Adaptive Pulse Wave Imaging: Automated Spatial Vessel Wall Inhomogeneity Detection in Phantoms and in-Vivo

Low-dose radiation promotes high-fat diet-induced atherosclerosis by activating cGAS signal pathway

BACKGROUND

Atherosclerosis (AS) is the most prevalent cardiovascular disease, with an exceptionally high burden. High-fat diet (HFD) is a popular diet behavior, whereas low-dose radiation (LDR) is an environmental physical factor. There is evidence to suggest that an HFD may exacerbate the onset of atherosclerosis. Whether the combination effect of HFD and LDR would have potential on atherosclerosis development remains incompletely unclear.

METHODS

In this study, ApoE-/- mice were used as atherosclerosis model animals to investigate the combination effects of HFD and LDR (10 × 0.01Gy, or 20 × 0.01Gy) on vascular lesions. Doppler ultrasound imaging, H&E staining, oil red O staining, western blotting, and immunohistochemistry (IHC) were used to assess the pro-atherosclerotic effects. LC-MS was used to detect the non-targeted lipidomic.

RESULTS

Long-term exposure of low-dose radiation at an accumulated dose of 0.2Gy significantly increased the occurrence of vascular stiffness and the aortic lesion in ApoE-/- mice. The synergistic effect of HFD and LDR was observed in the development of atherosclerosis, which might be linked to both the dysbiosis of lipid metabolism and the stimulation of the inflammatory signaling system. Moreover, LDR but not HFD can activate the cGAS-STING signaling through increasing the yield of cytosolic mitochondrial DNAs as well as the expression of cGAS protein. The activation of cGAS-STING signal triggers the release of IFN-α/-β, which functions as an inflammatory amplifier in the formation of atherosclerotic plaque.

CONCLUSION

The current study offers fresh insights into the risks and mechanism that underlie the development of atherosclerosis by LDR, and there is a combination effect of LDR and HFD with the involvement of cGAS-STING signal pathway.

Visualization of Pulse-Wave Velocity on Arterial Wall of Mice Through High-Frequency Ultrafast Doppler Imaging

Arterial pulse-wave velocity (PWV) is widely used in clinical applications to assess cardiovascular diseases. Ultrasound methods have been proposed for estimating regional PWV in human arteries. Furthermore, high-frequency ultrasound (HFUS) has been applied to perform preclinical small-animal PWV measurements; however, electrocardiogram (ECG)-gated retrospective imaging is required to achieve high-frame-rate imaging, which might be affected by arrhythmia-related problems. In this article, HFUS PWV mapping based on 40-MHz ultrafast HFUS imaging is proposed to visualize PWV on mouse carotid artery to measure arterial stiffness without ECG gating. In contrast to most other studies that used cross-correlation methods to detect arterial motion, ultrafast Doppler imaging was applied in this study to measure arterial wall velocity for PWV estimations. The performance of the proposed HFUS PWV mapping method was verified using a polyvinyl alcohol (PVA) phantom with various freeze-thaw cycles. Small-animal studies were then performed in wild-type (WT) mice and in apolipoprotein E knockout (ApoE KO) mice that were fed a high-fat diet (for 16 and 24 weeks). The Young's modulus of the PVA phantom measured through HFUS PWV mapping was 15.3 ± 0.81, 20.8 ± 0.32, and 32.2 ± 1.11 kPa for three, four, and five freeze-thaw cycles, respectively, and the corresponding measurement biases (relative to theoretical values) were 1.59%, 6.41%, and 5.73%, respectively. In the mouse study, the average PWVs were 2.0 ± 0.26, 3.3 ± 0.45, and 4.1 ± 0.22 m/s for 16-week WT, 16-week ApoE KO, and 24-week ApoE KO mice, respectively. The PWVs of ApoE KO mice increased during the high-fat diet feeding period. HFUS PWV mapping was used to visualize the regional stiffness of mouse artery, and a histology confirmed that the plaque formation in the bifurcation region increased the regional PWV. All the results indicate that the proposed HFUS PWV mapping method is a convenient tool for investigating arterial properties in preclinical small-animal studies.

