A machine-learning regional clustering approach to understand ventilator-induced lung injury: a proof-of-concept experimental study.

BACKGROUND: The spatiotemporal progression and patterns of tissue deformation in ventilator-induced lung injury (VILI) remain understudied. Our aim was to identify lung clusters based on their regional mechanical behavior over space and time in lungs subjected to VILI using machine-learning techniques. RESULTS: Ten anesthetized pigs (27 ± 2 kg) were studied. Eight subjects were analyzed. End-inspiratory and end-expiratory lung computed tomography scans were performed at the beginning and after 12 h of one-hit VILI model. Regional image-based biomechanical analysis was used to determine end-expiratory aeration, tidal recruitment, and volumetric strain for both early and late stages. Clustering analysis was performed using principal component analysis and K-Means algorithms. We identified three different clusters of lung tissue: Stable, Recruitable Unstable, and Non-Recruitable Unstable. End-expiratory aeration, tidal recruitment, and volumetric strain were significantly different between clusters at early stage. At late stage, we found a step loss of end-expiratory aeration among clusters, lowest in Stable, followed by Unstable Recruitable, and highest in the Unstable Non-Recruitable cluster. Volumetric strain remaining unchanged in the Stable cluster, with slight increases in the Recruitable cluster, and strong reduction in the Unstable Non-Recruitable cluster. CONCLUSIONS: VILI is a regional and dynamic phenomenon. Using unbiased machine-learning techniques we can identify the coexistence of three functional lung tissue compartments with different spatiotemporal regional biomechanical behavior.

Mechanical and morphological characterization of the emphysematous lung tissue.

Irreversible alveolar airspace enlargement is the main characteristic of pulmonary emphysema, which has been extensively studied using animal models. While the alterations in lung mechanics associated with these morphological changes have been documented in the literature, the study of the mechanical behavior of parenchymal tissue from emphysematous lungs has been poorly investigated. In this work, we characterize the mechanical and morphological properties of lung tissue in elastase-induced emphysema rat models under varying severity conditions. We analyze the non-linear tissue behavior using suitable hyperelastic constitutive models that enable to compare different non-linear responses in terms of hyperelastic material parameters. We further analyze the effect of the elastase dose on alveolar morphology and tissue material parameters and study their connection with respiratory-system mechanical parameters. Our results show that while the lung mechanical function is not significantly influenced by the elastase treatment, the tissue mechanical behavior and alveolar morphology are markedly affected by it. We further show a strong association between alveolar enlargement and tissue softening, not evidenced by respiratory-system compliance. Our findings highlight the importance of understanding tissue mechanics in emphysematous lungs, as changes in tissue properties could detect the early stages of emphysema remodeling. STATEMENT OF SIGNIFICANCE: Gas exchange is vital for life and strongly relies on the mechanical function of the lungs. Pulmonary emphysema is a prevalent respiratory disease where alveolar walls are damaged, causing alveolar enlargement that induces harmful changes in the mechanical response of the lungs. In this work, we study how the mechanical properties of lung tissue change during emphysema. Our results from animal models show that tissue properties are more sensitive to alveolar enlargement due to emphysema than other mechanical properties that describe the function of the whole respiratory system.

WarpPINN: Cine-MR image registration with physics-informed neural networks.

