Acoustic biomolecules enhance hemodynamic functional ultrasound imaging of neural activity

Maresca, David; Payen, Thomas; Lee‐Gosselin, Audrey; Ling, Bill; Malounda, Dina; Demené, Charlie; Tanter, Mickaël; Shapiro, Mikhail G.

doi:10.1101/734939

Cited by 7 publications

(12 citation statements)

References 34 publications

(41 reference statements)

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“…Indeed, the 3 rd decile regions of cerebral vasculature mostly consists of sub-resolution cortical vessel endings. This result is consistent with the hypothesis that functional hyperemia arises from sub-resolution vessels of the primary unit 20,51 . This finding agrees with previous studies in rodents 52 and ferrets 24 .…”

Section: Figure 4: a Decoding Accuracy As A Function Of Spatial Resolution Accuracy Decreases With Resolution In Both The X-direction (Acsupporting

confidence: 92%

Single-trial decoding of movement intentions using functional ultrasound neuroimaging

Norman

Maresca

Christopoulos

et al. 2021

Neuron

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Brain-machine interfaces (BMI) are powerful devices for restoring function to people living with paralysis. Leveraging significant advances in neurorecording technology, computational power, and understanding of the underlying neural signals, BMI have enabled severely paralyzed patients to control external devices, such as computers and robotic limbs. However, high-performance BMI currently require highly invasive recording techniques, and are thus only available to niche populations. Here, we show that a minimally invasive neuroimaging approach based on functional ultrasound (fUS) imaging can be used to detect and decode movement intention signals usable for BMI. We trained non-human primates to perform memory-guided movements while using epidural fUS imaging to record changes in cerebral blood volume from the posterior parietal cortex -a brain area important for spatial perception, multisensory integration, and movement planning. Using hemodynamic signals acquired during movement planning, we classified left-cued vs. right-cued movements, establishing the feasibility of ultrasonic BMI. These results demonstrate the ability of fUS-based neural interfaces to take advantage of the excellent spatiotemporal resolution, sensitivity, and field of view of ultrasound without breaching the dura or physically penetrating brain tissue.

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Section: Figure 4: a Decoding Accuracy As A Function Of Spatial Resolution Accuracy Decreases With Resolution In Both The X-direction (Acsupporting

confidence: 92%

Single-trial decoding of movement intentions using functional ultrasound neuroimaging

Norman

Maresca

Christopoulos

et al. 2021

Neuron

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“…In pulse-echo imaging, the ultrasound would have to cross the skull twice, and the focus will be deflected due to the non-uniform bone thickness and density. These limitations could be partly overcome by using contrast agents to enhance the ultrasound signal [48][49][50] .…”

Section: Discussionmentioning

confidence: 99%

Deep-fUS: Functional ultrasound imaging of the brain using deep learning and sparse data

Ianni

Airan

2020

Preprint

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Functional ultrasound imaging is rapidly establishing itself as a state-of-the-art neuroimaging modality owing to its ability to image neural activation in awake and mobile small animals, its relatively low cost, and its unequaled portability. To achieve high blood flow sensitivity in the brain microvasculature, functional ultrasound relies on long sequences of ultrasound data acquired at high frame rates, which pose high demands on the hardware architecture and effectively limit the practical utility and clinical translation of this imaging modality. Here we propose Deep-fUS, a deep learning approach that aims to significantly reduce the amount of ultrasound data necessary, while retaining the imaging performance. We trained a neural network to learn the power Doppler reconstruction function from sparse sequences of compound ultrasound data, using ground truth images from high-quality in vivo acquisitions in rats, and with a custom loss function. The network produces highly accurate images with restored sensitivity in the smaller blood vessels even when using heavily under-sampled data. We tested the network performance in a task-evoked functional neuroimaging application, demonstrating that time series of power Doppler images can be reconstructed with adequate accuracy to compute functional activity maps. Notably, the network reduces the occurrence of motion artifacts in awake functional ultrasound imaging experiments. The proposed platform can facilitate the development of this neuroimaging modality in any setting where dedicated hardware is not available or even in clinical scanners, opening the way to new potential applications based on this technology. To our knowledge, this is the first attempt to implement a convolutional neural network approach for power Doppler reconstruction from sparse ultrasonic datasets.

