Measuring the acoustoelectric interaction constant using ultrasound current source density imaging

Simulation study on high spatio-temporal resolution acousto-electrophysiological neuroimaging

Objective.Acousto-electrophysiological neuroimaging (AENI) is a technique hypothesized to record electrophysiological activity of the brain with millimeter spatial and sub-millisecond temporal resolution. This improvement is obtained by tagging areas with focused ultrasound (fUS). Due to mechanical vibration with respect to the measuring electrodes, the electrical activity of the marked region will be modulated onto the ultrasonic frequency. The region's electrical activity can subsequently be retrieved via demodulation of the measured signal. In this study, the feasibility of this hypothesized technique is tested.Approach.This is done by calculating the forward electroencephalography response under quasi-static assumptions. The head is simplified as a set of concentric spheres. Two sizes are evaluated representing human and mouse brains. Moreover, feasibility is assessed for wet and dry transcranial, and for cortically placed electrodes. The activity sources are modeled by dipoles, with their current intensity profile drawn from a power-law power spectral density.Results.It is shown that mechanical vibration modulates the endogenous activity onto the ultrasonic frequency. The signal strength depends non-linearly on the alignment between dipole orientation, vibration direction and recording point. The strongest signal is measured when these three dependencies are perfectly aligned. The signal strengths are in the pV-range for a dipole moment of 5 nAm and ultrasonic pressures within Food and Drug Administration (FDA)-limits. The endogenous activity can then be accurately reconstructed via demodulation. Two interference types are investigated: vibrational and static. Depending on the vibrational interference, it is shown that millimeter resolution signal detection is possible also for deep brain regions. Subsequently, successful demodulation depends on the static interference, that at MHz-range has to be sub-picovolt.Significance.Our results show that mechanical vibration is a possible underlying mechanism of acousto-electrophyisological neuroimaging. This paper is a first step towards improved understanding of the conditions under which AENI is feasible.

Transcranial dipole localization and decoding study based on ultrasonic phased array for acoustoelectric brain imaging

Objective. Neuroimaging is one of the effective tools to understand the functional activities of the brain, but traditional non-invasive neuroimaging techniques are difficult to combine both high temporal and spatial resolution to satisfy clinical needs. Acoustoelectric brain imaging (ABI) can combine the millimeter spatial resolution advantage of focused ultrasound with the millisecond temporal resolution advantage of electroencephalogram signals.Approach. In this study, we first explored the transcranial modulated acoustic field distribution based on ABI, and further localized and decoded single and double dipoles signals.Main results. The results show that the simulation-guided acoustic field modulation results are significantly better than those of self-focusing, which can realize precise modulation focusing of intracranial target focusing. The single dipole transcranial localization error is less than 0.4 mm and the decoding accuracy is greater than 0.93. The double dipoles transcranial localization error is less than 0.2 mm and the decoding accuracy is greater than 0.89.Significance. This study enables precise focusing of transcranial acoustic field modulation, high-precision localization of source signals and decoding of their waveforms, which provides a technical method for ABI in localizing evoked excitatory neuron areas and epileptic focus.

Acoustoelectric Time-Reversal for Ultrasound Phase-Aberration Correction

Acoustoelectric imaging (AEI) is a technique that combines ultrasound (US) with radio frequency recording to detect and map local current source densities. This study demonstrates a new method called acoustoelectric time reversal (AETR), which uses AEI of a small current source to correct for phase aberrations through a skull or other US-aberrating layers with applications to brain imaging and therapy. Simulations conducted at three different US frequencies (0.5, 1.5, and 2.5 MHz) were performed through media layered with different sound speeds and geometries to induce aberrations of the US beam. Time delays of the acoustoelectric (AE) signal from a monopole within the medium were calculated for each element to enable corrections using AETR. Uncorrected aberrated beam profiles were compared with those after applying AETR corrections, which demonstrated a strong recovery (29%-100%) of lateral resolution and increases in focal pressure up to 283%. To further demonstrate the practical feasibility of AETR, we further conducted bench-top experiments using a 2.5 MHz linear US array to perform AETR through 3-D-printed aberrating objects. These experiments restored lost lateral restoration up to 100% for the different aberrators and increased focal pressure up to 230% after applying AETR corrections. Cumulatively, these results highlight AETR as a powerful tool for correcting focal aberrations in the presence of a local current source with applications to AEI, US imaging, neuromodulation, and therapy.

