Dynamic Ultrasound Localization Microscopy Without ECG-Gating.

OBJECTIVE: Dynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration. METHODS: We developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time. RESULTS: Initially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated. CONCLUSION: Results suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.

Boosting Cardiac Color Doppler Frame Rates with Deep Learning.

Color Doppler echocardiography enables visualization of blood flow within the heart. However, the limited frame rate impedes the quantitative assessment of blood velocity throughout the cardiac cycle, thereby compromising a comprehensive analysis of ventricular filling. Concurrently, deep learning is demonstrating promising outcomes in post-processing of echocardiographic data for various applications. This work explores the use of deep learning models for intracardiac Doppler velocity estimation from a reduced number of filtered I/Q signals. We used a supervised learning approach by simulating patient-based cardiac color Doppler acquisitions and proposed data augmentation strategies to enlarge the training dataset. We implemented architectures based on convolutional neural networks. In particular, we focused on comparing the U-Net model and the recent ConvNeXt models, alongside assessing real-valued versus complex-valued representations. We found that both models outperformed the state-of-the-art autocorrelator method, effectively mitigating aliasing and noise. We did not observe significant differences between the use of real and complex data. Finally, we validated the models on in vitro and in vivo experiments. All models produced quantitatively comparable results to the baseline and were more robust to noise. ConvNeXt emerged as the sole model to achieve high-quality results on in vivo aliased samples. These results demonstrate the interest of supervised deep learning methods for Doppler velocity estimation from a reduced number of acquisitions.

Curved toroidal row column addressed transducer for 3D ultrafast ultrasound imaging.

3D Imaging of the human heart at high frame rate is of major interest for various clinical applications. Electronic complexity and cost has prevented the dissemination of 3D ultrafast imaging into the clinic. Row column addressed (RCA) transducers provide volumetric imaging at ultrafast frame rate by using a low electronic channel count, but current models are ill-suited for transthoracic cardiac imaging due to field-of-view limitations. In this study, we proposed a mechanically curved RCA with an aperture adapted for transthoracic cardiac imaging (24 × 16 mm²). The RCA has a toroidal curved surface of 96 elements along columns (curvature radius rC = 4.47 cm) and 64 elements along rows (curvature radius rR = 3 cm). We implemented delay and sum beamforming with an analytical calculation of the propagation of a toroidal wave which was validated using simulations (Field II). The imaging performance was evaluated on a calibrated phantom. Experimental 3D imaging was achieved up to 12 cm deep with a total angular aperture of 30° for both lateral dimensions. The Contrast-to-Noise ratio increased by 12 dB from 2 to 128 virtual sources. Then, 3D Ultrasound Localization Microscopy (ULM) was characterized in a sub-wavelength tube diameter. Finally, 3D ULM was demonstrated on a perfused ex-vivo swine heart to image the coronary microcirculation.

Quantitative pulsatility measurements using 3D dynamic ultrasound localization microscopy.

A rise in blood flow velocity variations (i.e. pulsatility) in the brain, caused by the stiffening of upstream arteries, is associated with cognitive impairment and neurodegenerative diseases. The study of this phenomenon requires brain-wide pulsatility measurements, with large penetration depth and high spatiotemporal resolution. The development of dynamic ultrasound localization microscopy (DULM), based on ULM, has enabled pulsatility measurements in the rodent brain in 2D. However, 2D imaging accesses only one slice of the brain and measures only 2D-projected and hence biased velocities . Herein, we present 3D DULM: using a single ultrasound scanner at high frame rate (1000-2000 Hz), this method can produce dynamic maps of microbubbles flowing in the bloodstream and extract quantitative pulsatility measurements in the cat brain with craniotomy and in the mouse brain through the skull, showing a wide range of flow hemodynamics in both large and small vessels. We highlighted a decrease in pulsatility along the vascular tree in the cat brain, which could be mapped with ultrasound down to a few tens of micrometers for the first time. We also performed an intra-animal validation of the method by showing consistent measurements between the two sides of the Willis circle in the mouse brain. Our study provides the first step towards a new biomarker that would allow the detection of dynamic abnormalities in microvessels in the brain, which could be linked to early signs of neurodegenerative diseases.

