A 3-D hybrid finite element model to characterize the electrical behavior of cutaneous tissues.

Finite element modeling of the skin is useful to study the electrical properties of cutaneous tissues and gain a better understanding of the current distribution within the skin. Such an epithelial finite element model comprises extremely thin structures like cellular membranes, nuclear membranes, and the extracellular fluid. Meshing such narrow spaces considerably increases the number of elements leading to longer computing time. This also greatly reduces the number of epithelial cells that can be assembled before reaching computing limitations. To avoid the problem of meshing extremely narrow spaces while unnecessarily increasing the number of elements, we present a new hybrid modeling approach to develop a 3-D finite element model of the skin. This skin model comprises all skin layers, different lesion types, and a complete electrode model. It is used to analyze the complex electrical behavior of normal and malignant skin tissues. The current distribution within this model is also simulated to assess the depth of field achievable by an electrical impedance tomography system at different operating frequencies.

Experimental setup for developing acousto-electric interaction imaging.

Acousto-Electric Interaction (AEI) is a physical phenomenon identified in the literature as potentially useful for imaging the electrical conductivity of biological tissues. AEI could lead to a non-invasive technique for detecting breast tumors, since the conductivity of pathological tissues differs significantly from the conductivity of healthy breast tissues. Applying AEI to image heterogeneous structures of the size of the breast represents a major technical challenge. We present in this paper an experimental setup designed to address the various instrumentation issues of AEI. Tests results are presented showing the ultrasonic vibration potential (also known as the Debye effect) and the AEI signals. A preliminary analysis of the AEI signal we recorded suggests that cavitation effects can be measured with this technique.

A multi-frequency EIT system design based on telecommunication signal processors.

A multi-frequency electrical impedance tomography system for cardiopulmonary monitoring has been designed with specialized digital signal processors developed primarily for the telecommunications sector. The system consists of two modules: a scan-head and a base-station. The scan-head, located close to the patient's torso, contains front-end circuits for measuring transfer impedance with a 16-electrode array. The base-station, placed at the bedside, comprises 16 direct digital synthesizers, 32 digital down-converters, digital circuits to control the data acquisition sequence and a USB-2.0 microcontroller. At every step of the scan sequence, the system simultaneously measures four complex variables at eight frequencies. These variables are the potential difference between the selected pair of sense electrodes, the currents applied by the source and sink electrodes, and the current flowing through the ground electrode. Frequencies are programmable from 10 kHz to 2 MHz with a resolution of 2 mHz. Characterization tests were performed with a precision mesh phantom connected to the scan-head. For a 5 Hz frame rate, the mean signal-to-noise ratio and accuracy are, respectively, 43 dB and 95.4% for eight frequencies logarithmically spaced from 70 to 950 kHz. In vitro and in vivo time-difference images have been reconstructed.

Real-time management of faulty electrodes in electrical impedance tomography.

Completely or partially disconnected electrodes are a fairly common occurrence in many electrical impedance tomography (EIT) clinical applications. Several factors can contribute to electrode disconnection: patient movement, perspiration, manipulations by clinical staff, and defective electrode leads or electronics. By corrupting several measurements, faulty electrodes introduce significant image artifacts. In order to properly manage faulty electrodes, it is necessary to: 1) account for invalid data in image reconstruction algorithms and 2) automatically detect faulty electrodes. This paper presents a two-part approach for real-time management of faulty electrodes based on the principle of voltage-current reciprocity. The first part allows accounting for faulty electrodes in EIT image reconstruction without a priori knowledge of which electrodes are at fault. The method properly weights each measurement according to its compliance with the principle of voltage-current reciprocity. Results show that the algorithm is able to automatically determine the valid portion of the data and use it to calculate high-quality images. The second part of the approach allows automatic real-time detection of at least one faulty electrode with 100% sensitivity and two faulty electrodes with 80% sensitivity enabling the clinical staff to fix the problem as soon as possible to minimize data loss.

Comparison of applied and induced current electrical impedance tomography.

Several papers on induced current electrical impedance tomography (IC-EIT) have dwelt on potential advantages of this technique over conventional EIT which uses applied current (AC-EIT). Experimental evidence that IC-EIT could surpass AC-EIT in similar imaging conditions is lacking. In this paper, we describe a system that can switch rapidly between both AC-EIT and IC-EIT. The system makes it possible to image objects in a saline-filled tank, providing data acquired in identical test conditions for comparing the performance of the two modes. The system uses eight circular coils and 16 electrodes to acquire 120 linearly independent measurements in IC-EIT and 104 in AC-EIT. Difference images were reconstructed from data acquired with both modes using the maximum a posteriori method. Spatial resolution was lower in IC-EIT images than in AC-EIT, especially in the radial direction. IC-EIT also exhibits a bias toward the center for positioning a conductivity perturbation. These results were obtained for a typical coil configuration widely used in the literature and may not be representative of alternate coil configurations. The system described in this paper provides stable experimental conditions for comparing the performance of the two EIT imaging modes and would be a valuable tool for validating new coil configurations.

Accounting for hardware imperfections in EIT image reconstruction algorithms.