The diagnosis of heart failure usually includes a global functional assessment, such as ejection fraction measured by magnetic resonance imaging. However, these metrics have low discriminate power to distinguish different cardiomyopathies, which may not affect the global function of the heart. Quantifying local deformations in the form of cardiac strain can provide helpful information, but it remains a challenge. In this work, we introduce WarpPINN, a physics-informed neural network to perform image registration to obtain local metrics of heart deformation. We apply this method to cine magnetic resonance images to estimate the motion during the cardiac cycle. We inform our neural network of the near-incompressibility of cardiac tissue by penalizing the Jacobian of the deformation field. The loss function has two components: an intensity-based similarity term between the reference and the warped template images, and a regularizer that represents the hyperelastic behavior of the tissue. The architecture of the neural network allows us to easily compute the strain via automatic differentiation to assess cardiac activity. We use Fourier feature mappings to overcome the spectral bias of neural networks, allowing us to capture discontinuities in the strain field. The algorithm is tested on synthetic examples and on a cine SSFP MRI benchmark of 15 healthy volunteers, where it is trained to learn the deformation mapping of each case. We outperform current methodologies in landmark tracking and provide physiological strain estimations in the radial and circumferential directions. WarpPINN provides precise measurements of local cardiac deformations that can be used for a better diagnosis of heart failure and can be used for general image registration tasks. Source code is available at https://github.com/fsahli/WarpPINN.

Morphometric analysis of airways in pre-COPD and mild COPD lungs using continuous surface representations of the bronchial lumen.

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory disease that presents a high rate of underdiagnosis during onset and early stages. Studies have shown that in mild COPD patients, remodeling of the small airways occurs concurrently with morphological changes in the proximal airways. Despite this evidence, the geometrical study of the airway tree from computed tomography (CT) lung images remains underexplored due to poor representations and limited tools to characterize the airway structure. Methods: We perform a comprehensive morphometric study of the proximal airways based on geometrical measures associated with the different airway generations. To this end, we leverage the geometric flexibility of the Snakes IsoGeometric Analysis method to accurately represent and characterize the airway luminal surface and volume informed by CT images of the respiratory tree. Based on this framework, we study the airway geometry of smoking pre-COPD and mild COPD individuals. Results: Our results show a significant difference between groups in airway volume, length, luminal eccentricity, minimum radius, and surface-area-to-volume ratio in the most distal airways. Discussion: Our findings suggest a higher degree of airway narrowing and collapse in COPD patients when compared to pre-COPD patients. We envision that our work has the potential to deliver a comprehensive tool for assessing morphological changes in airway geometry that take place in the early stages of COPD.

Whole-lung finite-element models for mechanical ventilation and respiratory research applications.

Mechanical ventilation has been a vital treatment for Covid-19 patients with respiratory failure. Lungs assisted with mechanical ventilators present a wide variability in their response that strongly depends on air-tissue interactions, which motivates the creation of simulation tools to enhance the design of ventilatory protocols. In this work, we aim to create anatomical computational models of the lungs that predict clinically-relevant respiratory variables. To this end, we formulate a continuum poromechanical framework that seamlessly accounts for the air-tissue interaction in the lung parenchyma. Based on this formulation, we construct anatomical finite-element models of the human lungs from computed-tomography images. We simulate the 3D response of lungs connected to mechanical ventilation, from which we recover physiological parameters of high clinical relevance. In particular, we provide a framework to estimate respiratory-system compliance and resistance from continuum lung dynamic simulations. We further study our computational framework in the simulation of the supersyringe method to construct pressure-volume curves. In addition, we run these simulations using several state-of-the-art lung tissue models to understand how the choice of constitutive models impacts the whole-organ mechanical response. We show that the proposed lung model predicts physiological variables, such as airway pressure, flow and volume, that capture many distinctive features observed in mechanical ventilation and the supersyringe method. We further conclude that some constitutive lung tissue models may not adequately capture the physiological behavior of lungs, as measured in terms of lung respiratory-system compliance. Our findings constitute a proof of concept that finite-element poromechanical models of the lungs can be predictive of clinically-relevant variables in respiratory medicine.

Fully Three-Dimensional Hemodynamic Characterization of Altered Blood Flow in Bicuspid Aortic Valve Patients With Respect to Aortic Dilatation: A Finite Element Approach.