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network.

Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers ( [Formula: see text]). Transcranial ULM remains challenging in presence of aberrations caused by the skull, which lead to localization errors. Herein, we propose a deep learning approach based on recently introduced complex-valued convolutional neural networks (CV-CNNs) to retrieve the aberration function, which can then be used to form enhanced images using standard delay-and-sum beamforming. CV-CNNs were selected as they can apply time delays through multiplication with in-phase quadrature input data. Predicting the aberration function rather than corrected images also confers enhanced explainability to the network. In addition, 3D spatiotemporal convolutions were used for the network to leverage entire microbubble tracks. For training and validation, we used an anatomically and hemodynamically realistic mouse brain microvascular network model to simulate the flow of microbubbles in presence of aberration. The proposed CV-CNN performance was compared to the coherence-based method by using microbubble tracks. We then confirmed the capability of the proposed network to generalize to transcranial in vivo data in the mouse brain (n=3). Vascular reconstructions using a locally predicted aberration function included additional and sharper vessels. The CV-CNN was more robust than the coherence-based method and could perform aberration correction in a 6-month-old mouse. After correction, we measured a resolution of [Formula: see text] for younger mice, representing an improvement of 25.8%, while the resolution was improved by 13.9% for the 6-month-old mouse. This work leads to different applications for complex-valued convolutions in biomedical imaging and strategies to perform transcranial ULM.

Equivalent-time-active-cavitation-imaging enables vascular-resolution blood-brain-barrier-opening-therapy planning.

Objective. Linking cavitation and anatomy was found to be important for predictable outcomes in focused-ultrasound blood-brain-barrier-opening and requires high resolution cavitation mapping. However, cavitation mapping techniques for planning and monitoring of therapeutic procedures either (1) do not leverage the full resolution capabilities of ultrasound imaging or (2) place constraints on the length of the therapeutic pulse. This study aimed to develop a high-resolution technique that could resolve vascular anatomy in the cavitation map.Approach. Herein, we develop BandPass-sampled-equivalent-time-active-cavitation-imaging (BP-ETACI), derived from bandpass sampling and dual-frequency contrast imaging at 12.5 MHz to produce cavitation maps prior and during blood-brain barrier opening with long therapeutic bursts using a 1.5 MHz focused transducer in the brain of C57BL/6 mice.Main results. The BP-ETACI cavitation maps were found to correlate with the vascular anatomy in ultrasound localization microscopy vascular maps and in histological sections. Cavitation maps produced from non-blood-brain-barrier disrupting doses showed the same cavitation-bearing vasculature as maps produced over entire blood-brain-barrier opening procedures, allowing use for (1) monitoring focused-ultrasound blood-brain-barrier-opening (FUS-BBBO), but also for (2) therapy planning and target verification.Significance. BP-ETACI is versatile, created high resolution cavitation maps in the mouse brain and is easily translatable to existing FUS-BBBO experiments. As such, it provides a means to further study cavitation phenomena in FUS-BBBO.

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-velocity tissue motion if motion compensation (MoCo) is not considered. While many studies have recently shown the interest of deep learning for the reconstruction of high-quality static images from PW or DW, its ability to achieve such performance while maintaining the capability of tracking cardiac motion has yet to be assessed. In this article, we addressed such issue by deploying a complex-weighted convolutional neural network (CNN) for image reconstruction and a state-of-the-art speckle-tracking method. The evaluation of this approach was first performed by designing an adapted simulation framework, which provides specific reference data, i.e., high-quality, motion artifact-free cardiac images. The obtained results showed that, while using only three DWs as input, the CNN-based approach yielded an image quality and a motion accuracy equivalent to those obtained by compounding 31 DWs free of motion artifacts. The performance was then further evaluated on nonsimulated, experimental in vitro data, using a spinning disk phantom. This experiment demonstrated that our approach yielded high-quality image reconstruction and motion estimation, under a large range of velocities and outperforms a state-of-the-art MoCo-based approach at high velocities. Our method was finally assessed on in vivo datasets and showed consistent improvement in image quality and motion estimation compared to standard compounding. This demonstrates the feasibility and effectiveness of deep learning reconstruction for ultrafast speckle-tracking echocardiography.

