2018
DOI: 10.3390/app8020286
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Riding the Plane Wave: Considerations for In Vivo Study Designs Employing High Frame Rate Ultrasound

Abstract: Advancements in diagnostic ultrasound have allowed for a rapid expansion of the quantity and quality of non-invasive information that clinical researchers can acquire from cardiovascular physiology. The recent emergence of high frame rate ultrasound (HiFRUS) is the next step in the quantification of complex blood flow behavior, offering angle-independent, high temporal resolution data in normal physiology and clinical cases. While there are various HiFRUS methods that have been tested and validated in simulati… Show more

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Cited by 9 publications
(6 citation statements)
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“…On the topic of RF data access, one important feature shared by different types of ultrasound OPs is that they possess tens and hundreds of gigabytes of RAM to store full RF data frames over multiple heart beats. Such raw data storage capacity makes it possible for researchers to conduct in vivo studies with OPs by acquiring multibeat in vivo data [110] and storing these data sets for offline processing. No restrictions are then enforced on the complexity of the processing, and the image videos can later be evaluated by medical doctors for multiple patients in double blinded trials as described in [111] .…”
Section: Discussionmentioning
confidence: 99%
“…On the topic of RF data access, one important feature shared by different types of ultrasound OPs is that they possess tens and hundreds of gigabytes of RAM to store full RF data frames over multiple heart beats. Such raw data storage capacity makes it possible for researchers to conduct in vivo studies with OPs by acquiring multibeat in vivo data [110] and storing these data sets for offline processing. No restrictions are then enforced on the complexity of the processing, and the image videos can later be evaluated by medical doctors for multiple patients in double blinded trials as described in [111] .…”
Section: Discussionmentioning
confidence: 99%
“…For each acquired dataset, parallel beamforming and signal processing were performed in Matlab (R2016a; Mathworks Inc., Natick, MA, USA) . In brief, the received radiofrequency data were input to generate image frames with different receive steering angles, forming six unique transmit–receive angle pair images for each frame.…”
Section: Methodsmentioning
confidence: 99%
“…For each acquired dataset, parallel beamforming and signal processing were performed in Matlab (R2016a; Mathworks Inc., Natick, MA, USA). 19,32 In brief, the received radiofrequency data were input to generate image frames with different receive steering angles, forming six unique transmit-receive angle pair images for each frame. For each of these sets, slow-time processing was conducted on a per pixel basis including clutter suppression, mean Doppler frequency estimation, and manual dealiasing.…”
Section: C1 Flow Vector Estimation and Dynamic Visualizationmentioning
confidence: 99%
“…In this Case Study in Physiology, we report incidental findings from a recent experiment in which we observed a femoral "trifurcation" at rest, and during experimental manipulation of retrograde blood flow in the SFA to induce highly complex hemodynamic behavior at the femoral branching point. While conventional ultrasound imaging is unable to quantify blood velocity within bifurcations due to nonlaminar blood flow, our laboratory has refined the vector flow imaging technique (5,7) to visualize and quantify angle-independent blood velocity vectors at high frame rates (Ͼ1,000 fps) to better characterize multidirectional blood flow features (2,17,18). These emerging techniques are highly relevant to study complex hemodynamics in atherosclerotic-prone regions such as arterial bifurcations, as in the specific case of the femoral arterial branches.…”
Section: Introductionmentioning
confidence: 99%