between different time points. Respiratory system elastance (Ers) values were calculated at 10 lung volume levels during low-flow maneuver. The GI index decreased during low-flow inflation, while the percentage of open lung regions increased. The values correlated highly in both ARDS (r2 = 0.88 ± 0.08, p < 0.01) and lung-healthy patients (r2 = 0.92 ± 0.05, p < 0.01). Ers and GI index were also significantly correlated in 16 out of 18 ARDS (r2 = 0.84 ± 0.13, p < 0.01) and in 6 out of 8 lung-healthy patients (r2 = 0.84 ± 0.07, p < 0.01). Significant differences were found in GI values between two groups (0.52 ± 0.21 for ARDS and 0.41 ± 0.04 for lung-healthy patients, p < 0.05) as well in Ers values (0.017 ± 0.008 cmH2O/ml for ARDS and 0.009 ± 0.001 cmH2O/ml for lung-healthy patients, p < 0.01). We conclude that the GI index is a reliable measure of ventilation heterogeneity highly correlated with lung recruitability measured with EIT. The GI index may prove to be a useful EIT-based index to guide ventilation therapy.
Introduction: Electrical impedance tomography (EIT) is able to trace ventilation-related changes in electrical properties of lung tissue. Previous studies using computed tomography (CT) suggested a good correlation between regional EIT data and lung tissue density. However, no validation data exist in regional acute lung injury (ALI). Objective: To validate EIT measurements of regional ventilation (rVa) by dynamic Xenon-multidetector-row CT (Xe-MDCT) in two animal models of regional ALI. Methods: 9 anaesthetized mechanically ventilated pigs were examined before and after induction of ALI within two adjacent sub-lobar lung segments by repetitive saline lavage (n=4) or endotoxin sepsis injury (n=5). EIT data were acquired at 25 scans/s (GoeMF II system, CareFusion, Hochberg, Germany). Xe-MDCT (Sensation 64, Siemens AG, Forchheim, Germany) was performed at the same thoracic region. EIT and Xe-MDCT rVa images during control and ALI were divided into 32 regions of interest (ROI) in each hemithorax. rVa differences for both methods were obtained by subtracting the corresponding values in each ROI. EIT and CT measurements were compared by Spearman9s Rho correlation. Results: In 4 of 9 animals analyzed so far, rVa difference images revealed a ventilation decrease in the injured (right) lung and an increase in the non-injured (left) lung compared to control. rVa changes occurred in spatially similar locations. Spearman9s rho ranged from 0.931-0.936 for the right and 0.943-0.979 for the left hemithorax in control. In ALI, ranges were 0.857-0.933 and 0.948-0.981, respectively (p Conclusion: A good correlation existed of rVa determined by EIT and Xe-MDCT in the 4 animals with regional ALI compared to date.
