Effect of routine suction on lung aeration in critically ill neonates and young infants measured with electrical impedance tomography

Endotracheal suctioning is a widely used procedure to remove secretions from the airways of ventilated patients. Despite its prevalence, regional effects of this maneuver have seldom been studied. In this study, we explore its effects on regional lung aeration in neonates and young infants using electrical impedance tomography (EIT) as part of the large EU-funded multicenter observational study CRADL. 200 neonates and young infants in intensive care units were monitored with EIT for up to 72 h. EIT parameters were calculated to detect changes in ventilation distribution, ventilation inhomogeneity and ventilation quantity on a breath-by-breath level 5-10 min before and after suctioning. The intratidal change in aeration over time was investigated by means of regional expiratory time constants calculated from all respiratory cycles using an innovative procedure and visualized by 2D maps of the thoracic cross-section. 344 tracheal suctioning events from 51 patients could be analyzed. They showed no or very small changes of EIT parameters, with a dorsal shift of the center of ventilation by 0.5% of the chest diameter and a 7% decrease of tidal impedance variation after suctioning. Regional time constants did not change significantly. Routine suctioning led to EIT-detectable but merely small changes of the ventilation distribution in this study population. While still a measure requiring further study, the time constant maps may help clinicians interpret ventilation mechanics in specific cases.

An Imaged Based Method for Universal Performance Evaluation of Electrical Impedance Tomography Systems

This paper describes a simple and reproducible method for universal evaluation of the performance of electrical impedance tomography (EIT) systems using reconstructed images. To address the issues where common electrical parameters are not directly related to the quality of EIT images, based on objective full reference (FR) image quality assessment, the method provides a visually distinguishable hot colormap and two new FR metrics, the global and the more specific 'region of interest'. A passive 16 electrode EIT system using an application specific integrated circuit front-end was used to evaluate the proposed method. The measured results show, both visually and in terms of the proposed FR metrics, the impact on recorded EIT images with different design parameters and non-idealities. The paper also compares the image results of a passive electrode system with a matched 'single variable' active electrode system and demonstrates the merit of an active electrode system for noise interference. A figure of merit based on the FR metrics is proposed.

Compressive sensing in electrical impedance tomography for breathing monitoring

OBJECTIVE

Electrical impedance tomography (EIT) is a functional imaging technique in which cross-sectional images of structures are reconstructed based on boundary trans-impedance measurements. Continuous functional thorax monitoring using EIT has been extensively researched. Increasing the number of electrodes, number of planes and frame rate may improve clinical decision making. Thus, a limiting factor in high temporal resolution, 3D and fast EIT is the handling of the volume of raw impedance data produced for transmission and its subsequent storage. Owing to the periodicity (i.e. sparsity in frequency domain) of breathing and other physiological variations that may be reflected in EIT boundary measurements, data dimensionality may be reduced efficiently at the time of sampling using compressed sensing techniques. This way, a fewer number of samples may be taken.

APPROACH

Measurements using a 32-electrode, 48-frames-per-second EIT system from 30 neonates were post-processed to simulate random demodulation acquisition method on 2000 frames (each consisting of 544 measurements) for compression ratios (CRs) ranging from 2 to 100. Sparse reconstruction was performed by solving the basis pursuit problem using SPGL1 package. The global impedance data (i.e. sum of all 544 measurements in each frame) was used in the subsequent studies. The signal to noise ratio (SNR) for the entire frequency band (0 Hz-24 Hz) and three local frequency bands were analysed. A breath detection algorithm was applied to traces and the subsequent error-rates were calculated while considering the outcome of the algorithm applied to a down-sampled and linearly interpolated version of the traces as the baseline.

MAIN RESULTS

SNR degradation was generally proportional with CR. The mean degradation for 0 Hz-8 Hz (of interest for the target physiological variations) was below ~15 dB for all CRs. The error-rates in the outcome of the breath detection algorithm in the case of decompressed traces were lower than those associated with the corresponding down-sampled traces for CR  ⩾  25, corresponding to sub-Nyquist rate for breathing frequency. For instance, the mean error-rate associated with CR  =  50 was ~60% lower than that of the corresponding down-sampled traces.

SIGNIFICANCE

To the best of our knowledge, no other study has evaluated the applicability of compressive sensing techniques on raw boundary impedance data in EIT. While further research should be directed at optimising the acquisition and decompression techniques for this application, this contribution serves as the baseline for future efforts.

Optimized breath detection algorithm in electrical impedance tomography

OBJECTIVE

This paper defines a method for optimizing the breath delineation algorithms used in electrical impedance tomography (EIT). In lung EIT the identification of the breath phases is central for generating tidal impedance variation images, subsequent data analysis and clinical evaluation. The optimisation of these algorithms is particularly important in neonatal care since the existing breath detectors developed for adults may give insufficient reliability in neonates due to their very irregular breathing pattern.

APPROACH

Our approach is generic in the sense that it relies on the definition of a gold standard and the associated definition of detector sensitivity and specificity, an optimisation criterion and a set of detector parameters to be investigated. The gold standard has been defined by 11 clinicians with previous experience with EIT and the performance of our approach is described and validated using a neonatal EIT dataset acquired within the EU-funded CRADL project.

