Four-channel current switching device to enable multi-electrode magnetic resonance current density imaging

Neurostimulation with multiple scalp electrodes has shown enhanced effects in recent studies. However, visualizations of stimulation-induced internal current distributions in brain is only possible through simulated current distributions obtained from computer model of human head. While magnetic resonance current density imaging (MRCDI) has a potential for direct in-vivo measurement of currents induced in brain with multi-electrode stimulation, existing MRCDI methods are only developed for two-electrode neurostimulation. A major bottleneck is the lack of a current switching device which is typically used to convert the DC current of neurostimulation devices into user-defined waveforms of positive and negative polarity with delays between them. In this work, we present a design of a four-electrode current switching device to enable simultaneous switching of current flowing through multiple scalp electrodes.

Analyzing the Effect of Resolution of Network Nodes on the Resting State Functional Connectivity Maps of Schizophrenic Human Brains

Functional connectivity (FC) mapping from resting-state functional magnetic resonance imaging (rsfMRI) data is a widely used technique to characterize the brain abnormalities in mental health disorders. Using atlases for brain parcellation is an important intermediate step in calculation of FC maps. Atlases with varying resolution (number of nodes in an atlas) have been deployed by researchers to study the abnormal brain functions in Schizophrenia. In this work, we compared the variations in FC maps of Schizophrenic brains obtained from three different atlases: AAL atlas (2002), Dosenbach atlas (2010), and the Brainnetome atlas (2016). To evaluate the atlas-dependent variations in FC maps, we relied on the capability of the features of FC maps in accurately classifying a given data into healthy or Schizophrenia group. Our results indicate that the high-resolution Dosenbach and Brainnetome atlases perform better than AAL atlas in terms of the accuracy, sensitivity and specificity of the SVM classifier.

Humanoid Robot Based Platform to Evaluate the Efficacy of Using Inertial Sensors for Spasticity Assessment in Cerebral Palsy

Spasticity is commonly present in individuals with cerebral palsy (CP) and manifests itself as shaky movements, muscle tightness and joint stiffness. Accurate and objective measurement of spasticity is investigated using inertial measurement unit (IMU) sensors. However, use of current IMU-based devices is limited to clinics in urban areas where experienced and trained health professionals are available to collect spasticity data. Designing these devices based on the wearable internet of things based architectures with edge computing will expand their use to home, aged care or remote clinics enabling less-experienced health professionals or care givers to collect spasticity data. However, these new designs require rigorous testing during their prototyping stage and collection of supporting data for regulatory approvals. This work demonstrates that a humanoid robot can act as an accurate model of the movements of CP individuals performing pendulum test during their spasticity assessment. Utilizing this model, we present a robust platform to evaluate new designs of IMU-based spasticity measurement devices.

Measuring Kidney Perfusion, pH, and Renal Clearance Consecutively Using MRI and Multispectral Optoacoustic Tomography

Purpose: To establish multi-modal imaging for the assessment of kidney pH, perfusion, and clearance rate using magnetic resonance imaging (MRI) and multispectral optoacoustic tomography (MSOT) in healthy mice. Kidney pH and perfusion values were measured on a pixel-by-pixel basis using the MRI acidoCEST and FAIR-EPI methods. Kidney filtration rate was measured by analyzing the renal clearance rate of IRdye 800 using MSOT. To test the effect of one imaging method on the other, a set of 3 animals were imaged with MSOT followed by MRI, and a second set of 3 animals were imaged with MRI followed by MSOT. In a subsequent study, the reproducibility of pH, perfusion, and renal clearance measurements were tested by imaging 4 animals twice, separated by 4 days. The contrast agents used for acidoCEST based pH measurements influenced the results of MSOT. Specifically, the exponential decay time from the kidney cortex, as measured by MSOT, was significantly altered when MRI was performed prior to MSOT. However, no significant difference in the cortex to pelvis area under the curve (AUC) was noted. When the order of experiments was reversed, no significant differences were noted in the pH or perfusion values. Reproducibility measurements demonstrated similar pH and cortex to pelvis AUC; however, perfusion values were significantly different with the cortex values being higher and the pelvic values being lower in the second imaging time. We demonstrate that using a combination of MRI and MSOT, physiological measurements of pH, blood flow, and clearance rates can be measured in the mouse kidney in the same imaging session.

Evaluation of magnetohydrodynamic effects in magnetic resonance electrical impedance tomography at ultra-high magnetic fields

PURPOSE

Artifacts observed in experimental magnetic resonance electrical impedance tomography images were hypothesized to be because of magnetohydrodynamic (MHD) effects.

THEORY AND METHODS

Simulations of MREIT acquisition in the presence of MHD and electrical current flow were performed to confirm findings. Laminar flow and (electrostatic) electrical conduction equations were bidirectionally coupled via Lorentz force equations, and finite element simulations were performed to predict flow velocity as a function of time. Gradient sequences used in spin-echo and gradient echo acquisitions were used to calculate overall effects on MR phase images for different electrical current application or phase-encoding directions.

RESULTS

Calculated and experimental phase images agreed relatively well, both qualitatively and quantitatively, with some exceptions. Refocusing pulses in spin echo sequences did not appear to affect experimental phase images.

CONCLUSION

MHD effects were confirmed as the cause of observed experimental phase changes in MREIT images obtained at high fields. These findings may have implications for quantitative measurement of viscosity using MRI techniques. Methods developed here may be also important in studies of safety and in vivo artifacts observed in high field MRI systems.

Wearable Internet of Things - from human activity tracking to clinical integration

Wearable devices for human activity tracking have been emerging rapidly. Most of them are capable of sending health statistics to smartphones, smartwatches or smart bands. However, they only provide the data for individual analysis and their data is not integrated into clinical practice. Leveraging on the Internet of Things (IoT), edge and cloud computing technologies, we propose an architecture which is capable of providing cloud based clinical services using human activity data. Such services could supplement the shortage of staff in primary healthcare centers thereby reducing the burden on healthcare service providers. The enormous amount of data created from such services could also be utilized for planning future therapies by studying recovery cycles of existing patients. We provide a prototype based on our architecture and discuss its salient features. We also provide use cases of our system in personalized and home based healthcare services. We propose an International Telecommunication Union based standardization (ITU-T) for our design and discuss future directions in wearable IoT.

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.

In vivo high-resolution conductivity 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.

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 B(z), generated due to current injection, to find conductivity distribution inside an object. This B(z) can be measured from MR phase images using spin echo pulse sequence. The SNR of B(z) and the sensitivity of phase produced by B(z) 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 B(z) 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.

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 B(z) 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.

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.