Pulmonary function testing dataset of pressure and flow, dynamic circumference, heart rate, and aeration monitoring

Respiratory data was collected from 20 subjects, with an even sex distribution, in the low-risk clinical unit at the University of Canterbury. Ethical consent for this trial was granted by the University of Canterbury Human Research Ethics Committee (Ref: HREC 2023/30/LR-PS). Respiratory data were collected, for each subject, over three tests consisting of: 1) increasing set PEEP from a starting point of ZEEP using a CPAP machine; 2) test 1 repeated with two simulated apnoea's (breath holds) at each set PEEP; and 3) three forced expiratory manoeuvres at ZEEP. Data were collected using a custom pressure and flow sensor device, ECG, PPG, Garmin HRM Dual heartrate belt, and a Dräeger PulmoVista 500 Electrical Impedance Tomography (EIT) machine. Subject demographic data was also collected prior to the trial, in a questionnaire, with measurement equipment available. These data aim to inform the development of pulmonary mechanics models and titration algorithms.

Do contaminants compromise the use of recycled nutrients in organic agriculture? A review and synthesis of current knowledge on contaminant concentrations, fate in the environment and risk assessment

Use of nutrients recycled from societal waste streams in agriculture is part of the circular economy, and in line with organic farming principles. Nevertheless, diverse contaminants in waste streams create doubts among organic farmers about potential risks for soil health. Here, we gather the current knowledge on contaminant levels in waste streams and recycled nutrient sources, and discuss associated risks. For potentially toxic elements (PTEs), the input of zinc (Zn) and copper (Cu) from mineral feed supplements remains of concern, while concentrations of PTEs in many waste streams have decreased substantially in Europe. The same applies to organic contaminants, although new chemical groups such as flame retardants are of emerging concern and globally contamination levels differ strongly. Compared to inorganic fertilizers, application of organic fertilizers derived from human or animal feces is associated with an increased risk for environmental dissemination of antibiotic resistance. The risk depends on the quality of the organic fertilizers, which varies between geographical regions, but farmland application of sewage sludge appears to be a safe practice as shown by some studies (e.g. from Sweden). Microplastic concentrations in agricultural soils show a wide spread and our understanding of its toxicity is limited, hampering a sound risk assessment. Methods for assessing public health risks for organic contaminants must include emerging contaminants and potential interactions of multiple compounds. Evidence from long-term field experiments suggests that soils may be more resilient and capable to degrade or stabilize pollutants than often assumed. In view of the need to source nutrients for expanding areas under organic farming, we discuss inputs originating from conventional farms vs. non-agricultural (i.e. societal) inputs. Closing nutrient cycles between agriculture and society is feasible in many cases, without being compromised by contaminants, and should be enhanced, aided by improved source control, waste treatment and sound risk assessments.

Respiratory monitoring dataset, with rapid expiratory occlusions, over increasing positive airway pressure ventilation

Resting breathing data was collected from 80 smokers, vapers, asthmatics, and otherwise healthy people in the low-risk clinical unit at the University of Canterbury. Subjects were asked to breathe normally through a full-face mask connected to a Fisher and Paykel Healthcare SleepStyle SPSCAA CPAP device. PEEP (Positive End-Expiratory Pressure) support was increased from 4 to 12 cmH2O in 0.5 cmH2O increments. Data was also collected during resting breathing at ZEEP (0 cmH2O) before and after the PEEP trial. The trial was conducted under University of Canterbury Human Research Ethics Committee consent (Ref: HREC 2023/04/LR-PS). Data was collected by and Dräeger PulmoVista 500 EIT machine and a custom Venturi-based pressure and flow sensor device connected in series with the CPAP and full-face mask. The outlined dataset includes pressure, flow, volume, dynamic circumference (thoracic and abdominal, and cross-sectional aeration. Subject demographic data was self-reported using a questionnaire given prior to the trial.

Pulmonary response prediction through personalized basis functions in a virtual patient model

BACKGROUND AND OBJECTIVE

Recruitment maneuvers with subsequent positive-end-expiratory-pressure (PEEP) have proven effective in recruiting lung volume and preventing alveoli collapse. However, determining a safe, effective, and patient-specific PEEP is not standardized, and this more optimal PEEP level evolves with patient condition, requiring personalised monitoring and care approaches to maintain optimal ventilation settings.

METHODS

This research examines 3 physiologically relevant basis function sets (exponential, parabolic, cumulative) to enable better prediction of elastance evolution for a virtual patient or digital twin model of MV lung mechanics, including novel elements to model and predict distension elastance. Prediction accuracy and robustness are validated against recruitment maneuver data from 18 volume-controlled ventilation (VCV) patients at 7 different baseline PEEP levels (0 to 12 cmH2O) and 14 pressure-controlled ventilation (PCV) patients at 4 different baseline PEEP levels (6 to 12 cmH2O), yielding 623 and 294 prediction cases, respectively. Predictions were made up to 12 cmH2O of added PEEP ahead, covering 6 × 2 cmH2O PEEP steps.

RESULTS

The 3 basis function sets yield median absolute peak inspiratory pressure (PIP) prediction error of 1.63 cmH2O for VCV patients, and median peak inspiratory volume (PIV) prediction error of 0.028 L for PCV patients. The exponential basis function set yields a better trade-off of overall performance across VCV and PCV prediction than parabolic and cumulative basis function sets from other studies. Comparing predicted and clinically measured distension prediction in VCV demonstrated consistent, robust high accuracy with R2 = 0.90-0.95.

CONCLUSIONS

The results demonstrate recruitment mechanics are best captured by an exponential basis function across different mechanical ventilation modes, matching physiological expectations, and accurately capture, for the first time, distension mechanics to within 5-10 % accuracy. Enabling the risk of lung injury to be predicted before changing ventilator settings. The overall outcomes significantly extend and more fully validate this digital twin or virtual mechanical ventilation patient model.

Finite element analysis of the interaction between high-compliant balloon catheters and non-cylindrical vessel structures: towards tactile sensing balloon catheters

Aiming for sensing balloon catheters which are able to provide intraoperative information of the vessel stiffness and shape, the present study uses finite element analysis (FEA) to evaluate the interaction between high-compliant elastomer balloon catheters with the inner wall of a non-cylindrical-shaped lumen structure. The contact simulations are based on 3D models with varying balloon thicknesses and varying tissue geometries to analyse the resulting balloon and tissue deformation as well as the inflation pressure dependent contact area. The wrinkled tissue structure is modelled by utilizing a two-layer fibre-based Holzapfel-Gasser-Ogden constitutive model and the model parameters are adapted based on available biomechanical data for human urethral vessel samples. The balloon catheter structure is implemented as a high-compliant hyper-elastic silicone material (based on polydimethylsiloxane (PDMS)) with a varying catheter wall thickness between 0.5 and 2.5 µm. Two control parameters are introduced to describe the balloon shape adaption in reaction to a wrinkled vessel wall during the inflation process. Basic semi-quantitative relations are revealed depending on the evolving balloon deformation and contact surface. Based on these relations some general design guidelines for balloon-based sensor catheters are presented. The results of the conducted in-silico study reveal some general interdependencies with respect to the compliance ratio between balloon and tissue and also in respect of the tissue aspect ratio. Further they support the proposed concept of high-compliant balloon catheters equipped for tactile sensing as diagnosis approach in urology and angioplasty.

Optimal machine learning methods for prediction of high-flow nasal cannula outcomes using image features from electrical impedance tomography

BACKGROUND

High-flow nasal cannula (HNFC) is able to provide ventilation support for patients with hypoxic respiratory failure. Early prediction of HFNC outcome is warranted, since failure of HFNC might delay intubation and increase mortality rate. Existing methods require a relatively long period to identify the failure (approximately 12 h) and electrical impedance tomography (EIT) may help identify the patient's respiratory drive during HFNC.

