The arterial Windkessel

Understanding perioperative risk determinants in carotid endarterectomy: the impact of compromised circle of Willis morphology on inter-hemispheric blood flow indices based on intraoperative internal carotid artery stump pulse pressure and backflow patterns

Carotid artery stenosis (CAS) often requires surgical intervention through carotid endarterectomy (CEA) to prevent stroke. Accurate cerebrovascular risk assessments are crucial in CEA, as poor collateral circulation can lead to insufficient interhemispheric blood flow compensation, resulting in ischemic complications. Therefore, understanding perioperative risk determinants is vital. This study aims to determine the impact of compromised circle of Willis (CoW) morphology on inter-hemispheric blood flow, focusing on indices based on intraoperative internal carotid artery stump pulse pressure and backflow patterns. In 80 CAS patients who underwent CEA, preoperative CT angiography for CoW was conducted. Patients were categorized into five subgroups based on their CoW anatomy and three additional groups based on intraoperative internal carotid artery (ICA) stump backflow patterns evaluated by the surgeon. Continuous blood pressure signals, including systolic, diastolic, mean, and pulse pressure values, were recorded during the procedure. The relationship between CoW anatomical variants and the systolic and diastolic segments of the averaged pressure waveforms, particularly diastolic pressure decay, was analyzed. The correlation between CoW anatomy and stump backflow intensity was also examined. Significant variability in ICA stump backflow and pressure values was evident across CoW variants. Patients with compromised CoW morphology exhibited weaker backflow patterns and lower ICA stump pulse pressure values, consistent with impaired interhemispheric blood flow. Notably, ICA stump diastolic pressure decay was consistent across most CoW variant groups, indicating developed collateral circulation in cases with CoW anomalies. Thus, impaired CoW integrity is associated with compromised interhemispheric blood flow indices based on intraoperative ICA stump pulse pressure and backflow patterns during CEA. Integrating intraoperative pulse waveform analysis with preoperative CT angiography provides a more detailed assessment of cerebrovascular risk, guiding the selective use of shunts. This combined approach may improve surgical outcomes and patient safety by identifying patients at increased risk of perioperative neurological events due to CoW anomalies.

Effect of a reduced arterial axial pre-stretch ratio during aging on the cardiac output and cerebral blood flow in the healthy elders

BACKGROUND AND OBJECTIVE

It is an indisputable physiological phenomenon that the arterial axial pre-stretch ratio (AAPSR) decreases with age, but little attention has been paid to the effect of this reduction on chronic diseases during aging.

METHODS

Here we reported an experimental method to simulate arteries aging, developed a fluid-structure interaction model with the effect of AAPSR changes, and compared it with the anatomy data and structural parameters of the human thoracic aorta.

RESULTS

We showed that with the process of aging, the decrease of AAPSR leads to a decline of arterial elasticity, a decrease of arterial elastic strain energy, which weakens the ability to promote blood circulation, the corresponding decrease in cardiac output (CO) and cerebral blood flow (CBF) causes distal organ and body tissue ischemia, which is one of the main causes of increased blood pressure and decreased cerebral perfusion in the elderly.

CONCLUSIONS

Thus, reduced AAPSR is the one of main manifestation of arteries aging and has an important impact on hypertension and hypoperfusion of the brain in the process of human aging. The research contributes to a better understanding of the physiological and pathological mechanisms of aging-related diseases.

