Atul S. Minhas

In Vivo High-ResolutionConductivity Imaging of the Human Leg Using MREIT: The First Human Experiment

We present the first in vivo cross-sectional conductivity image of the human leg with 1.7 mm pixel size using the magnetic resonance electrical impedance tomography (MREIT) technique. After a review of its experimental protocol by an Institutional Review Board (IRB), we performed MREIT imaging experiments of four human subjects using a 3 T MRI scanner. Adopting thin and flexible carbon-hydrogel electrodes with a large surface area and good contact, we could inject as much as 9 mA current in a form of 15 ms pulse into the leg without producing a painful sensation and motion artifact. Sequentially injecting two imaging currents in two different directions, we collected induced magnetic flux density data inside the leg. Scaled conductivity images reconstructed by using the single-step harmonic B z algorithm well distinguished different parts of the subcutaneous adipose tissue, muscle, crural fascia, intermuscular septum and bone inside the leg. We could observe spurious noise spikes in the outer layer of the bone primarily due to the MR signal void phenomenon there. Around the fat, the chemical shift of about two pixels occurred obscuring the boundary of the fat region. Future work should include a fat correction method incorporated in the MREIT pulse sequence and improvements in radio-frequency coils and image reconstruction algorithms. Further human imaging experiments are planned and being conducted to produce conductivity images from different parts of the human body.

MREIT conductivity imaging of the postmortem canine abdomen using CoReHA.

Magnetic resonance electrical impedance tomography (MREIT) is a new bio-imaging modality providing cross-sectional conductivity images from measurements of internal magnetic flux densities produced by externally injected currents. Recent experimental results of postmortem and in vivo imaging of the canine brain demonstrated its feasibility by showing conductivity images with meaningful contrast among different brain tissues. MREIT image reconstructions involve a series of data processing steps such as k-space data handling, phase unwrapping, image segmentation, meshing, modelling, finite element computation, denoising and so on. To facilitate experimental studies, we need a software tool that automates these data processing steps. In this paper, we summarize such an MREIT software package called CoReHA (conductivity reconstructor using harmonic algorithms). Performing imaging experiments of the postmortem canine abdomen, we demonstrate how CoReHA can be utilized in MREIT. The abdomen with a relatively large field of view and various organs imposes new technical challenges when it is chosen as an imaging domain. Summarizing a few improvements in the experimental MREIT technique, we report our first conductivity images of the postmortem canine abdomen. Illustrating reconstructed conductivity images, we discuss how they discern different organs including the kidney, spleen, stomach and small intestine. We elaborate, as an example, that conductivity images of the kidney show clear contrast among cortex, internal medulla, renal pelvis and urethra. We end this paper with a brief discussion on future work using different animal models.

Experimental performance evaluation of multi-echo ICNE pulse sequence in magnetic resonance electrical impedance tomography

Latest experimental results in magnetic resonance electrical impedance tomography (MREIT) demonstrated high‐resolution in vivo conductivity imaging of animal and human subjects using imaging currents of 5 to 9 mA. Externally injected imaging currents induce magnetic flux density distributions, which are affected by a conductivity distribution. Since we extract the induced magnetic flux density images from MR phase images, it is essential to reduce noise in the phase images. In vivo human and disease model animal experiments require reduction of imaging current amplitudes and scan times. In this article, we investigate a multi‐echo based MREIT pulse sequence where we utilize a remaining time after the first echo within one TR to obtain more echo signals. It also allows us to prolong the total current injection time. From phantom and animal imaging experiments, we found that this method significantly reduces the noise level in measured magnetic flux density images. We describe experimental validation of the multi‐echo sequence by comparing its performance with a single‐echo method using 3 mA imaging currents. The proposed method will be advantageous for an imaging region with long T2 values such as the brain and knee. Depending on T2 values, we suggest using two or three echoes in future experimental studies. Magn Reson Med, 2011.