Ultrafast Myocardial Principal Strain Ultrasound Elastography During Stress Tests: In Vitro Validation and In Vivo Feasibility.

Objective myocardial contractility assessment during stress tests aims to improve the diagnosis of myocardial ischemia. Tissue Doppler imaging (TDI) or optical flow (OF) speckle tracking echocardiography (STE) has been used to quantify myocardial contractility at rest. However, this is more challenging during stress tests due to image decorrelation at high heart rates. Moreover, stress tests imply a high frame rate which leads to a limited lateral field of view. Therefore, a large lateral field-of-view robust ultrafast myocardial regularized OF-TDI principal strain estimator has been developed for high-frame-rate echocardiography of coherently compounded transmitted diverging waves. The feasibility and accuracy of the proposed estimator were validated in vitro (using sonomicrometry as the gold standard) and in vivo stress experiments. Compared with OF strain imaging, the proposed estimator improved the accuracy of principal major and minor strains during stress tests, with an average contrast-to-noise ratio improvement of 4.4 ± 2.7 dB ( p -value < 0.01). Moreover, there was a significant correlation and a very close agreement between the proposed estimator and sonomicrometry for tested heart rates between 60 and 180 beats per minute (bpm). The averages ± standard deviations (STD) of R2 and biases ± STD between them were 0.96 ± 0.04 ( p -value < 0.01) and 0.01 ± 0.03% in the axial direction, respectively; and 0.94 ± 0.02 ( p -value < 0.01) and 0.04 ± 0.06% in the lateral direction, respectively. These results suggest that the proposed estimator could be useful clinically to provide an accurate and quantitative 2-D large lateral field-of-view myocardial strain assessment at high heart rates during stress echocardiography.

In Vivo Pulsatility Measurement of Cerebral Microcirculation in Rodents Using Dynamic Ultrasound Localization Microscopy.

An increased pulse pressure, due to arteries stiffening with age and cardiovascular disease, may lead to downstream brain damage in microvessels and cognitive decline. Brain-wide imaging of the pulsatility propagation from main feeding arteries to capillaries in small animals could improve our understanding of the link between pulsatility and cognitive decline. However, it requires higher spatiotemporal resolution and penetration depth than currently available with existing brain imaging techniques. Herein, we show the feasibility of performing Dynamic Ultrasound Localization Microscopy (DULM), a novel imaging approach to capture hemodynamics with a subwavelength resolution. By producing cine-loops of flowing microbubbles in 2D in the whole rodent brain lasting several cardiac cycles, DULM performed pulsatility measurements in microvessels in-depth, in vivo, with and without craniotomy. Cortical veins and arteries were shown to have a significatively different pulsatility index and the method was compared against Contrast Enhanced Ultrafast Ultrasound Doppler (CEUFD) pulsatility measurements.

Equivalent time active cavitation imaging.

