Sex dependence of opioid-mediated responses to subanesthetic ketamine in rats.

Subanesthetic ketamine is increasingly used for the treatment of varied psychiatric conditions, both on- and off-label. While it is commonly classified as an N-methyl D-aspartate receptor (NMDAR) antagonist, our picture of ketamine's mechanistic underpinnings is incomplete. Recent clinical evidence has indicated, controversially, that a component of the efficacy of subanesthetic ketamine may be opioid dependent. Using pharmacological functional ultrasound imaging in rats, we found that blocking opioid receptors suppressed neurophysiologic changes evoked by ketamine, but not by a more selective NMDAR antagonist, in limbic regions implicated in the pathophysiology of depression and in reward processing. Importantly, this opioid-dependent response was strongly sex-dependent, as it was not evident in female subjects and was fully reversed by surgical removal of the male gonads. We observed similar sex-dependent effects of opioid blockade affecting ketamine-evoked postsynaptic density and behavioral sensitization, as well as in opioid blockade-induced changes in opioid receptor density. Together, these results underscore the potential for ketamine to induce its affective responses via opioid signaling, and indicate that this opioid dependence may be strongly influenced by subject sex. These factors should be more directly assessed in future clinical trials.

High-throughput ultrasound neuromodulation in awake and freely behaving rats.

Transcranial ultrasound neuromodulation is a promising potential therapeutic tool for the noninvasive treatment of neuropsychiatric disorders. However, the expansive parameter space and difficulties in controlling for peripheral auditory effects make it challenging to identify ultrasound sequences and brain targets that may provide therapeutic efficacy. Careful preclinical investigations in clinically relevant behavioral models are critically needed to identify suitable brain targets and acoustic parameters. However, there is a lack of ultrasound devices allowing for multi-target experimental investigations in awake and unrestrained rodents. We developed a miniaturized 64-element ultrasound array that enables neurointerventional investigations with within-trial active control targets in freely behaving rats. We first characterized the acoustic field with measurements in free water and with transcranial propagation. We then confirmed in vivo that the array can target multiple brain regions via electronic steering, and verified that wearing the device does not cause significant impairments to animal motility. Finally, we demonstrated the performance of our system in a high-throughput neuromodulation experiment, where we found that ultrasound stimulation of the rat central medial thalamus, but not an active control target, promotes arousal and increases locomotor activity.

Mu Opioid Receptor Activation Mediates (S)-ketamine Reinforcement in Rats: Implications for Abuse Liability.

BACKGROUND: (S)-ketamine is an NMDA receptor antagonist, but it also binds to and activates mu opioid receptors (MORs) and kappa opioid receptors in vitro. However, the extent to which these receptors contribute to (S)-ketamine's in vivo pharmacology is unknown. METHODS: We investigated the extent to which (S)-ketamine interacts with opioid receptors in rats by combining in vitro and in vivo pharmacological approaches, in vivo molecular and functional imaging, and behavioral procedures relevant to human abuse liability. RESULTS: We found that the preferential opioid receptor antagonist naltrexone decreased (S)-ketamine self-administration and (S)-ketamine-induced activation of the nucleus accumbens, a key brain reward region. A single reinforcing dose of (S)-ketamine occupied brain MORs in vivo, and repeated doses decreased MOR density and activity and decreased heroin reinforcement without producing changes in NMDA receptor or kappa opioid receptor density. CONCLUSIONS: These results suggest that (S)-ketamine's abuse liability in humans is mediated in part by brain MORs.

Deep-fUS: A Deep Learning Platform for Functional Ultrasound Imaging of the Brain Using Sparse Data.

Functional ultrasound (fUS) is a rapidly emerging modality that enables whole-brain imaging of neural activity in awake and mobile rodents. To achieve sufficient blood flow sensitivity in the brain microvasculature, fUS relies on long ultrasound data acquisitions at high frame rates, posing high demands on the sampling and processing hardware. Here we develop an image reconstruction method based on deep learning that significantly reduces the amount of data necessary while retaining imaging performance. We trained convolutional neural networks to learn the power Doppler reconstruction function from sparse sequences of ultrasound data with compression factors of up to 95%. High-quality images from in vivo acquisitions in rats were used for training and performance evaluation. We demonstrate that time series of power Doppler images can be reconstructed with sufficient accuracy to detect the small changes in cerebral blood volume (~10%) characteristic of task-evoked cortical activation, even though the network was not formally trained to reconstruct such image series. The proposed platform may facilitate the development of this neuroimaging modality in any setting where dedicated hardware is not available or in clinical scanners.

Focused Ultrasound for Noninvasive, Focal Pharmacologic Neurointervention.