Background and Purpose: Prognostic models based on cardiovascular hemodynamic parameters may bring new information for an early assessment of patients with bicuspid aortic valve (BAV), playing a key role in reducing the long-term risk of cardiovascular events. This work quantifies several three-dimensional hemodynamic parameters in different patients with BAV and ranks their relationships with aortic diameter. Materials and Methods: Using 4D-flow CMR data of 74 patients with BAV (49 right-left and 25 right-non-coronary) and 48 healthy volunteers, aortic 3D maps of seventeen 17 different hemodynamic parameters were quantified along the thoracic aorta. Patients with BAV were divided into two morphotype categories, BAV-Non-AAoD (where we include 18 non-dilated patients and 7 root-dilated patients) and BAV-AAoD (where we include the 49 patients with dilatation of the ascending aorta). Differences between volunteers and patients were evaluated using MANOVA with Pillai's trace statistic, Mann-Whitney U test, ROC curves, and minimum redundancy maximum relevance algorithm. Spearman's correlation was used to correlate the dilation with each hemodynamic parameter. Results: The flow eccentricity, backward velocity, velocity angle, regurgitation fraction, circumferential wall shear stress, axial vorticity, and axial circulation allowed to discriminate between volunteers and patients with BAV, even in the absence of dilation. In patients with BAV, the diameter presented a strong correlation (> |+/-0.7|) with the forward velocity and velocity angle, and a good correlation (> |+/-0.5|) with regurgitation fraction, wall shear stress, wall shear stress axial, and vorticity, also for morphotypes and phenotypes, some of them are correlated with the diameter. The velocity angle proved to be an excellent biomarker in the differentiation between volunteers and patients with BAV, BAV morphotypes, and BAV phenotypes, with an area under the curve bigger than 0.90, and higher predictor important scores. Conclusions: Through the application of a novel 3D quantification method, hemodynamic parameters related to flow direction, such as flow eccentricity, velocity angle, and regurgitation fraction, presented the best relationships with a local diameter and effectively differentiated patients with BAV from healthy volunteers.

Distribution and Magnitude of Regional Volumetric Lung Strain and Its Modification by PEEP in Healthy Anesthetized and Mechanically Ventilated Dogs.

The present study describes the magnitude and spatial distribution of lung strain in healthy anesthetized, mechanically ventilated dogs with and without positive end-expiratory pressure (PEEP). Total lung strain (LSTOTAL) has a dynamic (LSDYNAMIC) and a static (LSSTATIC) component. Due to lung heterogeneity, global lung strain may not accurately represent regional total tissue lung strain (TSTOTAL), which may also be described by a regional dynamic (TSDYNAMIC) and static (TSSTATIC) component. Six healthy anesthetized beagles (12.4 ± 1.4 kg body weight) were placed in dorsal recumbency and ventilated with a tidal volume of 15 ml/kg, respiratory rate of 15 bpm, and zero end-expiratory pressure (ZEEP). Respiratory system mechanics and full thoracic end-expiratory and end-inspiratory CT scan images were obtained at ZEEP. Thereafter, a PEEP of 5 cmH2O was set and respiratory system mechanics measurements and end-expiratory and end-inspiratory images were repeated. Computed lung volumes from CT scans were used to evaluate the global LSTOTAL, LSDYNAMIC, and LSSTATIC during PEEP. During ZEEP, LSSTATIC was assumed zero; therefore, LSTOTAL was the same as LSDYNAMIC. Image segmentation was applied to CT images to obtain maps of regional TSTOTAL, TSDYNAMIC, and TSSTATIC during PEEP, and TSDYNAMIC during ZEEP. Compliance increased (p = 0.013) and driving pressure decreased (p = 0.043) during PEEP. PEEP increased the end-expiratory lung volume (p < 0.001) and significantly reduced global LSDYNAMIC (33.4 ± 6.4% during ZEEP, 24.0 ± 4.6% during PEEP, p = 0.032). LSSTATIC by PEEP was larger than the reduction in LSDYNAMIC; therefore, LSTOTAL at PEEP was larger than LSDYNAMIC at ZEEP (p = 0.005). There was marked topographic heterogeneity of regional strains. PEEP induced a significant reduction in TSDYNAMIC in all lung regions (p < 0.05). Similar to global findings, PEEP-induced TSSTATIC was larger than the reduction in TSDYNAMIC; therefore, PEEP-induced TSTOTAL was larger than TSDYNAMIC at ZEEP. In conclusion, PEEP reduced both global and regional estimates of dynamic strain, but induced a large static strain. Given that lung injury has been mostly associated with tidal deformation, limiting dynamic strain may be an important clinical target in healthy and diseased lungs, but this requires further study.

