Dynamic Effects of Aortic Arch Stiffening on Pulsatile Energy Transmission to Cerebral Vasculature as A Determinant of Brain-Heart Coupling

The global effect of aortic coarctation on carotid and renal pulsatile hemodynamics

Coarctation of the aorta (CoA) is a congenital disease characterized by the narrowing of the aorta, typically the descending portion after the left subclavian artery. If left untreated, by the time individuals reach 50 years of age, the mortality rate can reach 90%. Previous studies have highlighted the adverse effects of CoA on local hemodynamics. However, no study has investigated the global hemodynamic effects of CoA in end-organ (brain and kidney) damage. Clinical studies have shown that coarctation acts as a reflection site, potentially damaging the hemodynamics of the brain and kidneys. Our goal in this study is to investigate the underlying mechanisms of these altered wave dynamics and their impacts on the pulsatile hemodynamics of end-organs. In this study, we use a physiologically accurate in-vitro experimental setup that simulates the hemodynamics of systemic circulation. Experiments are conducted across various cardiac outputs, heart rates, and coarctation degrees using aortas across a wide range of aortic stiffnesses. Our principal finding is that CoA increases cerebral blood flow and harmful pulsatile energy transmission to the brain. Conversely, both renal blood flow and pulsatile energy transmission to the kidneys are reduced in CoA at every level of aortic stiffness.

Development of a High-Fidelity Benchtop Model for Simultaneous Flow, Pressure, and Imaging Assessment of Transarterial Embolization Procedures

PURPOSE

The development of new endovascular technologies for transarterial embolization has relied on animal studies to validate efficacy before clinical trials are undertaken. Because embolizations in animals and patients are primarily conducted with fluoroscopy alone, local hemodynamic changes are not assessed during testing. However, such hemodynamic metrics could be important indicators of procedure efficacy that could support improved patient outcomes, such as via the determination of procedural endpoints. The purpose of this study is to create a high-fidelity benchtop system for multiparametric (i.e., hemodynamic and imaging) assessment of transarterial embolization procedures.

METHODS

The benchtop system consists of a 3D printed, anatomically accurate vascular phantom; a flow loop with a cardiac output simulator; a high-speed video camera; and pressure transducers and flow meters. This system enabled us to vary the heart rate and blood pressure and to simulate clinically relevant hemodynamic states, such as healthy adult, aortic regurgitation, and hypovolemic shock.

RESULTS

With our radiation-free angiography-mimetic imaging system, we could simultaneously assess gauge pressure and flow values during transarterial embolization. We demonstrated the feasibility of recapitulating the digital subtraction angiography workflow. Finally, we highlighted the utility of this system by characterizing the relationship between an imaging-based metric of procedural endpoint and intravascular flow. We also characterized hemodynamic changes associated with particle embolization within a branch of the hepatic artery and found them to be within reported patient data.

CONCLUSION

Our benchtop vascular system was low-cost and reproduced transarterial embolization-related hemodynamic phenomena with high fidelity. We believe that this novel platform enables the characterization of patient physiology, novel catheterization devices, and techniques.

A new methodology for determining the central pressure waveform from peripheral measurement using Fourier-based machine learning

Radial applanation tonometry is a well-established technique for hemodynamic monitoring and is becoming popular in affordable non-invasive wearable healthcare electronics. To assess the central aortic pressure using radial-based measurements, there is an essential need to develop mathematical approaches to estimate the central pressure waveform. In this study, we propose a new Fourier-based machine learning (F-ML) methodology to transfer non-invasive radial pressure measurements to the central pressure waveform. To test the method, collection of tonometry recordings of the radial and carotid pressure measurements are used from the Framingham Heart Study (2640 individuals, 55 % women) with mean (range) age of 66 (40-91) years. Method-derived estimates are significantly correlated with the measured ones for three major features of the pressure waveform (systolic blood pressure, r=0.97, p < 0.001; diastolic blood pressure, r=0.99, p < 0.001; and mean blood pressure, r=0.99, p < 0.001). In all cases, the Bland-Altman analysis shows negligible bias in the estimations and error is bounded to 5.4 mmHg. Findings also suggest that the F-ML approach reconstructs the shape of the central pressure waveform accurately with the average normalized root mean square error of 5.5 % in the testing population which is blinded to all stages of machine learning development. The results show that the F-ML transfer function outperforms the conventional generalized transfer function, particularly in terms of reconstructing the shape of the central pressure waveform morphology. The proposed F-ML transfer function can provide accurate estimates for the central pressure waveform, and ultimately expand the usage of non-invasive devices for central hemodynamic assessment.