An adaptive acoustoelectric signal decoding algorithm based on Fourier fitting for brain function imaging

Acousticelectric brain imaging (ABI), which is based on the acoustoelectric (AE) effect, is a potential brain function imaging method for mapping brain electrical activity with high temporal and spatial resolution. To further enhance the quality of the decoded signal and the resolution of the ABI, the decoding accuracy of the AE signal is essential. An adaptive decoding algorithm based on Fourier fitting (aDAF) is suggested to increase the AE signal decoding precision. The envelope of the AE signal is first split into a number of harmonics by Fourier fitting in the suggested aDAF. The least square method is then utilized to adaptively select the greatest harmonic component. Several phantom experiments are implemented to assess the performance of the aDAF, including 1-source with various frequencies, multiple-source with various frequencies and amplitudes, and multiple-source with various distributions. Imaging resolution and decoded signal quality are quantitatively evaluated. According to the results of the decoding experiments, the decoded signal amplitude accuracy has risen by 11.39% when compared to the decoding algorithm with envelope (DAE). The correlation coefficient between the source signal and the decoded timing signal of aDAF is, on average, 34.76% better than it was for DAE. Finally, the results of the imaging experiment show that aDAF has superior imaging quality than DAE, with signal-to noise ratio (SNR) improved by 23.32% and spatial resolution increased by 50%. According to the experiments, the proposed aDAF increased AE signal decoding accuracy, which is vital for future research and applications related to ABI.

Biological current source imaging method based on acoustoelectric effect: A systematic review

Neuroimaging can help reveal the spatial and temporal diversity of neural activity, which is of utmost importance for understanding the brain. However, conventional non-invasive neuroimaging methods do not have the advantage of high temporal and spatial resolution, which greatly hinders clinical and basic research. The acoustoelectric (AE) effect is a fundamental physical phenomenon based on the change of dielectric conductivity that has recently received much attention in the field of biomedical imaging. Based on the AE effect, a new imaging method for the biological current source has been proposed, combining the advantages of high temporal resolution of electrical measurements and high spatial resolution of focused ultrasound. This paper first describes the mechanism of the AE effect and the principle of the current source imaging method based on the AE effect. The second part summarizes the research progress of this current source imaging method in brain neurons, guided brain therapy, and heart. Finally, we discuss the problems and future directions of this biological current source imaging method. This review explores the relevant research literature and provides an informative reference for this potential non-invasive neuroimaging method.

In vivo acoustoelectric imaging for high-resolution visualization of cardiac electric spatiotemporal dynamics

Acoustoelectric cardiac imaging (ACI) is a hybrid modality that exploits the interaction of an ultrasonic pressure wave and the resistivity of tissue to map current densities in the heart. This study demonstrates for the first time in vivo ACI in a swine model. ACI measured beat-to-beat variability (n=20) of the peak of the cardiac activation wave at one location of the left ventricle as 5.32±0.74µV, 3.26±0.54mm below the epicardial surface, and 2.67±0.56ms before the peak of the local electrogram. Cross-sectional ACI images exhibited propagation velocities of 0.192±0.061m/s along the epicardial-endocardial axis with an SNR of 24.9 dB. This study demonstrates beat-to-beat and multidimensional ACI, which might reveal important information to help guide electroanatomic mapping procedures during ablation therapy.

Acoustoelectric imaging of deep dipoles in a human head phantom for guiding treatment of epilepsy

OBJECTIVE

This study employs a human head model with real skull to demonstrate the feasibility of transcranial acoustoelectric brain imaging (tABI) as a new modality for electrical mapping of deep dipole sources during treatment of epilepsy with much better resolution and accuracy than conventional mapping methods.

APPROACH

This technique exploits an interaction between a focused ultrasound (US) beam and tissue resistivity to localize current source densities as deep as 63 mm at high spatial resolution (1 to 4 mm) and resolve fast time-varying currents with sub-ms precision.

MAIN RESULTS

Detection thresholds through a thick segment of the human skull at biologically safe US intensities was below 0.5 mA and within range of strong currents generated by the human brain.

SIGNIFICANCE

This work suggests that 4D tABI may emerge as a revolutionary modality for real-time high-resolution mapping of neuronal currents for the purpose of monitoring, staging, and guiding treatment of epilepsy and other brain disorders characterized by abnormal rhythms.