Determination of the Respiratory Compensation Point by Detecting Changes in Intercostal Muscles Oxygenation by Using Near-Infrared Spectroscopy.

This study aimed to evaluate if the changes in oxygen saturation levels at intercostal muscles (SmO2-m.intercostales) assessed by near-infrared spectroscopy (NIRS) using a wearable device could determine the respiratory compensation point (RCP) during exercise. Fifteen healthy competitive triathletes (eight males; 29 ± 6 years; height 167.6 ± 25.6 cm; weight 69.2 ± 9.4 kg; V˙O2-máx 58.4 ± 8.1 mL·kg−1·min−1) were evaluated in a cycle ergometer during the maximal oxygen-uptake test (V˙O2-máx), while lung ventilation (V˙E), power output (watts, W) and SmO2-m.intercostales were measured. RCP was determined by visual method (RCPvisual: changes at ventilatory equivalents (V˙E·V˙CO2−1, V˙E·V˙O2−1) and end-tidal respiratory pressure (PetO2, PetCO2) and NIRS method (RCPNIRS: breakpoint of fall in SmO2-m.intercostales). During exercise, SmO2-m.intercostales decreased continuously showing a higher decrease when V˙E increased abruptly. A good agreement between methods used to determine RCP was found (visual vs NIRS) at %V˙O2-máx, V˙O2, V˙E, and W (Bland-Altman test). Correlations were found to each parameters analyzed (r = 0.854; r = 0.865; r = 0.981; and r = 0,968; respectively. p < 0.001 in all variables, Pearson test), with no differences (p < 0.001 in all variables, Student's t-test) between methods used (RCPvisual and RCPNIRS). We concluded that changes at SmO2-m.intercostales measured by NIRS could adequately determine RCP in triathletes.

Three-Dimensional Whole-Organ Characterization of the Regional Alveolar Morphology in Normal Murine Lungs.

Alveolar architecture plays a fundamental role in the processes of ventilation and perfusion in the lung. Alterations in the alveolar surface area and alveolar cavity volume constitute the pathophysiological basis of chronic respiratory diseases such as pulmonary emphysema. Previous studies based on micro-computed tomography (micro-CT) of lung samples have allowed the geometrical study of acinar units. However, our current knowledge is based on the study of a few tissue samples in random locations of the lung that do not give an account of the spatial distributions of the alveolar architecture in the whole lung. In this work, we combine micro-CT imaging and computational geometry algorithms to study the regional distribution of key morphological parameters throughout the whole lung. To this end, 3D whole-lung images of Sprague-Dawley rats are acquired using high-resolution micro-CT imaging and analyzed to estimate porosity, alveolar surface density, and surface-to-volume ratio. We assess the effect of current gold-standard dehydration methods in the preparation of lung samples and propose a fixation protocol that includes the application of a methanol-PBS solution before dehydration. Our results show that regional porosity, alveolar surface density, and surface-to-volume ratio have a uniform distribution in normal lungs, which do not seem to be affected by gravitational effects. We further show that sample fixation based on ethanol baths for dehydration introduces shrinking and affects the acinar architecture in the subpleural regions. In contrast, preparations based on the proposed dehydration protocol effectively preserve the alveolar morphology.

Evaluation of Lung Aeration and Respiratory System Mechanics in Obese Dogs Ventilated With Tidal Volumes Based on Ideal vs. Current Body Weight.

