Acoustic images of the carotid artery

__Abstract__ Arteries are strong and flexible structures that supply oxygenated blood to the organs. Their strength and flexibility rely on three distinctive layers, called the adventitia, media and intima. These layers of the arterial wall are rich in elastin, collagen and smooth muscle cells, which give the arteries complex elastic properties, allowing them to sustain and facilitate rapid and large variations in blood pressure

Monodisperse versus polydisperse ultrasound contrast agents: nonlinear response, sensitivity, and deep tissue imaging potential

Monodisperse microbubble ultrasound contrast agents have been proposed to further increase the signal-to-noise-ratio of contrast enhanced ultrasound imaging. Here, the sensitivity of a polydisperse preclinical agent was compared experimentally to that of its size- and acoustically-sorted derivatives by using narrowband pressure- and frequency-dependent scattering and attenuation measurements. The sorted monodisperse agents showed up to a two orders of magnitude increase in sensitivity, i.e. in the average scattering cross-section per bubble. Moreover, we demonstrate here, for the first time, that the highly nonlinear response of acoustically sorted microbubbles can be exploited to confine scattering and attenuation to the focal region of ultrasound fields used in clinical imaging. This property is a result of minimal prefocal scattering and attenuation and can be used to minimize shadowing effects in deep tissue imaging. Moreover, it potentially allows for more localized therapy using microbubbles through the spatial control of resonant microbubble oscillations

Swept-3-D Ultrasound Imaging of the Mouse Brain Using a Continuously Moving 1-D-Array-Part I:Doppler Imaging

Volumetric 3-D Doppler ultrasound imaging can be used to investigate large scale blood dynamics outside of the limited view that conventional 2-D power Doppler images (PDIs) provide. To create 3-D PDIs, 2-D-matrix array transducers can be used to insonify a large volume for every transmission; however, these matrices suffer from low sensitivity, high complexity, and high cost. More typically, a 1-D-Array transducer is used to scan a series of stationary 2-D PDIs, after which a 3-D volume is created by concatenating the 2-D PDIs in postprocessing, which results in long scan times due to repeated measurements. Our objective was to achieve volumetric 3-D Doppler ultrasound imaging with a high Doppler sensitivity, similar to that of a typical stationary recording using a 1-D-Array transducer, while being more affordable than using 2-D-matrix arrays. We achieved this by mounting a 1-D-Array transducer to a high-precision motorized linear stage and continuously translating over the mouse brain in a sweeping manner. For Part I of this article, we focused on creating the best vascular images by investigating how to best combine filtered beamformed ultrasound frames, which were not acquired at the same spatial locations, into PDIs. Part II focuses on the implications of sampling transient brain hemodynamics through functional ultrasound (fUS) while continuously translating over the mouse brain. In Part I, we show how the speed at which we sweep our 1-D-Array transducer affects the Doppler spectrum in a flow phantom. In vivo recordings were performed on the mouse brain while varying the sweeping speed, showing how higher sweeping speeds negatively affect the PDI quality. A weighting vector is found to combine frames while continuously moving over the mouse brain, allowing us to create swept PDIs of similar sensitivity when compared with those obtained using a stationary 1-D-Array while allowing a significantly higher 3-D Doppler volume rate and maintaining the benefits of having a low computational and monetary cost. We show that a vascular subvolume of 6 mm can be scanned in 2.5 s, with a PDI reconstructed every $200 \mu \text{m}$ , outperforming classical staged recording methods.</p

Deconvolution of the Functional Ultrasound Response in the Mouse Visual Pathway Using Block-Term Decomposition

Functional ultrasound (fUS) indirectly measures brain activity by recording changes in cerebral blood volume and flow in response to neural activation. Conventional approaches model such functional neuroimaging data as the convolution between an impulse response, known as the hemodynamic response function (HRF), and a binarized representation of the input (i.e., source) signal based on the stimulus onsets, the so-called experimental paradigm (EP). However, the EP may not be enough to characterize the whole complexity of the underlying source signals that evoke the hemodynamic changes, such as in the case of spontaneous resting state activity. Furthermore, the HRF varies across brain areas and stimuli. To achieve an adaptable framework that can capture such dynamics and unknowns of the brain function, we propose a deconvolution method for multivariate fUS time-series that reveals both the region-specific HRFs, and the source signals that induce the hemodynamic responses in the studied regions. We start by modeling the fUS time-series as convolutive mixtures and use a tensor-based approach for deconvolution based on two assumptions: (1) HRFs are parametrizable, and (2) source signals are uncorrelated. We test our approach on fUS data acquired during a visual experiment on a mouse subject, focusing on three regions within the mouse brain's colliculo-cortical, image-forming pathway: the lateral geniculate nucleus, superior colliculus and visual cortex. The estimated HRFs in each region are in agreement with prior works, whereas the estimated source signal is observed to closely follow the EP. Yet, we note a few deviations from the EP in the estimated source signal that most likely arise due to the trial-by-trial variability of the neural response across different repetitions of the stimulus observed in the selected regions

Spectroscopic photoacoustic imaging of radiofrequency ablation in the left atrium

Catheter-based radiofrequency ablation for atrial fibrillation has long-term success in 60-70% of cases. A better assessment of lesion quality, depth, and continuity could improve the procedure’s outcome. We investigate here photoacoustic contrast between ablated and healthy atrial-wall tissue in vitro in wavelengths spanning from 410 nm to 1000 nm. We studied single-and multi-wavelength imaging of ablation lesions and we demonstrate that a two-wavelength technique yields precise detection of lesions, achieving a diagnostic accuracy of 97%. We compare this with a best single-wavelength (640 nm) analysis that correctly identifies 82% of lesions. We discuss the origin of relevant spectroscopic features and perspectives for translation to clinical imaging

Laser-driven resonance of dye-doped oil-coated microbubbles: A theoretical and numerical study

Microbubbles are used to enhance the contrast in ultrasound imaging. When coated with an optically absorbing material, these bubbles can also provide contrast in photoacoustic imaging. This multimodal aspect is of pronounced interest to the field of medical imaging. The aim of this paper is to provide a theoretical framework to describe the physical phenomena underlying the photoacoustic response. This article presents a model for a spherical gas microbubble suspended in an aqueous environment and coated with an oil layer containing an optically absorbing dye. The model includes heat transfer between the gas core and the surrounding liquids. This framework is suitable for the investigation of both continuous wave and pulsed laser excitation. This work utilizes a combination of finite difference simulations and numerical integration to determine the dependancy on the physical properties, including composition and thickness of the oil layer on the microbubble response. A normalization scheme for a linearized version of the model was derived to facilitate comparison with experimental measurements. The results show that viscosity and thickness of the oil layer determine whether or not microbubble resonance can be excited. This work also examines the use of non-sinusoidal excitation to promote harmonic imaging techniques to further improve the imaging sensitivity

Compressive 3D ultrasound imaging using a single sensor

Three-dimensional ultrasound is a powerful imaging technique, but it requires thousands of sensors and complex hardware. Very recently, the discovery of compressive sensing has shown that the signal structure can be exploited to reduce the burden posed by traditional sensing requirements. In this spirit, we have designed a simple ultrasound imaging device that can perform three-dimensional imaging using just a single ultrasound sensor. Our device makes a compressed measurement of the spatial ultrasound field using a plastic aperture mask placed in front of the ultrasound sensor. The aperture mask ensures that every pixel in the image is uniquely identifiable in the compressed measurement. We demonstrate that this device can successfully image two structured objects placed in water. The need for just one sensor instead of thousands paves the way for cheaper, faster, simpler, and smaller sensing devices and possible new clinical applications