A long-standing goal of translational neuroscience is the ability to noninvasively deliver therapeutic agents to specific brain regions with high spatiotemporal resolution. Focused ultrasound (FUS) is an emerging technology that can noninvasively deliver energy up the order of 1 kW/cm2 with millimeter and millisecond resolution to any point in the human brain with Food and Drug Administration-approved hardware. Although FUS is clinically utilized primarily for focal ablation in conditions such as essential tremor, recent breakthroughs have enabled the use of FUS for drug delivery at lower intensities (i.e., tens of watts per square centimeter) without ablation of the tissue. In this review, we present strategies for image-guided FUS-mediated pharmacologic neurointerventions. First, we discuss blood-brain barrier opening to deliver therapeutic agents of a variety of sizes to the central nervous system. We then describe the use of ultrasound-sensitive nanoparticles to noninvasively deliver small molecules to millimeter-sized structures including superficial cortical regions and deep gray matter regions within the brain without the need for blood-brain barrier opening. We also consider the safety and potential complications of these techniques, with attention to temporal acuity. Finally, we close with a discussion of different methods for mapping the ultrasound field within the brain and describe future avenues of research in ultrasound-targeted drug therapies.

Ultrasound/microbubble-mediated targeted delivery of anticancer microRNA-loaded nanoparticles to deep tissues in pigs.

In this study, we designed and validated a platform for ultrasound and microbubble-mediated delivery of FDA-approved pegylated poly lactic-co-glycolic acid (PLGA) nanoparticles loaded with anticancer microRNAs (miRNAs) to deep tissues in a pig model. Small RNAs have been shown to reprogram tumor cells and sensitize them to clinically used chemotherapy. To overcome their short intravascular circulation half-life and achieve controlled and sustained release into tumor cells, anticancer miRNAs need to be encapsulated into nanocarriers. Focused ultrasound combined with gas-filled microbubbles provides a noninvasive way to improve the permeability of tumor vasculature and increase the delivery efficiency of drug-loaded particles. A single handheld, curvilinear ultrasound array was used in this study for image-guided therapy with clinical-grade SonoVue contrast agent. First, we validated the platform on phantoms to optimize the microbubble cavitation dose based on acoustic parameters, including peak negative pressure, pulse length, and pulse repetition frequency. We then tested the system in vivo by delivering PLGA nanoparticles co-loaded with antisense-miRNA-21 and antisense-miRNA-10b to pig liver and kidney. Enhanced miRNA delivery was observed (1.9- to 3.7-fold increase) as a result of the ultrasound treatment compared to untreated control regions. Additionally, we used highly fluorescent semiconducting polymer nanoparticles to visually assess nanoparticle extravasation. Fluorescent microscopy suggested the presence of nanoparticles in the extravascular compartment. Hematoxylin and eosin staining of treated tissues did not reveal tissue damage. The results presented in this manuscript suggest that the proposed platform may be used to safely and noninvasively enhance the delivery of miRNA-loaded nanoparticles to target regions in deep organs in large animal models.

Portable Vector Flow Imaging Compared With Spectral Doppler Ultrasonography.

In this study, a vector flow imaging (VFI) method developed for a portable ultrasound scanner was used for estimating peak velocity values and variation in beam-to-flow angle over the cardiac cycle in vivo on healthy volunteers. Peak-systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index (RI) measured with VFI were compared to spectral Doppler ultrasonography (SDU). Seventeen healthy volunteers were scanned on the left and right common carotid arteries (CCAs). The standard deviation (SD) of VFI measurements averaged over the cardiac cycle was 7.3% for the magnitude and 3.84° for the angle. Bland-Altman plots showed a positive bias for the PSV measured with SDU (mean difference: 0.31 ms -1 ), and Pearson correlation analysis showed a highly significant correlation ( r = 0.6 ; ). A slightly positive bias was found for EDV and RI measured with SDU (mean difference: 0.08 ms -1 and -0.01 ms -1 , respectively). However, the correlation was low and not significant. The beam-to-flow angle was estimated over the systolic part of the cardiac cycle, and its variations were for all measurements larger than the precision of the angle estimation. The range spanned deviations from -25.2° (-6.0 SD) to 23.7° (4.2 SD) with an average deviation from -15.2° to 9.7°. This can significantly affect PSV values measured by SDU as the beam-to-flow angle is not constant and not aligned with the vessel surface. The study demonstrates that the proposed VFI method can be used in vivo for the measurement of PSV in the CCAs, and that angle variations across the cardiac cycle can lead to significant errors in SDU velocity estimates.

A Vector Flow Imaging Method for Portable Ultrasound Using Synthetic Aperture Sequential Beamforming.

