Correlation between alveolar ventilation and electrical properties of lung parenchyma

A novel two-dimensional phantom for electrical impedance tomography using 3D printing

Electrical impedance tomography (EIT) is an imaging method that can be used to image electrical impedance contrasts within various tissues of the body. To support development of EIT measurement systems, a phantom is required that represents the electrical characteristics of the imaging domain. No existing type of EIT phantom combines good performance in all three characteristics of resistivity resolution, spatial resolution, and stability. Here, a novel EIT phantom concept is proposed that uses 3D printed conductive material. Resistivity is controlled using the 3D printing infill percentage parameter, allowing arbitrary resistivity contrasts within the domain to be manufactured automatically. The concept of controlling resistivity through infill percentage is validated, and the manufacturing accuracy is quantified. A method for making electrical connections to the 3D printed material is developed. Finally, a prototype phantom is printed, and a sample EIT analysis is performed. The resulting phantom, printed with an Ultimaker S3, has high reported spatial resolution of 6.9 µm, 6.9 µm, and 2.5 µm for X, Y, and Z axis directions, respectively (X and Y being the horizontal axes, and Z the vertical). The number of resistivity levels that are manufacturable by varying infill percentage is 15 (calculated by dividing the available range of resistivities by two times the standard deviation of the manufacturing accuracy). This phantom construction technique will allow assessment of the performance of EIT devices under realistic physiological scenarios.

Real-Time Identification of Upper Airway Occlusion Using Electrical Impedance Tomography

STUDY OBJECTIVES

Real-time monitoring of upper airway collapse during sleep could be instrumental for studies in biomechanics of obstructive sleep apnea (OSA) and selecting individualized treatment modalities. Although some imaging techniques are used under sedated sleep, none are available during the entire natural sleep process. We hypothesized that electrical impedance tomography (EIT) can be used for noninvasive continuous imaging of the upper airway during natural sleep and quantifying upper airway collapse in terms of its size.

METHODS

After determining surface landmarks to attach the electrodes for monitoring the retroglossal airway, EIT was conducted in 10 healthy participants. As a feasibility test of EIT in detecting upper airway collapse, transient airway closure was induced by the swallowing maneuver. These EIT images were confirmed by simultaneous magnetic resonance imaging (MRI) scans. Subsequently, EIT scans were conducted in 7 healthy participants and 10 patients with OSA under nonsedated sleep to determine whether it could identify upper airway narrowing or collapse. Respiratory events were identified by concurrent polysomnography (PSG).

RESULTS

Swallowing-induced airway closure was identified successfully in all 10 participants on simultaneous EIT and MRI scans. Sizes and positions of the upper airway closures in reconstructed EIT images were well correlated with those in magnetic resonance images. Obstructive hypopnea and apnea were detected successfully by EIT in 10 patients with OSA, and no significant changes in EIT data were observed in 7 healthy participants during concurrent EIT and PSG tests. Additionally, conductivity changes in the airway were greater during obstructive apnea than during hypopnea (64.3% versus 26.3%, respectively; P < .001) compared with those during baseline respiration.

CONCLUSIONS

EIT could be a useful real-time monitoring device for detecting upper airway narrowing or collapse during natural sleep in patients with OSA. Currently, changes in the upper airway size can be estimated with good accuracy, but shape estimation needs future improvements in the EIT image quality.

