Accuracy and Precision of a Plane Wave Vector Flow Imaging Method in the Healthy Carotid Artery

Ultrasound deep learning for monitoring of flow-vessel dynamics in murine carotid artery

Several arterial diseases are closely related with mechanical properties of the blood vessel and interactions of flow-vessel dynamics such as mean flow velocity, wall shear stress (WSS) and vascular strain. However, there is an opportunity to improve the measurement accuracy of vascular properties and hemodynamics by adopting deep learning-based ultrasound imaging for flow-vessel dynamics (DL-UFV). In this study, the DL-UFV is proposed by devising an integrated neural network for super-resolved localization and vessel wall segmentation, and it is also combined with tissue motion estimation and flow measurement techniques such as speckle image velocimetry and speckle tracking velocimetry for measuring velocity field information of blood flow. Performance of the DL-UFV is verified by comparing with other conventional techniques in tissue-mimicking phantoms. After the performance verification, in vivo feasibility is demonstrated in the murine carotid artery with different pathologies: aging and diabetes mellitus (DM). The mutual comparison of flow-vessel dynamics and histological analyses shows correlations between the immunoreactive region and abnormal flow-vessel dynamics interactions. The DL-UFV improves biases in measurements of velocity, WSS, and strain with up to 4.6-fold, 15.1-fold, and 22.2-fold in the tissue-mimicking phantom, respectively. Mean flow velocities and WSS values of the DM group decrease by 30% and 20% of those of the control group, respectively. Mean flow velocities and WSS values of the aging group (34.11 cm/s and 13.17 dyne/cm²) are slightly smaller than those of the control group (36.22 cm/s and 14.25 dyne/cm²). However, the strain values of the aging and DM groups are much smaller than those of the control group (p < 0.05). This study shows that the DL-UFV performs better than the conventional ultrasound-based flow and strain measurement techniques for measuring vascular stiffness and complicated flow-vessel dynamics. Furthermore, the DL-UFV demonstrates its excellent performance in the analysis of the hemodynamic and hemorheological effects of DM and aging on the flow and vascular characteristics. This work provides useful hemodynamic information, including mean flow velocity, WSS and strain with high-resolution for diagnosing the pathogenesis of arterial diseases. This information can be used for monitoring progression and regression of atherosclerotic diseases in clinical practice.

US Velocimetry in Participants with Aortoiliac Occlusive Disease

Background The accurate quantification of blood flow in aortoiliac arteries is challenging but clinically relevant because local flow patterns can influence atherosclerotic disease. Purpose To investigate the feasibility and clinical application of two-dimensional blood flow quantification using high-frame-rate contrast-enhanced US (HFR-CEUS) and particle image velocimetry (PIV), or US velocimetry, in participants with aortoiliac stenosis. Materials and Methods In this prospective study, participants with a recently diagnosed aortoiliac stenosis underwent HFR-CEUS measurements of the pre- and poststenotic vessel segments (August 2018 to July 2019). Two-dimensional quantification of blood flow was achieved by performing PIV analysis, which was based on pairwise cross-correlation of the HFR-CEUS images. Visual inspection of the entire data set was performed by five observers to evaluate the ability of the technique to enable adequate visualization of blood flow. The contrast-to-background ratio and average vector correlation were calculated. In two participants who showed flow disturbances, the flow complexity and vorticity were calculated. Results Thirty-five participants (median age, 67 years; age range, 56-84 years; 22 men) were included. Visual scoring showed that flow quantification was achieved in 41 of 42 locations. In 25 locations, one or multiple issues occurred that limited optimal flow quantification, including loss of correlation during systole (n = 12), shadow regions (n = 8), a short vessel segment in the image plane (n = 7), and loss of contrast during diastole (n = 5). In the remaining 16 locations, optimal quantification was achieved. The contrast-to-background ratio was higher during systole than during diastole (11.0 ± 2.9 vs 6.9 ± 3.4, respectively; P < .001), whereas the vector correlation was lower (0.58 ± 0.21 vs 0.47 ± 0.13; P < .001). The flow complexity and vorticity were high in regions with disturbed flow. Conclusion Blood flow quantification with US velocimetry is feasible in patients with an aortoiliac stenosis, but several challenges must be overcome before implementation into clinical practice. Clinical trial registration no. NTR6980 © RSNA, 2021 Online supplemental material is available for this article.

Contrast-Enhanced High-Frame-Rate Ultrasound Imaging of Flow Patterns in Cardiac Chambers and Deep Vessels

Cardiac function and vascular function are closely related to the flow of blood within. The flow velocities in these larger cavities easily reach 1 m/s, and generally complex spatiotemporal flow patterns are involved, especially in a non-physiologic state. Visualization of such flow patterns using ultrasound can be greatly enhanced by administration of contrast agents. Tracking the high-velocity complex flows is challenging with current clinical echographic tools, mostly because of limitations in signal-to-noise ratio; estimation of lateral velocities; and/or frame rate of the contrast-enhanced imaging mode. This review addresses the state of the art in 2-D high-frame-rate contrast-enhanced echography of ventricular and deep-vessel flow, from both technological and clinical perspectives. It concludes that current advanced ultrasound equipment is technologically ready for use in human contrast-enhanced studies, thus potentially leading to identification of the most clinically relevant flow parameters for quantifying cardiac and vascular function.

A Systematic Review for the Design of In Vitro Flow Studies of the Carotid Artery Bifurcation

PURPOSE

In vitro blood flow studies in carotid artery bifurcation models may contribute to understanding the influence of hemodynamics on carotid artery disease. However, the design of in vitro blood flow studies involves many steps and selection of imaging techniques, model materials, model design, and flow visualization parameters. Therefore, an overview of the possibilities and guidance for the design process is beneficial for researchers with less experience in flow studies.

METHODS

A systematic search to in vitro flow studies in carotid artery bifurcation models aiming at quantification and detailed flow visualization of blood flow dynamics results in inclusion of 42 articles.

RESULTS

Four categories of imaging techniques are distinguished: MRI, optical particle image velocimetry (PIV), ultrasound and miscellaneous techniques. Parameters for flow visualization are categorized into velocity, flow, shear-related, turbulent/disordered flow and other parameters. Model materials and design characteristics vary between study type.

CONCLUSIONS

A simplified three-step design process is proposed for better fitting and adequate match with the pertinent research question at hand and as guidance for less experienced flow study researchers. The three consecutive selection steps are: flow parameters, image modality, and model materials and designs. Model materials depend on the chosen imaging technique, whereas choice of flow parameters is independent from imaging technique and is therefore only determined by the goal of the study.

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.

In Vivo Blood Velocity Vector Imaging Using Adaptive Velocity Compounding in the Carotid Artery Bifurcation

Visualization and quantification of blood flow are considered important for early detection of atherosclerosis and patient-specific diagnosis and intervention. As conventional Doppler imaging is limited to 1-D velocity estimates, 2-D and 3-D techniques are being developed. We introduce an adaptive velocity compounding technique that estimates the 2-D velocity vector field using predominantly axial displacements estimated by speckle tracking from dual-angle plane wave acquisitions. Straight-vessel experiments with a 7.8-MHz linear array transducer connected to a Verasonics Vantage ultrasound system revealed that the technique performed with a maximum velocity magnitude bias and angle bias of -3.7% (2.8% standard deviation) and -0.16° (0.41° standard deviation), respectively. In vivo, complex flow patterns were visualized in two healthy and three diseased carotid arteries and quantified using a vector complexity measure that increased with increasing wall irregularity. This measure could potentially be a relevant clinical parameter which might aid in early detection of atherosclerosis.

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.