MAIN RESULTS

Three different algorithms are proposed that improve the breath detector performance by adding conditions on (1) maximum tidal breath rate obtained from zero-crossings of the EIT breathing signal, (2) minimum tidal impedance amplitude and (3) minimum tidal breath rate obtained from time-frequency analysis. As a baseline a zero-crossing algorithm has been used with some default parameters based on the Swisstom EIT device.

SIGNIFICANCE

Based on the gold standard, the most crucial parameters of the proposed algorithms are optimised by using a simple exhaustive search and a weighted metric defined in connection with the receiver operating characterics. This provides a practical way to achieve any desirable trade-off between the sensitivity and the specificity of the detectors.

Design and calibration of a compact multi-frequency EIT system for acute stroke imaging

A new, compact UCLH Mk 2.5 EIT system has been developed and calibrated for EIT imaging of the head. Improvements include increased input and output impedances, increased bandwidth and improved CMRR (80 dB) and linearity over frequencies and load (0.2% on a single channel, +/-0.7% on a saline tank over 20 Hz-256 kHz and 10-65 Omega). The accuracy of the system is sufficient to image severe acute stroke according to the specification from recent detailed anatomical modelling (Horesh et al 2005 3rd European Medical and Biological Engineering Conference EMBEC'05). A preliminary human study has validated the main specifications of the modelling, the range of trans-impedance from the head (8-70 Omega) using a 32 electrode, 258 combination protocol and contact impedances of 300 Omega to 2.7 kOmega over 20 Hz to 256 kHz.

Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of an analysis method and calibration

MFEIT (multi-frequency electrical impedance tomography) could distinguish between ischaemic and haemorrhagic stroke and permit the urgent use of thrombolytic drugs in patients with ischaemic stroke. The purpose of this study was to characterize the UCLH Mk 2 MFEIT system, designed for this purpose, with 32 electrodes and a multiplexed 2 kHz to 1.6 MHz single impedance measuring circuit. Data were collected in seven subjects with brain tumours, arteriovenous malformations or chronic stroke, as these resembled the changes in haemorrhagic or ischaemic stroke. Calibration studies indicated that the reliable bandwidth was only 16-64 kHz because of front-end components placed to permit simultaneous EEG recording. In raw in-phase component data, the SD of 16-64 kHz data for one electrode combination across subjects was 2.45 +/- 0.9%, compared to a largest predicted change of 0.35% estimated using the FEM of the head. Using newly developed methods of examining the most sensitive channels from the FEM, and nonlinear imaging constrained to the known site of the lesion, no reproducible changes between pathologies were observed. This study has identified a specification for accuracy in EITS in acute stroke, identified the size of variability in relation to this in human recordings, and presents new methods for analysis of data. Although no reproducible changes were identified, we hope this will provide a foundation for future studies in this demanding but potentially powerful novel application.

Spatial resolution improvement of 3D EIT images by the shrinking sLORETA-FOCUSS algorithm

This paper describes the use of the shrinking sLORETA-FOCUSS algorithm to improve the spatial resolution of three-dimensional (3D) EIT images. Conventional EIT yields inaccurate, low spatial resolution images, due to noise, the low sensitivity of boundary voltages to inner conductivity perturbations and a limited number of boundary voltage measurements. The focal underdetermined system solver (FOCUSS) algorithm produces a localized energy solution based on the weighted minimum-norm least-squares (MNLS) solution. It was successfully applied for the spatial resolution improvement of EIT images of simulated and tank data for a 2D homogeneous circular disc. However, due to the fact that a 3D mesh system contains many more elements, much more memory is required to store the weighting matrix. In order to extend the work to 3D, the shrinking-FOCUSS method is utilized to shrink the solution space as well as the weighting matrix in each iteration step. The solution of the standardized low resolution electromagnetic tomography algorithm (sLORETA) is adopted as the initial estimate of the shrinking-FOCUSS. The effectiveness is verified by implementing the new algorithm on tank data for a three-dimensional homogeneous sphere.

The spatial resolution improvement of EIT images by GVSPM-FOCUSS algorithm

The focal underdetermined system solver (FOCUSS) algorithm is a recursive algorithm to find the localized energy solution. It is an initialization-dependent algorithm. The generalized vector sample pattern matching (GVSPM) method has been applied to solve the inverse problem of electrical impedance tomography (EIT) and obtain smooth reconstructed images. By combining the GVSPM solution as the initial estimation of the FOCUSS algorithm, an idea termed the GVSPM-FOCUSS method is presented in this paper to improve the spatial resolution and precision of localization for EIT images. The comparisons are carried out between the EIT images reconstructed with the GVSPM-FOCUSS method and the GVSPM method alone. The effectiveness is verified by simulated and tank data for a model of a two-dimensional homogeneous circular disk.

The application of the generalized vector sample pattern matching method for EIT image reconstruction

This paper presents a new application of a generalized vector sample pattern matching (GVSPM) method for image reconstruction of conductivity changes in electrical impedance tomography. GVSPM is an iterative method for linear inverse problems. The key concept of the GVSPM is that the objective function is defined in terms of an angular component between the inner product of the known vector and solution of a system of equations. Comparisons are presented between images of simulated and experimental data, reconstructed using truncated singular value decomposition and GVSPM. In both cases, a normalized sensitivity matrix is constructed using the finite volume method to solve the forward problem.