Unsupervised deep learning-based displacement estimation for vascular elasticity imaging applications

Objective. Arterial wall stiffness can provide valuable information on the proper function of the cardiovascular system. Ultrasound elasticity imaging techniques have shown great promise as a low-cost and non-invasive tool to enable localized maps of arterial wall stiffness. Such techniques rely upon motion detection algorithms that provide arterial wall displacement estimation.Approach. In this study, we propose an unsupervised deep learning-based approach, originally proposed for image registration, in order to enable improved quality arterial wall displacement estimation at high temporal and spatial resolutions. The performance of the proposed network was assessed through phantom experiments, where various models were trained by using ultrasound RF signals, or B-mode images, as well as different loss functions.Main results. Using the mean square error (MSE) for the training process provided the highest signal-to-noise ratio when training on the B-modes images (30.36 ± 1.14 dB) and highest contrast-to-noise ratio when training on the RF signals (32.84 ± 1.89 dB). In addition, training the model on RF signals demonstrated the capability of providing accurate localized pulse wave velocity (PWV) maps, with a mean relative error (MREPWV) of 3.32 ± 1.80% and anR2 of 0.97 ± 0.03. Finally, the developed model was tested in human common carotid arteriesin vivo, providing accurate tracking of the distension pulse wave propagation, with an MREPWV= 3.86 ± 2.69% andR2 = 0.95 ± 0.03.Significance. In conclusion, a novel displacement estimation approach was presented, showing promise in improving vascular elasticity imaging techniques.

Pulse wave and vector flow Imaging for atherosclerotic disease progression in hypercholesterolemic swine

Non-invasive monitoring of atherosclerosis remains challenging. Pulse Wave Imaging (PWI) is a non-invasive technique to measure the local stiffness at diastolic and end-systolic pressures and quantify the hemodynamics. The objective of this study is twofold, namely (1) to investigate the capability of (adaptive) PWI to assess progressive change in local stiffness and homogeneity of the carotid in a high-cholesterol swine model and (2) to assess the ability of PWI to monitor the change in hemodynamics and a corresponding change in stiffness. Nine (n=9) hypercholesterolemic swine were included in this study and followed for up to 9 months. A ligation in the left carotid was used to cause a hemodynamic disturbance. The carotids with detectable hemodynamic disturbance showed a reduction in wall shear stress immediately after ligation (2.12 ± 0.49 to 0.98 ± 0.47 Pa for 40-90% ligation (Group B) and 1.82 ± 0.25 to 0.49 ± 0.46 Pa for >90% ligation (Group C)). Histology revealed subsequent lesion formation after 8-9 months, and the type of lesion formation was dependent on the type of the induced ligation, with more complex plaques observed in the carotids with a more significant ligation (C: >90%). The compliance progression appears differed for groups B and C, with an increase in compliance to 2.09 ± 2.90×10-10 m2 Pa-1 for group C whereas the compliance of group B remained low at 8 months (0.95 ± 0.94×10-10 m2 Pa-1). In summary, PWI appeared capable of monitoring a change in wall shear stress and separating two distinct progression pathways resulting in distinct compliances.

