Robert Guardo

Electrical impedance tomography: regularized imaging and contrast detection

Dynamic electrical impedance tomography (EIT) images changes in the conductivity distribution of a medium from low frequency electrical measurements made at electrodes on the medium surface. Reconstruction of the conductivity distribution is an under-determined and ill-posed problem, typically requiring either simplifying assumptions or regularization based on a priori knowledge. This paper presents a maximum a posteriori (MAP) approach to linearized image reconstruction using knowledge of the noise variance of the measurements and the covariance of the conductivity distribution. This approach has the advantage of an intuitive interpretation of the algorithm parameters as well as fast (near real time) image reconstruction. In order to compare this approach to existing algorithms, the authors develop figures of merit to measure the reconstructed image resolution, the noise amplification of the image reconstruction, and the fidelity of positioning in the image. Finally, the authors develop a communications systems approach to calculate the probability of detection of a conductivity contrast in the reconstructed image as a function of the measurement noise and the reconstruction algorithm used.

Regularized reconstruction in electrical impedance tomography using a variance uniformization constraint

This paper describes a new approach to reconstruction of the conductivity field in electrical impedance tomography. Our goal is to improve the tradeoff between the quality of the images and the numerical complexity of the reconstruction method. In order to reduce the computational load, we adopt a linearized approximation to the forward problem that describes the relationship between the unknown conductivity and the measurements. In this framework, we focus on finding a proper way to cope with the ill-posed nature of the problem, mainly caused by strong attenuation phenomena; this is done by devising regularization techniques well suited to this particular problem. First, we propose a solution which is based on Tikhonov regularization of the problem. Second, we introduce an original regularized reconstruction method in which the regularization matrix is determined by space-uniformization of the variance of the reconstructed conductivities. Both methods are nonsupervised, i.e., all tuning parameters are automatically determined from the measured data. Tests performed on simulated and real data indicate that Tikhonov regularization provides results similar to those obtained with iterative methods, but with a much smaller amount of computations. Regularization using a variance uniformization constraint yields further improvements, particularly in the central region of the unknown object where attenuation is most severe. We anticipate that the variance uniformization approach could be adapted to iterative methods that preserve the nonlinearity of the forward problem. More generally, it appears as a useful tool for solving other severely ill-posed reconstruction problems such as eddy current tomography.

A neural network image reconstruction technique for electrical impedance tomography

Reconstruction of images in electrical impedance tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically ill-conditioned and requires either simplifying assumptions or regularization based on a priori knowledge. The authors present a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse problem directly from finite element simulations of the forward problem. This inverse is adapted to the geometry of the medium and the signal-to-noise ratio (SNR) used during network training. Results show good conductivity reconstruction where measurement SNR is similar to the training conditions. The advantages of this method are its conceptual simplicity and ease of implementation, and the ability to control the compromise between the noise performance and resolution of the image reconstruction.

An Integrated System for Intraoperative Cardiac Activation Mapping

This paper describes an electrophysiological data acquisition and processing system which is programmed to rapidly generate cardiac activation maps for experimental studies and antiarrhythmia surgery. The basic system consists of a PDP-11/23+ minicomputer (DEC) with 1.5 Mbit memory and a 10 Mbit hard disk, a 64-channel data acquisition unit controlled by a specially designed interface card, and a modified video terminal. The data acquisition unit includes 64 instrumentation amplifiers with programmable gain and bandwidth. Signals are sampled and digitized at a maximum rate of 1000 samples/s/channel (10 bits) and transferred to the interface card by an optically isolated data bus. The operator controls the system by pointing to function boxes and signals appearing on the graphic terminal with a light pen. The software is based on a general-purpose data acquisition program with a command language interpreter. This program includes a setup section to define the systems parameters (gains, bandwidths, sampling rate) and an acquisition section to initiate data recording into a ring buffer, display the signals simultaneously on the screen, select heartbeats, and store or retrieve data on disk. The data processing procedures (in this case, mapping) can be easily interchanged to accommodate future signal processing needs. Current mapping procedures include an automatic detection section and an editor to manually define the local activation times on any electrogram. Another section displays the activation sequence as a map of isochronal lines. Typical processing time from the selection of a heartbeat to the visualization of the corresponding isochrone map is 2 min.

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 EITs 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.