A viscoelastic constitutive framework for aging muscular and elastic arteries

The evolution of arterial biomechanics and microstructure with age and disease plays a critical role in understanding the health and function of the cardiovascular system. Accurately capturing these adaptative processes and their effects on the mechanical environment is critical for predicting arterial responses. This challenge is exacerbated by the significant differences between elastic and muscular arteries, which have different structural organizations and functional demands. In this study, we aim to shed light to these adaptive processes by comparing the viscoelastic mechanics of autologous thoracic aortas (TA) and femoropopliteal arteries (FPA) in different age groups. We have extended our fractional viscoelastic framework, originally developed for FPA, to both types of arteries. To evaluate this framework, we analyzed experimental mechanical data from TA and FPA specimens from 21 individuals aged 13 to 73 years. Each specimen was subjected to a multi-ratio biaxial mechanical extension and relaxation test complemented by bidirectional histology to quantify the structural density and microstructural orientations. Our new constitutive model accurately captured the mechanical responses and microstructural differences of the tissues and closely matched the experimentally measured densities. It was found that the viscoelastic properties of collagen and smooth muscle cells (SMCs) in both the FPA and TA remained consistent with age, but the viscoelasticity of the SMCs in the FPA was twice that of the TA. Additionally, changes in collagen nonlinearity with age were similar in both TA and FPA. This model provides valuable insights into arterial mechanophysiology and the effects of pathological conditions on vascular biomechanics. STATEMENT OF SIGNIFICANCE: Developing durable treatments for arterial diseases necessitates a deeper understanding of how mechanical properties evolve with age in response to mechanical environments. In this work, we developed a generalized viscoelastic constitutive model for both elastic and muscular arteries and analyzed both the thoracic aorta (TA) and the femoropopliteal artery (FPA) from 21 donors aged 13 to 73. The derived parameters correlate well with histology, allowing further examination of how viscoelasticity evolves with age. Correlation between the TA and FPA of the same donors suggest that the viscoelasticity of the FPA may be influenced by the TA, necessitating more detailed analysis. In summary, our new model proves to be a valuable tool for studying arterial mechanophysiology and exploring pathological impacts.

Patient-specific compliant simulation framework informed by 4DMRI-extracted pulse wave Velocity: Application post-TEVAR

We introduce a new computational framework that utilises Pulse Wave Velocity (PWV) extracted directly from 4D flow MRI (4DMRI) to inform patient-specific compliant computational fluid dynamics (CFD) simulations of a Type-B aortic dissection (TBAD), post-thoracic endovascular aortic repair (TEVAR). The thoracic aortic geometry, a 3D inlet velocity profile (IVP) and dynamic outlet boundary conditions are derived from 4DMRI and brachial pressure patient data. A moving boundary method (MBM) is applied to simulate aortic wall displacement. The aortic wall stiffness is estimated through two methods: one relying on area-based distensibility and the other utilising regional pulse wave velocity (RPWV) distensibility, further fine-tuned to align with in vivo values. Predicted pressures and outlet flow rates were within 2.3 % of target values. RPWV-based simulations were more accurate in replicating in vivo hemodynamics than the area-based ones. RPWVs were closely predicted in most regions, except the endograft. Systolic flow reversal ratios (SFRR) were accurately captured, while differences above 60 % in in-plane rotational flow (IRF) between the simulations were observed. Significant disparities in predicted wall shear stress (WSS)-based indices were observed between the two approaches, especially the endothelial cell activation potential (ECAP). At the isthmus, the RPWV-driven simulation indicated a mean ECAP>1.4 Pa-1 (critical threshold), indicating areas potentially prone to thrombosis, not captured by the area-based simulation. RPWV-driven simulation results agree well with 4DMRI measurements, validating the proposed pipeline and facilitating a comprehensive assessment of surgical decision-making scenarios and potential complications, such as thrombosis and aortic growth.

Multiscale structure and function of the aortic valve apparatus

Whereas studying the aortic valve in isolation has facilitated the development of life-saving procedures and technologies, the dynamic interplay of the aortic valve and its surrounding structures is vital to preserving their function across the wide range of conditions encountered in an active lifestyle. Our view is that these structures should be viewed as an integrated functional unit, here referred to as the aortic valve apparatus (AVA). The coupling of the aortic valve and root, left ventricular outflow tract, and blood circulation is crucial for AVA's functions: unidirectional flow out of the left ventricle, coronary perfusion, reservoir function, and support of left ventricular function. In this review, we explore the multiscale biological and physical phenomena that underlie the simultaneous fulfillment of these functions. A brief overview of the tools used to investigate the AVA, such as medical imaging modalities, experimental methods, and computational modeling, specifically fluid-structure interaction (FSI) simulations, is included. Some pathologies affecting the AVA are explored, and insights are provided on treatments and interventions that aim to maintain quality of life. The concepts explained in this article support the idea of AVA being an integrated functional unit and help identify unanswered research questions. Incorporating phenomena through the molecular, micro, meso, and whole tissue scales is crucial for understanding the sophisticated normal functions and diseases of the AVA.