Adaptive Wall Shear Stress Imaging in Phantoms, Simulations and In Vivo

WSS measurement is challenging since it requires sensitive flow measurements at a distance close to the wall. The aim of this study is to develop an ultrasound imaging technique which combines vector flow imaging with an unsupervised data clustering approach that automatically detects the region close to the wall with optimally linear flow profile, to provide direct and robust WSS estimation. The proposed technique was evaluated in phantoms, mimicking normal and atherosclerotic vessels, and spatially registered Fluid Structure Interaction (FSI) simulations. A relative error of 6.7% and 19.8% was obtained for peak systolic (WSSPS) and end diastolic (WSSED) WSS in the straight phantom, while in the stenotic phantom, a good similarity was found between measured and simulated WSS distribution, with a correlation coefficient, R, of 0.89 and 0.85 for WSSPS and WSSED, respectively. Moreover, the feasibility of the technique to detect pre-clinical atherosclerosis was tested in an atherosclerotic swine model. Six swines were fed atherogenic diet, while their left carotid artery was ligated in order to disturb flow patterns. Ligated arterial segments that were exposed to low WSSPS and WSS characterized by high frequency oscillations at baseline, developed either moderately or highly stenotic plaques (p < 0.05). Finally, feasibility of the technique was demonstrated in normal and atherosclerotic human subjects. Atherosclerotic carotid arteries with low stenosis had lower WSSPS as compared to control subjects (p < 0.01), while in one subject with high stenosis, elevated WSS was found on an arterial segment, which coincided with plaque rupture site, as determined through histological examination.

PM2.5 induce the defective efferocytosis and promote atherosclerosis via HIF-1α activation in macrophage

Epidemiological studies demonstrate that fine particulate matter (PM_2.5) promotes the development of atherosclerosis. However, the mechanism insight of PM_2.5-induced atherosclerosis is still lacking. The aim of this study was to explore the biological effects of hypoxia-inducible factor 1α (HIF-1α) on PM_2.5-triggered atherosclerosis. The vascular stiffness, carotid intima-media thickness (CIMT), lipid and atherosclerotic lesion were increased when von Hippel-Lindau (VHL)-null mice were exposed to PM_2.5. Yet, knockout of HIF-1α markedly decreased the PM_2.5-triggered atherosclerotic lesion. We firstly performed microarray analysis in PM_2.5-treated bone morrow-derived macrophages (BMDMs), which showed that PM_2.5 significantly changed the genes expression patterns and affected biological processes such as phagocytosis, apoptotic cell clearance, cellular response to hypoxia, apoptotic process and inflammatory response. Moreover, the data showed knockout of HIF-1α remarkably relieved PM_2.5-induced defective efferocytosis. Mechanistically, PM_2.5 inhibited the level of genes and proteins of efferocytosis receptor c-Mer tyrosine kinase (MerTK), especially in VHL-null BMDMs. In addition, PM_2.5 increased the genes and proteins of a disintegrin and metallopeptidase domain 17 (ADAM17), which caused the MerTK cleavage to form soluble MerTK (sMer) in plasma and cellular supernatant. The sMer was significantly up-regulated in plasma of VHL-null PM_2.5-exposed mice. Moreover, PM_2.5 could induce defective efferocytosis and activate inflammatory response through MerTK/IFNAR1/STAT1 signaling pathway in macrophages. Our results demonstrate that PM_2.5 could induce defective efferocytosis and inflammation by activating HIF-1α in macrophages, ultimately resulting in accelerating atherosclerotic lesion formation and development. Our data suggest HIF-1α in macrophages might be a potential target for PM_2.5-related atherosclerosis.

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.

Feasibility of longitudinal monitoring of atherosclerosis with pulse wave imaging in a swine model