High resolution transcranial acoustoelectric imaging of current densities from a directional deep brain stimulator

OBJECTIVE

New innovations in deep brain stimulation (DBS) enable directional current steering-allowing more precise electrical stimulation of the targeted brain structures for Parkinson's disease, essential tremor and other neurological disorders. While intra-operative navigation through MRI or CT approaches millimeter accuracy for placing the DBS leads, no existing modality provides feedback of the currents as they spread from the contacts through the brain tissue. In this study, we investigate transcranial acoustoelectric imaging (tAEI) as a new modality to non-invasively image and characterize current produced from a directional DBS lead. tAEI uses ultrasound (US) to modulate tissue resistivity to generate detectable voltage signals proportional to the local currents.

APPROACH

An 8-channel directional DBS lead (Infinity 6172ANS, Abbott Inc) was inserted inside three adult human skulls submerged in 0.9% NaCl. A 2.5 MHz linear array delivered US pulses through the transtemporal window and focused near the contacts on the lead, while a custom amplifier and acquisition system recorded the acoustoelectric (AE) interaction used to generate images.

MAIN RESULTS

tAEI detected monopolar current with stimulation pulses as short as 100 µs with an SNR ranging from 10-27 dB when using safe US pressure (mechanical indices  <0.78) and injected current of ~2 mA peak amplitude. Adjacent contacts were discernable along the length and within each ring of the lead with a mean radial separation between contacts of 2.10 and 1.34 mm, respectively.

SIGNIFICANCE

These results demonstrate the feasibility of tAEI for high resolution mapping of directional DBS currents using clinically-relevant stimulation parameters. This new modality may improve the accuracy for placing the DBS leads, guide calibration and programming, and monitor long-term performance of DBS for treatment of Parkinson's disease.

Selective Mapping of Deep Brain Stimulation Lead Currents Using Acoustoelectric Imaging

We describe a new application of acoustoelectric imaging for non-invasive mapping of the location, magnitude and polarity of current generated by a clinical deep brain stimulation (DBS) device. Ultrasound at 1MHz was focused near the DBS device as short current pulses were injected across different DBS leads. A recording electrode detected the high-frequency acoustoelectric interaction signal. Linear scans of the US beam produced time-varying images of the magnitude and polarity of the induced current, enabling precise localization of the DBS leads within 0.70mm, a detection threshold of 1.75mA at 1 MPa and a sensitivity of 0.52 ± 0.07 μV/(mA*MPa). Monopole and dipole configurations in saline were repeated through a human skullcap. Despite 13.8-dB ultrasound attenuation through bone, acoustoelectric imaging was still >10dB above background with a sensitivity of 0.56 ± 0.10 μV/(mA*MPa). This proof-of-concept study indicates that selective mapping of lead currents through a DBS device may be possible using non-invasive acoustoelectric imaging.

Tissue Acoustoelectric Effect Modeling From Solid Mechanics Theory

The acoustoelectric (AE) effect is a basic physical phenomenon, which underlies the changes made in the conductivity of a medium by the application of focused ultrasound. Recently, based on the AE effect, several biomedical imaging techniques have been widely studied, such as ultrasound-modulated electrical impedance tomography and ultrasound current source density imaging. To further investigate the mechanism of the AE effect in tissue and to provide guidance for such techniques, we have modeled the tissue AE effect using the theory of solid mechanics. Both bulk compression and thermal expansion of tissue are considered and discussed. Computation simulation shows that the muscle AE effect result, conductivity change rate, is 3.26×10^-3 with 4.3-MPa peak pressure, satisfying the theoretical value. Bulk compression plays the main role for muscle AE effect, while thermal expansion makes almost no contribution to it. In addition, the AE signals of porcine muscle are measured at different focal positions. With the same magnitude order and the same change trend, the experiment result confirms that the simulation result is effective. Both simulation and experimental results validate that tissue AE effect modeling using solid mechanics theory is feasible, which is of significance for the further development of related biomedical imaging techniques.