Estimation of pulmonary vascular resistance for Glenn physiology

Children with single ventricle heart disease typically require a series of three operations, (1) Norwood, (2) Glenn, and (3) Fontan, which ultimately results in complete separation of the pulmonary and systemic circuits to improve pulmonary/systemic circulation. In the last stage, the Fontan operation, the inferior vena cava (IVC) is connected to the pulmonary arteries (PAs), allowing the remainder of deoxygenated blood to passively flow to the pulmonary circuit. It is hypothesized that optimizing the Fontan anatomy would lead to decreased power loss and more balanced hepatic flow distribution. One approach to optimizing the geometry is to create a patient-specific digital twin to simulate various configurations of the Fontan conduit, which requires a computational model of the proximal PA anatomy and resistance, as well as the distal Pulmonary Vascular Resistance (PVR), at the Glenn stage. To that end, an optimization pipeline was developed using 3D computational fluid dynamics (CFD) and 0D lumped parameter (LP) simulations to iteratively refine the PVR of each lung by minimizing the simulated flow and pressure error relative to patients' cardiac magnetic resonance (CMR) and catheterization (CATH) data. While the PVR can also be estimated directly by computing the ratio of pressure gradients and flow from CATH and CMR data, the computational approach can separately identify the different components of PVR along the Glenn pathway, allowing for a more detailed depiction of the Glenn vasculature. Results indicate good correlation between the optimized PVR of the CFD and LP models (n = 16), with an intraclass correlation coefficient (ICC) of 0.998 (p = 0.976) and 0.991 (p = 0.943) for the left and right lung, respectively. Furthermore, compared to CMR flow and CATH pressure data, the optimized PVR estimates result in mean outlet flow and pressure errors of less than 5%. The optimized PVR estimates also agree well with the computed PVR estimates from CATH pressure and CMR flow for both lungs, yielding a mean difference of less than 4%.

Measuring global cerebrovascular pulsatility transmission using 4D flow MRI

Pulse wave encephalopathy (PWE) is hypothesised to initiate many forms of dementia, motivating its identification and risk assessment. As candidate pulsatility based biomarkers for PWE, pulsatility index and pulsatility damping have been studied and, currently, do not adequately stratify risk due to variability in pulsatility and spatial bias. Here, we propose a locus-independent pulsatility transmission coefficient computed by spatially tracking pulsatility along vessels to characterise the brain pulse dynamics at a whole-organ level. Our preliminary analyses in a cohort of 20 subjects indicate that this measurement agrees with clinical observations relating blood pulsatility with age, heart rate, and sex, making it a suitable candidate to study the risk of PWE. We identified transmission differences between vascular regions perfused by the basilar and internal carotid arteries attributed to the identified dependence on cerebral blood flow, and some participants presented differences between the internal carotid perfused regions that were not related to flow or pulsatility burden, suggesting underlying mechanical differences. Large populational studies would benefit from retrospective pulsatility transmission analyses, providing a new comprehensive arterial description of the hemodynamic state in the brain. We provide a publicly available implementation of our tools to derive this coefficient, built into pre-existing open-source software.

Assessing pressure wave components for aortic stiffness monitoring through spectral regression learning

Aims

The ageing process notably induces structural changes in the arterial system, primarily manifesting as increased aortic stiffness, a precursor to cardiovascular events. While wave separation analysis is a robust tool for decomposing the components of blood pressure waveform, its relationship with cardiovascular events, such as aortic stiffening, is incompletely understood. Furthermore, its applicability has been limited due to the need for concurrent measurements of pressure and flow. Our aim in this study addresses this gap by introducing a spectral regression learning method for pressure-only wave separation analysis.

Methods and results

Leveraging data from the Framingham Heart Study (2640 individuals, 55% women), we evaluate the accuracy of pressure-only estimates, their interchangeability with a reference method based on ultrasound-derived flow waves, and their association with carotid-femoral pulse wave velocity (PWV). Method-derived estimates are strongly correlated with the reference ones for forward wave amplitude ( R 2 = 0.91 ), backward wave amplitude ( R 2 = 0.88 ), and reflection index ( R 2 = 0.87 ) and moderately correlated with a time delay between forward and backward waves ( R 2 = 0.38 ). The proposed pressure-only method shows interchangeability with the reference method through covariate analysis. Adjusting for age, sex, body size, mean blood pressure, and heart rate, the results suggest that both pressure-only and pressure-flow evaluations of wave separation parameters yield similar model performances for predicting carotid-femoral PWV, with forward wave amplitude being the only significant factor (P < 0.001; 95% confidence interval, 0.056-0.097).