Objective.Atherosclerosis is a vascular disease characterized by compositional and mechanical changes in the arterial walls that lead to a plaque buildup. Depending on its geometry and composition, a plaque can ruptured and cause stroke, ischemia or infarction. Pulse wave imaging (PWI) is an ultrasound-based technique developed to locally quantify the stiffness of arteries. This technique has shown promising results when applied to patients. The objective of this study is to assess the capability of PWI to monitor the disease progression in a swine model that mimics human pathology.Approach.The left common carotid of three hypercholesterolemic Wisconsin miniature swines, fed an atherogenic diet, was ligated. Ligated and contralateral carotids were imaged once a month over 9 months, at a high-frame-rate, with a 5-plane wave compounding sequence and a 5 MHz linear array. Each acquisition was repeated after probe repositioning to evaluate the reproducibility. Wall displacements were estimated from the beamformed RF-data and were arranged as spatiotemporal maps depicting the wave propagation. The pulse wave velocity (PWV) estimated by tracking the 50% upstroke of the wave was converted in compliance using the Bramwell-Hill model. At the termination of the experiment, the carotids were extracted for histology analysis.Main results.PWI was able to monitor the evolution of compliance in both carotids of the animals. Reproducibility was demonstrated as the difference of PWV between cardiac cycles was similar to the difference between acquisitions (9.04% versus 9.91%). The plaque components were similar to the ones usually observed in patients. Each animal presented a unique pattern of compliance progression, which was confirmed by the plaque composition observed histologically.Significance.This study provides important insights on the vascular wall stiffness progression in an atherosclerotic swine model. It therefore paves the way for a thorough longitudinal study that examines the role of stiffness in both the plaque formation and plaque progression.

Feasibility of Bilinear Mechanical Characterization of the Abdominal Aorta in a Hypertensive Mouse Model

A change in elastin and collagen content is indicative of damage caused by hypertension, which changes the non-linear behavior of the vessel wall. This study was aimed at investigating the feasibility of monitoring the non-linear material behavior in an angiotensin II hypertensive mice model. Aortas from 13 hypertensive mice were imaged with pulse wave imaging (PWI) over 4 wk using a 40-MHz linear array. The pulse wave velocity was estimated using two wave features: (i) the maximum axial acceleration of the foot (PWV_dia) and (ii) the maximum axial acceleration of the dicrotic notch (PWV_end-sys). The Bramwell-Hill equation was used to derive the compliance at diastolic and end-systolic pressure. This study determined the potential of PWI in a hypertensive mouse model to image and quantify the non-linear material behavior in vivo. End-systolic compliance could differentiate between the sham and angiotensin II groups, whereas diastolic compliance could not, indicating that PWI can detect early collagen-dominated remodeling.

Evaluation of fine particulate matter on vascular endothelial function in vivo and in vitro

Ambient fine particulate matter (PM_2.5) and high-fat diet (HFD) are linked to the development of atherosclerosis. However, there is still unknown about the PM_2.5-induced atherosclerosis formation on vascular endothelial injury after co-exposed to PM_2.5 and HFD. Thus, the aim of this study was to evaluate the effects of PM_2.5 on atherogenesis in C57BL/6 mice and endothelial cells, as well as the co-exposure effect of PM_2.5 and HFD. In vivo study, C57BL/6 mice exposed to PM_2.5 and fed with standard chow diet (STD) or HFD for 1 month. PM_2.5 could increase vascular stiffness accessed by Doppler ultrasound, and more serious in co-exposure group. PM_2.5 impaired vascular endothelial layer integrity, exfoliated endothelial cells, and inflammatory cells infiltration through H&E staining. PM_2.5 reduced the expression of platelet/endothelial cell adhesion molecule-1 (PECAM-1) in vessel. Moreover, PM_2.5 could induce systemic inflammation detected by Mouse Inflammation Array. In vitro study, PM_2.5 triggered markedly mitochondrial damage by transmission electron microscope (TEM) and flow cytometer. Inflammatory cytokines were significantly increased in PM_2.5-exposed group. The cell viability and migration of endothelial cells were significantly suppressed. In addition, PM_2.5 remarkably declined the expression of vascular endothelial growth factor receptor 2 (VEGFR2) and increased the expression of somatostatin (SST) and its receptor. In conclusion, co-exposure of PM_2.5 and HFD might induce systemic inflammation and endothelial dysfunction in normal mice. Moreover, PM_2.5 could reduce vascular endothelial repair capacity through inhibiting the proliferation and migration of endothelial cells.