Electrical impedance tomography (EIT) is a non-invasive technique for imaging the conductivity distribution of a body section. Different types of EIT images can be reconstructed: absolute, time difference and frequency difference. Reconstruction algorithms are sensitive to many errors which translate into image artefacts. These errors generally result from incorrect modelling or inaccurate measurements. Every reconstruction algorithm incorporates a model of the physical set-up which must be as accurate as possible since any discrepancy with the actual set-up will cause image artefacts. Several methods have been proposed in the literature to improve the model realism, such as creating anatomical-shaped meshes, adding a complete electrode model and tracking changes in electrode contact impedances and positions. Absolute and frequency difference reconstruction algorithms are particularly sensitive to measurement errors and generally assume that measurements are made with an ideal EIT system. Real EIT systems have hardware imperfections that cause measurement errors. These errors translate into image artefacts since the reconstruction algorithm cannot properly discriminate genuine measurement variations produced by the medium under study from those caused by hardware imperfections. We therefore propose a method for eliminating these artefacts by integrating a model of the system hardware imperfections into the reconstruction algorithms. The effectiveness of the method has been evaluated by reconstructing absolute, time difference and frequency difference images with and without the hardware model from data acquired on a resistor mesh phantom. Results have shown that artefacts are smaller for images reconstructed with the model, especially for frequency difference imaging.

Electrical impedance tomography's correlation to lung volume is not influenced by anthropometric parameters.

STUDY OBJECTIVES: Electrical impedance tomography (EIT) is able to reflect physiological parameters such as real-time changes in global and regional lung volume. EIT can aid in the assessment of lung recruitment, and its use has been validated in preliminary studies monitoring mechanical ventilation at the bedside. ICU patients vary widely in their body habitus, and obesity is becoming more prevalent. Our primary research purpose was to establish whether anthropometric parameters influence EIT's reliability. Our secondary question was whether body position alters its correlation to spirometric measurements. SUBJECTS: 22 healthy adult volunteers (12 male, 10 female) with broadly variable anthropometric parameters. INTERVENTIONS: Simultaneous measurements of changes in lung volume using EIT imaging and a pneumotachograph were obtained with two breathing patterns (quiet and deep breathing) and in four body positions (standing, sitting, semi-reclining and supine). MEASUREMENTS AND RESULTS: Correlation between measurements of changes in lung volume using EIT imaging and a pneumotachograph was excellent. Variations attributable to anthropometric measurements accounted for at most a 1.3% difference. CONCLUSIONS: Anthropometric variability and body position do not adversely influence the EIT estimation of changes in lung volume. These data suggest EIT could be used to monitor critically ill mechanically ventilated adults with variable body habitus regardless of position.

A method for modelling and optimizing an electrical impedance tomography system.

Electrical impedance tomography (EIT) image reconstruction is an ill-posed problem requiring maximum measurement precision. Recent EIT systems claim 60 to 80 dB precision. Achieving higher values is hard in practice since measurements must be performed at relatively high frequency, on a living subject, while using components whose tolerance is usually higher than 0.1%. To circumvent this difficulty, a method for modelling the electronic circuits of an EIT system was developed in order to optimize the circuits and incorporate the model in the reconstruction algorithms. The proposed approach is based on a matrix method for solving electrical circuits and has been applied to the scan-head which contains the front-end electronic circuits of our system. The method is used to simulate the system characteristic curves which are then optimized with the Levenberg-Marquardt method to find optimal component values. A scan-head was built with the new component values and its simulated performance curves were compared with network analyser measurements. As a result of the optimization, the impedance at the operating frequency was increased to minimize the effects of variations in skin/electrode contact impedance. The transconductance and gain frequency responses were also reshaped to reduce noise sensitivity and unintended signal modulation. Integrating the model in the reconstruction algorithms should further improve overall performance of an EIT system.

Development of a multi-channel system for intrinsic cardiac neural recording.

Recent clinical evidence suggests that abnormal neural input can contribute to the onset perpetuation of atrial arrhythmias, such that neural elements have become potential targets for ablation. A better understanding of the influence of the cardiac autonomous nervous system is required to improve therapy. We have developed a multi-channel system to record neural activity simultaneously at different intra and pericardiac locations. The paper presents the specific requirements to be met for recording neuronal extracellular potentials in these repertoires of neurons and the solutions that were adopted.

A parametric model of the relationship between EIT and total lung volume.

Spirometry and electrical impedance tomography (EIT) data from 26 healthy subjects (14 males, 12 females) were used to develop a model linking contrast variations in EIT difference images to lung volume changes. Eight recordings, each 64 s long, were made for each subject in four postures (standing, sitting, reclining at 45 degrees, supine) and two breathing modes (quiet tidal and deep breathing). Age, gender and five anthropometric variables were recorded. The database was divided into four subsets. The first subset, data from 22 subjects (12 males, 10 females) recorded in deep breathing mode, was used to create the model. Validation was done with the other subsets: data recorded during quiet tidal breathing in the same 22 subjects, and data recorded in both breathing modes for the other four subjects. A quadratic equation in DeltaV(P) (lung volume changes recorded by the spirometer) provided a very good fit to total contrast changes in the EIT images. The model coefficients were found to depend on posture, gender, thoracic circumference and scapular skin fold. To validate the model, the quadratic equation was inverted to estimate lung volume changes from the EIT images. The estimated changes were then compared to the measured volume changes. Validations with each data subset yielded mean standard errors ranging from 9.3% to 12.4%. The proposed model is a first step in enabling inter individual comparisons of EIT images since: (1) it provides a framework for incorporating the effects of anthropometric variables, gender and posture, and (2) it references the images to a physical quantity (volume) verifiable by spirometry.