Ion mobility imaging and contrast mechanism of apparent conductivity in MREIT

Magnetic resonance electrical impedance tomography (MREIT) aims to produce high-resolution cross-sectional images of conductivity distribution inside the human body. Injected current into an imaging object induces a distribution of internal magnetic flux density, which is measured by using an MRI scanner. We can reconstruct a conductivity image based on its relation with the measured magnetic flux density. In this paper, we explain the contrast mechanism in MREIT by performing and analyzing a series of numerical simulations and imaging experiments. We built a stable conductivity phantom including a hollow insulating cylinder with holes. Filling both inside and outside the hollow cylinder with the same saline, we controlled ion mobilities to create a conductivity contrast without being affected by the ion diffusion process. From numerical simulations and imaging experiments, we found that slopes of induced magnetic flux densities change with hole diameters and therefore conductivity contrasts. Associating the hole diameter with apparent conductivity of the region inside the hollow cylinder with holes, we could experimentally validate the contrast mechanism in MREIT. Interpreting reconstructed apparent conductivity images of the phantom as ion mobility images, we discuss the meaning of the apparent conductivity seen by a certain probing method. In designing MREIT imaging experiments, the ion mobility imaging method using the proposed stable conductivity phantom will enable us to estimate a distinguishable conductivity contrast for a given set of imaging parameters.

Magnetic flux density measurement with balanced steady state free precession pulse sequence for MREIT: A simulation study

Magnetic Resonance Electrical Impedance Tomography (MREIT) utilizes the magnetic flux density Bz, generated due to current injection, to find conductivity distribution inside an object. This Bz can be measured from MR phase images using spin echo pulse sequence. The SNR of Bz and the sensitivity of phase produced by Bz in MR phase image are critical in deciding the resolution of MREIT conductivity images. The conventional spin echo based data acquisition has poor phase sensitivity to current injection. Longer scan time is needed to acquire data with higher SNR. We propose a balanced steady state free precession (b-SSFP) based pulse sequence which is highly sensitive to small off-resonance phase changes. A procedure to reconstruct Bz from MR signal obtained with b-SSFP sequence is described. Phases for b-SSFP signals for two conductivity phantoms of TX 151 and Gelatin are simulated from the mathematical models of b-SSFP signal. It was observed that the phase changes obtained from b-SSFP pulse sequence are highly sensitive to current injection and hence would produce higher magnetic flux density. However, the b-SSFP signal is dependent on magnetic field inhomogeneity and the signal deteriorated highly for small offset from resonance frequency. The simulation results show that the b-SSFP sequence can be utilized for conductivity imaging of a local region where magnetic field inhomogeneity is small. A proper shimming of magnet is recommended before using the b-SSFP sequence.

Neural network based approach for anomaly detection in the lungs region by electrical impedance tomography

In this paper, we have shown a simple procedure to detect anomalies in the lungs region by electrical impedance tomography. The main aim of the present study is to investigate the possibility of anomaly detection by using neural networks. Radial basis function neural networks are used as classifiers to classify the anomaly as belonging to the anterior or posterior region of the left lung or the right lung. The neural networks are trained and tested with the simulated data obtained by solving the mathematical model equation governing current flow through the simulated thoracic region. The equation solution and model simulation are done with FEMLAB. The effect of adding a higher number of neurons to the hidden layer can be clearly seen by the reduction in classification error. The study shows that there is interaction between the size (radius) and conductivity of anomalies and for some combination of these two factors the classification error of neural networks will be very small.

MREIT conductivity imaging of canine head using multi-echo pulse sequence

In magnetic resonance electrical impedance tomography (MREIT), we measure induced magnetic flux densities subject to multiple injection currents to reconstruct cross-sectional conductivity images. Spin echo pulse sequence has been widely used in MREIT and produce postmortem and in vivo conductivity images of animal and human subjects. The image quality depends on the SNR of the measured magnetic flux density image. In order to reduce the scan time and current amplitude while keeping the image quality, we have developed a multi-echo pulse sequence for MREIT. In this study, we show results of canine head MREIT imaging experiments using the multi-echo pulse sequence. Compared to the injection current nonlinear encoding (ICNE) pulse sequence, it provides a higher SNR of MR magnitude images by combining multiple echo signals. Noise in measured magnetic flux density data is significantly reduced due to an increased current injection time over multiple echo signals. These allow us to significantly decrease the total scan time. Reconstructed conductivity images of a canine head show enhanced conductivity contrast between gray and white matter using the multi-echo pulse sequence. In our future work, we will focus on in vivo human and disease model animal experiments using the new MREIT pulse sequence.