The origin of intraluminal pressure waves in gastrointestinal tract

The gastrointestinal (GI) peristalsis is an involuntary wave-like contraction of the GI wall that helps to propagate food along the tract. Many GI diseases, e.g., gastroparesis, are known to cause motility disorders in which the physiological contractile patterns of the wall get disrupted. Therefore, to understand the pathophysiology of these diseases, it is necessary to understand the mechanism of GI motility. We present a coupled electromechanical model to describe the mechanism of GI motility and the transduction pathway of cellular electrical activities into mechanical deformation and the generation of intraluminal pressure (IP) waves in the GI tract. The proposed model consolidates a smooth muscle cell (SMC) model, an actin-myosin interaction model, a hyperelastic constitutive model, and a Windkessel model to construct a coupled model that can describe the origin of peristaltic contractions in the intestine. The key input to the model is external electrical stimuli, which are converted into mechanical contractile waves in the wall. The model recreated experimental observations efficiently and was able to establish a relationship between change in luminal volume and pressure with the compliance of the GI wall and the peripheral resistance to bolus flow. The proposed model will help us understand the GI tract's function in physiological and pathophysiological conditions.

Modeling the effect of patient size on cerebral perfusion during veno-arterial extracorporeal membrane oxygenation

INTRODUCTION

A well-known complication of veno-arterial extracorporeal membrane oxygenation (VA ECMO) is differential hypoxia, in which poorly-oxygenated blood ejected from the left ventricle mixes with and displaces well-oxygenated blood from the circuit, thereby causing cerebral hypoxia and ischemia. We sought to characterize the impact of patient size and anatomy on cerebral perfusion under a range of different VA ECMO flow conditions.

METHODS

We use one-dimensional (1D) flow simulations to investigate mixing zone location and cerebral perfusion across 10 different levels of VA ECMO support in eight semi-idealized patient geometries, for a total of 80 scenarios. Measured outcomes included mixing zone location and cerebral blood flow (CBF).

RESULTS

Depending on patient anatomy, we found that a VA ECMO support ranging between 67-97% of a patient's ideal cardiac output was needed to perfuse the brain. In some cases, VA ECMO flows exceeding 90% of the patient's ideal cardiac output are needed for adequate cerebral perfusion.

CONCLUSIONS

Individual patient anatomy markedly affects mixing zone location and cerebral perfusion in VA ECMO. Future fluid simulations of VA ECMO physiology should incorporate varied patient sizes and geometries in order to best provide insights toward reducing neurologic injury and improved outcomes in this patient population.

Nonlinear biomechanical behaviour of extracranial carotid artery aneurysms in the framework of Windkessel effect via FSI technique

Extracranial carotid artery aneurysms (ECCA) lead to rupture and neurologic symptoms from embolisation, with potentially fatal outcomes. Investigating the biomechanical behaviour of EECA with blood flow dynamics is crucial for identifying regions more susceptible to rupture. A coupled three-dimensional (3D) Windkessel-framework and hyperelastic fluid-structure interaction (FSI) analysis of ECCAs with patient-specific geometries, was developed in this paper with a particular focus on hemodynamic parameters and the arterial wall's biomechanical response. The blood flow has been modelled as non-Newtonian, pulsatile, and turbulent. The biomechanical characteristics of the aneurysm and artery are characterised employing a 5-parameter Mooney-Rivlin hyperelasticity model. The Windkessel effect is also considered to efficiently simulate pressure profile of the outlets and to capture the dynamic changes over the cardiac cycle. The study found the aneurysm carotid artery exhibited the high levels of pressure, wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT) compared to the healthy one. The deformation of the arterial wall and the corresponding von Mises (VM) stress were found significantly increased in aneurysm cases, in comparison to that of no aneurysm cases, which strongly correlated with the hemodynamic characteristics of the blood flow and the geometric features of the aneurysms. This escalation would intensify the risk of aneurysm wall rupture. These findings have critical implications for enhancing treatment strategies for patients with extracranial aneurysms.

Elective root replacement increases the risk of type B dissection in patients with Marfan syndrome

OBJECTIVE

Marfan syndrome is a genetic disorder with increased risk of aortic dissection. Currently, type A aortic dissection risk is mitigated by aortic root replacement with Dacron. It is unclear if root replacement increases the risk of distal aortic disease given the noncompliant nature of Dacron.

