Electrical Impedance Tomography of Cell Viability in Tissue With Application to Cryosurgery

2004 ◽  
Vol 126 (2) ◽  
pp. 305-309 ◽  
Author(s):  
Rafael Davalos ◽  
Boris Rubinsky

Tissue damage that is associated with the loss of cell membrane integrity should alter the bulk electrical properties of the tissue. This study shows that electrical impedance tomography (EIT) should be able to detect and image necrotic tissue inside the body due to the permeabilization of the membrane to ions. Cryosurgery, a minimally invasive surgical procedure that uses freezing to destroy undesirable tissue, was used to investigate the hypothesis. Experimental results with liver tissue demonstrate that cell damage during freezing results in substantial changes in tissue electrical properties. Two-dimensional EIT simulations of liver cryosurgery, which employ the experimental data, demonstrate the feasibility of this application.

Author(s):  
Georgios Lymperopoulos ◽  
Panagiotis Lymperopoulos ◽  
Victoria Alikari ◽  
Chrisoula Dafogianni ◽  
Sofia Zyga ◽  
...  

2016 ◽  
Vol 2 (1) ◽  
pp. 511-514 ◽  
Author(s):  
Florian Thürk ◽  
Andreas D. Waldmann ◽  
Karin H. Wodack ◽  
Constantin J. Trepte ◽  
Daniel Reuter ◽  
...  

AbstractAn accurate detection of anatomical structures in electrical impedance tomography (EIT) is still at an early stage. Aorta detection in EIT is of special interest, since it would favor non-invasive assessment of hemodynamic processes in the body. Here, diverse EIT reconstruction parameters of the GREIT algorithm were systematically evaluated to detect the aorta after saline bolus injection in apnea. True aorta position and size were taken from computed tomography (CT). A comparison with CT showed that the smallest error for aorta displacement was attained for noise figure nf = 0.7, weighting radius rw = 0.15, and target size ts = 0.01. The spatial extension of the aorta was most precise for nf = 0.7, rw = 0.25, and ts = 0.07. Detection accuracy (F1-score) was highest with nf = 0.6, rw = 0.15, and ts = 0.04. This work provides algorithm-related evidence for potentially accurate aorta detection in EIT after injection of a saline bolus.


2007 ◽  
Vol 2007 ◽  
pp. 1-7 ◽  
Author(s):  
Mustapha Azzouz ◽  
Martin Hanke ◽  
Chantal Oesterlein ◽  
Karl Schilcher

We present numerical results for two reconstruction methods for a new planar electrical impedance tomography device. This prototype allows noninvasive medical imaging techniques if only one side of a patient is accessible for electric measurements. The two reconstruction methods have different properties: one is a linearization-type method that allows quantitative reconstructions; the other one, that is, the factorization method, is a qualitative one, and is designed to detect anomalies within the body.


2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Melody Alsaker ◽  
Benjamin Bladow ◽  
Scott E. Campbell ◽  
Emma M. Kar

<p style='text-indent:20px;'>For patients undergoing mechanical ventilation due to respiratory failure, 2D electrical impedance tomography (EIT) is emerging as a means to provide functional monitoring of pulmonary processes. In EIT, electrical current is applied to the body, and the internal conductivity distribution is reconstructed based on subsequent voltage measurements. However, EIT images are known to often suffer from large systematic artifacts arising from various limitations and exacerbated by the ill-posedness of the inverse problem. The direct D-bar reconstruction method admits a nonlinear Fourier analysis of the EIT problem, providing the ability to process and filter reconstructions in the nonphysical frequency regime. In this work, a technique is introduced for automated Fourier-domain filtering of known systematic artifacts in 2D D-bar reconstructions. The new method is validated using three numerically simulated static thoracic datasets with induced artifacts, plus two experimental dynamic human ventilation datasets containing systematic artifacts. Application of the method is shown to significantly reduce the appearance of artifacts and improve the shape of the lung regions in all datasets.</p>


2019 ◽  
Vol 4 (4) ◽  
pp. 52-55
Author(s):  
Md Rabiul Islam

Electrical Impedance Tomography (EIT) is a non-invasive imaging technique that displays changes in conductivity within a body. This method finds application in biomedical and geology. EIT finds use in medical applications, as the different tissues of the body have different conductivity and dielectric constants. In this paper a phantom model is designed considering Finite Element Model (FEM). AC current of amplitude 1 mA and frequency 1 KHz is applied considering adjacent protocol with noise less and noisy cases. From the computed voltage data image is reconstructed using Kalman algorithm. For noisy case noise levels equal to Signal-to-Noise Ratio (SNR) 30 dB, 15 dB and 7 dB were considered. Kalman algorithm is studied for EIT image reconstruction in noise free and noisy case, in terms of shape, size, spatial location of the target object.