In vivo conductivity imaging of canine male pelvis using a 3T MREIT system

The prostate is an imaging area of growing concern related with aging. Prostate cancer and benign prostatic hyperplasia are the most common diseases and significant cause of death for elderly men. Hence, the conductivity imaging of the male pelvis is a challenging task with a clinical significance. In this study, we performed in vivo MREIT imaging experiments of the canine male pelvis using a 3T MRI scanner. Adopting carbon-hydrogel electrodes and a multi-echo pulse sequence, we could inject as much as 10 mA current in a form of 51 ms pulse into the pelvis. Collecting magnetic flux density data inside the pelvis subject to multiple injection currents, we reconstructed cross-sectional conductivity images using a MREIT software package CoReHA. Scaled conductivity images of the prostate show a clear contrast between the central and peripheral zones which are related with prostate diseases including cancer and benign prostatic hyperplasia. In our future work, we will focus on prostate cancer model animal experiments.

Simulation of MREIT using balanced steady state free precession (b-SSFP) pulse sequence

Magnetic resonance electrical impedance tomography (MREIT) utilizes the relation between conductivity and magnetic flux density induced by externally injected current to perform conductivity imaging of body tissues. A spin echo pulse sequence has been predominantly used in MREIT to acquire the z-component Bz of the induced magnetic flux density data from MR phase images. Spin echo based MREIT pulse sequences are most stable and successful in producing high-resolution conductivity images in postmortem and in vivo animal and human experiments. In some applications, localization of a physiological event is desirable. Examples may include detection of neural activities through conductivity changes. In such a case, it would be necessary to maximize the sensitivity. In this paper, we suggest using a balanced steady state free precession (b-SSFP) pulse sequence to localize a small conductivity change. The induced magnetic flux density Bz subject to an injection current makes an off-resonance phase in b-SSFP signals. We expect the high sensitivity of b-SSFP signals to any off-resonance phase change will be advantageous for detecting a small conductivity change. Using computer simulations, we show the feasibility of functional or time-difference MREIT using the b-SSFP pulse sequence.

Electrical conductivity imaging of lower extremities using MREIT: Postmortem swine and in vivo human experiments

Cross-sectional conductivity images of lower extremities were reconstructed using Magnetic Resonance Electrical Impedance Tomography (MREIT) techniques. Carbon-hydrogel electrodes were adopted for postmortem swine and in vivo human imaging experiments. Due to their large surface areas and good contacts on the skin, we could inject as much as 10 mA into the lower extremities of human subjects without producing a painful sensation. Using a 3T MREIT system, we first performed a series of postmortem swine experiments and produced high-resolution conductivity images of swine legs. Validating the experimental protocol for the lower extremities, we revised it for the following human experiments. After the review of the Institutional Review Board (IRB), we conducted our first MREIT experiments of human subjects using the same 3T MREIT system. Collecting magnetic flux density data inside lower extremities subject to multiple injection currents, we reconstructed cross-sectional conductivity images using the harmonic Bz algorithm. The conductivity images very well distinguished different parts of muscles inside the lower extremities. The outermost fatty layer was clearly shown in each conductivity image. We could observe severe noise in the outer layer of the bones primarily due to the MR signal void phenomenon there. Reconstructed conductivity images indicated that the internal regions of the bones have relatively high conductivity values. Future study is desired in terms of the conductivity image reconstruction algorithm to improve the image quality. Further human imaging experiments are planned and being conducted to produce high-resolution conductivity images from different parts of the human body.