Conclusion

We propose an interchangeable pressure-only wave separation analysis method and demonstrate its clinical applicability in capturing aortic stiffening. The proposed method provides a valuable non-invasive tool for assessing cardiovascular health.

Mechanistic insights on age-related changes in heart-aorta-brain hemodynamic coupling using a pulse wave model of the entire circulatory system

Age-related changes in aortic biomechanics can impact the brain by reducing blood flow and increasing pulsatile energy transmission. Clinical studies have shown that impaired cardiac function in patients with heart failure is associated with cognitive impairment. Although previous studies have attempted to elucidate the complex relationship between age-associated aortic stiffening and pulsatility transmission to the cerebral network, they have not adequately addressed the effect of interactions between aortic stiffness and left ventricle (LV) contractility (neither on energy transmission nor on brain perfusion). In this study, we use a well-established and validated one-dimensional blood flow and pulse wave computational model of the circulatory system to address how age-related changes in cardiac function and vasculature affect the underlying mechanisms involved in the LV-aorta-brain hemodynamic coupling. Our results reveal how LV contractility affects pulsatile energy transmission to the brain, even with preserved cardiac output. Our model demonstrates the existence of an optimal heart rate (near the normal human heart rate) that minimizes pulsatile energy transmission to the brain at different contractility levels. Our findings further suggest that the reduction in cerebral blood flow at low levels of LV contractility is more prominent in the setting of age-related aortic stiffening. Maintaining optimal blood flow to the brain requires either an increase in contractility or an increase in heart rate. The former consistently leads to higher pulsatile power transmission, and the latter can either increase or decrease subsequent pulsatile power transmission to the brain.NEW & NOTEWORTHY We investigated the impact of major aging mechanisms of the arterial system and cardiac function on brain hemodynamics. Our findings suggest that aging has a significant impact on heart-aorta-brain coupling through changes in both arterial stiffening and left ventricle (LV) contractility. Understanding the underlying physical mechanisms involved here can potentially be a key step for developing more effective therapeutic strategies that can mitigate the contributions of abnormal LV-arterial coupling toward neurodegenerative diseases and dementia.

On the Longitudinal Wave Pumping in Fluid-filled Compliant Tubes

This study investigates the physics of the longitudinal stretching-based wave pumping mechanism, a novel extension of the traditional impedance pump. In its simplest form, an impedance pump consists of a fluid-filled elastic tube connected to rigid tubes with a wave generator. These valveless pumps operate based on the principles of wave propagation in a fluid-filled compliant tube. Cardiovascular magnetic resonance imaging of the human circulatory system has shown substantial stretching of the aorta (the largest compliant artery of the body carrying blood) during the heart contraction and recoil of the aorta during the relaxation. Inspired by this dynamic mechanism, a comprehensive analysis of a longitudinal impedance pump is conducted in this study where waves are generated by stretching of the elastic wall and its recoil. We developed a fully coupled fluid-structure interaction computational model consisting of a straight fluid-filled elastic tube with longitudinal stretch at one end and fixed reflection site at the other end. The pump's behavior is quantified as a function of stretching frequency and tube wall characteristics. Our results indicate that stretch-related wave propagation and reflection can induce frequency-dependent pumping. Findings suggest a non-linear pattern for the mean flow-frequency relationship. Based on the analysis of the propagated waveforms, the underlying physical mechanism in the longitudinal impedance pump is discussed. It is shown that both the direction and magnitude of the net flow strongly depend on the wave characteristics. These findings provide a fundamental understanding of stretch-related wave pumping and can inform the future design of such pumps.

The effect of cyclic stretch on aortic viscoelasticity and the putative role of smooth muscle focal adhesion

Due to its viscoelastic properties, the aorta aids in dampening blood pressure pulsatility. At the level of resistance-arteries, the pulsatile flow will be transformed into a continuous flow to allow for optimal perfusion of end organs such as the kidneys and the brain. In this study, we investigated the ex vivo viscoelastic properties of different regions of the aorta of healthy C57Bl6/J adult mice as well as the interplay between (altered) cyclic stretch and viscoelasticity. We demonstrated that the viscoelastic parameters increase along the distal aorta and that the effect of altered cyclic stretch is region dependent. Increased cyclic stretch, either by increased pulse pressure or pulse frequency, resulted in decreased aortic viscoelasticity. Furthermore, we identified that the vascular smooth muscle cell (VSMC) is an important modulator of viscoelasticity, as we have shown that VSMC contraction increases viscoelastic parameters by, in part, increasing elastin fiber tortuosity. Interestingly, an acute increase in stretch amplitude reverted the changes in viscoelastic properties induced by VSMC contraction, such as a decreasing contraction-induced elastin fiber tortuosity. Finally, the effects of altered cyclic stretch and VSMC contraction on viscoelasticity were more pronounced in the abdominal infrarenal aorta, compared to both the thoracic ascending and descending aorta, and were attributed to the activity and stability of VSMC focal adhesion. Our results indicate that cyclic stretch is a modulator of aortic viscoelasticity, acting on VSMC focal adhesion. Conditions of (acute) changes in cyclic stretch amplitude and/or frequency, such as physical exercise or hypertension, can alter the viscoelastic properties of the aorta.