OBJECTIVES

This study aimed to investigate a proper machine-learning model to predict HFNC outcomes promptly by EIT image features.

METHODS

The Z-score standardization method was adopted to normalize the samples from 43 patients who underwent HFNC and six EIT features were selected as model input variables through the random forest feature selection method. Machine-learning methods including discriminant, ensembles, k-nearest neighbour (KNN), artificial neural network (ANN), support vector machine (SVM), AdaBoost, xgboost, logistic, random forest, bernoulli bayes, gaussian bayes and gradient-boosted decision trees (GBDT) were used to build prediction models with the original data and balanced data proceeded by the synthetic minority oversampling technique.

RESULTS

Prior to data balancing, an extremely low specificity (less than 33.33%) as well as a high accuracy in the validation data set were observed in all the methods. After data balancing, the specificity of KNN, xgboost, random forest, GBDT, bernoulli bayes and AdaBoost significantly reduced (p<0.05) while the area under curve did not improve considerably (p>0.05); and the accuracy and recall decreased significantly (p<0.05).

CONCLUSIONS

The xgboost method showed better overall performance for balanced EIT image features, which may be considered as the ideal machine learning method for early prediction of HFNC outcomes.

The influence of gravity on electrical impedance tomography measurements during upper body position change

Objective

The aim of the study was to examine the influence of gravity on regional ventilation measured by electrical impedance tomography (EIT) with the standard electrode belt position at the 5th intercostal space during tilting from supine to sitting positions.

Methods

A total of 30 healthy volunteers were examined prospectively in supine position during quiet tidal breathing. Subsequently, the bed was tilted so that the upper body of the subjects achieved 30, 60 and 90° every 3 min. Regional ventilation distribution and end-expiratory lung impedance (EELI) were monitored with EIT throughout the whole experiment. Absolute tidal volumes were measured with spirometry and the volume-impedance ratio was calculated for each position.

Results

The volume-impedance ratio did not differ statistically between the studied body positions but 11 subjects exhibited a large change in ratio at one of the positions (outside 99.3% coverage). In general, ventilation distribution became more heterogeneous and moved towards dorsal regions as the upper body was tilted to 90-degree position. EELI increased and tidal volume decreased. The lung regions identified at various positions differed significantly.

Conclusion

Gravity has non-negligible influence on EIT data, as the upper body tilted from supine to sitting positions. The standard electrode belt position might be reconsidered if ventilation distribution is to be compared between supine and sitting positions.

Initial engagement and axial force model for self-tapping bone screws

Correctly torquing bone screws is important for implant fixation longevity and strength. A model-based smart screwdriver has been proposed to regulate torque, however current models ignore axial force and the initial engagement of the screw. This was addressed here by deriving a model based on the concept of a net axial force generated by a difference in contact areas on the inward and outward sides of the screw threads. This force is opposed by the shear strength of the material around the threads. The results of the derivation were able to predict the effects of different axial forces during insertion in relation to the hole material strength. The results may be used to compensate for initial thread breakage in future model-based smart screwdrivers to improve their accuracy.

Robustness evaluation on different training state of a CNN model

Convolutional neural networks (CNNs) have proved to be successful in many applications such as image processing. However, even imperceptible perturbations applied to the images can make the neural network performance unreliable. To guarantee an accurate performance in safety critical fields, it is necessary to assess the robustness of CNN solutions before launching. Adversarial attack is a machine learning approach to generate perturbations on real samples to detect the vulnerability of CNN. In this paper, we will use an adversarial attack technique to evaluate a CNN at different training states. The model was trained to perform surgical tool classification task, which was applied to recognize surgical tool in Cholecystectomy to further analyze surgical process. The experiments demonstrate the relation between training states and robustness, i.e. the robustness improved at higher training states, especially for some particular classes. In future work, additional training with generated adversarial images may improve the robustness of the model.

Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography

Introduction

Coronavirus disease-2019 (COVID-19) pneumonia has different phenotypes. Selecting the patient individualized and optimal respirator settings for the ventilated patient is a challenging process. Electric impedance tomography (EIT) is a real-time, radiation-free functional imaging technique that can aid clinicians in differentiating the “low” (L-) and “high” (H-) phenotypes of COVID-19 pneumonia described previously.

Methods

Two patients (“A” and “B”) underwent a stepwise positive end-expiratory pressure (PEEP) recruitment by 3 cmH₂O of steps from PEEP 10 to 25 and back to 10 cmH₂O during a pressure control ventilation of 15 cmH₂O. Recruitment maneuvers were performed under continuous EIT recording on a daily basis until patients required controlled ventilation mode.

Results

Patients “A” and “B” had a 7- and 12-day long trial, respectively. At the daily baseline, patient “A” had significantly higher compliance: mean ± SD = 53 ± 7 vs. 38 ± 5 ml/cmH₂O (p < 0.001) and a significantly higher physiological dead space according to the Bohr–Enghoff equation than patient “B”: mean ± SD = 52 ± 4 vs. 45 ± 6% (p = 0.018). Following recruitment maneuvers, patient “A” had a significantly higher cumulative collapse ratio detected by EIT than patient “B”: mean ± SD = 0.40 ± 0.08 vs. 0.29 ± 0.08 (p = 0.007). In patient “A,” there was a significant linear regression between the cumulative collapse ratios at the end of the recruitment maneuvers (R² = 0.824, p = 0.005) by moving forward in days, while not for patient “B” (R² = 0.329, p = 0.5).

Conclusion

Patient “B” was recognized as H-phenotype with high elastance, low compliance, higher recruitability, and low ventilation-to-perfusion ratio; meanwhile patient “A” was identified as the L-phenotype with low elastance, high compliance, and lower recruitability. Observation by EIT was not just able to differentiate the two phenotypes, but it also could follow the transition from L- to H-type within patient “A.”

Clinical Trial Registration

www.ClinicalTrials.gov, identifier: NCT04360837.

Reconstructing asynchrony for mechanical ventilation using a hysteresis loop virtual patient model

BACKGROUND

Patient-specific lung mechanics during mechanical ventilation (MV) can be identified from measured waveforms of fully ventilated, sedated patients. However, asynchrony due to spontaneous breathing (SB) effort can be common, altering these waveforms and reducing the accuracy of identified, model-based, and patient-specific lung mechanics.

METHODS

Changes in patient-specific lung elastance over a pressure-volume (PV) loop, identified using hysteresis loop analysis (HLA), are used to detect the occurrence of asynchrony and identify its type and pattern. The identified HLA parameters are then combined with a nonlinear mechanics hysteresis loop model (HLM) to extract and reconstruct ventilated waveforms unaffected by asynchronous breaths. Asynchrony magnitude can then be quantified using an energy-dissipation metric, Easyn, comparing PV loop area between model-reconstructed and original, altered asynchronous breathing cycles. Performance is evaluated using both test-lung experimental data with a known ground truth and clinical data from four patients with varying levels of asynchrony.

RESULTS

Root mean square errors for reconstructed PV loops are within 5% for test-lung experimental data, and 10% for over 90% of clinical data. Easyn clearly matches known asynchrony magnitude for experimental data with RMS errors < 4.1%. Clinical data performance shows 57% breaths having Easyn > 50% for Patient 1 and 13% for Patient 2. Patient 3 only presents 20% breaths with Easyn > 10%. Patient 4 has Easyn = 0 for 96% breaths showing accuracy in a case without asynchrony.

CONCLUSIONS

Experimental test-lung validation demonstrates the method's reconstruction accuracy and generality in controlled scenarios. Clinical validation matches direct observations of asynchrony in incidence and quantifies magnitude, including cases without asynchrony, validating its robustness and potential efficacy as a clinical real-time asynchrony monitoring tool.

