Multifrequency and parametric EIT images of neonatal lungs

A Review on Electrical Impedance Tomography Spectroscopy

Electrical Impedance Tomography Spectroscopy (EITS) enables the reconstruction of material distributions inside an object based on the frequency-dependent characteristics of different substances. In this paper, we present a review of EITS focusing on physical principles of the technology, sensor geometries, existing measurement systems, reconstruction algorithms, and image representation methods. In addition, a novel imaging method is proposed which could fill some of the gaps found in the literature. As an example of an application, EITS of ice and water mixtures is used.

A Novel Approach to the Identification of Compromised Pulmonary Systems in Smokers by Exploiting Tidal Breathing Patterns

Smoking causes unalterable physiological abnormalities in the pulmonary system. This is emerging as a serious threat worldwide. Unlike spirometry, tidal breathing does not require subjects to undergo forceful breathing maneuvers and is progressing as a new direction towards pulmonary health assessment. The aim of the paper is to evaluate whether tidal breathing signatures can indicate deteriorating adult lung condition in an otherwise healthy person. If successful, such a system can be used as a pre-screening tool for all people before some of them need to undergo a thorough clinical checkup. This work presents a novel systematic approach to identify compromised pulmonary systems in smokers from acquired tidal breathing patterns. Tidal breathing patterns are acquired during restful breathing of adult participants. Thereafter, physiological attributes are extracted from the acquired tidal breathing signals. Finally, a unique classification approach of locally weighted learning with ridge regression (LWL-ridge) is implemented, which handles the subjective variations in tidal breathing data without performing feature normalization. The LWL-ridge classifier recognized compromised pulmonary systems in smokers with an average classification accuracy of 86.17% along with a sensitivity of 80% and a specificity of 92%. The implemented approach outperformed other variants of LWL as well as other standard classifiers and generated comparable results when applied on an external cohort. This end-to-end automated system is suitable for pre-screening people routinely for early detection of lung ailments as a preventive measure in an infrastructure-agnostic way.

Heterogeneous Distribution of Pulmonary Ventilation in Intensive Care Patients Detected by Functional Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a new noninvasive imaging technique which utilizes the different electrical properties of biological tissues to produce cross-sectional images of selected parts of the body. When applied on the thorax, the cyclic fluctuations of electrical impedance of the lung tissue, associated with different air contents of the lungs in the course of the respiratory cycle, can be used to generate derived EIT tomograms which represent the spatial distribution of ventilation in the chosen transverse plane. The corresponding evaluation technique, the functional EIT, was used for the first time to follow the regional ventilation in three intensive care patients. The method was shown (1) to identify the redistribution of inspired air in the lungs associated with controlled ventilation in a patient undergoing elective laparotomy, (2) to follow the improvement of locally impaired lung ventilation in the course of severe pneumonia, and (3) to detect regional reduction of ventilation due to lobar atelectasis with stasis pneumonia in a patient with bronchial carcinoma.

Correction of electrode modelling errors in multi-frequency EIT imaging

The differentiation of haemorrhagic from ischaemic stroke using electrical impedance tomography (EIT) requires measurements at multiple frequencies, since the general lack of healthy measurements on the same patient excludes time-difference imaging methods. It has previously been shown that the inaccurate modelling of electrodes constitutes one of the largest sources of image artefacts in non-linear multi-frequency EIT applications. To address this issue, we augmented the conductivity Jacobian matrix with a Jacobian matrix with respect to electrode movement. Using this new algorithm, simulated ischaemic and haemorrhagic strokes in a realistic head model were reconstructed for varying degrees of electrode position errors. The simultaneous recovery of conductivity spectra and electrode positions removed most artefacts caused by inaccurately modelled electrodes. Reconstructions were stable for electrode position errors of up to 1.5 mm standard deviation along both surface dimensions. We conclude that this method can be used for electrode model correction in multi-frequency EIT.

A Reconstruction-Classification Method for Multifrequency Electrical Impedance Tomography

Multifrequency Electrical Impedance Tomography is an imaging technique which distinguishes biological tissues by their unique conductivity spectrum. Recent results suggest that the use of spectral constraints can significantly improve image quality. We present a combined reconstruction-classification method for estimating the spectra of individual tissues, whilst simultaneously reconstructing the conductivity. The advantage of this method is that a priori knowledge of the spectra is not required to be exact in that the constraints are updated at each step of the reconstruction. In this paper, we investigate the robustness of the proposed method to errors in the initial guess of the tissue spectra, and look at the effect of introducing spatial smoothing. We formalize and validate a frequency-difference variant of reconstruction-classification, and compare the use of absolute and frequency-difference data in the case of a phantom experiment.

Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT

This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.

Multifrequency electrical impedance tomography using spectral constraints

Multifrequency electrical impedance tomography (MFEIT) exploits the dependence of tissue impedance on frequency to recover an image of conductivity. MFEIT could provide emergency diagnosis of pathologies such as acute stroke, brain injury and breast cancer. We present a method for performing MFEIT using spectral constraints. Boundary voltage data is employed directly to reconstruct the volume fraction distribution of component tissues using a nonlinear method. Given that the reconstructed parameter is frequency independent, this approach allows for the simultaneous use of all multifrequency data, thus reducing the degrees of freedom of the reconstruction problem. Furthermore, this method allows for the use of frequency difference data in a nonlinear reconstruction algorithm. Results from empirical phantom measurements suggest that our fraction reconstruction method points to a new direction for the development of multifrequency EIT algorithms in the case that the spectral constraints are known, and may provide a unifying framework for static EIT imaging.

Towards non-invasive EIT imaging of domains with deformable boundaries

We investigate on the use of the Domain Embedding Method (DEM) for the forward modelling in EIT. This approach is suitably configured to overcome the model meshing bottleneck since it does not require that the mesh on the domain is adapted to the boundary surface. This is of crucial importance for, e.g., clinical applications of EIT, as it avoids tedious and time-consuming (re-)meshing procedures. The suggested DEM approach can accommodate arbitrary yet Lipschitz smooth boundary surfaces and is not limited to polygonal domains. For the discretisation purposes, we employ B-splines as they allow for arbitrary accuracy by raising the polynomial degree and are easy to implement due to their inherent piecewise polynomial structure. Numerical experiments confirm that a B-spline discretization yields, similarly to conventional Finite Difference discretizations, increasing condition numbers of the system matrix with respect to the discretisation levels. Fortunately, multiresolution ideas based on B-splines allow for optimal wavelet preconditioning.

Lung-function tests in neonates and infants with chronic lung disease: tidal breathing and respiratory control

This paper is the fourth in a series of reviews that will summarize available data and critically discuss the potential role of lung-function testing in infants with acute neonatal respiratory disorders and chronic lung disease of infancy. The current paper addresses information derived from tidal breathing measurements within the framework outlined in the introductory paper of this series, with particular reference to how these measurements inform on control of breathing. Infants with acute and chronic respiratory illness demonstrate differences in tidal breathing and its control that are of clinical consequence and can be measured objectively. The increased incidence of significant apnea in preterm infants and infants with chronic lung disease, together with the reportedly increased risk of sudden unexplained death within the latter group, suggests that control of breathing is affected by both maturation and disease. Clinical observations are supported by formal comparison of tidal breathing parameters and control of breathing indices in the research setting.

Lung function tests in neonates and infants with chronic lung disease: global and regional ventilation inhomogeneity

This review considers measurement of global and regional ventilation inhomogeneity (VI) in infants and young children with acute neonatal respiratory disorders and chronic lung disease of infancy (CLDI). We focus primarily on multiple-breath inert gas washout (MBW) and electrical impedance tomography (EIT). The literature is critically reviewed and the relevant methods, equipment, and studies are summarized, including the limitations and strengths of individual techniques, together with the availability and appropriateness of any reference data. There has been a recent resurgence of interest in using MBW to monitor lung function within individuals and between different groups. In the mechanically ventilated, sedated, and paralyzed patient, VI indices can identify serial changes occurring following exogenous surfactant. Similarly, global VI indices appear to be increased in infants with CLDI and to differentiate between infants without lung disease and those with mild, moderate, and severe lung disease following preterm birth. While EIT is a relatively new technique, recent studies suggest that it is feasible in newborn infants, and can quantitatively identify changes in regional lung ventilation following alterations to ventilator settings, positive end expiratory pressure (PEEP), and administration of treatments such as surfactant. As such, EIT represents one of the more exciting prospects for continuous bedside pulmonary monitoring. For both techniques, there is an urgent need to establish guidelines regarding data collection, analysis, and interpretation in infants both with and without CLDI.