A review on the biomechanical behaviour of the aorta

Large aortic aneurysm and acute and chronic aortic dissection are pathologies of the aorta requiring surgery. Recent advances in medical intervention have improved patient outcomes; however, a clear understanding of the mechanisms leading to aortic failure and, hence, a better understanding of failure risk, is still missing. Biomechanical analysis of the aorta could provide insights into the development and progression of aortic abnormalities, giving clinicians a powerful tool in risk stratification. The complexity of the aortic system presents significant challenges for a biomechanical study and requires various approaches to analyse the aorta. To address this, here we present a holistic review of the biomechanical studies of the aorta by categorising articles into four broad approaches, namely theoretical, in vivo, experimental and combined investigations. Experimental studies that focus on identifying mechanical properties of the aortic tissue are also included. By reviewing the literature and discussing drawbacks, limitations and future challenges in each area, we hope to present a more complete picture of the state-of-the-art of aortic biomechanics to stimulate research on critical topics. Combining experimental modalities and computational approaches could lead to more comprehensive results in risk prediction for the aortic system.

Associations of carotid artery flow parameters with MRI markers of cerebral small vessel disease and patterns of brain atrophy

OBJECTIVES

A growing body of evidence links age related brain pathologies to systemic vascular processes. We aimed to study the prevalence and interrelations between magnetic resonance imaging (MRI) markers of cerebral small vessel disease and patterns of brain atrophy, and their association to carotid duplex ultrasound flow parameters.

MATERIALS AND METHODS

We investigated a population based randomised cohort of older adults (n=391) aged 70-87, part of the Swedish Good Aging in Skåne Study. Peak systolic and end diastolic velocities of the carotid arteries were measured by ultrasound, and resistivity- and pulsatility indexes were calculated. Subjects with increased peak systolic velocity indicating carotid stenosis were excluded from analysis. Nine MRI findings were rated by visual scales: white matter changes, pontine white matter changes, microbleeds, lacunar infarctions, medial temporal lobe atrophy, global cortical atrophy, parietal atrophy, precuneus atrophy and central atrophy.

RESULTS

MRI pathologies were found in 80% of subjects. Mean end diastolic velocity in common carotid arteries was inversely associated with white matter hyperintensities (OR=0.92; p=0.004), parietal lobe atrophy (OR=0.94; p=0.039), global cortical atrophy (OR=0.90; p=0.013), precuneus atrophy (OR=0.94; p=0.022), "number of CSV pathologies" (β=-0.07; p<0.001) and "MRI-burden score" (β=-0.11; p<0.001), after adjustment for age and sex. The latter three were also associated with pulsatility and resistivity indexes.

CONCLUSIONS

Low carotid end diastolic velocity, as well as increased carotid resistivity and pulsatility, were associated with signs of cerebral small vessel disease and patterns of brain atrophy, indicating a vascular component in the process of brain aging.

Direct 0D-3D coupling of a lattice Boltzmann methodology for fluid-structure aortic flow simulations

This work introduces a numerical approach and implementation for the direct coupling of arbitrary complex ordinary differential equation- (ODE-)governed zero-dimensional (0D) boundary conditions to three-dimensional (3D) lattice Boltzmann-based fluid-structure systems for hemodynamics studies. In particular, a most complex configuration is treated by considering a dynamic left ventricle- (LV-)elastance heart model which is governed by (and applied as) a nonlinear, non-stationary hybrid ODE-Dirichlet system. Other ODE-based boundary conditions, such as lumped parameter Windkessel models for truncated vasculature, are also considered. Performance studies of the complete 0D-3D solver, including its treatment of the lattice Boltzmann fluid equations and elastodynamics equations as well as their interactions, is conducted through a variety of benchmark and convergence studies that demonstrate the ability of the coupled 0D-3D methodology in generating physiological pressure and flow waveforms-ultimately enabling the exploration of various physical and physiological parameters for hemodynamics studies of the coupled LV-arterial system. The methods proposed in this paper can be easily applied to other ODE-based boundary conditions as well as to other fluid problems that are modeled by 3D lattice Boltzmann equations and that require direct coupling of dynamic 0D boundary conditions.