Pulse Wave Imaging Coupled With Vector Flow Mapping: A Phantom, Simulation, and In Vivo Study

Pulse wave imaging (PWI) is an ultrasound imaging modality that estimates the wall stiffness of an imaged arterial segment by tracking the pulse wave propagation. The aim of the present study is to integrate PWI with vector flow imaging, enabling simultaneous and co-localized mapping of vessel wall mechanical properties and 2-D flow patterns. Two vector flow imaging techniques were implemented using the PWI acquisition sequence: 1) multiangle vector Doppler and 2) a cross-correlation-based vector flow imaging (CC VFI) method. The two vector flow imaging techniques were evaluated in vitro using a vessel phantom with an embedded plaque, along with spatially registered fluid structure interaction (FSI) simulations with the same geometry and inlet flow as the phantom setup. The flow magnitude and vector direction obtained through simulations and phantom experiments were compared in a prestenotic and stenotic segment of the phantom and at five different time frames. In most comparisons, CC VFI provided significantly lower bias or precision than the vector Doppler method ( ) indicating better performance. In addition, the proposed technique was applied to the carotid arteries of nonatherosclerotic subjects of different ages to investigate the relationship between PWI-derived compliance of the arterial wall and flow velocity in vivo. Spearman's rank-order test revealed positive correlation between compliance and peak flow velocity magnitude ( rs = 0.90 and ), while significantly lower compliance ( ) and lower peak flow velocity magnitude ( ) were determined in older (54-73 y.o.) compared with young (24-32 y.o.) subjects. Finally, initial feasibility was shown in an atherosclerotic common carotid artery in vivo. The proposed imaging modality successfully provided information on blood flow patterns and arterial wall stiffness and is expected to provide additional insight in studying carotid artery biomechanics, as well as aid in carotid artery disease diagnosis and monitoring.

Evaluation of Plaque Characteristics and Inflammation Using Magnetic Resonance Imaging

Atherosclerosis is an inflammatory disease of large and medium-sized arteries, characterized by the growth of atherosclerotic lesions (plaques). These plaques often develop at inner curvatures of arteries, branchpoints, and bifurcations, where the endothelial wall shear stress is low and oscillatory. In conjunction with other processes such as lipid deposition, biomechanical factors lead to local vascular inflammation and plaque growth. There is also evidence that low and oscillatory shear stress contribute to arterial remodeling, entailing a loss in arterial elasticity and, therefore, an increased pulse-wave velocity. Although altered shear stress profiles, elasticity and inflammation are closely intertwined and critical for plaque growth, preclinical and clinical investigations for atherosclerosis mostly focus on the investigation of one of these parameters only due to the experimental limitations. However, cardiovascular magnetic resonance imaging (MRI) has been demonstrated to be a potent tool which can be used to provide insights into a large range of biological parameters in one experimental session. It enables the evaluation of the dynamic process of atherosclerotic lesion formation without the need for harmful radiation. Flow-sensitive MRI provides the assessment of hemodynamic parameters such as wall shear stress and pulse wave velocity which may replace invasive and radiation-based techniques for imaging of the vascular function and the characterization of early plaque development. In combination with inflammation imaging, the analyses and correlations of these parameters could not only significantly advance basic preclinical investigations of atherosclerotic lesion formation and progression, but also the diagnostic clinical evaluation for early identification of high-risk plaques, which are prone to rupture. In this review, we summarize the key applications of magnetic resonance imaging for the evaluation of plaque characteristics through flow sensitive and morphological measurements. The simultaneous measurements of functional and structural parameters will further preclinical research on atherosclerosis and has the potential to fundamentally improve the detection of inflammation and vulnerable plaques in patients.