A review of the hormones involved in the endocrine dysfunctions of polycystic ovary syndrome and their interactions

Polycystic ovary syndrome (PCOS) affects up to 20% of women but remains poorly understood. It is a heterogeneous condition with many potential comorbidities. This review offers an overview of the dysregulation of the reproductive and metabolic systems associated with PCOS. Review of the literature informed the development of a comprehensive summarizing 'wiring' diagram of PCOS-related features. This review provides a justification for each diagram aspect from the relevant academic literature, and explores the interactions between the hypothalamus, ovarian follicles, adipose tissue, reproductive hormones and other organ systems. The diagram will provide an efficient and useful tool for those researching and treating PCOS to understand the current state of knowledge on the complexity and variability of PCOS.

Detection of Different COVID-19 Pneumonia Phenotypes with Estimated Alveolar Collapse and Overdistention by Bedside Electrical Impedance Tomography

COVID-19 induced acute respiratory distress syndrome (ARDS) could have two different phenotypes, which was reported to have different response and outcome to the typical ARDS positive end-expiration pressure (PEEP) treatment. The identification of the different phenotypes in terms of the recruitability can help improve the patient outcome. In this contribution we conducted alveolar overdistention and collapse analysis with the long term electrical impedance tomography monitoring data on two severe COVID-19 pneumonia patients. The result showed different patient reactions to the PEEP trial, revealed the progressive change in the patient status, and indicted a possible phenotype transition in one patient. It might suggest that EIT can be a practical tool to identify phenotypes and to provide progressive information of COVID-19 pneumonia.

Image processing to delineate the boundaries of peripheral arterial walls

The analysis of the arterial wall properties is vital in the prediction of stroke events and arterial hypertension in humans. Numerous researchers have experimented with several approaches to model arterial vessels and to analyse their biomechanical behaviour for many years now. Our study is focussed on image processing of peripheral arterial cross sections to detect and isolate the distinct layers. These boundaries will enable the creation of FEM models for further analysis of arterial wall properties. In a clinical setting, it facilitates doctors to identify the optimum pressure that can be applied to the artery for the treatment of stenosis without damaging the morphology of the blood vessels. This paper aims at distinguishing the various layers of arterial walls from images by minimizing human intervention. Cross section images of arteries from various sources were collected[10][11]. The boundaries from the image were obtained using image processing techniques of MATLAB(R2021a). The approach identified was to convert the input RGB images to grayscale, thresholding and applying morphological operators to delineate the Intima, Media, and Adventitia. These regions of interests (ROI) were then superimposed to generate an image with differentiated boundaries and void of unnecessary noise and inhomogeneity. This approach gave us an insight of the differences in various methods of boundary detection and to infer the optimum approach for accurate demarcation of boundaries of the three layers of arterial walls. It paves a pathway for forward modelling and to perform detailed FEM analysis in in-vitro diagnostics. In a nutshell, it was observed that the edge detection procedure implemented could be used for healthy and stenotic arteries. Further studies must be conducted to test the efficiency across a wide range of images and hence generalise its usage. Upon satisfactory boundary detection, forward modelling could be performed using the identified geometric forms.

Generating adversarial images to monitor the training state of a CNN model

Deep neural networks have shown effectiveness in many applications, however, in regulated applications like automotive or medicine, quality guarantees are required. Thus, it is important to understand the robustness of the solutions to perturbations in the input space. In order to identify the vulnerability of a trained classification model and evaluate the effect of different perturbations in the input on the output class, two different methods to generate adversarial examples were implemented. The adversarial images created were developed into a robustness index to monitor the training state and safety of a convolutional neural network model. In the future work, some generated adversarial images will be included into the training phase to improve the model robustness.

Comparison of a histology based multi layer artery model to its simplified axisymmetric model

Arteries are vessel structures that serve vital function of transportation of blood to different parts of the body. Researchers have experimented with some approaches to model the arterial behaviour and to analyse its biomechanical properties. To analyse the in-vivo arterial properties, at Furtwangen University an inflatable sensoractuator system is being developed, which provides the basis for a decision support system for vascular surgeons. The capabilities of this sensor shall be evaluated in simulations which requires appropriate modelling of the arteries. The inverse problem, i.e. how to efficiently identify arterial wall properties from sensor readings is targeted. A histology motivated 3D artery model was implemented in FEM using COMSOL (v5.5). The geometry of one model was based on a cross section of a real artery. The second model was axisymmetric and of equal dimensions with respect to volume, layer thickness etc. A biomechanical pressure-stretch analysis was performed applying an inflating pressure inside the walls of the vessels. Stretch in different areas of the first model was evaluated and the circumferential strain was compared to the axisymmetric model. The results show variation of strains within the segments of the first model of upto 10 percent. In addition, its outer wall circumferential stretch was found to be 10 percent lower compared to the axisymmetric setup. This comparison sheds light upon whether a simplification of arterial models is possible, without loss of accuracy in the context of the novel sensor evaluation. It provides useful information whether e.g. standardizing vessel structures to axisymmetric models will still provide results within allowable tolerance limits. Simulations proved useful to evaluate different vessel model formulations in the context of arterial diagnostics.

Analysis of expansion within a pressure inflated section of an urethral stricture model

The Urethra is a long tubular structure in the genitourinary tract and serves important functions. Researchers have experimented with some approaches to model the urethra and to analyse its biomechanical properties. However, experiments to model the in-vivo behaviour of urethra with strictures is not thoroughly explored. To analyse the in-vivo urethral properties and specifically for supporting treatment of strictures, a new inflatable sensor-actuator system is being developed. The capabilities of this sensor shall be evaluated in simulations which require appropriate modelling of the human male urethra with strictures. This forms a part of the identification procedure for a variety of urethra conditions and geometries, which in turn forms a basis for inverse modelling. As an initial simplified approach, an axisymmetric Finite Element model was generated that resembled the urethra incorporating a stricture region. An ideal actuator with sensor elements exerting a pressure on inner wall of this urethra was simulated. Three circumference measurement zones within the sensor height (top surface, centre and bottom surface) were implemented. The resulting pressure-extension (circumferential) responses were determined at these measurement zones. The sensor was placed at different lengths within this urethral tube and inflated and the pressure-extension responses were noted. It was found that depending on the position of the sensor-actuator, the extension of tissue can vary. The possible factors for this variation were the finite length of the actuator as well as the influence of tissue properties around the measurement zones. This is important information for the interpretation of sensor data to be gained by the current development. It was possible to generate datasets based on an ideal sensor model, that proved helpful in the evaluation of biomechanical tissue properties in healthy and stricture conditions. This indicates simulations are a versatile and prospective way to test new sensors prior to real experiments.

Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study

BACKGROUND

The aim of this study was to validate whether regional ventilation and perfusion data measured by electrical impedance tomography (EIT) with saline bolus could discriminate three broad acute respiratory failure (ARF) etiologies.

METHODS

Perfusion image was generated from EIT-based impedance-time curves caused by 10 ml 10% NaCl injection during a respiratory hold. Ventilation image was captured before the breath holding period under regular mechanical ventilation. DeadSpace_%, Shunt_% and VQMatch_% were calculated based on lung perfusion and ventilation images. Ventilation and perfusion maps were divided into four cross-quadrants (lower left and right, upper left and right). Regional distribution defects of each quadrant were scored as 0 (distribution% ≥ 15%), 1 (15% > distribution% ≥ 10%) and 2 (distribution% < 10%). Data percentile distributions in the control group and clinical simplicity were taken into consideration when defining the scores. Overall defect scores (Defect_V, Defect_Q and Defect_V+Q) were the sum of four cross-quadrants of the corresponding images.