The Relationship of Vascular Aging to Reduced Cognitive Function: Pulsatile and Steady State Arterial Hemodynamics

Aortic stiffness increases with age and is a robust predictor of cerebrovascular events and cognitive decline including Alzheimer's disease and other forms of dementia. Recent clinical studies have investigated the association between proximal aortic stiffness and pulsatile energy transmission that has deleterious effects on the cerebrovascular network in order to identify potential therapeutic targets. Aging causes disproportionate stiffening of the aorta compared with the carotid arteries, reducing protective impedance mismatches at their interface, increasing the transmission of destructive pulsatile pressure and energy to the cerebral circulation, and leading to cerebral small vessel disease. Thus, aortic stiffening and high-flow pulsatility are associated with alterations in the microvasculature of the brain, vascular endothelial dysfunction, and white matter damage, which contribute to impaired memory function with advancing age. Previous studies have also shown that silent lacunar infarcts and white matter hyperintensities are strongly associated with arterial stiffness. More and more evidence suggests that vascular etiologies, including aortic stiffness, impedance match, and microvascular damage, are associated with cognitive impairment and the pathogenesis of dementia. The measurement of arterial flow and pressure can help understand pulsatile hemodynamics and its impact on vital organs. Interventions that reduce aortic stiffness, such as improvement of the living environment, management of risk factors, and innovation and development of novel drugs, may reduce the risk for dementia.

A coupled atrioventricular-aortic setup for in-vitro hemodynamic study of the systemic circulation: Design, fabrication, and physiological relevancy

In-vitro models of the systemic circulation have gained a lot of interest for fundamental understanding of cardiovascular dynamics and for applied hemodynamic research. In this study, we introduce a physiologically accurate in-vitro hydraulic setup that models the hemodynamics of the coupled atrioventricular-aortic system. This unique experimental simulator has three major components: 1) an arterial system consisting of a human-scale artificial aorta along with the main branches, 2) an artificial left ventricle (LV) sac connected to a programmable piston-in-cylinder pump for simulating cardiac contraction and relaxation, and 3) an artificial left atrium (LA). The setup is designed in such a way that the basal LV is directly connected to the aortic root via an aortic valve, and to the LA via an artificial mitral valve. As a result, two-way hemodynamic couplings can be achieved for studying the effects that the LV, aorta, and LA have on each other. The collected pressure and flow measurements from this setup demonstrate a remarkable correspondence to clinical hemodynamics. We also investigate the physiological relevancies of isolated effects on cardiovascular hemodynamics of various major global parameters found in the circulatory system, including LV contractility, LV preload, heart rate, aortic compliance, and peripheral resistance. Subsequent control over such parameters ultimately captures physiological hemodynamic effects of LV systolic dysfunction, preload (cardiac) diseases, and afterload (arterial) diseases. The detailed design and fabrication of the proposed setup is also provided.

Model-Based Fluid-Structure Interaction Approach for Evaluation of Thoracic Endovascular Aortic Repair Endograft Length in Type B Aortic Dissection

Thoracic endovascular aortic repair (TEVAR) is a commonly performed operation for patients with type B aortic dissection (TBAD). The goal of TEVAR is to cover the proximal entry tear between the true lumen (TL) and the false lumen (FL) with an endograft to induce FL thrombosis, allow for aortic healing, and decrease the risk of aortic aneurysm and rupture. While TEVAR has shown promising outcomes, it can also result in devastating complications including stroke, spinal cord ischemia resulting in paralysis, as well as long-term heart failure, so treatment remains controversial. Similarly, the biomechanical impact of aortic endograft implantation and the hemodynamic impact of endograft design parameters such as length are not well-understood. In this study, a fluid-structure interaction (FSI) computational fluid dynamics (CFD) approach was used based on the immersed boundary and Lattice–Boltzmann method to investigate the association between the endograft length and hemodynamic variables inside the TL and FL. The physiological accuracy of the model was evaluated by comparing simulation results with the true pressure waveform measurements taken during a live TEVAR operation for TBAD. The results demonstrate a non-linear trend towards increased FL flow reversal as the endograft length increases but also increased left ventricular pulsatile workload. These findings suggest a medium-length endograft may be optimal by achieving FL flow reversal and thus FL thrombosis, while minimizing the extra load on the left ventricle. These results also verify that a reduction in heart rate with medical therapy contributes favorably to FL flow reversal.