Detection and analysis of cartilage degeneration by spatially resolved streaming potentials

Cartilage molecular changes in osteoarthritis are most commonly related to the degradation and loss of proteoglycan and collagen fibrils of the extracellular matrix, which directly influence tissue stiffness and compression‐generated streaming potentials. In this study, we evaluated the potential of a new technique, spatially resolved mapping of streaming potentials, to non‐destructively indicate cartilage health or degeneration. Matched pairs of bovine cartilage/bone explant disks were cultured for 11 days in a serum free medium with and without interleukin‐1α (IL‐1α). The electromechanical properties (static stiffness, dynamic stiffness and streaming potentials) of cartilage disks were measured during unconfined compression using a mechanical tester coupled with a linear array of eight 50 μm diameter platinum‐iridium microelectrodes. After 11 days of culture, the proteoglycan content of IL‐1α treated disks was significantly reduced and the denatured and cleaved collagen content was increased compared to control disks. These biochemical alterations were concomitant with the reductions in the amplitudes of the static stiffness, the dynamic stiffness and the streaming potential profile as well as changes in the shape of the streaming potential profile. We found that spatial mapping of streaming potentials presents several advantages for the development of a clinical instrument to evaluate the degeneration of articular cartilage.

An experimental study in electrical impedance tomography using backprojection reconstruction

The results of experiments designed to evaluate the performance of the equipotentials backprojection method under conditions modeling those of proposed applications of electrical impedance tomography are reported. Small spherical targets were placed inside a saline-filled tank with dimensions similar to a human torso. Data were acquired with a computer-based instrument that applies current to pairs of electrodes located on two horizontal planes and records potential differences between electrodes of a third plane. The relative contrast produced by nonconducting spheres in a uniform saline background was measured on the reconstructed images and used to determine system sensitivity to target volume and to the radial and vertical positions of single spheres. Results show that for radial positions within a critical radius sensitivity is always maximum when the spheres center is on the recording plane and decreases gradually when the target is moved outside this plane. Localization of simple targets in 3-D, with data acquired from multiple recording planes, appears feasible. The results provide guidelines for the interpretation of images with complex 3-D conductivity distributions.<<ETX>>

Evaluation of FFT-Based and Moder Parametrc Methods for the Spectral Analysis of Bioprosthetic Valve Sounds

The objective of this paper is to compare the performance of conventional FFT-based (basic periodogram and Welchs method) and modern parametric (all-pole and pole-zero modeling) methods in estimating the spectral distribution of cardiac bioprosthetic valve sounds, and for the extraction of the two most dominant frequency peaks (DFP). These methods were tested for stability by adding random noise and truncating the bioprosthetic valve closing sounds, and for reproducibility by measuring the variance of the spectra obtained from three consecutive recordings of each patient. Results from a group of 11 patients show that the basic periodogram and Steiglitz-McBrides method with maximum entropy (pole-zero modeling) provide the most consistent (minimal variance) estimates of the DFPs of the closing sounds. However, for estimating spectral distributions, the most stable methods appear to be the basic periodogram and Steiglitz-McBrides method with extrapolation to zero. The basic periodogram appears to be the best compromise to estimate both the spectral distribution and the DFPs of the bioprosthetic closing sounds.

Localization of cardiac ectopic activity in man by a single moving dipole. Comparison of different computation techniques

The accuracy of different computation techniques for the non-invasive localization of cardiac ectopic activity was evaluated. Body surface potentials were recorded from 63 leads in 14 patients with implanted pacemakers. The location, orientation and magnitude of a single moving dipole (SMD) were computed from the first eight terms of a truncated multipole expansion estimated from the body surface potentials. The SMD trajectories obtained during the QRS complex were plotted along with the heart outlines and pacing leads obtained independently from chest x-rays. The origin of the SMD trajectories was compared to the position of the pacing lead to evaluate the accuracy of the SMD. The optimum computation technique used a least-squares (LS) estimation of the multipole expansion truncated at 15 multipoles, in conjunction with a torso model that included regions of lower conductivity representing the lungs. With this method, the SMD trajectories originated near the pacing lead (25 +/- 12 mm) and adequately represented the progression of the ectopic wavefront across the entire heart silhouette. With the LS techniques using 8 or 24 multipoles, the spans of the trajectories were respectively too short, or too long to cover the heart, and the average distance between the SMD at QRS onset and the pacing lead was larger. With a surface integration technique, the SMD-pacing lead distances were similar, both for a finite homogeneous torso model with a fixed geometry, as well as for torso models adapted to the torso geometry of each patient. The SMD was found adequate to represent the progression of an ectopic wavefront, and to localize its origin in man.

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.