RESULTS

A total of 108 ICU patients were prospectively included: 93 with ARF and 15 without as a control. PaO₂/FiO₂ was significantly correlated with VQMatch_% (r = 0.324, P = 0.001). Three broad etiologies of ARF were identified based on clinical judgment: pulmonary embolism-related disease (PED, n = 14); diffuse lung involvement disease (DLD, n = 21) and focal lung involvement disease (FLD, n = 58). The PED group had a significantly higher DeadSpace_% [40(24)% vs. 14(15)%, PED group vs. the rest of the subjects; median(interquartile range); P < 0.0001] and Defect_Q score than the other groups [1(1) vs. 0(1), PED vs. the rest; P < 0.0001]. The DLD group had a significantly lower Defect_V+Q score than the PED and FLD groups [0(1) vs. 2.5(2) vs. 3(3), DLD vs. PED vs. FLD; P < 0.0001]. The FLD group had a significantly higher Defect_V score than the other groups [2(2) vs. 0(1), FLD vs. the rest; P < 0.0001]. The area under the receiver operating characteristic (AUC) for using DeadSpace_% to identify PED was 0.894 in all ARF patients. The AUC for using the Defect_V+Q score to identify DLD was 0.893. The AUC for using the Defect_V score to identify FLD was 0.832.

CONCLUSIONS

Our study showed that it was feasible to characterize three broad etiologies of ARF with EIT-based regional ventilation and perfusion. Further study is required to validate clinical applicability of this method. Trial registration clinicaltrials, NCT04081142. Registered 9 September 2019-retrospectively registered, https://clinicaltrials.gov/show/NCT04081142 .

Lung ventilation distribution in patients after traditional full sternotomy and minimally invasive thoracotomy: An observational study

BACKGROUND

The aim of the study was to examine the post-operative ventilation distribution changes in cardiac surgical patients after traditional full sternotomy (FS) or minimally invasive thoracotomy (MIT).

METHODS

A total of 40 patients scheduled for FS with two-lung ventilation or MIT with one-lung ventilation were included. Ventilation distribution was measured with electrical impedance tomography (EIT) at T1, before surgery; T2, after surgery in ICU before weaning; T3, 24 hours after extubation. EIT-based parameters were calculated to assess the ventilation distribution, including the left-to-right lung ratio, ventral-to-dorsal ratio, and the global inhomogeneity index.

RESULTS

The global inhomogeneity index increased at T2 and T3 compared to T1 in all patients but only statistically significant in patients with MIT (FS, P = .06; MIT, P < .01). Notable decrease in the dorsal regions (FS) or in the non-ventilated side (MIT) was observed at T2. Ventilation distribution was partially improved at T3 but huge variations of recovery progresses were found in all patients regardless of the surgery types. Subgroup analysis indicated that operation duration was significantly lower in the MIT group (240 ± 40 in FS vs 205 ± 90 minutes in MIT, median ± interquartile range, P < .05) but the incidence of atrial fibrillation/flutter was significantly higher (5% in FS vs 50% in MIT, P < .01). Other exploratory outcomes showed no statistical differences.

CONCLUSIONS

Ventilation distribution was impaired after cardiac surgery. The recovery process of ventilation homogeneity was strongly depending on individuals so that MIT was not always superior in this aspect. EIT may help to identify the patients requiring further care after surgery.

Scoring System to Evaluate the Performance of ICU Ventilators in the Pandemic of COVID-19: A Lung Model Study

Ventilators in the intensive care units (ICU) are life-support devices that help physicians to gain additional time to cure the patients. The aim of the study was to establish a scoring system to evaluate the ventilator performance in the context of COVID-19. The scoring system was established by weighting the ventilator performance on five different aspects: the stability of pressurization, response to leaks alteration, performance of reaction, volume delivery, and accuracy in oxygen delivery. The weighting factors were determined with analytic hierarchy process (AHP). Survey was sent out to 66 clinical and mechanical experts. The scoring system was built based on 54 valid replies. A total of 12 commercially available ICU ventilators providing non-invasive ventilation were evaluated using the novel scoring system. A total of eight ICU ventilators with non-invasive ventilation mode and four dedicated non-invasive ventilators were tested according to the scoring system. Four COVID-19 phenotypes were simulated using the ASL5000 lung simulator, namely (1) increased airway resistance (IR) (10 cm H₂O/L/s), (2) low compliance (LC) (compliance of 20 ml/cmH₂O), (3) low compliance plus increased respiratory effort (LCIE) (respiratory rate of 40 and inspiratory effort of 10 cmH₂O), (4) high compliance (HC) (compliance of 50 ml/cmH₂O). All of the ventilators were set to three combinations of pressure support and positive end-expiratory pressure levels. The data were collected at baseline and at three customized leak levels. Significant inaccuracies and variations in performance between different non-invasive ventilators were observed, especially in the aspect of leaks alteration, oxygen and volume delivery. Some ventilators have stable performance in different simulated phenotypes whereas the others have over 10% scoring differences. It is feasible to use the proposed scoring system to evaluate the ventilator performance. In the COVID-19 pandemic, clinicians should be aware of possible strengths and weaknesses of ventilators.

Early individualized positive end-expiratory pressure guided by electrical impedance tomography in acute respiratory distress syndrome: a randomized controlled clinical trial

Background

Individualized positive end-expiratory pressure (PEEP) by electrical impedance tomography (EIT) has potential interest in the optimization of ventilation distribution in acute respiratory distress syndrome (ARDS). The aim of the study was to determine whether early individualized titration of PEEP with EIT improved outcomes in patients with ARDS.

Methods

A total of 117 ARDS patients receiving mechanical ventilation were randomly assigned to EIT group (n = 61, PEEP adjusted based on ventilation distribution) or control group (n = 56, low PEEP/FiO₂ table). The primary outcome was 28-day mortality. Secondary and exploratory outcomes were ventilator-free days, length of ICU stay, incidence of pneumothorax and barotrauma, and difference in Sequential Organ Failure Assessment (SOFA) score at day 1 (ΔD1-SOFA) and day 2 (ΔD2-SOFA) compared with baseline.

Measurements and main results

There was no statistical difference in the value of PEEP between the EIT group and control group, but the combination of PEEP and FiO₂ was different between groups. In the control group, a significantly positive correlation was found between the PEEP value and the corresponding FiO₂ (r = 0.47, p < 0.00001) since a given matched table was used for PEEP settings. Diverse combinations of PEEP and FiO₂ were found in the EIT group (r = 0.05, p = 0.68). There was no significant difference in mortality rate (21% vs. 27%, EIT vs. control, p = 0.63), ICU length of stay (13.0 (7.0, 25.0) vs 10.0 (7.0, 14.8), median (25th–75th percentile); p = 0.17), and ventilator-free days at day 28 (14.0 (2.0, 23.0) vs 19.0 (0.0, 24.0), p = 0.55) between the two groups. The incidence of new barotrauma was zero. Compared with control group, significantly lower ΔD1-SOFA and ΔD2-SOFA were found in the EIT group (p < 0.001) in a post hoc comparison. Moreover, the EIT group exhibited a significant decrease of SOFA at day 2 compared with baseline (paired t-test, difference by − 1 (− 3.5, 0), p = 0.001). However, the control group did show a similar decrease (difference by 1 (− 2, 2), p = 0.131).

Conclusion

Our study showed a 6% absolute decrease in mortality in the EIT group: a statistically non-significant, but clinically non-negligible result. This result along with the showed improvement in organ function might justify further reserach to validate the beneficial effect of individualized EIT-guided PEEP setting on clinical outcomes of patients with ARDS.

Trial registration: ClinicalTrials, NCT02361398. Registered 11 February 2015—prospectively registered, https://clinicaltrials.gov/show/NCT02361398.

Regional ventilation distribution in healthy lungs: can reference values be established for electrical impedance tomography parameters?