Perflubron Distribution During Transition From Gas to Total Liquid Ventilation

Total liquid ventilation (TLV) using perfluorocarbons has shown promising results for the management of neonatal respiratory distress. However, one important safety consideration for TLV is a better understanding of the early events during the transition to TLV, especially regarding the fate of residual air in the non-dependent-lung regions. Our objective was to assess perflubron distribution during transition to TLV using electrical impedance tomography, complemented by fluoroscopy, in a neonatal lamb model of induced surfactant deficiency. Eight lambs were anesthetized and ventilated in supine position. Surfactant deficit was induced by saline lung lavage. After deflation, lungs were filled with 25 ml/kg perflubron over 18 s, and TLV was initiated. Electrical impedance tomography data was recorded from electrodes placed around the chest, during the first 10 and at 120 min of TLV. Lung perfusion was also assessed using hypertonic saline injection during apnea. In addition, fluoroscopic sequences were recorded during initial lung filling with perfluorocarbons, then at 10 and 60 min of TLV. Twelve lambs were used as controls for histological comparisons. Transition to TLV involved a short period of increased total lung volume (p = 0.01) secondary to recruitment of the dependent lung regions. Histological analysis shows that TLV was protective of these same regions when compared to gas-ventilated lambs (p = 0.03). The non-dependent lung regions filled with perflubron over at least 10 min, without showing signs of overdistention. Tidal volume distribution was more homogenous in TLV than during the preceding gas ventilation. Perflubron filling was associated with a non-significant increase in the anterior distribution of the blood perfusion signal, from 46 ± 17% to 53 ± 6% (p = 0.4). However, combined to the effects on ventilation, TLV had an instantaneous effect on ventilation-perfusion relationship (p = 0.03), suggesting better coupling. Conclusion: transition to TLV requires at least 10 min, and involves air evacuation or dissolution in perflubron, dependent lung recruitment and rapid ventilation-perfusion coupling modifications. During that time interval, the total lung volume transiently increases. Considering the potential deleterious effect of high lung volumes, one must manage this transition phase with care and, we suggest using a real-time monitoring system such as electrical impedance tomography.

Weaning from Mechanical Ventilation in ARDS: Aspects to Think about for Better Understanding, Evaluation, and Management

Acute respiratory distress syndrome (ARDS) is characterized by severe inflammatory response and hypoxemia. The use of mechanical ventilation (MV) for correction of gas exchange can cause worsening of this inflammatory response, called “ventilator-induced lung injury” (VILI). The process of withdrawing mechanical ventilation, referred to as weaning from MV, may cause worsening of lung injury by spontaneous ventilation. Currently, there are few specific studies in patients with ARDS. Herein, we reviewed the main aspects of spontaneous ventilation and also discussed potential methods to predict the failure of weaning in this patient category. We also reviewed new treatments (modes of mechanical ventilation, neuromuscular blocker use, and extracorporeal membrane oxygenation) that could be considered in weaning ARDS patients from MV.

Capturing complexity in pulmonary system modelling

Respiratory disease is a significant problem worldwide, and it is a problem with increasing prevalence. Pathology in the upper airways and lung is very difficult to diagnose and treat, as response to disease is often heterogeneous across patients. Computational models have long been used to help understand respiratory function, and these models have evolved alongside increases in the resolution of medical imaging and increased capability of functional imaging, advances in biological knowledge, mathematical techniques and computational power. The benefits of increasingly complex and realistic geometric and biophysical models of the respiratory system are that they are able to capture heterogeneity in patient response to disease and predict emergent function across spatial scales from the delicate alveolar structures to the whole organ level. However, with increasing complexity, models become harder to solve and in some cases harder to validate, which can reduce their impact clinically. Here, we review the evolution of complexity in computational models of the respiratory system, including successes in translation of models into the clinical arena. We also highlight major challenges in modelling the respiratory system, while making use of the evolving functional data that are available for model parameterisation and testing.

Dielectric imaging for differentiation between cancer and inflammation in vivo

In this study, we develop an in vivo dielectric imaging technique that measures capacitance using pin-type electrode arrays. Compared to normal tissues, cancer tissues exhibit higher capacitance values, allowing us to image the cancer region and monitor the chemotherapeutic effects of cancer in real-time. A comparison with the histopathological results shows that the in vivo dielectric imaging technique is able to detect small tumors (<3 mm) and tumor-associated changes. In addition, we demonstrate that cancer and inflammation may be distinguished by measuring the capacitance images at different frequencies. In contrast, the positron emission tomography using 2-[¹⁸F]-fluoro-2-deoxy-D-glucose was not capable of discriminating between cancer and inflammation.

