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

Acoustoelectric brain imaging with different conductivities and acoustic distributions

Objective: Acoustoelectric brain imaging (AEBI) is a promising imaging method for mapping brain biological current densities with high spatiotemporal resolution. Currently, it is still challenging to achieve human AEBI with an unclear acoustoelectric (AE) signal response of medium characteristics, particularly in conductivity and acoustic distribution. This study introduces different conductivities and acoustic distributions into the AEBI experiment, and clarifies the response interaction between medium characteristics and AEBI performance to address these key challenges. Approach: AEBI with different conductivities is explored by the imaging experiment, potential measurement, and simulation on a pig's fat, muscle, and brain tissue. AEBI with different acoustic distributions is evaluated on the imaging experiment and acoustic field measurement through a deep and surface transmitting model built on a human skullcap and pig brain tissue. Main results: The results show that conductivity is not only inversely proportional to the AE signal amplitude but also leads to a higher AEBI spatial resolution as it increases. In addition, the current source and sulcus can be located simultaneously with a strong AE signal intensity. The transcranial focal zone enlargement, pressure attenuation in the deep-transmitting model, and ultrasound echo enhancement in the surface-transmitting model cause a reduced spatial resolution, FFT-SNR, and timing correlation of AEBI. Under the comprehensive effect of conductivity and acoustics, AEBI with skull finally shows reduced imaging performance for both models compared with no-skull AEBI. On the contrary, the AE signal amplitude decreases in the deep-transmitting model and increases in the surface-transmitting model. Significance: This study reveals the response interaction between medium characteristics and AEBI performance, and makes an essential step toward developing AEBI as a practical neuroimaging technique.

The frontooccipital interaction mechanism of high-frequency acoustoelectric signal

Based on acoustoelectric effect, acoustoelectric brain imaging has been proposed, which is a high spatiotemporal resolution neural imaging method. At the focal spot, brain electrical activity is encoded by focused ultrasound, and corresponding high-frequency acoustoelectric signal is generated. Previous studies have revealed that acoustoelectric signal can also be detected in other non-focal brain regions. However, the processing mechanism of acoustoelectric signal between different brain regions remains sparse. Here, with acoustoelectric signal generated in the left primary visual cortex, we investigated the spatial distribution characteristics and temporal propagation characteristics of acoustoelectric signal in the transmission. We observed a strongest transmission strength within the frontal lobe, and the global temporal statistics indicated that the frontal lobe features in acoustoelectric signal transmission. Then, cross-frequency phase-amplitude coupling was used to investigate the coordinated activity in the AE signal band range between frontal and occipital lobes. The results showed that intra-structural cross-frequency coupling and cross-structural coupling co-occurred between these two lobes, and, accordingly, high-frequency brain activity in the frontal lobe was effectively coordinated by distant occipital lobe. This study revealed the frontooccipital long-range interaction mechanism of acoustoelectric signal, which is the foundation of improving the performance of acoustoelectric brain imaging.

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.

Expediting Image Acquisition in Reflection Ultrasound Computed Tomography

Reflection ultrasound computed tomography (RUCT) attains optimal image quality from objects that can be fully accessed from multiple directions, such as the human breast or small animals. Owing to the full-view tomography approach based on the compounding of images taken from multiple angles, RUCT effectively mitigates several deficiencies afflicting conventional pulse-echo ultrasound (US) systems, such as speckle patterns and interuser variability. On the other hand, the small interelement pitch required to fulfill the spatial sampling criterion in the circular transducer configuration used in RUCT typically implies the use of an excessive number of independent array elements. This increases the system's complexity and costs, and limits the achievable imaging speed. Here, we explore acquisition schemes that enable RUCT imaging with the reduced number of transmit/receive elements. We investigated the influence of the element size in transmission and reception in a ring array geometry. The performance of a sparse acquisition approach based on partial acquisition from a subset of the elements has been further assessed. A larger element size is shown to preserve contrast and resolution at the center of the field of view (FOV), while a reduced number of elements is shown to cause uniform loss of contrast and resolution across the entire FOV. The tradeoffs of achievable FOV, contrast-to-noise ratio, and temporal and spatial resolutions are assessed in phantoms and in vivo mouse experiments. The experimental analysis is expected to aid the development of optimized hardware and image acquisition strategies for RUCT and, thus, result in more affordable imaging systems facilitating wider adoption.