Background

Although electrical impedance tomography (EIT) is widely used for monitoring regional ventilation distribution, reference values have yet to be established for clinical use. The present study aimed to evaluate the feasibility of creating reference values for standard EIT parameters for potential clinical application.

Methods

A total of 75 participants with healthy lungs were included in this prospective study (male:female, 48:27; age, 34±14 years; height, 172±7 cm; weight, 73±12 kg). The subjects were examined during spontaneous breathing in the supine position. EIT measurements were performed at the level of the 4^th intercostal space. Commonly used EIT-based parameters, including the center of ventilation (CoV), dorsal and most dorsal fractions of ventilation distribution (TV_D and TV_ROI4 respectively), global inhomogeneity (GI) index, and standard deviation of regional ventilation delay index (RVD_SD) were calculated.

Results

Following outlier detection, EIT data from 71 subjects were finally evaluated. The values of the evaluated parameters were: CoV, 48.7%±1.7%; TVD, 48.1%±5.4%; TV_ROI4, 7.1%±1.8%; GI, 0.49±0.04; and RVD_SD, 7.0±2.0. The coefficients of variation for CoV and GI were low (0.03 and 0.07, respectively), but those for TV_ROI4 and RVD_SD were comparatively high (0.26 and 0.28, respectively). None of the evaluated parameters showed a significant correlation with age. The GI index showed a weak but significant correlation with body mass index (R=0.29, P=0.01). The RVD_SD was slightly higher in males than in females.

Conclusions

Our study indicated that CoV and GI were stable parameters with small coefficients of variation in participants with healthy lungs. The creation of EIT parameter reference values for setting treatment targets may be feasible.

Lung regions identified with CT improve the value of global inhomogeneity index measured with electrical impedance tomography

Background

The global inhomogeneity (GI) index is a functional electrical impedance tomography (EIT) parameter which is used clinically to assess ventilation distribution. However, GI may underestimate the actual heterogeneity when the size of lung regions is underestimated. We propose a novel method to use anatomical information to correct the GI index calculation.

Methods

EIT measurements were performed at the level of the fifth intercostal space in six patients with acute respiratory distress syndrome. The thorax and lungs were segmented automatically from serial individual CT scans. The anatomically derived lung regions were calculated in EIT images from simulating a homogeneous ventilation distribution in a finite element model. The conventional approach (GI_meas,func ), analyzes images in functionally-defined lung regions, while our proposed measure (GI_meas,anat ) is based on analysis in anatomically-defined regions. We additionally define a simulated comparison (GI_sim,anat ) to determine the lower limit of the GI measure for a homogenous distribution of ventilation.

Results

As expected, the conventional GI_meas,func [0.382 (0.088), median (interquartile range)] were significantly lower than the proposed GI_meas,anat [0.823 (0.152), P<0.05], and were much closer to the lower limit GI_sim,anat [0.343 (0.039)]. Both GI_meas,anat and GI_meas,func were strongly correlated with arterial oxygen partial pressure to fractional inspired oxygen ratio (R=-0.88, P<0.05), whereas GI_sim,anat (R=0.23) was not. GI_meas,anat had a linear-regression slope 3.2 times that of GI_meas,func suggesting a higher sensitivity to the changes in lung condition.

Conclusions

The proposed GI_meas,anat (or shortened as GI_anat ) is an improved measure of ventilation inhomogeneity over GI, and better reflects portion of non-ventilated regions due to alveolar collapse or overdistension.

Positive end-expiratory pressure titration with electrical impedance tomography and pressure-volume curve: a randomized trial in moderate to severe ARDS

OBJECTIVE

The aim of the study was to compare titration of positive end-expiratory pressure (PEEP) with electrical impedance tomography (EIT) and with ventilator-embedded pressure-volume (PV) loop in moderate to severe acute respiratory distress syndrome (ARDS).

APPROACH

Eighty-seven moderate to severe ARDS patients (arterial oxygen partial pressure to fractional inspired oxygen ratio, PaO₂/FiO₂ ≤ 200 mmHg) were randomized to either EIT group (n = 42) or PV group (n = 45). All patients received identical medical care using the same general support guidelines and protective mechanical ventilation. In the EIT group, the selected PEEP equaled the airway pressure at the intercept between cumulated collapse and overdistension percentages curves and in the PV group, at the pressure where maximal hysteresis was reached.

MAIN RESULTS

Baseline characteristics and settings were comparable between the groups. After optimization, PEEP was significantly higher in the PV group (17.4 ± 1.7 versus 16.2 ± 2.6 cmH₂O, PV versus EIT groups, p = 0.02). After 48 h, driving pressure was significantly higher in the PV group (12.4 ± 3.6 versus 10.9 ± 2.5 cmH₂O, p = 0.04). Lung mechanics and oxygenation were better in the EIT group but did not statistically differ between the groups. The survival rate was lower in the PV group (44.4% versus 69.0%, p = 0.02; hazard ratio 2.1, confidence interval 1·1-3.9). None of the other pre-specified exploratory clinical endpoints were significantly different.

SIGNIFICANCE

In moderate to severe ARDS, PEEP titration guided with EIT, compared with PV curve, might be associated with improved driving pressure and survival rate.

TRIAL REGISTRATION

NCT03112512, 13 April, 2017.

Virtual patients for mechanical ventilation in the intensive care unit

BACKGROUND

Mechanical ventilation (MV) is a core intensive care unit (ICU) therapy. Significant inter- and intra- patient variability in lung mechanics and condition makes managing MV difficult. Accurate prediction of patient-specific response to changes in MV settings would enable optimised, personalised, and more productive care, improving outcomes and reducing cost. This study develops a generalised digital clone model, or in-silico virtual patient, to accurately predict lung mechanics in response to changes in MV.

METHODS

An identifiable, nonlinear hysteresis loop model (HLM) captures patient-specific lung dynamics identified from measured ventilator data. Identification and creation of the virtual patient model is fully automated using the hysteresis loop analysis (HLA) method to identify lung elastances from clinical data. Performance is evaluated using clinical data from 18 volume-control (VC) and 14 pressure-control (PC) ventilated patients who underwent step-wise recruitment maneuvers.

RESULTS

Patient-specific virtual patient models accurately predict lung response for changes in PEEP up to 12 cmH₂O for both volume and pressure control cohorts. R² values for predicting peak inspiration pressure (PIP) and additional retained lung volume, V_frc in VC, are R²=0.86 and R²=0.90 for 106 predictions over 18 patients. For 14 PC patients and 84 predictions, predicting peak inspiratory volume (PIV) and V_frc yield R²=0.86 and R²=0.83. Absolute PIP, PIV and V_frc errors are relatively small.

CONCLUSIONS

Overall results validate the accuracy and versatility of the virtual patient model for capturing and predicting nonlinear changes in patient-specific lung mechanics. Accurate response prediction enables mechanically and physiologically relevant virtual patients to guide personalised and optimised MV therapy.

Prediction of lung mechanics throughout recruitment maneuvers in pressure-controlled ventilation

Mechanical ventilation (MV) is a core therapy in the intensive care unit (ICU). Some patients rely on MV to support breathing. However, it is a difficult therapy to optimise, where inter- and intra- patient variability leads to significantly increased risk of lung damage. Excessive volume and/or pressure can cause volutrauma or barotrauma, resulting in increased length of time on ventilation, length of stay, cost and mortality. Virtual patient modelling has changed care in other areas of ICU medicine, enabling more personalized and optimal care, and have emerged for volume-controlled MV. This research extends this MV virtual patient model into the increasingly more commonly used pressure-controlled MV mode. The simulation methods are extended to use pressure, instead of both volume and flow, as the known input, increasing the output variables to be predicted (flow and its integral, volume). The model and methods are validated using data from N = 14 pressure-control ventilated patients during recruitment maneuvers, with n = 558 prediction tests over changes of PEEP ranging from 2 to 16 cmH₂O. Prediction errors for peak inspiratory volume for an increase of 16 cmH₂O were 80 [30 - 140] mL (15.9 [8.4 - 31.0]%), with RMS fitting errors of 0.05 [0.03 - 0.12] L. These results show very good prediction accuracy able to guide personalised MV care.