METHODS

All adult patients with a diagnosis of Marfan syndrome at a single academic center, excluding those with history of dissection or concomitant arch repair, were studied (n = 322). Student t test or Wilcoxon Mann-Whitney test was used for continuous variables; chi-square or Fisher exact test was used for categorical variables. Propensity matching used age, sex, hypertension, race, body mass index, family history of Marfan syndrome, and genetic mutational class. Differences in freedom from type B aortic dissection were determined using the log-rank test.

RESULTS

A total of 124 patients underwent root replacement compared with 198 patients with no prior aortic surgery. Median follow-up time was 9.90 years. Male sex, weight, and hypertension prevalence were higher in the root replacement group (P < .05). Distribution of fibrillin-1 mutations was homogenous (P > .9). Type B aortic dissection frequency in the root replacement group was higher (21% [n = 20] vs 4.2% [n = 4], P < .001). Aortic-related mortality was higher in the root replacement group (11% [n = 14] vs 3.5% [n = 7], P < .01). Distal aortic intervention frequency was higher in the root replacement group (P = .009).

CONCLUSIONS

Patients with Marfan syndrome who undergo elective aortic root replacement appear to have a higher incidence of subsequent type B aortic dissection, independent of other risk factors. Careful consideration must be made to the management of the distal aorta in patients with Marfan syndrome who undergo root replacement.

Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins

Understanding the evolving nature of coronary hemodynamics is crucial for early disease detection and monitoring progression. We require digital twins that mimic a patient's circulatory system by integrating continuous physiological data and computing hemodynamic patterns over months. Current models match clinical flow measurements but are limited to single heartbeats. To this end, we introduced the longitudinal hemodynamic mapping framework (LHMF), designed to tackle critical challenges: (1) computational intractability of explicit methods; (2) boundary conditions reflecting varying activity states; and (3) accessible computing resources for clinical translation. We show negligible error (0.0002-0.004%) between LHMF and explicit data of 750 heartbeats. We deployed LHMF across traditional and cloud-based platforms, demonstrating high-throughput simulations on heterogeneous systems. Additionally, we established LHMFC, where hemodynamically similar heartbeats are clustered to avoid redundant simulations, accurately reconstructing longitudinal hemodynamic maps (LHMs). This study captured 3D hemodynamics over 4.5 million heartbeats, paving the way for cardiovascular digital twins.

A review of computational methodologies to predict the fractional flow reserve in coronary arteries with stenosis

Computational methodologies for predicting the fractional flow reserve (FFR) in coronary arteries with stenosis have gained significant attention due to their potential impact on healthcare outcomes. Coronary artery disease is a leading cause of mortality worldwide, prompting the need for accurate diagnostic and treatment approaches. The use of medical image-based anatomical vascular geometries in computational fluid dynamics (CFD) simulations to evaluate the hemodynamics has emerged as a promising tool in the medical field. This comprehensive review aims to explore the state-of-the-art computational methodologies focusing on the possible considerations. Key aspects include the rheology of blood, boundary conditions, fluid-structure interaction (FSI) between blood and the arterial wall, and multiscale modelling (MM) of stenosis. Through an in-depth analysis of the literature, the goal is to obtain an overview of the major achievements regarding non-invasive methods to compute FFR and to identify existing gaps and challenges that inform further advances in the field. This research has the major objective of improving the current diagnostic capabilities and enhancing patient care in the context of cardiovascular diseases.

Fluid-structure interaction analysis of a healthy aortic valve and its surrounding haemodynamics

The opening and closing dynamics of the aortic valve (AV) has a strong influence on haemodynamics in the aortic root, and both play a pivotal role in maintaining normal physiological functions of the valve. The aim of this study was to establish a subject-specific fluid-structure interaction (FSI) workflow capable of simulating the motion of a tricuspid healthy valve and the surrounding haemodynamics under physiologically realistic conditions. A subject-specific aortic root was reconstructed from magnetic resonance (MR) images acquired from a healthy volunteer, whilst the valve leaflets were built using a parametric model fitted to the subject-specific aortic root geometry. The material behaviour of the leaflets was described using the isotropic hyperelastic Ogden model, and subject-specific boundary conditions were derived from 4D-flow MR imaging (4D-MRI). Strongly coupled FSI simulations were performed using a finite volume-based boundary conforming method implemented in FlowVision. Our FSI model was able to simulate the opening and closing of the AV throughout the entire cardiac cycle. Comparisons of simulation results with 4D-MRI showed a good agreement in key haemodynamic parameters, with stroke volume differing by 7.5% and the maximum jet velocity differing by less than 1%. Detailed analysis of wall shear stress (WSS) on the leaflets revealed much higher WSS on the ventricular side than the aortic side and different spatial patterns amongst the three leaflets.