We describe the respiratory mechanics and lung aeration in anesthetized obese dogs ventilated with tidal volumes (VT) based on ideal (VTi) vs. current (VTc) body weight. Six dogs with body condition scores ≥ 8/9 were included. End-expiratory respiratory mechanics and end-expiratory CT-scan were obtained at baseline for each dog. Thereafter, dogs were ventilated with VT 15 ml kg-1 based on VTi and VTc, applied randomly. Respiratory mechanics and CT-scan were repeated at end-inspiration during VTi and VTc. Data analyzed with linear mixed models and reported as mean ± SD or median [range]. Statistical significance p < 0.05. The elastance of the lung, chest wall and respiratory system indexed by ideal body weight (IBW) were positively correlated with body fat percentage, whereas the functional residual capacity indexed by IBW was negatively correlated with body fat percentage. At end-expiration, aeration (%) was: hyperaeration 0.03 [0.00-3.35], normoaeration 69.7 [44.6-82.2], hypoaeration 29.3 [13.6-49.4] and nonaeration (1.06% [0.37-6.02]). Next to the diaphragm, normoaeration dropped to 12 ± 11% and hypoaeration increased to 90 ± 8%. No differences in aeration between groups were found at end-inspiration. Airway driving pressure (cm H2O) was higher (p = 0.002) during VTc (9.8 ± 0.7) compared with VTi (7.6 ± 0.4). Lung strain was higher (p = 0.014) during VTc (55 ± 21%) than VTi (38 ± 10%). The stress index was higher (p = 0.012) during VTc (SI = 1.07 [0.14]) compared with VTi (SI = 0.93 [0.18]). This study indicates that body fat percentage influences the magnitude of lung, chest wall, and total respiratory system elastance and resistance, as well as functional residual capacity. Further, these results indicate that obese dogs have extensive areas of hypoaerated lungs, especially in caudodorsal regions. Finally, lung strain and airway driving pressure, surrogates of lung deformation, are higher during VTc than during VTi, suggesting that in obese anesthetized dogs, ventilation protocols based on IBW may be advantageous.

Estimation of changes in cyclic lung strain by electrical impedance tomography: Proof-of-concept study.

RATIONALE: Cyclic strain may be a determinant of ventilator-induced lung injury. The standard for strain assessment is the computed tomography (CT), which does not allow continuous monitoring and exposes to radiation. Electrical impedance tomography (EIT) is able to monitor changes in regional lung ventilation. In addition, there is a correlation between mechanical deformation of materials and detectable changes in its electrical impedance, making EIT a potential surrogate for cyclic lung strain measured by CT (StrainCT ). OBJECTIVES: To compare the global StrainCT with the change in electrical impedance (ΔZ). METHODS: Acute respiratory distress syndrome patients under mechanical ventilation (VT 6 mL/kg ideal body weight with positive end-expiratory pressure 5 [PEEP 5] and best PEEP according to EIT) underwent whole-lung CT at end-inspiration and end-expiration. Biomechanical analysis was used to construct 3D maps and determine StrainCT at different levels of PEEP. CT and EIT acquisitions were performed simultaneously. Multilevel analysis was employed to determine the causal association between StrainCT and ΔZ. Linear regression models were used to predict the change in lung StrainCT between different PEEP levels based on the change in ΔZ. MAIN RESULTS: StrainCT was positively and independently associated with ΔZ at global level (P < .01). Furthermore, the change in StrainCT (between PEEP 5 and Best PEEP) was accurately predicted by the change in ΔZ (R2 0.855, P < .001 at global level) with a high agreement between predicted and measured StrainCT . CONCLUSIONS: The change in electrical impedance may provide a noninvasive assessment of global cyclic strain, without radiation at bedside.

Progression of regional lung strain and heterogeneity in lung injury: assessing the evolution under spontaneous breathing and mechanical ventilation.