Rationale. Despite the development of a large number of neurologically active drugs, brain diseases are difficult to treat due to the inability of many drugs to penetrate the blood-brain barrier. High-intensity focused ultrasound (HIFU) blood-brain barrier opening in a site-specific manner could significantly expand the spectrum of available drug treatments. However, without monitoring, brain damage and off-target effects can occur during these treatments. While some methods can monitor inertial cavitation, temperature increase, or passively monitor cavitation events, to the best of our knowledge none of them can actively and spatiotemporally map the HIFU pressure field during treatment.Methods. Here we detail the development of a novel ultrasound imaging modality called equivalent time active cavitation imaging (ETACI) capable of characterizing the HIFU pressure field through stable cavitation events across the field of view with an ultrafast active imaging setup. This work introduces (1) a novel plane wave sequence whose transmit delays increase linearly with transmit events enabling the sampling of high-frequency cavitation events, and (2) an algorithm allowing the processing of the microbubble signal for pressure field mapping. The pressure measurements with our modality were first carried outin vitrofor hydrophone comparison and thenin vivoduring blood-brain barrier opening treatment in mice.Results. This study demonstrates the capability of ETACI to spatiotemporally characterize a modulation pressure field with an active imaging setup. The resulting pressure field mapping reveals a good correlation with hydrophone measurements. Further results iareprovided experimentallyin vivowith promising results.Conclusion. This proof of concept establishes the first steps towards a novel ultrasound modality for monitoring focused ultrasound blood-brain barrier opening, allowing new possibilities for a safe and precise monitoring method.

Dynamic Myocardial Ultrasound Localization Angiography.

Dynamic Myocardial Ultrasound Localization Angiography (MULA) is an ultrasound-based imaging modality destined to enhance the diagnosis and treatment monitoring of coronary pathologies. Current diagnosis methods of coronary artery disease focus on the observation of vessel narrowing in the coronary vasculature to assess the organ's condition. However, we would strongly benefit from mapping and measuring flow from intramyocardial arterioles and capillaries as they are the direct vehicle of the myocardium blood income. With the advent of ultrafast ultrasound scanners, imaging modalities based on the localization and tracking of injected microbubbles allow for the subwavelength resolution imaging of an organ's vasculature. Yet, the application of these vascular imaging modalities relies on an accumulation of cine loops of a region of interest undergoing no or minimal tissue motion. This work introduces the MULA framework that combines 1) the mapping of the dynamics of the microvascular flow using an ultrasound sequence triggered by the electrocardiogram with a 2) novel Lagrangian beamformer based on non-rigid motion registration algorithm to form images directly in the myocardium's material coordinates and thus correcting for the large myocardial motion and deformation. Specifically, we show that this framework enables the non-invasive imaging of the angioarchitecture and dynamics of intramyocardial flow in vessels as small as a few tens of microns in the rat's beating heart in vivo.

Sparse channel sampling for ultrasound localization microscopy (SPARSE-ULM).

Ultrasound localization microscopy (ULM) has recently enabled the mapping of the cerebral vasculaturein vivowith a resolution ten times smaller than the wavelength used, down to ten microns. However, with frame rates up to 20000 frames per second, this method requires large amount of data to be acquired, transmitted, stored, and processed. The transfer rate is, as of today, one of the main limiting factors of this technology. Herein, we introduce a novel reconstruction framework to decrease this quantity of data to be acquired and the complexity of the required hardware by randomly subsampling the channels of a linear probe. Method performance evaluation as well as parameters optimization were conductedin silicousing the SIMUS simulation software in an anatomically realistic phantom and then compared toin vivoacquisitions in a rat brain after craniotomy. Results show that reducing the number of active elements deteriorates the signal-to-noise ratio and could lead to false microbubbles detections but has limited effect on localization accuracy. In simulation, the false positive rate on microbubble detection deteriorates from 3.7% for 128 channels in receive and 7 steered angles to 11% for 16 channels and 7 angles. The average localization accuracy ranges from 10.6µm and 9.93µm for 16 channels/3 angles and 128 channels/13 angles respectively. These results suggest that a compromise can be found between the number of channels and the quality of the reconstructed vascular network and demonstrate feasibility of performing ULM with a reduced number of channels in receive, paving the way for low-cost devices enabling high-resolution vascular mapping.

A Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy.