A simplified parametrised model for lung microstructures capable of mimicking realistic geometrical and mechanical properties

The respiratory zone of mammalian lungs contains several millions of so-called alveoli. The geometrical and mechanical properties of this microstructure are crucial for respiration and influence the macroscopic behaviour of the entire organ in health and disease. Hence, if computational models are sought to gain more insight into lung behaviour, predict lung states in certain scenarios or suggest better treatment options in early stages of respiratory dysfunction, an adequate representation of this microstructure is essential. However, investigating the real alveolar architecture requires complex medical-imaging methods and would be computationally extremely expensive. Even worse, there is currently no way of obtaining the real patient-specific microstructure in vivo. Hence, we present a fast and easy to compute parametrised model of lung microstructures based on tetrakaidecahedra which can represent both geometrical and mechanical properties of the parenchyma. We show that gas transport pathways and stress and strain distributions are comparable to real alveolar microstructures and even capable of capturing variations present in biology. The created parametrised lung microstructure models can be utilized in finite element simulations to study, e.g., alveolar flow phenomena, particle deposition, or alveolar stresses and strains during mechanical ventilation. Due to the simpler geometry of the parametrised microgeometries compared to imaging-based microstructures, remarkable savings in CPU time can be achieved. We show that our model requires a minimum of 10% of the computational time for computing the same strain state in structural mechanics simulations compared to imaging-based alveolar microstructures.

Coupling of EIT with computational lung modeling for predicting patient-specific ventilatory responses

Providing optimal personalized mechanical ventilation for patients with acute or chronic respiratory failure is still a challenge within a clinical setting for each case anew. In this article, we integrate electrical impedance tomography (EIT) monitoring into a powerful patient-specific computational lung model to create an approach for personalizing protective ventilatory treatment. The underlying computational lung model is based on a single computed tomography scan and able to predict global airflow quantities, as well as local tissue aeration and strains for any ventilation maneuver. For validation, a novel “virtual EIT” module is added to our computational lung model, allowing to simulate EIT images based on the patient's thorax geometry and the results of our numerically predicted tissue aeration. Clinically measured EIT images are not used to calibrate the computational model. Thus they provide an independent method to validate the computational predictions at high temporal resolution. The performance of this coupling approach has been tested in an example patient with acute respiratory distress syndrome. The method shows good agreement between computationally predicted and clinically measured airflow data and EIT images. These results imply that the proposed framework can be used for numerical prediction of patient-specific responses to certain therapeutic measures before applying them to an actual patient. In the long run, definition of patient-specific optimal ventilation protocols might be assisted by computational modeling.

NEW & NOTEWORTHY In this work, we present a patient-specific computational lung model that is able to predict global and local ventilatory quantities for a given patient and any selected ventilation protocol. For the first time, such a predictive lung model is equipped with a virtual electrical impedance tomography module allowing real-time validation of the computed results with the patient measurements. First promising results obtained in an acute respiratory distress syndrome patient show the potential of this approach for personalized computationally guided optimization of mechanical ventilation in future.

Dynamic modeling of uteroplacental blood flow in IUGR indicates vortices and elevated pressure in the intervillous space - a pilot study

Ischemic placental disease is a concept that links intrauterine growth retardation (IUGR) and preeclampsia (PE) back to insufficient remodeling of uterine spiral arteries. The rheological consequences of insufficient remodeling of uterine spiral arteries were hypothesized to mediate the considerably later manifestation of obstetric disease. However, the micro-rheology in the intervillous space (IVS) cannot be examined clinically and rheological animal models of the human IVS do not exist. Thus, an in silico approach was implemented to provide in vivo inaccessible data. The morphology of a spiral artery and the inflow region of the IVS were three-dimensionally reconstructed to provide a morphological stage for the simulations. Advanced high-end supercomputing resources were used to provide blood flow simulations at high spatial resolution. Our simulations revealed turbulent blood flow (high-velocity jets and vortices) combined with elevated blood pressure in the IVS and increased wall shear stress at the villous surface in conjunction with insufficient spiral artery remodeling only. Post-hoc histological analysis of uterine veins showed evidence of increased trophoblast shedding in an IUGR placenta. Our data support that rheological alteration in the IVS is a relevant mechanism linking ischemic placental disease to altered structural integrity and function of the placenta.