Qualitative and quantitative assessment of pendelluft: a simple method based on electrical impedance tomography

Background

Pendelluft, defined as asynchronous alveolar ventilation, is caused by different regional time constants or dynamic pleural pressure variations. The aim of the present study was to propose a simple method to evaluate pendelluft based on electrical impedance tomography (EIT). The efficacy of this method was demonstrated in well-known pendelluft scenarios in 6 patients.

Methods

Two patients with flail chest after accidents, two patients with acute respiratory distress syndrome (ARDS) and two patients with acutely exacerbated obstructive lung disease were prospectively included. EIT measurements were performed before and after surgery (in patients with flail chest, who had video-assisted thoracoscopic surgery with ribs fixation), or at two different levels of positive end-expiratory pressure (PEEP; ARDS patients), or two different time points (obstructive lung disease). Pendelluft was assessed by regional phase shift (defined as time difference between global and regional impedance-time curves) and amplitude differences (defined as the impedance difference between sum of all regional tidal variation and the global tidal variation).

Results

In patients with flail chest, pendelluft diminished several days after surgery (pendelluft amplitude normalized to tidal impedance variation reduced from 88% to 2% in one patient, 12% to 2% in the other). Increased PEEP reduced the amplitude of pendelluft (from 3% to 0% in one patient, 20% to 2% in the other) but not necessarily the phase shifts (average time differences were <0.1 second for both patients for both ins- and expiration) in ARDS patients. Pendelluft assessment in obstructive lung diseases reflected the change in airway resistance (from 5% to 1% in one patient after broncholytic medication administration, as airway resistance fell from 15 to 11 cmH₂O/L/s; from 9% to 35% in the other patient with acute exacerbation, the corresponding airway resistance increased from 15 to 22 cmH₂O/L/s).

Conclusions

The proposed EIT-based method can be used to evaluate the degree of pendelluft in dimension of phase shift and amplitude difference.

Influence of overdistension/recruitment induced by high positive end-expiratory pressure on ventilation-perfusion matching assessed by electrical impedance tomography with saline bolus

BACKGROUND

High positive end-expiratory pressures (PEEP) may induce overdistension/recruitment and affect ventilation-perfusion matching (VQMatch) in mechanically ventilated patients. This study aimed to investigate the association between PEEP-induced lung overdistension/recruitment and VQMatch by electrical impedance tomography (EIT).

METHODS

The study was conducted prospectively on 30 adult mechanically ventilated patients: 18/30 with ARDS and 12/30 with high risk for ARDS. EIT measurements were performed at zero end-expiratory pressures (ZEEP) and subsequently at high (12-15 cmH2O) PEEP. The number of overdistended pixels over the number of recruited pixels (O/R ratio) was calculated, and the patients were divided into low O/R (O/R ratio < 15%) and high O/R groups (O/R ratio ≥ 15%). The global inhomogeneity (GI) index was calculated to evaluate the ventilation distribution. Lung perfusion image was calculated from the EIT impedance-time curves caused by 10 ml 10% NaCl injection during a respiratory pause (> 8 s). DeadSpace%, Shunt%, and VQMatch% were calculated based on lung EIT perfusion and ventilation images.

RESULTS

Increasing PEEP resulted in recruitment mainly in dorsal regions and overdistension mainly in ventral regions. ΔVQMatch% (VQMatch% at high PEEP minus that at ZEEP) was significantly correlated with recruited pixels (r = 0.468, P = 0.009), overdistended pixels (r = - 0.666, P < 0.001), O/R ratio (r = - 0.686, P < 0.001), and ΔSpO2 (r = 0.440, P = 0.015). Patients in the low O/R ratio group (14/30) had significantly higher Shunt% and lower VQMatch% than those in the high O/R ratio group (16/30) at ZEEP but not at high PEEP. Comparable DeadSpace% was found in both groups. A high PEEP caused a significant improvement of VQMatch%, DeadSpace%, Shunt%, and GI in the low O/R ratio group, but not in the high O/R ratio group. Using O/R ratio of 15% resulted in a sensitivity of 81% and a specificity of 100% for an increase of VQMatch% > 20% in response to high PEEP.

CONCLUSIONS

Change of ventilation-perfusion matching was associated with regional overdistention and recruitment induced by PEEP. A low O/R ratio induced by high PEEP might indicate a more homogeneous ventilation and improvement of VQMatch.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04081155 . Registered on 9 September 2019-retrospectively registered.

A convolutional neural network with a two-stage LSTM model for tool presence detection in laparoscopic videos

Surgical tool presence detection in laparoscopic videos is a challenging problem that plays a critical role in developing context-aware systems in operating rooms (ORs). In this work, we propose a deep learning-based approach for detecting surgical tools in laparoscopic images using a convolutional neural network (CNN) in combination with two long short-term memory (LSTM) models. A pre-trained CNN model was trained to learn visual features from images. Then, LSTM was employed to include temporal information through a video clip of neighbour frames. Finally, the second LSTM was utilized to model temporal dependencies across the whole surgical video. Experimental evaluation has been conducted with the Cholec80 dataset to validate our approach. Results show that the most notable improvement is achieved after employing the two-stage LSTM model, and the proposed approach achieved better or similar performance compared with state-of-the-art methods.

Cheek support affects lung mechanics measurements of tidal-based spontaneous breathing

BACKGROUND AND OBJECTIVE

Patients are required to support their cheeks during breath-occluding lung function tests. This prevents cheek expansion which would alter pressure measured at the mouth, and, consequently, lung mechanics measurements. To date, the effect of cheek support on airway resistance measurements has been assessed. However other lung mechanics have not been studied as thoroughly, and no algorithm to account for the effect of missing cheek support on lung mechanics measurements has been developed.

METHODS

Lung mechanics were assessed with a breath occlusion test during light panting in healthy subjects with and without cheek support in a body plethysmograph. Average model-based airway resistance, lung elastance, and a parameter representing the viscoelastic were measured. Results were compared to quantify the effect of cheek support on these three parameters.

RESULTS

In the nine healthy subjects (5 Female, 4 Male) recruited for this study, all mechanics tended to be underestimated when cheeks were unsupported. Changes in elastance, resistance, and viscoelastic parameter ranged between 1.6-66.8 %, -4.5-21.8 %, and -4.7-68.2 %, respectively, when cheek support was added. The underestimation was due to reduced mouth pressure during cheek expansion when the breath was occluded. The variance of lung mechanics parameters did not change with cheek support in all subjects.

CONCLUSIONS

The error in lung mechanics measurement caused by unsupported cheeks was subject dependent. Hence, no rule-of-thumb could be identified to reconstruct missing cheek support. For correct lung mechanics measurements during breath-occluding lung tests, patients must have adequate cheek support.

ABBREVIATIONS

ROCC: Occlusion resistance; COPD: Chronic Obstructive Pulmonary Disorder; SB: spontaneous breathing.

Sensitivity analysis of a computer model of neonatal oxygen transport

Computer models of neonatal oxygenation could serve as a tool for a comprehensive comparison of closed-loop automated oxygen control systems. The behaviour of such models depends, besides the input data of the inspired fraction of oxygen and the premature infant's breath pattern, on internal parameters of the model. The aim of this study was to perform a sensitivity analysis of a computer model of neonatal oxygen transport to clarify the influence of its internal physiological parameters on the output signal of peripheral oxygen saturation (SpO2). We performed a multi-parameter sensitivity analysis using Monte Carlo simulations for randomly generated values of eight internal parameters. The influence on the model output SpO2 signal was evaluated using five characteristics of the output signal. The relations between the parameters and the output characteristics were displayed using scatter plots and analysed by linear correlation, standardized regression, and partial correlation. The main result of the study is that in our model the oxygen consumption in the tissue and the cardiac output have the greatest influence on the SpO2 drop and minimal SpO2 value during simulated desaturation. The rate of development of desaturation and its duration are most affected by the diffusion resistance of the alveolar-capillary membrane. The results of the sensitivity analysis will help to optimize the performance of the computer model of neonatal oxygen transport.