Small Vessel Disease, a Marker of Brain Health: What the Radiologist Needs to Know

Small vessel disease, a disorder of cerebral microvessels, is an expanding epidemic and a common cause of stroke and dementia. Despite being almost ubiquitous in brain imaging, the clinicoradiologic association of small vessel disease is weak, and the underlying pathogenesis is poorly understood. The STandards for ReportIng Vascular changes on nEuroimaging (STRIVE) criteria have standardized the nomenclature. These include white matter hyperintensities of presumed vascular origin, recent small subcortical infarcts, lacunes of presumed vascular origin, prominent perivascular spaces, cerebral microbleeds, superficial siderosis, cortical microinfarcts, and brain atrophy. Recently, the rigid categories among cognitive impairment, vascular dementia, stroke, and small vessel disease have become outdated, with a greater emphasis on brain health. Conventional and advanced small vessel disease imaging markers allow a comprehensive assessment of global brain heath. In this review, we discuss the pathophysiology of small vessel disease neuroimaging nomenclature by means of the STRIVE criteria, clinical implications, the role of advanced imaging, and future directions.

The Impact of Aging on the Association Between Aortic Stiffness and Cerebral Pulsatility Index

The central arteries dampen the pulsatile forces from myocardial contraction, limiting the pulsatility that reaches the cerebral vasculature, although there are limited data on this relationship with aging in humans. The purpose of this study was to determine the association between aortic stiffness and cerebral artery pulsatility index in young and older adults. We hypothesized that cerebral pulsatility index would be associated with aortic stiffness in older adults, but not in young adults. We also hypothesized that both age and aortic stiffness would be significant predictors for cerebral pulsatility index. This study included 23 healthy older adults (aged 62 ± 6 years) and 33 healthy young adults (aged 25 ± 4 years). Aortic stiffness was measured using carotid-femoral pulse wave velocity (cfPWV), while cerebral artery pulsatility index in the internal carotid arteries (ICAs), middle cerebral arteries (MCAs), and basilar artery were assessed using 4D Flow MRI. Cerebral pulsatility index was calculated as (maximum flow - minimum flow) / mean flow. In the combined age group, there was a positive association between cfPWV and cerebral pulsatility index in the ICAs (r = 0.487; p < 0.001), MCAs (r = 0.393; p = 0.003), and basilar artery (r = 0.576; p < 0.001). In young adults, there were no associations between cfPWV and cerebral pulsatility index in any of the arteries of interest (ICAs: r = 0.253; p = 0.156, MCAs: r = -0.059; p = 0.743, basilar artery r = 0.171; p = 0.344). In contrast, in older adults there was a positive association between cfPWV and cerebral pulsatility index in the MCAs (r = 0.437; p = 0.037) and basilar artery (r = 0.500; p = 0.015). However, the relationship between cfPWV and cerebral pulsatility index in the ICAs of the older adults did not reach the threshold for significance (r = 0.375; p = 0.078). In conclusion, age and aortic stiffness are significant predictors of cerebral artery pulsatility index in healthy adults. This study highlights the importance of targeting aortic stiffness in our increasingly aging population to reduce the burden of age-related changes in cerebral hemodynamics.

Effectiveness of pulsatility index of carotid Doppler ultrasonography to predict cardiovascular events

PURPOSE

The pulsatility index (PI) obtained from carotid ultrasonography is considered to be a marker of cerebrovascular resistance. However, the impact of PI on cardiovascular events has yet to be fully addressed.

METHOD

Fifty-four patients who underwent both carotid ultrasonography and coronary angiography were followed for 5.9 ± 3.2 years. The relationship between the incidence of cardiovascular events and PI was investigated.

RESULT

There were 10 (19%) deaths, four (7%) cardiovascular deaths, and nine (17%) major adverse cardiovascular events (MACEs). The cardiovascular events-defined as all hospitalization for MACEs plus heart failure, revascularization, and cardiovascular surgery-occurred in 21 patients (39%). The patients were divided into two groups according to each threshold of PI value for common carotid arteries (CCA), internal carotid arteries (ICA), and external carotid arteries (ECA), respectively. The thresholds were calculated based on receiver-operating characteristic curves for cardiovascular events. Log-rank test showed that the groups with CCA-PI ≥ 1.71, ICA-PI ≥ 1.20, and ECA-PI ≥ 2.46 had a higher incidence of cardiovascular events, respectively (p < 0.05). ECA-PI ≥ 2.46 was associated with an increased incidence of MACEs. Multivariate Cox regression analysis adjusting for cardiovascular risk factors showed that high PI of CCA, ICA, or ECA was a risk factor for cardiovascular events, respectively (CCA-PI ≥ 1.71, hazard ratio (HR) 3.242, p = 0.042; ICA-PI ≥ 1.20, HR 3.639, p = 0.012; ECA-PI ≥ 2.46, HR 11.322, p = 0.001).