An integrated and highly sensitive ultrafast acoustoelectric imaging system for biomedical applications

Direct imaging of the electrical activation of the heart is crucial to better understand and diagnose diseases linked to arrhythmias. This work presents an ultrafast acoustoelectric imaging (UAI) system for direct and non-invasive ultrafast mapping of propagating current densities using the acoustoelectric effect. Acoustoelectric imaging is based on the acoustoelectric effect, the modulation of the medium's electrical impedance by a propagating ultrasonic wave. UAI triggers this effect with plane wave emissions to image current densities. An ultrasound research platform was fitted with electrodes connected to high common-mode rejection ratio amplifiers and sampled by up to 128 independent channels. The sequences developed allow for both real-time display of acoustoelectric maps and long ultrafast acquisition with fast off-line processing. The system was evaluated by injecting controlled currents into a saline pool via copper wire electrodes. Sensitivity to low current and low acoustic pressure were measured independently. Contrast and spatial resolution were measured for varying numbers of plane waves and compared to line per line acoustoelectric imaging with focused beams at equivalent peak pressure. Temporal resolution was assessed by measuring time-varying current densities associated with sinusoidal currents. Complex intensity distributions were also imaged in 3D. Electrical current densities were detected for injected currents as low as 0.56 mA. UAI outperformed conventional focused acoustoelectric imaging in terms of contrast and spatial resolution when using 3 and 13 plane waves or more, respectively. Neighboring sinusoidal currents with opposed phases were accurately imaged and separated. Time-varying currents were mapped and their frequency accurately measured for imaging frame rates up to 500 Hz. Finally, a 3D image of a complex intensity distribution was obtained. The results demonstrated the high sensitivity of the UAI system proposed. The plane wave based approach provides a highly flexible trade-off between frame rate, resolution and contrast. In conclusion, the UAI system shows promise for non-invasive, direct and accurate real-time imaging of electrical activation in vivo.

Polarity detection in ultrasound current source density imaging

Modulating the electric dipole field with ultrasound pulse, ultrasound current source density imaging (UCSDI) can detect current direction and form spatial 3D imaging of dipole changing in one period of treatment. As ultrasound pulse passes through the conductive media, it convolves/correlates with the inner product of the electric field of a dipole and lead field of a pair of detectors, making the shifting frequency of polarity lower than the center frequency of the ultrasound pulse. After acoustoelectric (AE) signal is shifted to base band, the AE voltage is positive at anode and negative at cathode. In the simulation, the lead fields of detectors and electric field of dipole were calculated by the finite element (FE) method; the convolution and correlation in the computation of AE signal were accelerated using 3-D fast Fourier transforms. The current direction and amplitude are encoded in the phase and amplitude of the AE signal. Based on the analysis of polarity algorithms on the simulated and in-vitro ultrasound current source density images, it is concluded that the cross-correlation method is significantly better than the autocorrelation method to extract the frequency shift for high pulse bandwidth.

Complementary Detection of Multiple Electrical Sources in Tissue Using Acoustoelectric Effects

Accurate 3-D mapping of multiple bioelectric sources in nerve fibers with high spatial resolution is challenging for the diagnosis and treatment of a variety of neural abnormalities. Ultrasound current source density imaging exploits the acoustoelectric (AE) effect, an interaction between electrical current and acoustic pressure waves propagating through a conducting material, and has distinct advantages over conventional electrophysiology (i.e., without ultrasound) for mapping electrical current flow in tissue. Ultrasound current source density imaging and two complementary Wheatstone bridge circuits were used to simultaneously detect two separate current flows induced in tissue phantoms. It has been found that the addition and subtraction of AE signals acquired by two circuits are independent components, regardless of whether the two sources are positioned at the same or different depths. In the ultrasound field, the AE signal from the bridge circuits is stronger, with a higher signal-to-noise ratio, than without a bridge circuit. Both experimental and simulated AE images depend on the magnitude and direction of the current, as well as the geometry (shape and thickness) and location of the current sources in the ultrasound field (2.25-MHz transducer). The experimental results are consistent with simulations consisting of multiple current sources. Real-time 3-D ultrasound current source density images of multiple current flows co-registered with convention pulse echo ultrasound potentially facilitate monitoring of neurologic disorders.

