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Electrical Impedance Tomography (EIT), an imaging technique which operates non-invasively and without radiation exposure, provides information about ventilation- and cardiac-synchronous (pulsatile) changes in the lung. It is well known, that perfusion within the thorax is influenced by lung volume or intrathoracic pressure. In this observational study, it shall be investigated if this phenomenon can be monitored by EIT. Therefore, the impact of the amount of air within the lung on the pulsatile EIT signal was evaluated by carrying out EIT measurements with a spontaneously breathing lung healthy subject holding the breath at three different inspiratory and three various expiratory volume levels during normal tidal breathing. For EIT data analysis, a region of interest was defined by including lung tissue and excluding the heart region. The EIT data revealed, that the shape and the amplitude of the pulsatile EIT signal (evaluated per heartbeat) during the phases of breath holding were dependent on the enclosed lung volume. For lung volumes > 4 L, the amplitude of the pulsatile EIT signal increased with rising inspiratory level and the shape remained almost unchanged. For lung volumes < 4 L, a change in shape was visible but the amplitude remained more or less the same with decreasing expiratory level. Since the results of this observational study show that the pulsatile EIT signal is influenced by the lung volume, it might be used in future to draw conclusions of cardiacpulmonary interactions or intrathoracic pressure states, benefitting the treatment of intensive care patients.

To estimate the severity of airway abnormalities in cystic fibrosis (CF) Brody et al. developed a computed tomography (CT) scoring system. Each pulmonary lobe is analyzed separately considering various morphological defects. A study from Zhao et al. demonstrates that this CTbased score correlates with regional airway obstruction (RAO) measured by the real-time imaging method Electrical Impedance Tomography (EIT). Zhao et al. performed EIT measurements at the 5th intercostal space (ICS) and median RAO, including both lungs, was correlated with the associated score. In the present feasibility study, it was investigated if RAO determined by EIT within the left and right lung respectively at the 3rd and 5th ICS corresponds with the scores of the left and right lobes. EIT measurements and CT-based scoring were carried out on two CF patients. RAO was identified by ratios of impedance values associated to the maximal forced expiratory flow at 25% and 75% of the forced vital capacity. Mean RAO of each lung within both thorax sections was compared with the lobar scores. Airway abnormalities within upper lobes are assigned to RAO measured within the 3rd ICS, whereas abnormalities of the right middle lobe, both lower lobes and the lingula are mainly represented by EIT images of the 5th ICS. Results show that differences in the CT-based score between the left and right lung concur with differences in EIT derived RAO. The regional information provided by EIT might be used for a more targeted therapy of CF-related lung diseases.

Electrical Impedance Tomography (EIT) is a novel medical imaging technology which is expected to give valuable information for the treatment of mechanically ventilated patients as well as for patients with obstructive lung diseases. In lung-EIT electrodes are attached around the thorax to inject small alternating currents and to measure resulting voltages. These voltages depend on the internal conductivity distribution and thus on the amount of air in the lungs. Based on the measured voltages, image reconstruction algorithms are employed to generate tomographic images reflecting the regional ventilation of the lungs. However, the ill-posedness of the reconstruction problem leads to reconstructed images that are severely blurred compared to morphological imaging technologies, such as X-ray computed tomography or Magnetic Resonance Imaging. Thus, a correct identification of the particular ventilation in anatomically assignable units, e.g. lung-lobes, is often hindered. In this study a 3D-FEM model of a human thorax has been used to simulate electrode voltages at different lung conditions. Two electrode planes with 16 electrodes at each layer have been used and different amount of emphysema and mucus plugging was simulated with different severity in the lung lobes. Patient specific morphological information about the lung lobes is used in the image reconstruction process. It is shown that this kind of prior information leads to better reconstructions of the conductivity change in particular lung lobes than in classical image reconstruction approaches, where the anatomy of the patients’ lungs is not considered. Thus, the described approach has the potential to open new and promising applications for EIT. It might be used for diagnosis and disease monitoring for patients with obstructive lung diseases but also in other applications, e.g. during the placement of endobronchial valves in patients with severe emphysema.

Electrical impedance tomography (EIT) can be used to monitor regional lung ventilation. Due to its relatively high temporal resolution, EIT has already been applied during lung function tests in spontaneously breathing subjects with obstructive lung diseases like chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF). In our study, ratios of the maximal volume exhaled in 1 s during forced expiration and forced vital capacity (FEV1/FVC) were calculated in predefined lung regions for five CF patients and five lung healthy subjects. The degree of FEV1/FVC homogeneity was assessed by using a slightly modified version of the global inhomogeneity index (GIFEV1 /FVC). CF patients showed a higher degree of inhomogeneity in pixel FEV1/FVC than lung healthy subjects. Since EIT is able to deliver regional information to assess airway obstruction in CF patients, it might represent a promising supplement to existing methods like spirometry providing global lung parameters.

Electrical impedance tomography (EIT) is used to monitor the regional distribution of ventilation in a transversal plane of the thorax. In this manuscript we evaluate the impact of different quantities of electrodes used for current injection and voltage measurement on the reconstructed shape of the lungs. Results indicate that the shape of reconstructed impedance changes in the body depends on the number of electrodes. In this manuscript, we demonstrate that a higher number of electrodes do not necessarily increase the image quality. For the used stimulation pattern, utilizing neighboring electrodes for current injection and voltage measurement, we conclude that the shape of the lungs is best reconstructed if 16 electrodes are used.

In this study we evaluated open-source software for lung segmentation. Several parameters which emphasize on functionality, usability, image quality and 3D export are considered for this evaluation. Based on these parameters, a scoring system is generated. Our preliminary evaluation results indicated that the Pulmonary toolkit obtains the best overall performance according to the scoring system. However, the ranking of software shows a certain variation among different criteria. The selection of software should regard the focus and the specific interest of the user.

Electrical Impedance Tomography (EIT) intends to obtain the conductivity distribution of a domain from the electrical boundary conditions. This is an ill-posed inverse problem usually solved on finite element meshes. Wavelet transforms are widely used for medical image reconstruction. However, because of the irregular form of the finite element meshes, the canonical wavelet transforms is impossible to perform on meshes. In this article, we present a framework that combines multi-scales wavelet transforms and finite element meshes by viewing meshes as undirected graphs and applying spectral graph wavelet transform on the meshes.

Electrical Impedance Tomography (EIT) is used to visualize the regional ventilation of the lungs using voltage measurements on the surface of the thorax. Unfortunately the image reconstruction process is sensitive to shape deformation. During breathing the inevitable expansion of the thorax influences measured boundary voltages which leads to artifacts in the reconstructed images. A camera based motion-tracking-system was used to measure thorax excursion during breathing and systematically modify measured voltages. Results indicate that image artefacts can be reduced if the measured voltages are modified based on the measured thorax excursion.

Electrical Impedance tomography (EIT) imaging suffers greatly from the illposedness of the corresponding inverse problem. This is mainly caused by the high degree of freedom and the relatively large noise. One attempt to circumvent these difficulties is to use dual models. This article introduces a clustering based non-uniform dual model construction. With this framework, finite elements are grouped to reduce the complexity in inverse computations. The simulation and experiment results indicated that the k-means clustering method did not only preserve the sharp variations over conductivity mediums but also greatly filtered out artefacts found in the standard approach.