Ultrasound Localization Microscopy (ULM) can resolve the microvascular bed down to a few micrometers. To achieve such performance, microbubble contrast agents must perfuse the entire microvascular network. Microbubbles are then located individually and tracked over time to sample individual vessels, typically over hundreds of thousands of images. To overcome the fundamental limit of diffraction and achieve a dense reconstruction of the network, low microbubble concentrations must be used, which leads to acquisitions lasting several minutes. Conventional processing pipelines are currently unable to deal with interference from multiple nearby microbubbles, further reducing achievable concentrations. This work overcomes this problem by proposing a Deep Learning approach to recover dense vascular networks from ultrasound acquisitions with high microbubble concentrations. A realistic mouse brain microvascular network, segmented from 2-photon microscopy, was used to train a three-dimensional convolutional neural network (CNN) based on a V-net architecture. Ultrasound data sets from multiple microbubbles flowing through the microvascular network were simulated and used as ground truth to train the 3D CNN to track microbubbles. The 3D-CNN approach was validated in silico using a subset of the data and in vivo in a rat brain. In silico, the CNN reconstructed vascular networks with higher precision (81%) than a conventional ULM framework (70%). In vivo, the CNN could resolve micro vessels as small as 10 µ m with an improvement in resolution when compared against a conventional approach.

Dealiasing High-Frame-Rate Color Doppler Using Dual-Wavelength Processing.

Doppler ultrasound is the premier modality to analyze blood flow dynamics in clinical practice. With conventional systems, Doppler can either provide a time-resolved quantification of the flow dynamics in sample volumes (spectral Doppler) or an average Doppler velocity/power [color flow imaging (CFI)] in a wide field of view (FOV) but with a limited frame rate. The recent development of ultrafast parallel systems made it possible to evaluate simultaneously color, power, and spectral Doppler in a wide FOV and at high-frame rates but at the expense of signal-to-noise ratio (SNR). However, like conventional Doppler, ultrafast Doppler is subject to aliasing for large velocities and/or large depths. In a recent study, staggered multi-pulse repetition frequency (PRF) sequences were investigated to dealias color-Doppler images. In this work, we exploit the broadband nature of pulse-echo ultrasound and propose a dual-wavelength approach for CFI dealiasing with a constant PRF. We tested the dual-wavelength bandpass processing, in silico, in laminar flow phantom and validated it in vivo in human carotid arteries ( n = 25 ). The in silico results showed that the Nyquist velocity could be extended up to four times the theoretical limit. In vivo, dealiased CFI were highly consistent with unfolded Spectral Doppler ( r2=0.83 , y=1.1x+0.1 , N=25 ) and provided consistent vector flow images. Our results demonstrate that dual-wavelength processing is an efficient method for high-velocity CFI.

Wall Shear Stress Measurement by Ultrafast Vector Flow Imaging for Atherosclerotic Carotid Stenosis.

OBJECTIVE: Carotid plaque vulnerability assessment could guide the decision to perform endarterectomy. Ultrafast ultrasound imaging (UF) can evaluate local flow velocities over an entire 2D image, allowing measurement of the wall shear stress (WSS). We aimed at evaluating the feasibility of WSS measurement in a prospective series of patients with carotid stenosis. METHODS: UF acquisitions, performed with a linear probe, had an effective frame rate of 5000 Hz. The flow velocity was imaged over the entire plaque area. WSS was computed with the vector field speed using the formula: with the blood velocity and µ, the blood viscosity. The WSS measurement method was validated using a calibrated phantom. In vivo, WSS was analyzed in 5 areas of the carotid wall: common carotid artery, plaque ascent, plaque peak, plaque descent, internal carotid artery. RESULTS: Good correlation was found between in vitro measurement and the theoretical WSS values (R2 = 0.95; p < 0.001). 33 patients were prospectively evaluated, with a median carotid stenosis degree of 80 % [75-85]. The maximum WSS value over the cardiac cycle follows the shape of the plaque with an increase during the ascent, reaching its maximum value of 3.25 Pa [2.26-4.38] at the peak of the plaque, and a decrease after passing of the peak (0.93 Pa [0.80-1.19]) lower than the WSS values in the non-stenotic areas (1.47 Pa [1.12-1.77] for the common carotid artery). CONCLUSION: UF allowed local and direct evaluation of the plaque's WSS, thus better characterizing local hemodynamics to identify areas of vulnerability. KEY POINTS: · Ultrafast vector Doppler allows calculation of the wall shear stress (WSS) by measuring velocity vectors over the entire 2D image.. · The setup to measure the WSS has been validated in vitro on a linear flow phantom by comparing measurements to in silico calculations.. · Applying this method to carotid plaque allows us to better describe the hemodynamic constraints that apply along the entire length of the plaque..