Electrical impedance tomography (EIT) in applications related to lung and ventilation: a review of experimental and clinical activities

This review article is a summary of the publications dealing with the pulmonary applications of electrical impedance tomography (EIT). Original papers on EIT lung imaging published over 15 years are analysed and several aspects of the performed EIT measurements summarized. Information on the type of the EIT device and electrodes used, the studied transverse thoracic planes, the data acquisition rate, the number of studied animals, normal subjects or patients, the kind of lung pathology, the performed ventilatory manoeuvres and other interventions, as well as the applied reference techniques, is given. The type of the generated pulmonary EIT images and the quantitative analysis of the EIT data are described. Finally, the major results achieved are presented, followed by an analysis of the perspectives of EIT in clinical applications. A comparative analysis of the EIT hardware and the quality of the evaluation tools was not performed.

A comparison of neonatal and adult lung impedances derived from EIT images

An objective method of extracting respiratory data from lung images is presented, together with a technique for automatically generating regions of interest delineating the anterior and posterior regions of the lungs. The method is used to extract data on the change in lung impedance with frequency, and on calculated Cole parameters, from 19 normal neonates (gestational age 32 to 42 weeks) and 8 normal adults (age 21 to 82 years). A comparison of the impedance properties of neonatal and adult lungs was made. The variation of lung impedance with frequency in neonates, as derived from EIT images, is significantly different from that found for adults. The implications for a model of the electrical impedance of lung tissue are discussed.

Monitoring regional lung ventilation by functional electrical impedance tomography during assisted ventilation

A new approach in discriminating the regional air volume changes in the lungs associated with either spontaneous or mechanical ventilation during assisted ventilation is presented. Impedance data are obtained by conventional electrical impedance tomography (EIT). The data are filtered in the range of either the spontaneous or the ventilator rate and processed by the functional EIT (f-EIT) evaluation technique, whereby the variation of the respective EIT data with time is determined and imaged. EIT measurements performed in an infant during synchronized intermittent mandatory ventilation were evaluated with this method and indicated that the specific local lung volume swings related to spontaneous and mechanical inhalations can be separated and imaged as tomograms. This noninvasive approach may become useful in optimizing the ventilatory pattern during advanced forms of artificial ventilation and may help the clinician in the therapy management of individual patients.

Reproducibility of electrical impedance tomographic spectroscopy (EITS) parametric images of neonatal lungs

The reproducibility of electrical impedance tomographic spectroscopy (EITS) images of neonatal lungs have been investigated in 11 clinically stable babies. We have used the Sheffield Mark IIIa EITS system. An average inspiration frame was generated from the data frames associated with maximum inspiration. Frequency images were reconstructed from these frames. The frequency images were analysed to locate the pixel with the maximum change in the right lung field. The change was defined as the 614 kHz measurement relative to 9.6 kHz. A 3 x 3 pixel region of interest was centred at this point. The changes in impedance with frequency for this region of interest show good overall reproducibility between electrode applications for eight frequencies (95% limits of agreement +/- 28%). This reproducibility is improved (95% limits of agreement +/- 13%) by omitting the highest frequency (1.2 MHz) which is most subject to system noise. The parameters for the Cole model derived from data with the highest frequency omitted are less reproducible between electrode applications (95% limits of agreement, R/S +/- 0.83, fc +/- 81.6, RC +/- 0.52, SC +/- 0.39). We suspect that the parametric model used may have an effect on this. The signals recorded at the highest frequency (1.2 MHz) are a major source of variability. The reproducibility results are improved by omitting this frequency from the analysis.

Data processing techniques for serial EIT spectroscopy images: a review of some preliminary results

Mutlifrequency EIT imaging should allow specific organs within the body to be identified by their impedance spectrum, and the use of parametric imaging should lead to a much greater freedom from movement artefacts. This will make EIT more attractive as a monitoring technique, but the data rate will require automated processing of the images. The application of dynamic regions of interest, generated on a frame by frame basis, is described, with examples from the imaging of neonatal lungs and adult stomach. The lung can be objectively identified on a single frame from the fRSC, SC and RC images, but the stomach could only be identified on the dynamic images.