Spectral Analysis of Tissue Displacement for Cardiac Activation Mapping: Ex Vivo Working Heart and In Vivo Study

Characterizing myocardial activation is of major interest for understanding the underlying mechanism of cardiac arrhythmias. Electromechanical wave imaging (EWI) is an ultrafast ultrasound-based method used to map the propagation of the local contraction triggered by electrical activation of the heart. This study introduces a novel way to characterize cardiac activation based on the time evolution of the instantaneous frequency content of the cardiac tissue displacement curves. The first validation of this method was performed on an ex vivo dataset of 36 acquisitions acquired from two working heart models in paced rhythms. It was shown that the activation mapping described by spectral analysis of interframe displacement is similar to the standard EWI method based on zero-crossing of interframe strain. An average median error of 3.3 ms was found in the ex vivo dataset between the activation maps obtained with the two methods. The feasibility of mapping cardiac activation by EWI was then investigated on two open-chest pigs during sinus and paced rhythms in a pilot trial of cardiac mapping with an intracardiac probe. Seventy-five acquisitions were performed with reasonable stability and analyzed with the novel algorithm to map cardiac contraction propagation in the left ventricle (LV). Sixty-one qualitatively continuous isochrones were successfully computed based on this method. The region of contraction onset was coherently described while pacing in the imaging plane. These findings highlight the potential of implementing EWI acquisition on intracardiac probes and emphasize the benefit of performing short time-frequency analysis of displacement data to characterize cardiac activation in vivo.

Living Rat SSVEP Mapping with Acoustoelectric Brain Imaging

Acoustoelectric Brain Imaging (ABI) is a potential method for mapping brain electrical activity with high spatial resolution (millimeter). To resolve the key issue for eventual realization of ABI, testing the hypothesis that recorded acoustoelectric (AE) signal can be used to decode intrinsic brain electrical activity, the experiment of living rat SSVEP measurement with ABI is implemented.

METHOD

A 1-MHz ultrasound transducer is focused on the visual cortex of anesthetized rat. With visual stimulus, the electroencephalogram and AE signal are simultaneously recorded with Ag electrode. Besides, with FUS transducer scanning at the visual cortex, corresponding AE signals at different spatial positions are decoded and imaged.

RESULTS

Consistent with that of direct measurement of SSVEP, the decoded AE signal presents a clear event-related spectral perturbation (ERSP). And, the decoded AE signal is of high amplitude response at the base and harmonics of the visual stimulus frequency. Whats more, for timing signal, a significant positive amplitude correlation is observed between decoded AE signal and simultaneously measured SSVEP. In addition, the mean SNRs of SSVEP and decoded AE signal are both significantly higher than that of background EEG. Finally, with one fixed recording electrode, the active area with an inner diameter of 1mm is located within the 4mm4mm measurement region.

CONCLUSION

These experimental results demonstrate that the millimeter-level spatial resolution SSVEP measurement of living rat is achieved through ABI for the first time.

SIGNIFICANCE

This study confirms that ABI should shed light on spatiotemporal resolution neuroimaging.

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.

Mapping Biological Current Densities With Ultrafast Acoustoelectric Imaging: Application to the Beating Rat Heart

Ultrafast acoustoelectric imaging (UAI) is a novel method for the mapping of biological current densities, which may improve the diagnosis and monitoring of cardiac activation diseases such as arrhythmias. This paper evaluates the feasibility of performing UAI in beating rat hearts. A previously described system based on a 256-channel ultrasound research platform fitted with a 5-MHz linear array was used for simultaneous UAI, ultrafast B-mode, and electrocardiogram (ECG) recordings. In this paper, rat hearts (n = 4) were retroperfused within a Langendorff isolated heart system. A pair of Ag/Cl electrodes were positioned on the epicardium to simultaneously record ECG and UAI signals for imaging frame rates of up to 1000 Hz and a mechanical index of 1.3. To account for the potential effect of motion on the UAI maps, acquisitions for n = 3 hearts were performed with and without suppression of the mechanical contraction using 2,3-butanedione monoxime. Current densities were detected for all four rats in the region of the atrio-ventricular node, with an average contrast-to-noise ratios of 12. The UAI signals' frequency matched the sinus rhythm, even without mechanical contraction, suggesting that the signals measured correspond to physiological electrical activation. UAI signals appeared at the apex and within the ventricular walls with a delay estimated at 29 ms. Finally, the signals from different electrode positions along the myocardium wall showed the possibility of mapping the electrical activation throughout the heart. These results show the potential of UAI for cardiac activation mapping in vivo and in real time.

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.