CONCLUSION

The results suggested that carotid PIs were independent predictive factors for further cardiovascular events. In particular, high ECA-PI levels may reflect severe arteriosclerosis.

Effects of vessel wall mechanics on non-invasive evaluation of cardiovascular intrinsic frequencies

Intrinsic Frequency (IF) is a systems-based approach that provides valuable information for hemodynamic monitoring of the left ventricle (LV), the arterial system, and their coupling. Recent clinical studies have demonstrated the clinical significance of this method for prognosis and diagnosis of cardiovascular diseases. In IF analysis, two dominant instantaneous frequencies (ω₁ and ω₂) are extracted from arterial pressure waveforms. The value of ω₁ is related to the dynamics of the LV and the value of ω₂ is related to the dynamics of vascular function. This work investigates the effects of vessel wall mechanics on the accuracy and applicability of IFs extracted from vessel wall displacement waveforms compared to IFs extracted from pressure waveforms. In this study, we used a computational approach employing a fluid-structure interaction finite element method for various wall mechanics governed by linearly elastic, hyperelastic, and viscoelastic models. Results show that for vessels with elastic wall behavior, the error between displacement-based and pressure-based IFs is negligible. In the presence of stenosis or aneurysm in elastic arteries, the maximum errors associated with displacement-based IFs is less than 2%. For non-linear elastic and viscoelastic arteries, errors are more pronounced (where the former reaches up to 11% and the latter up to 27%). Our results ultimately suggest that displacement-based computations of ω₁ and ω₂ are accurate in vessels that exhibit elastic behavior (such as carotid arteries) and are suitable surrogates for pressure-based IFs. This is clinically significant because displacement-based IFs can be measured non-invasively.

Accuracy and applicability of non-invasive evaluation of aortic wave intensity using only pressure waveforms in humans

Background.Wave intensity (WI) analysis is a well-established method for quantifying the energy carried in arterial waves, providing valuable clinical information about cardiovascular function. The primary drawback of this method is the need for concurrent measurements of both pressure and flow waveforms.Objective. We have for the first time investigated the accuracy of a novel methodology for estimating wave intensity employing only single pressure waveform measurements; we studied both carotid- and radial-based estimations in a large heterogeneous cohort.Approach.Tonometry was performed alongside Doppler ultrasound to acquire measurements of both carotid and radial pressure waveforms as well as aortic flow waveforms in 2640 healthy and diseased participants (1439 female) in the Framingham Heart Study. Patterns consisting of two forward waves (Wf1, Wf2) and one backward wave (Wb1) along with reflection metrics were compared with those obtained from exact WI analysis.Main Results. Carotid-based estimates correlated well for forward peak amplitudes (Wf1,r = 0.85,p < 0.05; Wf2,r = 0.72,p < 0.05) and peak time (Wf1,r = 0.94,p < 0.05; Wf2,r = 0.98,p < 0.05), and radial-based estimates correlated fairly to poorly for amplitudes (Wf1,r = 0.62,p < 0.05; Wf2,r = 0.42,p < 0.05) and peak time (Wf1,r = 0.04,p = 0.10; Wf2,r = 0.75,p < 0.05). In all cases, estimated Wb1 measures were not correlated. Reflection metrics were well correlated for healthy patients (r = 0.67,p < 0.05), moderately correlated for valvular disease (r = 0.59,p < 0.05) and fairly correlated for CVD (r = 0.46,p < 0.05) and heart failure (r = 0.49,p < 0.05).Significance. These findings indicate that pressure-only WI produces accurate results only when forward contributions are of primary interest and only for carotid pressure waveforms. The pressure-only WI estimations of this work provide an important opportunity to further the goal of uncovering clinical insights through wave analysis affordably and non-invasively.

Single-cell RNA-seq reveals cellular heterogeneity of mouse carotid artery under disturbed flow