BACKGROUND: Protective mechanical ventilation (MV) aims at limiting global lung deformation and has been associated with better clinical outcomes in acute respiratory distress syndrome (ARDS) patients. In ARDS lungs without MV support, the mechanisms and evolution of lung tissue deformation remain understudied. In this work, we quantify the progression and heterogeneity of regional strain in injured lungs under spontaneous breathing and under MV. METHODS: Lung injury was induced by lung lavage in murine subjects, followed by 3 h of spontaneous breathing (SB-group) or 3 h of low Vt mechanical ventilation (MV-group). Micro-CT images were acquired in all subjects at the beginning and at the end of the ventilation stage following induction of lung injury. Regional strain, strain progression and strain heterogeneity were computed from image-based biomechanical analysis. Three-dimensional regional strain maps were constructed, from which a region-of-interest (ROI) analysis was performed for the regional strain, the strain progression, and the strain heterogeneity. RESULTS: After 3 h of ventilation, regional strain levels were significantly higher in 43.7% of the ROIs in the SB-group. Significant increase in regional strain was found in 1.2% of the ROIs in the MV-group. Progression of regional strain was found in 100% of the ROIs in the SB-group, whereas the MV-group displayed strain progression in 1.2% of the ROIs. Progression in regional strain heterogeneity was found in 23.4% of the ROIs in the SB-group, while the MV-group resulted in 4.7% of the ROIs showing significant changes. Deformation progression is concurrent with an increase of non-aerated compartment in SB-group (from 13.3% ± 1.6% to 37.5% ± 3.1%), being higher in ventral regions of the lung. CONCLUSIONS: Spontaneous breathing in lung injury promotes regional strain and strain heterogeneity progression. In contrast, low Vt MV prevents regional strain and heterogeneity progression in injured lungs.

A physiological approach to understand the role of respiratory effort in the progression of lung injury in SARS-CoV-2 infection.

Deterioration of lung function during the first week of COVID-19 has been observed when patients remain with insufficient respiratory support. Patient self-inflicted lung injury (P-SILI) is theorized as the responsible, but there is not robust experimental and clinical data to support it. Given the limited understanding of P-SILI, we describe the physiological basis of P-SILI and we show experimental data to comprehend the role of regional strain and heterogeneity in lung injury due to increased work of breathing.In addition, we discuss the current approach to respiratory support for COVID-19 under this point of view.

In-silico study of the cardiac arrhythmogenic potential of biomaterial injection therapy.

Biomaterial injection is a novel therapy to treat ischemic heart failure (HF) that has shown to reduce remodeling and restore cardiac function in recent preclinical studies. While the effect of biomaterial injection in reducing mechanical wall stress has been recently demonstrated, the influence of biomaterials on the electrical behavior of treated hearts has not been elucidated. In this work, we developed computational models of swine hearts to study the electrophysiological vulnerability associated with biomaterial injection therapy. The propagation of action potentials on realistic biventricular geometries was simulated by numerically solving the monodomain electrophysiology equations on anatomically-detailed models of normal, HF untreated, and HF treated hearts. Heart geometries were constructed from high-resolution magnetic resonance images (MRI) where the healthy, peri-infarcted, infarcted and gel regions were identified, and the orientation of cardiac fibers was informed from diffusion-tensor MRI. Regional restitution properties in each case were evaluated by constructing a probability density function of the action potential duration (APD) at different cycle lengths. A comparative analysis of the ventricular fibrillation (VF) dynamics for every heart was carried out by measuring the number of filaments formed after wave braking. Our results suggest that biomaterial injection therapy does not affect the regional dispersion of repolarization when comparing untreated and treated failing hearts. Further, we found that the treated failing heart is more prone to sustain VF than the normal heart, and is at least as susceptible to sustained VF as the untreated failing heart. Moreover, we show that the main features of VF dynamics in a treated failing heart are not affected by the level of electrical conductivity of the biogel injectates. This work represents a novel proof-of-concept study demonstrating the feasibility of computer simulations of the heart in understanding the arrhythmic behavior in novel therapies for HF.

Non-ohmic tissue conduction in cardiac electrophysiology: Upscaling the non-linear voltage-dependent conductance of gap junctions.