Parameterized Strain Estimation for Vascular Ultrasound Elastography With Sparse Representation.

Ultrasound vascular strain imaging has shown its potential to interrogate the motion of the vessel wall induced by the cardiac pulsation for predicting plaque instability. In this study, a sparse model strain estimator (SMSE) is proposed to reconstruct a dense strain field at a high resolution, with no spatial derivatives, and a high computation efficiency. This sparse model utilizes the highly-compacted property of discrete cosine transform (DCT) coefficients, thereby allowing to parameterize displacement and strain fields with truncated DCT coefficients. The derivation of affine strain components (axial and lateral strains and shears) was reformulated into solving truncated DCT coefficients and then reconstructed with them. Moreover, an analytical solution was derived to reduce estimation time. With simulations, the SMSE reduced estimation errors by up to 50% compared with the state-of-the-art window-based Lagrangian speckle model estimator (LSME). The SMSE was also proven to be more robust than the LSME against global and local noise. For in vitro and in vivo tests, residual strains assessing cumulated errors with the SMSE were 2 to 3 times lower than with the LSME. Regarding computation efficiency, the processing time of the SMSE was reduced by 4 to 25 times compared with the LSME, according to simulations, in vitro and in vivo results. Finally, phantom studies demonstrated the enhanced spatial resolution of the proposed SMSE algorithm against LSME.

Ultrafast Ultrasound Imaging for Super-Resolution Preclinical Cardiac PET.

PURPOSE: Physiological motion and partial volume effect (PVE) significantly degrade the quality of cardiac positron emission tomography (PET) images in the fast-beating hearts of rodents. Several Super-resolution (SR) techniques using a priori anatomical information have been proposed to correct motion and PVE in PET images. Ultrasound is ideally suited to capture real-time high-resolution cine images of rodent hearts. Here, we evaluated an ultrasound-based SR method using simultaneously acquired and co-registered PET-CT-Ultrafast Ultrasound Imaging (UUI) of the beating heart in closed-chest rodents. PROCEDURES: The method was tested with numerical and animal data (n = 2) acquired with the non-invasive hybrid imaging system PETRUS that acquires simultaneously PET, CT, and UUI. RESULTS: We showed that ultrasound-based SR drastically enhances the quality of PET images of the beating rodent heart. For the simulations, the deviations between expected and mean reconstructed values were 2 % after applying SR. For the experimental data, when using Ultrasound-based SR correction, contrast was improved by a factor of two, signal-to-noise ratio by 11 %, and spatial resolution by 56 % (~ 0.88 mm) with respect to static PET. As a consequence, the metabolic defect following an acute cardiac ischemia was delineated with much higher anatomical precision. CONCLUSIONS: Our results provided a proof-of-concept that image quality of cardiac PET in fast-beating rodent hearts can be significantly improved by ultrasound-based SR, a portable low-cost technique. Improved PET imaging of the rodent heart may allow new explorations of physiological and pathological situations related with cardiac metabolism.

Innovative Multiparametric Characterization of Carotid Plaque Vulnerability by Ultrasound.