Disturbed blood flow (d-flow) has been known to induce changes of the cells in the arterial wall, increasing the risk of atherosclerosis. However, the heterogeneity of the vascular cell populations under d-flow remains less understood. To generate d-flow in vivo, partial carotid artery ligation (PCL) was performed. Seven days after ligation, single-cell RNA sequencing of nine left carotid arteries (LCA) from the PCL group (10,262 cells) or control group (14,580 cells) was applied and a single-cell atlas of gene expression was constructed. The integrated analysis identified 15 distinct carotid cell clusters, including 10 d-flow-relevant subpopulations. Among endothelial cells, at least four subpopulations were identified, including Klk8hi ECs, Lrp1hi ECs, Dkk2hi ECs, and Cd36hi ECs. Analysis of GSVA and single-cell trajectories indicated that the previously undescribed Dkk2hi ECs subpopulation was mechanosensitive and potentially transformed from Klk8hi ECs under d-flow. D-flow-induced Spp1hi VSMCs subpopulation that appeared to be endowed with osteoblast differentiation, suggesting a role in arterial stiffness. Among the infiltrating cell subpopulations, Trem2hi Mφ, Birc5hi Mφ, DCs, CD4+ T cells, CXCR6+ T cells, NK cells, and granulocytes were identified under d-flow. Of note, the novel Birc5hi Mφ was identified as a potential contributor to the accumulation of macrophages in atherosclerosis. Finally, Dkk2hi ECs, and Cd36hi ECs were also found in the proatherosclerotic area of the aorta where the d-flow occurs. In conclusion, we presented a comprehensive single-cell atlas of all cells in the carotid artery under d-flow, identified previously unrecognized cell subpopulations and their gene expression signatures, and suggested their specialized functions.

Insulin resistance, cardiovascular stiffening and cardiovascular disease

The cardiometabolic syndrome (CMS) and obesity are typically characterized by a state of metabolic insulin resistance. As global and US rates of obesity increase there is an acceleration of the incidence and prevalence of insulin resistance along with associated cardiovascular disease (CVD). Under physiological conditions insulin regulates glucose homeostasis by enhancing glucose disposal in insulin sensitive tissues while also regulating delivery of nutrients through its vasodilation actions on small feed arteries. Specifically, insulin-mediated production of nitric oxide (NO) from the vascular endothelium leads to increased blood flow enhancing disposal of glucose. Typically, insulin resistance is considered as a decrease in sensitivity or responsiveness to the metabolic actions of insulin including insulin-mediated glucose disposal. However, a decreased sensitivity to the normal vascular actions of insulin, especially diminished nitric oxide production, plays an additional important role in the development of CVD in states of insulin resistance. One mechanism by which insulin resistance and attendant hyperinsulinemia promote CVD is via increases in vascular stiffness. Although obesity and insulin resistance are known to be associated with substantial increases in the prevalence of vascular fibrosis and stiffness the mechanisms and mediators that underlie vascular stiffening in insulin resistant states are complex and have only recently begun to be addressed. Current evidence supports the role of increased plasma levels of aldosterone and insulin and attendant reductions in bioavailable NO in the pathogenesis of impaired vascular relaxation and vascular stiffness in the CMS and obesity. Aldosterone and insulin both increase the activity of serum and glucocorticoid kinase 1 (SGK-1) which in turn is a major regulator of vascular and renal sodium (Na⁺⁾ channel activity.The importance of SGK-1 in the pathogenesis of the CMS is highlighted by observations that gain of function mutations in SGK-1 in humans promotes hypertension, insulin resistance and obesity. In endothelial cells, an increase in Na⁺ flux contributes to remodeling of the cytoskeleton, reduced NO bioavailability and vascular stiffening. Thus, endothelial SGK-1 may represent a point of convergence for insulin and aldosterone signaling in arterial stiffness associated with obesity and the CMS. This review examines our contemporary understanding of the link between insulin resistance and increased vascular stiffness with emphasis placed on a role for enhanced SGK-1 signaling as a key node in this pathological process.

Biophysics-based statistical learning: Application to heart and brain interactions

Initiatives such as the UK Biobank provide joint cardiac and brain imaging information for thousands of individuals, representing a unique opportunity to study the relationship between heart and brain. Most of research on large multimodal databases has been focusing on studying the associations among the available measurements by means of univariate and multivariate association models. However, these approaches do not provide insights about the underlying mechanisms and are often hampered by the lack of prior knowledge on the physiological relationships between measurements. For instance, important indices of the cardiovascular function, such as cardiac contractility, cannot be measured in-vivo. While these non-observable parameters can be estimated by means of biophysical models, their personalisation is generally an ill-posed problem, often lacking critical data and only applied to small datasets. Therefore, to jointly study brain and heart, we propose an approach in which the parameter personalisation of a lumped cardiovascular model is constrained by the statistical relationships observed between model parameters and brain-volumetric indices extracted from imaging, i.e. ventricles or white matter hyperintensities volumes, and clinical information such as age or body surface area. We explored the plausibility of the learnt relationships by inferring the model parameters conditioned on the absence of part of the target clinical features, applying this framework in a cohort of more than 3 000 subjects and in a pathological subgroup of 59 subjects diagnosed with atrial fibrillation. Our results demonstrate the impact of such external features in the cardiovascular model personalisation by learning more informative parameter-space constraints. Moreover, physiologically plausible mechanisms are captured through these personalised models as well as significant differences associated to specific clinical conditions.