Gap junctions are key mediators of intercellular communication in cardiac tissue, and their function is vital to sustaining normal cardiac electrical activity. Conduction through gap junctions strongly depends on the hemichannel arrangement and transjunctional voltage, rendering the intercellular conductance highly non-Ohmic, particularly under steady-state regimes of conduction. Despite this marked non-linear behavior, current tissue-level models of cardiac conduction are rooted in the assumption that gap-junctions conductance is constant (Ohmic), which results in inaccurate predictions of electrical propagation, particularly in the low junctional-coupling regime observed under pathological conditions. In this work, we present a novel non-Ohmic homogenization model (NOHM) of cardiac conduction that is suitable to tissue-scale simulations. Using non-linear homogenization theory, we develop a conductivity model that seamlessly upscales the voltage-dependent conductance of gap junctions, without the need of explicitly modeling gap junctions. The NOHM model allows for the simulation of electrical propagation in tissue-level cardiac domains that accurately resemble that of cell-based microscopic models for a wide range of junctional coupling scenarios, recovering key conduction features at a fraction of the computational complexity. A unique feature of the NOHM model is the possibility of upscaling the response of non-symmetric gap-junction conductance distributions, which result in conduction velocities that strongly depend on the direction of propagation, thus allowing to model the normal and retrograde conduction observed in certain regions of the heart. We envision that the NOHM model will enable organ-level simulations that are informed by sub- and inter-cellular mechanisms, delivering an accurate and predictive in-silico tool for understanding the heart function. Codes are available for download at https://github.com/dehurtado/NonOhmicConduction.

Non-invasive continuous respiratory monitoring using temperature-based sensors.

Respiratory rate (RR) is a key vital sign that has been traditionally employed in the clinical assessment of patients and in the prevention of respiratory compromise. Despite its relevance, current practice for monitoring RR in non-intubated patients strongly relies on visual counting, which delivers an intermittent and error-prone assessment of the respiratory status. Here, we present a novel non-invasive respiratory monitor that continuously measures the RR in human subjects. The respiratory activity of the user is inferred by sensing the thermal transfer between the breathing airflow and a temperature sensor placed between the nose and the mouth. The performance of the respiratory monitor is assessed through respiratory experiments performed on healthy subjects. Under spontaneous breathing, the mean RR difference between our respiratory monitor and visual counting was 0.4 breaths per minute (BPM), with a 95% confidence interval equal to [- 0.5, 1.3] BPM. The robustness of the respiratory sensor to the position is assessed by studying the signal-to-noise ratio in different locations on the upper lip, displaying a markedly better performance than traditional thermal sensors used for respiratory airflow measurements.

Low and Oscillatory Wall Shear Stress Is Not Related to Aortic Dilation in Patients With Bicuspid Aortic Valve: A Time-Resolved 3-Dimensional Phase-Contrast Magnetic Resonance Imaging Study.

OBJECTIVE: To assess the relationship between regional wall shear stress (WSS) and oscillatory shear index (OSI) and aortic dilation in patients with bicuspid aortic valve (BAV). Approach and Results: Forty-six consecutive patients with BAV (63% with right-left-coronary-cusp fusion, aortic diameter ≤ 45 mm and no severe valvular disease) and 44 healthy volunteers were studied by time-resolved 3-dimensional phase-contrast magnetic resonance imaging. WSS and OSI were quantified at different levels of the ascending aorta and the aortic arch, and regional WSS and OSI maps were obtained. Seventy percent of BAV had ascending aorta dilation. Compared with healthy volunteers, patients with BAV had increased WSS and decreased OSI in most of the ascending aorta and the aortic arch. In both BAV and healthy volunteers, regions of high WSS matched regions of low OSI and vice versa. No regions of both low WSS and high OSI were identified in BAV compared with healthy volunteers. Patients with BAV with dilated compared with nondilated aorta presented low and oscillatory WSS in the aortic arch, but not in the ascending aorta where dilation is more prevalent. Furthermore, no regions of concomitant low WSS and high OSI were identified when BAV were compared according to leaflet fusion pattern, despite the well-known differences in regional dilation prevalence. CONCLUSIONS: Regions with low WSS and high OSI do not match those with the highest prevalence of dilation in patients with BAV, thus providing no evidence to support the low and oscillatory shear stress theory in the pathogenesis of proximal aorta dilation in the presence of BAV.