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“…We first visualized intravascular GVs with ultrafast power Doppler imaging, leveraging the ability of intravenously (IV) injected GVs to enhance blood flow contrast. 25 We chose the brain as our target organ due to its practical advantages in mouse experiments: hemodynamic signals can be conveniently measured through intact skin and skull 25,37 and head-fixation reduces motion artifacts. We acquired images of a single coronal plane at a center frequency of 15 MHz and frame rate of 0.25 Hz (Fig.…”

Section: Gas Vesicle Blood Clearance Liver Uptake and Degradation Can Be Monitored By Ultrasoundmentioning

confidence: 99%

“…Once the internal temperature of the mouse stabilized at 37°C, power Doppler images were acquired every 4 s for up to 60 min using a previously described functional ultrasound script with slight modifications. 25 Briefly, the pulse sequence consisted of 11 tilted plane waves (varying from -10 to 10 degrees), each containing 8-half-cycle emissions at a voltage of 15V (900 kPa peak positive pressure measured in free water tank). An ensemble of 250 coherently compounded frames, collected at a framerate of 500 Hz, was then processed through a singular value decomposition filter to isolate blood signals from tissue motion and generate a single power Doppler image.…”

Section: Ultrasound Imagingmentioning

confidence: 99%

“…23 Because sound waves are strongly reflected by air-water interfaces, GVs have been developed as contrast agents for ultrasound imaging. 19,[24][25][26][27] Due to their innate stability, GVs are able to withstand repeated insonation without loss of contrast. 19 However, when the GV shell is compromised by mechanical or chemical disruption, the gaseous contents it encloses rapidly and irreversibly dissolve into the surrounding media, leading to the elimination of ultrasound contrast.…”

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confidence: 99%

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Biomolecular Ultrasound Imaging of Phagolysosomal Function

et al. 2020

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Phagocytic clearance and lysosomal processing of pathogens and debris are essential functions of the innate immune system. However, the assessment of these functions in vivo is challenging because most nanoscale contrast agents compatible with non-invasive imaging techniques are made from non-biodegradable synthetic materials that do not undergo regular lysosomal degradation. To overcome this challenge, we describe the use of an all-protein contrast agent to directly visualize and quantify phagocytic and lysosomal activities in vivo by ultrasound imaging.This contrast agent is based on gas vesicles (GVs), a class of air-filled protein nanostructures naturally expressed by buoyant microbes. Using a combination of ultrasound imaging, pharmacology, immunohistology and live-cell optical microscopy, we show that after intravenous injection, GVs are cleared from circulation by liver-resident macrophages. Once internalized, the GVs undergo lysosomal degradation, resulting in the elimination of their ultrasound contrast. By non-invasively monitoring the temporal dynamics of GV-generated ultrasound signal in circulation and in the liver and fitting them with a pharmacokinetic model, we can quantify the rates of phagocytosis and lysosomal degradation in living animals. We demonstrate the utility of this method by showing how these rates are perturbed in two models of liver dysfunction: phagocyte deficiency and non-alcoholic fatty liver disease. The combination of proteolytically-degradable nanoscale contrast agents and quantitative ultrasound imaging thus enables non-invasive functional imaging of cellular degradative processes.

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Acoustic biomolecules enhance hemodynamic functional ultrasound imaging of neural activity

Cited by 7 publications

References 34 publications

Single-trial decoding of movement intentions using functional ultrasound neuroimaging

Single-trial decoding of movement intentions using functional ultrasound neuroimaging

Deep-fUS: Functional ultrasound imaging of the brain using deep learning and sparse data

Biomolecular Ultrasound Imaging of Phagolysosomal Function

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