The development of an experimental setup to measure acousto-electric interaction signal

A new method is desirable for secure efficiency of FES treatment of degenerated denervated muscles. Degeneration of denervaed muscles as a consequence of spinal injuries are treated with functional electrical stimulation (FES). So far, no effective method to monitor the effectiveness of the treatment over the whole treated muscle is available. The most common method is placing finger on appropriate tendons and sense the movement. We suggest new approach. As pressure wave changes locally electrical conductivity in its propagation direction of the medium, a change in voltage is detected when electrical field is applied simultaneously at that location. This change in voltage is called acousto-electric interaction (AEI) signal. By recording AEI signal a distribution of electrical activity can be mapped, known as ultrasound current source density imaging (UCSDI). In this paper, an experimental setup to investigate the AEI signal is developed. The signal is measured and compared to calculated values. Debye effect and AEI signal is detected.

Application of Acoustic-Electric Interaction for Neuro-Muscular Activity Mapping: A Review

Acousto-electric interaction signal (AEI signal) resulting from interaction of acoustic pressure wave and electrical current field has received recent attention in biomedical field for detection and registration of bioelectrical current. The signal is very of small value and brings about several challenges when detecting it. Several observations has been done in saline solution and on nerves and tissues under controlled condition that give optimistic indication about its utilization. Ultrasound Current Source Density Imaging (UCSDI) has been introduced, that uses the AEI signal to image the current distribution. This review provides an overview of the investigations on the AEI signal and USCDI imaging that has been made, their results and several considerations on the limitations and future possibilities on using the acousto-electric interaction signal.

Ultrasound current source density imaging of the cardiac activation wave using a clinical cardiac catheter

Ultrasound current source density imaging (UCSDI), based on the acoustoelectric (AE) effect, is a noninvasive method for mapping electrical current in 4-D (space + time). This technique potentially overcomes limitations with conventional electrical mapping procedures typically used during treatment of sustained arrhythmias. However, the weak AE signal associated with the electrocardiogram is a major challenge for advancing this technology. In this study, we examined the effects of the electrode configuration and ultrasound frequency on the magnitude of the AE signal and quality of UCSDI using a rabbit Langendorff heart preparation. The AE signal was much stronger at 0.5 MHz (2.99 μV/MPa) than 1.0 MHz (0.42 μV/MPa). Also, a clinical lasso catheter placed on the epicardium exhibited excellent sensitivity without penetrating the tissue. We also present, for the first time, 3-D cardiac activation maps of the live rabbit heart using only one pair of recording electrodes. Activation maps were used to calculate the cardiac conduction velocity for atrial (1.31 m/s) and apical (0.67 m/s) pacing. This study demonstrated that UCSDI is potentially capable of real-time 3-D cardiac activation wave mapping, which would greatly facilitate ablation procedures for treatment of arrhythmias.

Simulation-based validation for four- dimensional multi-channel ultrasound current source density imaging

Ultrasound current source density imaging (UCSDI), which has application to the heart and brain, exploits the acoustoelectric (AE) effect and Ohm's law to detect and map an electrical current distribution. In this study, we describe 4-D UCSDI simulations of a dipole field for comparison and validation with bench-top experiments. The simulations consider the properties of the ultrasound pulse as it passes through a conductive medium, the electric field of the injected dipole, and the lead field of the detectors. In the simulation, the lead fields of detectors and electric field of the dipole were calculated by the finite element (FE) method, and the convolution and correlation in the computation of the detected AE voltage signal were accelerated using 3-D fast Fourier transforms. In the bench-top experiment, an electric dipole was produced in a bath of 0.9% NaCl solution containing two electrodes, which injected an ac pulse (200 Hz, 3 cycles) ranging from 0 to 140 mA. Stimulating and recording electrodes were placed in a custom electrode chamber made on a rapid prototype printer. Each electrode could be positioned anywhere on an x-y grid (5 mm spacing) and individually adjusted in the depth direction for precise control of the geometry of the current sources and detecting electrodes. A 1-MHz ultrasound beam was pulsed and focused through a plastic film to modulate the current distribution inside the saline-filled tank. AE signals were simultaneously detected at a sampling frequency of 15 MHz on multiple recording electrodes. A single recording electrode is sufficient to form volume images of the current flow and electric potentials. The AE potential is sensitive to the distance from the dipole, but is less sensitive to the angle between the detector and the dipole. Multi-channel UCSDI potentially improves 4-D mapping of bioelectric sources in the body at high spatial resolution, which is especially important for diagnosing and guiding treatment of cardiac and neurologic disorders, including arrhythmia and epilepsy.