Developments in Modelling Bone Screwing

INTRODUCTION: A torque-rotation model of the bone-screwing process has been proposed. Identification of model parameters using recorded data could potentially be used to determine the material properties of bone. These properties can then be used to recommend tightening torques to avoid over or under-tightening of bone screws. This paper improves an existing model to formulate it in terms of material properties and remove some assumptions. METHOD: The modelling methodology considers a critical torque, which is required to overcome friction and advance the screw into the bone. Below this torque the screw may rotate with elastic deformation of the bone tissue, and above this the screw moves relative to the bone, and the speed is governed by a speed-torque model of the operator’s hand. The model is formulated in terms of elastic modulus, ultimite tensile strength, and frictional coefficient of the bone and the geometry of the screw and hole. RESULTS: The model output shows the speed decreasing and torque increasing as the screw advances into the bone, due to increasing resistance. The general shape of the torque and speed follow the input effort. Compared with the existing model, this model removes the assumption of viscous friction, models the increase in friction as the screw advances into the bone, and is directly in terms of the bone material properties. CONCLUSION: The model presented makes significant improvements on the existing model. However it is intended for use in parameter identification, which was not evaluated here. Further simulation and experimental validation is required to establish the accuracy and fitness of this model for identifying bone material properties.

Global Inhomogeneity Index Evaluation of a DCT-based EIT Lung Imaging

Purpose: To evaluate a novel structural-functional DCT-based EIT lung imaging method against the classical EIT reconstruction. Method: Taken retrospectively from a former study, EIT data was evaluated using both reconstruction methods. For different phases of ventilation, EIT images are analyzed with respect to the global inhomogeneity (GI) index for comparison. Results: A significant less variant GI index was observed in the DCTbased method, compared to the index from classical method. Conclusion: The DCT-based method generates more accurate lung contour yet decreasing the essential information in the image which affects the GI index. These preliminary results must be consolidated with more patient data in different breathing states.

Data Recording Framework for Physiological and Surgical Data in Operating Theatres

Integrated operating rooms typically connect medical devices providing the clinical user a complete control over environment, device setting and digital management of intervention-related data. Consequently, the opportunity to analyse and present data from different perspectives and with different objectives has arisen. The available integrated ORs are so far designed as closed systems, thus connecting coexisting systems from different manufactures e.g. anaesthesia machines and surgical devices is demanding. The purpose of this project is to facilitate data collection from anaesthesiology, patient monitoring and surgical devices. The study is performed on laparoscopic procedures, and the data are going to be recorded at the Schwarzwald-Baar Klinikum (SBK) in Villingen-Schwenningen (Germany). Therefore, this part of the project focuses on the overall architecture for collecting data in the operating theatre at the SBK. In this work, (i) the system architecture (i.e. hardware components), (ii) software architecture and (iii) required protocols for synchronous recording of data in the OR are described. The proposed framework demonstrates that signal recording is possible with variety of devices at different sampling rates during surgical procedure.

Measuring lung mechanics of expiratory tidal breathing with non-invasive breath occlusion

Background and objective

Lung mechanics measurements provide clinically useful information about disease progression and lung health. Currently, there are no commonly practiced methods to non-invasively measure both resistive and elastic lung mechanics during tidal breathing, preventing the important information provided by lung mechanics from being utilised. This study presents a novel method to easily assess lung mechanics of spontaneously breathing subjects using a dynamic elastance, single-compartment lung model.

Methods

A spirometer with a built-in shutter was used to occlude expiration during tidal breathing, creating exponentially decaying flow when the shutter re-opened. The lung mechanics measured were respiratory system elastance and resistance, separated from the exponentially decaying flow, and interrupter resistance calculated at shutter closure. Progressively increasing resistance was added to the spirometer mouthpiece to simulate upper airway obstruction. The lung mechanics of 17 healthy subjects were successfully measured through spirometry.

Results

N = 17 (8 female, 9 male) healthy subjects were recruited. Measured decay rates ranged from 5 to 42/s, subjects with large variation of decay rates showed higher muscular breathing effort. Lung elastance measurements ranged from 3.9 to 21.2 cmH\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_2$$\end{document}2O/L, with no clear trend between change in elastance and added resistance. Resistance calculated from decay rate and elastance ranged from 0.15 to 1.95 cmH\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_2$$\end{document}2Os/L. These very small resistance values are due to the airflow measured originating from low-resistance areas in the centre of airways. Occlusion resistance measurements were as expected for healthy subjects, and increased as expected as resistance was added.

Conclusions

This test was able to identify reasonable dynamic lung elastance and occlusion resistance values, providing new insight into expiratory breathing effort. Clinically, this lung function test could impact current practice. It does not require high levels of cooperation from the subject, allowing a wider cohort of patients to be assessed more easily. Additionally, this test can be simply implemented in a small standalone device, or with standard lung function testing equipment.

Kernel density estimates for sepsis classification

OBJECTIVE

Severe sepsis is a leading cause of intensive care unit (ICU) admission, length of stay, mortality, and cost. systemic inflammatory response syndrome (SIRS) and organ failure due to infection define it, but also make it hard to diagnose. Early diagnosis reduces morbidity, mortality and cost, and diagnosis is often significantly delayed due to a lack of effective biomarkers. This research employs kernel density estimation (KDE) methods fusing a personalized, model-based insulin sensitivity (SI) metric with standard bedside measures of: temperature, heart rate, respiratory rate, systolic and diastolic blood pressure, and SIRS, as these measures are available hourly or more frequently.

METHODS

Model-based SI is a derived metric, identified using clinical data and a clinically validated metabolic model. The KDE classifier discriminates severe sepsis and septic shock from moderate sepsis using accepted consensus sepsis scores. A best case in-sample estimate, a worst case independent cross validation estimate, and an accepted .632 bootstrap estimate are calculated to assess performance using multi-level likelihood ratios, and sensitivity and specificity. Performance is assessed against clinically and statistically defined thresholds denoted for the minimum acceptable level as: "high accuracy, often providing useful information, and clinical significance," and similar definitions for greater or lesser quality.

RESULTS

The .632 bootstrap estimate performs near clinically defined levels of high accuracy, often providing useful information, and clinical significance based on sensitivity, specificity, and multilevel likelihood ratios.

CONCLUSION AND SIGNIFICANCE

The classifier created and this overall approach is useful for clinical decision making in diagnosing severe sepsis and septic shock in real time, for both case and control hours. However, improvements could be made with larger clinical data sets.

Optimal mean airway pressure during high-frequency oscillatory ventilation in an experimental model of acute respiratory distress syndrome: EIT-based method

Background

High-frequency oscillatory ventilation (HFOV) may theoretically provide lung protective ventilation. The negative clinical results may be due to inadequate mean airway pressure (mPaw) settings in HFOV. Our objective was to evaluate the air distribution, ventilatory and hemodynamic effects of individual mPaw titration during HFOV in ARDS animal based on oxygenation and electrical impedance tomography (EIT).

Methods

ARDS was introduced with repeated bronchoalveolar lavage followed by injurious mechanical ventilation in ten healthy male pigs (51.2 ± 1.9 kg). Settings of HFOV were 9 Hz (respiratory frequency), 33% (inspiratory time) and 70 cmH₂O (∆pressure). After lung recruitment, the mPaw was reduced in steps of 3 cmH₂O every 6 min. Hemodynamics and blood gases were obtained in each step. Regional ventilation distribution was determined with EIT.