OBJECTIVE: The degree of stenosis of a carotid plaque is a well-established risk factor for ischemic stroke. Nevertheless, the risk of ipsilateral stroke in asymptomatic carotid stenosis remains low and new imaging markers are needed to better target which patients would benefit most from endarterectomy or intensive medical therapy. Ultrafast ultrasound imaging offers parameters helping at characterizing the carotid plaque by shear wave elastography and Ultrafast Doppler (UFD). We aimed at using these techniques to characterize 3 different ultrasound biomarkers: plaque stiffness heterogeneity, wall shear stress (WSS) and intraplaque micro-flows and to correlate these biomarkers with findings on computed tomography angiography (CTA) and the pathological examination. METHODS: We present the case of a multimodal evaluation of a carotid plaque using ultrasound. Elastography has been coupled to the WSS assessment and the detection of intraplaque micro-flows by UFD. The data have been compared to CTA and to the pathology examination of the tissue after carotid endarterectomy. RESULTS: Elastography allowed at identifying stiff areas corresponding to calcifications, as well as a soft area corresponding to an intraplaque hemorrhage. The flow evaluation with UFD showed an increase of the WSS along the plaque and identified the presence of a plaque rupture, confirmed by the pathologist. CONCLUSION: Ultrafast ultrasound imaging is an innovative, easily accessible technique that provides imaging modalities on top of the conventional B-mode. Ultrafast ultrasound biomarkers such as plaque stiffness heterogeneity, WSS and intraplaque micro-flows could help to define the vulnerability of the carotid plaque in order to stratify patients that could benefit most from endarterectomy or intensive medical therapy.

4D Functional Imaging of the Rat Brain Using a Large Aperture Row-Column Array.

Functional ultrasound imaging (fUS) recently emerged as a promising neuroimaging modality to image and monitor brain activity based on cerebral blood volume response (CBV) and neurovascular coupling. fUS offers very good spatial and temporal resolutions compared to fMRI gold standard as well as simplicity and portability. It was recently extended to 4D fUS imaging in preclinical settings although this approach remains limited and complex. Indeed 4D fUS requires a 2D matrix probe and specific hardware able to drive the N2 elements of the probe with thousands of electronic channels. Several under-sampling approaches are currently investigated to limit the channel count and spread ultrasound 4D modalities. Among them, the Row Column Addressing (RCA) approach combined with ultrafast imaging is a compelling alternative using only N + N channels. We present a large field of view RCA probe prototype of 128 + 128 channels and 15 MHz central frequency adapted for preclinical imaging. Based on the Orthogonal Plane Wave compounding scheme, we were able to perform 4D vascular brain acquisitions at high volume rate. Doppler volumes of the whole rat brain were obtained in vivo at high rates (23 dB CNR at 156 Hz and 19 dB CNR at 313 Hz). Visual and whiskers stimulations were performed and the corresponding CBV increases were reconstructed in 3D with successful functional activation detected in the superior colliculus and somato-sensorial cortex respectively. This proof of concept study demonstrates for the first time the use of a low-channel count RCA array for in vivo 4D fUS imaging in the whole rat brain.

Carotid Stiffness Assessment With Ultrafast Ultrasound Imaging in Case of Bicuspid Aortic Valve.

AIMS: To compare the carotid stiffness and flow parameters by ultrafast ultrasound imaging (UF), in bicuspid aortic valve (BAV) patients to first-degree relatives (controls). METHODS: BAV patients (n = 92) and controls (n = 48) were consecutively included at a reference center for BAV. Aortic valve and ascending aorta were evaluated by echocardiography. Common carotid arteries were evaluated by UF with a linear probe. A high frame rate (2,000 frames/s) was used to measure the pulse wave velocity (PWV). The arterial diameter change over the cardiac cycle was obtained by UF-Doppler imaging. This allowed us to measure the distensibility and the maximal rate of systolic distension (MRSD). The wall shear stress (WSS) was measured based on the same acquisitions, by analyzing blood flow velocities close to the carotid walls. RESULTS: BAV patients had significantly larger aortic diameters (p < 0.001) at the Valsalva sinus and at the tubular ascending aorta but no larger carotid diameters. No significant differences were found in carotid stiffness parameters (distensibility, MRSD, and PWV), even though these patients had a higher aortic stiffness. Carotid stiffness correlated linearly with age and similar slopes were obtained for BAV patients and controls. No difference in carotid WSS was found between BAV patients and controls. CONCLUSION: Our results clearly show that the carotid stiffness and flow parameters are not altered in case of BAV compared with controls.