Cross-sectional chest circumference and shape development in infants

Objective: This study investigates the development of the thoracic cross-section at the nipple line level during the early stages of life. Unlike the descriptive awareness regarding chest development course, there exist no quantitative references concerning shape, circumference and possible dependencies to age, gender or body weight. The proposed mathematical relations are expected to help create guidelines for more realistic modelling and potential detection of abnormalities. One potential application is lung electrical impedance tomography (EIT) monitoring where accurate chest models are crucial in both extracting reliable parameters for regional ventilation function and design of EIT belts. Despite their importance, such reference data is not readily available for the younger age range due to insufficient data amid the regulations of neonatal imaging. Results: Chest circumference shows the highest correlation to body weight following the relation fx=18.3735ln0.0012x+2.1010 where x is the body weight in grams and f(x) is the chest circumference in cm at the nipple line level. No statistically significant difference in chest circumference between genders was detected. However, the shape indicated signs of both age and gender dependencies with on average boys developing a more rectangular shape than girls from the age of 1 years and 9 months

Effects of Patient Recumbency Position on Neonatal Chest EIT

This paper investigates the overlooked effects of the patient recumbency positions on one of the key clinically used parameters in chest electrical impedance tomography (EIT) monitoring – the silent spaces. This parameter could impact medical decisions and interventions by indicating how well each lung is being ventilated. Yet it is largely dependent on assumptions of prior model at the reconstruction stage and the closely linked region of interest (ROI) during the final calculations. The potential effect of switching recumbency modes on silent spaces as a results of internal organ movements and consequently changes in initial assumptions, has been studied. The displacement and deformations caused by posture changes from supine to lateral recumbent were evaluated via simulations considering the simultaneous gravity-dependent movement and/or deformations of heart, mediastinum, lungs and the diaphragm. The reliability of simulations was verified against reference radiography images of an 18-month-old infant in supine and decubitus lateral positions. Inspecting a set of 10 patients from age range of 1 to 2 years old revealed improvements of up to 30% in the silent space parameters when applying posture consistent amendments as opposed to fixed model/ROI to each individual. To minimize the influence of image reconstruction technique on the results two different EIT reconstruction algorithms were implemented. The outcome emphasized the importance of including recumbency situation during chest EIT monitoring within the considered age range

Torso shape detection to improve lung monitoring

Newborns with lung immaturity often require continuous monitoring and treatment of their lung ventilation in intensive care units, especially if born preterm. Recent studies indicate that Electrical Impedance Tomography (EIT) is feasible in newborn
 infants and children, and can quantitatively identify changes in regional lung aeration and ventilation following alterations to respiratory conditions. Information on the patient-specic shape of the torso and its role in minimizing the artefacts in the
 reconstructed images can improve the accuracy of the clinical parameters obtained from EIT. Currently, only idealized models or those segmented from CT scans are usually adopted. This study presents and compares two methodologies that can
 detect the patient-specic torso shape by means of wearable devices based on: (1) previously reported bend sensor technology and (2) a novel approach based on the use of accelerometers. The reconstruction of different phantoms, taking into account
 anatomical asymmetries and different sizes, are produced for comparison. As a result, the accelerometers are more versatile than bend sensors, which cannot be used on bigger cross-sections. The computational study estimates the optimal number of
 accelerometers required in order to generate an image reconstruction comparable to the use of a CT scan as the forward model. Furthermore, since the patient position is crucial to monitoring lung ventilation, the orientation of the phantoms is automatically
 detected by the accelerometer-based method. [Abstract copyright: © 2018 Institute of Physics and Engineering in Medicine.

Charge redistribution in correlated heterostuctures within nonequilibrium real-space dynamical mean-field theory

We address the steady-state behavior of a system consisting of several correlated monoatomic layers sandwiched between two metallic leads under the influence of a bias voltage. In particular, we investigate the effect of the local Hubbard and of the long-range Coulomb interactions on the charge redistribution at the interface. We provide a detailed study of the importance of the various system parameters, like Hubbard $U$, lead-correlated region coupling strength, and the applied voltage on the charge distribution in the correlated region and in the adjacent parts of the leads. Our results are obtained within non-equilibrium (steady-state) real-space dynamical mean-field theory (R-DMFT), with a self-consistent treatment of the long-range part of the Coulomb interaction by means of the Poisson equation. The latter is solved by the Newton-Raphson method and we find that this significantly reduces the computational cost compared to existing treatment. As impurity solver for R-DMFT we use the auxiliary master equation approach (AMEA), which addresses the impurity problem within a finite auxiliary system coupled to Markovian environments.Comment: 14 pages, 8 figure

Model selection based algorithm in neonatal Chest EIT

This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models. Absolute/static image reconstruction is performed as the core of the posterior probability calculations. The validity and reliability of the algorithm in detecting a suitable model in the presence of measurement noise is studied with simulated and measured data from 11 patients. The paper also demonstrates the potential improvements on the clinical parameters extracted from EIT images by considering a unique case study with a neonate patient undergoing computed tomography imaging as clinical indication prior to EIT monitoring. Two well-known image reconstruction techniques, namely GREIT and tSVD, are implemented to create the final tidal images. The impacts of appropriate model selection on the clinical extracted parameters such as center of ventilation and silent spaces are investigated. The results show significant improvements to the final reconstructed images and more importantly to the clinical EIT parameters extracted from the images that are crucial for decision-making and further interventions

Estimation of thorax shape for forward modelling in lungs EIT

The thorax models for pre-term babies are developed based on the CT scans from new-borns and their effect on image reconstruction is evaluated in comparison with other available models