Results

PaO₂/FiO₂ decreased significantly during the mPaw decremental phase (p < 0.001). Lung overdistended regions decreased, while recruitable regions increased as mPaw decreased. The optimal mPaw with respect to PaO₂/FiO₂ was 21 (18.0–21.0) cmH₂O, that is comparable to EIT-based center of ventilation (EIT-CoV) and EIT-collapse/over, 19.5 (15.0–21.0) and 19.5 (18.0–21.8), respectively (p = 0.07). EIT-CoV decreasing along with mPaw decrease revealed redistribution toward non-dependent regions. The individual mPaw titrated by EIT-based indices improved regional ventilation distribution with respect to overdistension and collapse (p = 0.035).

Conclusion

Our data suggested personalized optimal mPaw titration by EIT-based indices improves regional ventilation distribution and lung homogeneity during high-frequency oscillatory ventilation.

Regional air trapping in acute exacerbation of obstructive lung diseases measured with electrical impedance tomography: a feasibility study

BACKGROUND

Since bronchial abnormalities often exhibit spatial non-uniformity which may be not correctly assessed by conventional global lung function measures, regional information may help to characterize the disease progress. We hypothesized that regional air trapping during mechanical ventilation could be characterized by regional end-expiratory flow (EEF) derived from electrical impedance tomography (EIT).

METHODS

Twenty-five patients suffering from chronic obstructive pulmonary disease (COPD grade 3 or 4) or severe asthma with acute exacerbation were examined prospectively. Patients were ventilated under assist-control mode. EIT measurements were conducted before and one hour after inhaled combined corticosteroid and long-acting β2 agonist, on two consecutive days. Regional EEF was calculated as derivative of relative impedance for every image pixel in the lung regions. The results were normalized to global flow values measured by the ventilator.

RESULTS

Regional and global EEF were highly correlated (P<0.00001) and regional effects of medication and disease progression were visible in the regional EEF maps. The sums of regional EEF in lung regions were 3.8 [2.0, 5.1] and 3.6 [1.9, 4.5] L/min in COPD patients before and after medication (median [lower, upper quartiles]; P=0.37). The corresponding values in asthma patients were 3.0 [2.5, 4.2] and 2.2 [1.7, 3.2] L/min (P<0.05). Histograms of regional EEF showed high spatial heterogeneity of EEF before medication. After one day of treatment, the histograms exhibited less heterogeneous and a decrease in EEF level.

CONCLUSIONS

Regional EEF characterizes air trapping and intrinsic PEEP, which could provide diagnostic information for monitoring the disease progress during treatment.

Oxygen Therapy Delivery and Body Position Effects Measured With Electrical Impedance Tomography

BACKGROUND

The aim of this prospective randomized crossover study was to compare the short-term effects of high-flow nasal cannula (HFNC) therapy and a 45° head-up tilt to the short-term effects of conventional oxygen (O₂) therapy in post-abdominal surgery patients.

METHODS

A total of 18 subjects who were successfully weaned from ventilator support after abdominal surgery were included in the study. The subjects were randomly assigned to 2 groups: conventional O₂ was applied in group A for 15 min, and HFNC (60 L/min) was applied in group B for 15 min. A 15-min washout period with conventional O₂ was performed before the interventions were switched in both groups. Heart rate, blood pressure, breathing frequency, ratio of arterial partial pressure of oxygen to the fraction of inspired oxygen (P_aO2 /F_IO2 ), and subject-reported comfort scores were recorded. Changes in end-expiratory lung impedance (EELI) were calculated with electrical impedance tomography.

RESULTS

Results are presented as the percent change in lung volume compared to baseline during volume-controlled continuous mandatory ventilation before extubation. HFNC improved EELI in both the ventral (conventional O₂ vs HFNC, -48.2% ± 41.0 vs -30.0% ± 40.3, P < .001) and the dorsal (conventional O₂ vs HFNC, -37.0% ± 75.9 vs -26.5% ± 68.4, P = .02) regions of the lungs. Subjective subject-reported scores indicated that HFNC was more comfortable than conventional O₂ (conventional O₂ vs HFNC, 5.8 ± 1.5 vs 6.9 ± 1.9, P = .02). No differences were found in the other examined parameters. A head-up tilt position with conventional O₂ improved EELI in the dorsal regions (55.9% ± 100.1, P < .001) but not in the ventral regions (-37.9% ± 43.1%, P = .38) of the lungs compared to HFNC or conventional O₂ alone.

CONCLUSIONS

In post-abdominal surgery subjects who had been extubated, HFNC improved lung volume and patient comfort. A head-up tilt position introduced a heterogeneous increase in EELI in the dorsal regions of the lungs. HFNC therapy may be beneficial in this patient group. (ChiCTR1900020886, http://chictr.org.cn).

The incidence and interpretation of large differences in EIT-based measures for PEEP titration in ARDS patients

Positive end-expiratory pressure (PEEP) can be titrated by electrical impedance tomography (EIT). The aim of the present study was to examine the performance of different EIT measures during PEEP trials with the aim of identifying "optimum" PEEP and to provide possible interpretations of largely diverging results. After recruitment (maximum plateau pressure 35 cmH₂O), decremental PEEP trial with steps of 2 cmH₂O and duration of 2 min per step was performed. Ventilation gain and loss, the global inhomogeneity (GI) index, trend of end-expiratory lung impedance (EELI) and regional compliance (C_reg) for estimation of overdistension and collapse were calculated. Largely diverging results of PEEP selection among the measures were defined as differences ≥ 4 PEEP steps (i.e. ≥ 8 cmH₂O). In 30 ARDS patients we examined so far, 3 patients showed significant differences in PEEP selections. Overdistension and collapse estimation based on C_reg tended to select lower PEEP while the GI index and EELI trend suggested higher PEEP settings. Regional inspiration times were heterogeneous indicating that the assumption of a uniform driving pressure in the calculation of C_reg may not be valid. Judging by the predominant ventilation distribution in the most dependent regions, these patients were non-recruitable with the applied recruitment method or pressure levels. The existence of differences in the recommended PEEP among the analyzed EIT measures might be an indicator of non-recruitable lungs and heterogeneous airway resistances. In these extreme cases, the largely diverging results may prompt the attending clinician to develop individual ventilation strategies.Clinical Trial Registration Registration number NCT03112512, https://clinicaltrials.gov/ Registered 13 April 2017.

Model of SpO2 signal of the neonate

The advantages of automatic control of the fraction of inspired oxygen in neonates have been documented in recently published clinical trials. Many control algorithms are available, but their comparison is missing in the literature. A mathematical model of neonatal oxygen transport could be a useful tool to compare and enhance both automatic control algorithms and manual control of fraction of inspired oxygen. Besides other components, the model of neonatal oxygen transport must include a module linking arterial (SaO2) and peripheral (SpO2) oxygen saturation. The pulse oximeter module must reflect issues of SpO2 measurement typical for clinical practice, such as overestimation of SpO2 over SaO2 documented by several studies, or inaccurate pulse oximeter readings due to high noise. The aim of this study was to describe both the bias between SaO2 and SpO2 and the noise, characteristic for continuous SpO2 recording, for a computer model of oxygenation of a premature infant. The SpO2-SaO2 bias, derived from available clinical data, describes a typical deviation of the SpO2 measurement as a function of the true SaO2 value in three different SaO2 intervals. The SpO2 measurement noise was considered as a random process that affects biased SpO2values at each time point with statistical properties estimated from SpO2 continuous recordings of 5 stable newborns. The results of the study will help to adjust a computer model of neonatal oxygenation to the real situations observed in the clinical practice.