2020 ◽  
Vol 10 (2) ◽  
pp. 125
Author(s):  
Endarko Endarko ◽  
Ari Bangkit Sanjaya Umbu

Electrical impedance tomography is a non-invasive imaging modality that uses the electrical conductivity distribution to reconstruct images based on potential measurements from the object's surface. The proposed study was to design and fabricate a low-cost and simple reconstruction method for 3D electrical impedance tomography imaging. In this study, we have been successfully developed 3 Dimensional Electrical Impedance Tomography (3D-EIT) system using 16 copper electrodes (Cu) to detect and reconstruct the presence of objects in the Phantom. 3D-EIT was developed using Phantom as a test object with PVC pipe material, with an inner diameter of 7.2 cm and a height of 5.4 cm. Electrodes were arranged in two rings, with each ring having eight electrodes arranged in a planar line. Furthermore, the Gauss-Newton algorithm and Laplace prior regularization were used to image reconstruction of objects inside the Phantom using voltage measurement produced from sequential pairs of neighboring electrodes. The voltage is obtained from the injection of a constant current of 1 mA at 20 kHz into the system's electrode pairs. The objects used in this research are PVC pipe, solid aluminum, PVC pipes filled with wax glue, and copper trusses. The results obtained show that the reconstruction results can provide information about the position, the electrical properties, and the shape of real objects. Finally, the system can detect the location, height, and electrical properties of objects for all variations of angle and height variations.


2016 ◽  
Vol 2 (1) ◽  
pp. 499-502 ◽  
Author(s):  
Benjamin Schullcke ◽  
Sabine Krueger-Ziolek ◽  
Bo Gong ◽  
Knut Moeller

AbstractElectrical impedance tomography (EIT) is used to monitor the regional distribution of ventilation in a transversal plane of the thorax. In this manuscript we evaluate the impact of different quantities of electrodes used for current injection and voltage measurement on the reconstructed shape of the lungs. Results indicate that the shape of reconstructed impedance changes in the body depends on the number of electrodes. In this manuscript, we demonstrate that a higher number of electrodes do not necessarily increase the image quality. For the used stimulation pattern, utilizing neighboring electrodes for current injection and voltage measurement, we conclude that the shape of the lungs is best reconstructed if 16 electrodes are used.


2007 ◽  
Vol 2007 ◽  
pp. 1-9 ◽  
Author(s):  
Yair Granot ◽  
Antoni Ivorra ◽  
Boris Rubinsky

Electrical impedance tomography (EIT) produces an image of the electrical impedance distribution of tissues in the body, using electrodes that are placed on the periphery of the imaged area. These electrodes inject currents and measure voltages and from these data, the impedance can be computed. Traditional EIT systems usually inject current patterns in a serial manner which means that the impedance is computed from data collected at slightly different times. It is usually also a time-consuming process. In this paper, we propose a method for collecting data concurrently from all of the current patterns in biomedical applications of EIT. This is achieved by injecting current through all of the current injecting electrodes simultaneously, and measuring all of the resulting voltages at once. The signals from various current injecting electrodes are separated by injecting different frequencies through each electrode. This is called frequency-division multiplexing (FDM). At the voltage measurement electrodes, the voltage related to each current injecting electrode is isolated by using Fourier decomposition. In biomedical applications, using different frequencies has important implications due to dispersions as the tissue's electrical properties change with frequency. Another significant issue arises when we are recording data in a dynamic environment where the properties change very fast. This method allows simultaneous measurements of all the current patterns, which may be important in applications where the tissue changes occur in the same time scale as the measurement. We discuss the FDM EIT method from the biomedical point of view and show results obtained with a simple experimental system.


Author(s):  
Nabanita Saha ◽  
Mohammad Anisur Rahaman

Bone cancer is an uncommon sort of malignancy that alludes to irregular development of tissue inside the bone, with high opportunity to spread to different pieces of the body. It is extremely important to distinguish bone cancer at the beginning phase to cure it productively. Presently, in addition to a physical examination, magnetic resonance imaging, blood tests, positron emission tomography (PET), computed tomography (CT) or PET-CT scan, X-ray, Bone scan, Biopsy and computed tomography scan, are used to diagnose or determine the stage (or extent) of bone sarcoma. But these methods are costly and not free of radiation. Moreover, these machines are bulky. Electrical impedance tomography approach was proposed in this research for identifying bone cancer as this detection technique is able to distinguish between cancerous and non-cancerous cells by differentiating between their conductivity and it has the possibility to remove the limitations of conventional medical imaging techniques. Here, equivalent bone models were generated using (electrical impedance and diffused optical reconstruction software (EIDORS) which had been implemented in MATLAB, and three different image reconstruction algorithms-GREIT, Sheffield Backprojection, Gauss-Newton inverse algorithm had been used to detect the cancerous cells.


Sign in / Sign up

Export Citation Format

Share Document