Personalized computational electro-mechanics simulations to optimize cardiac resynchronization therapy

In this study, we present a computational framework designed to evaluate virtual scenarios of cardiac resynchronization therapy (CRT) and compare their effectiveness based on relevant clinical biomarkers. Our approach involves electro-mechanical numerical simulations personalized, for patients with left bundle branch block, by means of a calibration obtained using data from Electro-Anatomical Mapping System (EAMS) measures acquired by cardiologists during the CRT procedure, as well as ventricular pressures and volumes, both obtained pre-implantation. We validate the calibration by using EAMS data coming from right pacing conditions. Three patients with fibrosis and three without are considered to explore various conditions. Our virtual scenarios consist of personalized numerical experiments, incorporating different positions of the left electrode along reconstructed epicardial veins; different locations of the right electrode; different ventriculo-ventricular delays. The aim is to offer a comprehensive tool capable of optimizing CRT efficiency for individual patients. We provide preliminary answers on optimal electrode placement and delay, by computing some relevant biomarkers such as d P / d t max , ejection fraction, stroke work. From our numerical experiments, we found that the latest activated segment during sinus rhythm is an effective choice for the non-fibrotic cases for the location of the left electrode. Also, our results showed that the activation of the right electrode before the left one seems to improve the CRT performance for the non-fibrotic cases. Last, we found that the CRT performance seems to improve by positioning the right electrode halfway between the base and the apex. This work is on the line of computational works for the study of CRT and introduces new features in the field, such as the presence of the epicardial veins and the movement of the right electrode. All these studies from the different research groups can in future synergistically flow together in the development of a tool which clinicians could use during the procedure to have quantitative information about the patient's propagation in different scenarios.

Understanding the physiological transmission mechanisms of photoplethysmography signals: a comprehensive review

Objective. The widespread adoption of Photoplethysmography (PPG) as a non-invasive method for detecting blood volume variations and deriving vital physiological parameters reflecting health status has surged, primarily due to its accessibility, cost-effectiveness, and non-intrusive nature. This has led to extensive research around this technique in both daily life and clinical applications. Interestingly, despite the existence of contradictory explanations of the underlying mechanism of PPG signals across various applications, a systematic investigation into this crucial matter has not been conducted thus far. This gap in understanding hinders the full exploitation of PPG technology and undermines its accuracy and reliability in numerous applications.Approach. Building upon a comprehensive review of the fundamental principles and technological advancements in PPG, this paper initially attributes the origin of PPG signals to a combination of physical and physiological transmission processes. Furthermore, three distinct models outlining the concerned physiological transmission processes are synthesized, with each model undergoing critical examination based on theoretical underpinnings, empirical evidence, and constraints.Significance. The ultimate objective is to form a fundamental framework for a better understanding of physiological transmission processes in PPG signal generation and to facilitate the development of more reliable technologies for detecting physiological signals.

The role of pulse wave analysis indexes for critically ill patients: a narrative review

Objective.Arterial pulse wave analysis (PWA) is now established as a powerful tool to investigate the cardiovascular system, and several clinical studies have shown how PWA can provide valuable prognostic information over and beyond traditional cardiovascular risk factors. Typically these techniques are applied to chronic conditions, such as hypertension or aging, to monitor the slow structural changes of the vascular system which lead to important alterations of the arterial PW. However, their application to acute critical illness is not currently widespread, probably because of the high hemodynamic instability and acute dynamic alterations affecting the cardiovascular system of these patients.Approach.In this work we propose a review of the physiological and methodological basis of PWA, describing how it can be used to provide insights into arterial structure and function, cardiovascular biomechanical properties, and to derive information on wave propagation and reflection.Main results.The applicability of these techniques to acute critical illness, especially septic shock, is extensively discussed, highlighting the feasibility of their use in acute critical patients and their role in optimizing therapy administration and hemodynamic monitoring.Significance.The potential for the clinical use of these techniques lies in the ease of computation and availability of arterial blood pressure signals, as invasive arterial lines are commonly used in these patients. We hope that the concepts illustrated in the present review will soon be translated into clinical practice.