Mapping regional strain in anesthetised healthy subjects during spontaneous ventilation.

Introduction: Breathing produces a phenomenon of cyclic deformation throughout life. Biomechanically, deformation of the lung is measured as strain. Regional strain recently started to be recognised as a tool in the study of lung pathophysiology, but regional lung strain has not been studied in healthy subjects breathing spontaneously without voluntary or pharmacological control of ventilation. Our aim is to generate three-dimensional (3D) regional strain and heterogeneity maps of healthy rat lungs and describe their changes over time. Methods: Micro-CT and image-based biomechanical analysis by finite element approach were carried out in six anaesthetised rats under spontaneous breathing in two different states, at the beginning of the experiment and after 3 hours of observation. 3D regional strain maps were constructed and divided into 10 isovolumetric region-of-interest (ROI) in three directions (apex to base, dorsal to ventral and costal to mediastinal), allowing to regionally analyse the volumetric strain, the strain progression and the strain heterogeneity. To describe in depth these parameters, and systematise their report, we defined regional strain heterogeneity index [1+strain SD ROI(x)]/[1+strain mean ROI(x)] and regional strain progression index [ROI(x)-mean of final strain/ROI(x)-mean of initial strain]. Results: We were able to generate 3D regional strain maps of the lung in subjects without respiratory support, showing significant differences among the three analysed axes. We observed a significantly lower regional volumetric strain in the apex sector compared with the base, with no significant anatomical systematic differences in the other directions. This heterogeneity could not be identified with physiological or standard CT methods. There was no progression of the analysed regional volumetric strain when the two time-points were compared. Discussion: It is possible to map the regional volumetric strain in the lung for healthy subjects during spontaneous breathing. Regional strain heterogeneity and changes over time can be measured using a CT image-based numerical analysis applying a finite element approach. These results support that healthy lung might have significant regional strain and its spatial distribution is highly heterogeneous. This protocol for CT image acquisition and analysis could be a useful tool for helping to understand the mechanobiology of the lung in many diseases.

The role of three-dimensionality and alveolar pressure in the distribution and amplification of alveolar stresses.

Alveolar stresses are fundamental to enable the respiration process in mammalians and have recently gained increasing attention due to their mechanobiological role in the pathogenesis and development of respiratory diseases. Despite the fundamental physiological role of stresses in the alveolar wall, the determination of alveolar stresses remains challenging, and our current knowledge is largely drawn from 2D studies that idealize the alveolar septal wall as a spring or a planar continuum. Here we study the 3D stress distribution in alveolar walls of normal lungs by combining ex-vivo micro-computed tomography and 3D finite-element analysis. Our results show that alveolar walls are subject to a fully 3D state of stresses rather than to a pure axial stress state. To understand the contributions of the different components and deformation modes, we decompose the stress tensor field into hydrostatic and deviatoric components, which are associated with isotropic and distortional stresses, respectively. Stress concentrations arise in localized regions of the alveolar microstructure, with magnitudes that can be up to 27 times the applied alveolar pressure. Interestingly, we show that the stress amplification factor strongly depends on the level of alveolar pressure, i.e, stresses do not scale proportional to the applied alveolar pressure. In addition, we show that 2D techniques to assess alveolar stresses consistently overestimate the stress magnitude in alveolar walls, particularly for lungs under high transpulmonary pressure. These findings take particular relevance in the study of stress-induced remodeling of the emphysematous lung and in ventilator-induced lung injury, where the relation between transpulmonary pressure and alveolar wall stress is key to understand mechanotransduction processes in pneumocytes.