Deep Learning for Carotid Plaque Segmentation using a Dilated U-Net Architecture

Carotid plaque segmentation in ultrasound longitudinal B-mode images using deep learning is presented in this work. We report on 101 severely stenotic carotid plaque patients. A standard U-Net is compared with a dilated U-Net architecture in which the dilated convolution layers were used in the bottleneck. Both a fully automatic and a semi-automatic approach with a bounding box was implemented. The performance degradation in plaque segmentation due to errors in the bounding box is quantified. We found that the bounding box significantly improved the performance of the networks with U-Net Dice coefficients of 0.48 for automatic and 0.83 for semi-automatic segmentation of plaque. Similar results were also obtained for the dilated U-Net with Dice coefficients of 0.55 for automatic and 0.84 for semi-automatic when compared to manual segmentations of the same plaque by an experienced sonographer. A 5% error in the bounding box in both dimensions reduced the Dice coefficient to 0.79 and 0.80 for U-Net and dilated U-Net respectively.

Arterial wall mechanical inhomogeneity detection and atherosclerotic plaque characterization using high frame rate pulse wave imaging in carotid artery disease patients in vivo

Pulse wave imaging (PWI) is a non-invasive, ultrasound-based technique, which provides information on arterial wall stiffness by estimating the pulse wave velocity (PWV) along an imaged arterial wall segment. The aims of the present study were to: (1) utilize the PWI information to automatically and optimally divide the artery into the segments with most homogeneous properties and (2) assess the feasibility of this method to provide arterial wall mechanical characterization in normal and atherosclerotic carotid arteries in vivo. A silicone phantom consisting of a soft and stiff segment along its longitudinal axis was scanned at the stiffness transition, and the PWV in each segment was estimated through static testing. The proposed algorithm detected the stiffness interface with an average error of 0.98  ±  0.49 mm and 1.04  ±  0.27 mm in the soft-to-stiff and stiff-to-soft pulse wave transmission direction, respectively. Mean PWVs estimated in the case of the soft-to-stiff pulse wave transmission direction were 2.47 [Formula: see text] 0.04 m s^-1 and 3.43 [Formula: see text] 0.08 m s^-1 for the soft and stiff phantom segments, respectively, while in the case of stiff-to-soft transmission direction PWVs were 2.60 [Formula: see text] 0.18 m s^-1 and 3.72 [Formula: see text] 0.08 m s^-1 for the soft and stiff phantom segments, respectively, which were in good agreement with the PWVs obtained through static testing (soft segment: 2.41 m s^-1, stiff segment: 3.52 m s^-1). Furthermore, the carotid arteries of N  =  9 young subjects (22-32 y.o.) and N  =  9 elderly subjects (60-73 y.o.) with no prior history of carotid artery disease were scanned, in vivo, as well as the atherosclerotic carotid arteries of N  =  12 (59-85 y.o.) carotid artery disease patients. One-way ANOVA with Holm-Sidak correction showed that the number of most homogeneous segments in which the artery was divided was significantly higher in the case of carotid artery disease patients compared to young (3.25 [Formula: see text] 0.86 segments versus 1.00 [Formula: see text] 0.00 segments, p -value  <  0.0001) and elderly non-atherosclerotic subjects (3.25 [Formula: see text] 0.86 segments versus 1.44 [Formula: see text] 0.51 segments p -value  <  0.0001), indicating increased wall inhomogeneity in atherosclerotic arteries. The compliance provided by the proposed algorithm was significantly higher in non-calcified/high-lipid plaques as compared with calcified plaques (3.35 [Formula: see text] 2.45 *[Formula: see text] versus 0.22 [Formula: see text] 0.18 * [Formula: see text], p -value  <  0.01) and the compliance estimated in elderly subjects (3.35 [Formula: see text] 2.45 * [Formula: see text] versus 0.79 [Formula: see text] 0.30 * [Formula: see text], p -value  <  0.01). Moreover, lower compliance was estimated in cases where vulnerable plaque characteristics were present (i.e. necrotic lipid core, thrombus), compared to stable plaque components (calcification), as evaluated through plaque histological examination. The proposed algorithm was thus capable of evaluating arterial wall inhomogeneity and characterize wall mechanical properties, showing promise in vascular disease diagnosis and monitoring.