Modelling of an oesophageal electrode for cardiac function tomography

Addition of internal electrodes is beneficial for focused bioimpedance measurements in the lung

OBJECTIVE

Bioimpedance measurements such as bioimpedance spectroscopy (BIS) or electrical impedance tomography (EIT) are used in many biomedical applications. While BIS measures and analyzes the impedance in a frequency range at constant electrode positions, EIT aims to reconstruct images of the conductivity distribution from multiple measurements at different electrode positions. Our aim is to add spatial information to tetrapolar BIS measurements by using electrode positions that focus measurements on desired regions of interest. In this paper, we aim to investigate, whether internal electrodes that can be integrated into breathing or gastroesophageal tubes, can improve the local sensitivity of bioimpedance spectroscopy measurements.

APPROACH

We present the results of a simulation study, in which we investigated more than 4 M different electrode configurations on their ability to monitor specific regions of interest (ROI) in the lung. Based on the sensitivity, which describes the impact of a conductivity change on the measured impedance, we define three main criteria which we use to evaluate our simulation results: the selectivity [Formula: see text], which describes the impact of a conductivity change inside the region of interest compared to a conductivity change outside the ROI; the homogeneity [Formula: see text], which describes the distribution of the sensitivity inside the ROI; and the absolute impedance contribution ratio [Formula: see text], which describes the contribution of the ROI to the measured impedance.

MAIN RESULTS

Depending on the region of interest, electrode configurations using internal electrodes are between 9.8 % and 90 % better with respect to these criteria than configurations using external electrodes only.

SIGNIFICANCE

The combination of internal and external electrodes improves the focusing ability of tetrapolar impedance measurements on specific lung regions, which may be especially beneficial for lung monitoring in intensive care.

A shape-based quality evaluation and reconstruction method for electrical impedance tomography

Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community. In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed. Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images.

A local region of interest imaging method for electrical impedance tomography with internal electrodes

Electrical Impedance Tomography (EIT) is a very attractive functional imaging method despite the low sensitivity and resolution. The use of internal electrodes with the conventional reconstruction algorithms was not enough to enhance image resolution and accuracy in the region of interest (ROI). We propose a local ROI imaging method with internal electrodes developed from careful analysis of the sensitivity matrix that is designed to reduce the sensitivity of the voxels outside the local region and optimize the sensitivity of the voxel inside the local region. We perform numerical simulations and physical measurements to demonstrate the localized EIT imaging method. In preliminary results with multiple objects we show the benefits of using an internal electrode and the improved resolution due to the local ROI image reconstruction method. The sensitivity is further increased by allowing the surface electrodes to be unevenly spaced with a higher density of surface electrodes near the ROI. Also, we analyse how much the image quality is improved using several performance parameters for comparison. While these have not yet been studied in depth, it convincingly shows an improvement in local sensitivity in images obtained with an internal electrode in comparison to a standard reconstruction method.

An amplitude-to-time conversion technique suitable for multichannel data acquisition and bioimpedance imaging

In this paper we exploit the high timing resolution offered by microprocessors to develop an amplitude measurement approach that is convenient for high channel count portable sinusoidal recording systems such as the bioimpedance measurements used in impedance imaging. This approach reduces the number of components required per channel, reducing cost, size and power consumption compared to the traditional approaches. The setup uses two high performance comparators to convert amplitude difference to a timing difference. This is captured by a high speed microprocessor. A straightforward algorithm removes DC and timing offsets. We suggest three modes of operation: fast: less than one period of the input, normal: exactly one input period and high precision: multiple input periods. The mean signal-to-noise ratio was 40, 81, and 112.4 dB in fast, normal, and high precision mode respectively for a range of resistive loads.