This paper presents a vector flow imaging method for the integration of quantitative blood flow imaging in portable ultrasound systems. The method combines directional transverse oscillation (TO) and synthetic aperture sequential beamforming to yield continuous velocity estimation in the whole imaging region. Six focused emissions are used to create a high-resolution image (HRI), and a dual-stage beamforming approach is used to lower the data throughput between the probe and the processing unit. The transmit/receive focal points are laterally separated to obtain a TO in the HRI that allows for the velocity estimation along the lateral and axial directions using a phase-shift estimator. The performance of the method was investigated with constant flow measurements in a flow rig system using the SARUS scanner and a 4.1-MHz linear array. A sequence was designed with interleaved B-mode and flow emissions to obtain continuous data acquisition. A parametric study was carried out to evaluate the effect of critical parameters. The vessel was placed at depths from 20 to 40 mm, with beam-to-flow angles of 65°, 75°, and 90°. For the lateral velocities at 20 mm, a bias between -5% and -6.2% was obtained, and the standard deviation (SD) was between 6% and 9.6%. The axial bias was lower than 1% with an SD around 2%. The mean estimated angles were 66.70° ± 2.86°, 72.65° ± 2.48°, and 89.13° ± 0.79° for the three cases. A proof-of-concept demonstration of the real-time processing and wireless transmission was tested in a commercial tablet obtaining a frame rate of 27 frames/s and a data rate of 14 MB/s. An in vivo measurement of a common carotid artery of a healthy volunteer was finally performed to show the potential of the method in a realistic setting. The relative SD averaged over a cardiac cycle was 4.33%.

System-Level Design of an Integrated Receiver Front End for a Wireless Ultrasound Probe.

In this paper, a system-level design is presented for an integrated receive circuit for a wireless ultrasound probe, which includes analog front ends and beamformation modules. This paper focuses on the investigation of the effects of architectural design choices on the image quality. The point spread function is simulated in Field II from 10 to 160 mm using a convex array transducer. A noise analysis is performed, and the minimum signal-to-noise ratio (SNR) requirements are derived for the low-noise amplifiers (LNAs) and A/D converters (ADCs) to fulfill the design specifications of a dynamic range of 60 dB and a penetration depth of 160 mm in the B-mode image. Six front-end implementations are compared using Nyquist-rate and Σ∆ modulator ADCs. The image quality is evaluated as a function of the depth in terms of lateral full-width at half-maximum (FWHM) and -12-dB cystic resolution (CR). The designs that minimally satisfy the specifications are based on an 8-b 30-MSPS Nyquist converter and a single-bit third-order 240-MSPS Σ∆ modulator, with an SNR for the LNA in both cases equal to 64 dB. The mean lateral FWHM and CR are 2.4% and 7.1% lower for the Σ∆ architecture compared with the Nyquist-rate one. However, the results generally show minimal differences between equivalent architectures. Advantages and drawbacks are finally discussed for the two families of converters.

Compressive sensing of full wave field data for structural health monitoring applications.

Numerous nondestructive evaluations and structural health monitoring approaches based on guide waves rely on analysis of wave fields recorded through scanning laser Doppler vibrometers (SLDVs) or ultrasonic scanners. The informative content which can be extracted from these inspections is relevant; however, the acquisition process is generally time-consuming, posing a limit in the applicability of such approaches. To reduce the acquisition time, we use a random sampling scheme based on compressive sensing (CS) to minimize the number of points at which the field is measured. The CS reconstruction performance is mostly influenced by the choice of a proper decomposition basis to exploit the sparsity of the acquired signal. Here, different bases have been tested to recover the guided waves wave field acquired on both an aluminum and a composite plate. Experimental results show that the proposed approach allows a reduction of the measurement locations required for accurate signal recovery to less than 34% of the original sampling grid.

Model-based compressive sensing for damage localization in Lamb wave inspection.

Compressive sensing (CS) has emerged as a potentially viable technique for the efficient compression and analysis of high-resolution signals that have a sparse representation in a fixed basis. In this work, we have developed a CS approach for ultrasonic signal decomposition suitable to achieve high performance in Lamb-wave-based defect detection procedures. In the proposed approach, a CS algorithm based on an alternating minimization (AM) procedure is adopted to extract the information about both the system impulse response and the reflectivity function. The implemented tool exploits the dispersion compensation properties of the warped frequency transform as a means to generate the sparsifying basis for the signal representation. The effectiveness of the decomposition task is demonstrated on synthetic signals and successfully tested on experimental Lamb waves propagating in an aluminum plate. Compared with available strategies, the proposed approach provides an improvement in the accuracy of wave propagation path length estimation, a fundamental step in defect localization procedures.