The contribution of granger causality analysis to our understanding of cardiovascular homeostasis: from cardiovascular and respiratory interactions to central autonomic network control

Homeostatic regulation plays a fundamental role in maintenance of multicellular life. At different scales and in different biological systems, this principle allows a better understanding of biological organization. Consequently, a growing interest in studying cause-effect relations between physiological systems has emerged, such as in the fields of cardiovascular and cardiorespiratory regulations. For this, mathematical approaches such as Granger causality (GC) were applied to the field of cardiovascular physiology in the last 20 years, overcoming the limitations of previous approaches and offering new perspectives in understanding cardiac, vascular and respiratory homeostatic interactions. In clinical practice, continuous recording of clinical data of hospitalized patients or by telemetry has opened new applicability for these approaches with potential early diagnostic and prognostic information. In this review, we describe a theoretical background of approaches based on linear GC in time and frequency domains applied to detect couplings between time series of RR intervals, blood pressure and respiration. Interestingly, these tools help in understanding the contribution of homeostatic negative feedback and the anticipatory feedforward mechanisms in homeostatic cardiovascular and cardiorespiratory controls. We also describe experimental and clinical results based on these mathematical tools, consolidating previous experimental and clinical evidence on the coupling in cardiovascular and cardiorespiratory studies. Finally, we propose perspectives allowing to complete the understanding of these interactions between cardiovascular and cardiorespiratory systems, as well as the interplay between brain and cardiac, and vascular and respiratory systems, offering a high integrative view of cardiovascular and cardiorespiratory homeostatic regulation.

Hemodynamic influence of mild stenosis morphology in different coronary arteries: a computational fluid dynamic modelling study

Introduction: Mild stenosis [degree of stenosis (DS) < 50%] is commonly labeled as nonobstructive lesion. Some lesions remain stable for several years, while others precipitate acute coronary syndromes (ACS) rapidly. The causes of ACS and the factors leading to diverse clinical outcomes remain unclear. Method: This study aimed to investigate the hemodynamic influence of mild stenosis morphologies in different coronary arteries. The stenoses were modeled with different morphologies based on a healthy individual data. Computational fluid dynamics analysis was used to obtain hemodynamic characteristics, including flow waveforms, fractional flow reserve (FFR), flow streamlines, time-average wall shear stress (TAWSS), and oscillatory shear index (OSI). Results: Numerical simulation indicated significant hemodynamic differences among different DS and locations. In the 20%-30% range, significant large, low-velocity vortexes resulted in low TAWSS (<4 dyne/cm2) around stenoses. In the 30%-50% range, high flow velocity due to lumen area reduction resulted in high TAWSS (>40 dyne/cm2), rapidly expanding the high TAWSS area (averagely increased by 0.46 cm2) in left main artery and left anterior descending artery (LAD), where high OSI areas remained extensive (>0.19 cm2). Discussion: While mild stenosis does not pose any immediate ischemic risk due to a FFR > 0.95, 20%-50% stenosis requires attention and further subdivision based on location is essential. Rapid progression is a danger for lesions with 20%-30% DS near the stenoses and in the proximal LAD, while lesions with 30%-50% DS can cause plaque injury and rupture. These findings support clinical practice in early assessment, monitoring, and preventive treatment.

Physics-informed neural networks for parameter estimation in blood flow models

BACKGROUND

Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available. This is especially useful in hemodynamics since the boundary information is often difficult to model, and high-quality blood flow measurements are generally hard to obtain.

METHODS

In this work, we use the PINNs methodology for estimating reduced-order model parameters and the full velocity field from scatter 2D noisy measurements in the aorta. Two different flow regimes, stationary and transient were studied.

RESULTS

We show robust and relatively accurate parameter estimations when using the method with simulated data, while the velocity reconstruction accuracy shows dependence on the measurement quality and the flow pattern complexity. Comparison with a Kalman filter approach shows similar results when the number of parameters to be estimated is low to medium. For a higher number of parameters, only PINNs were capable of achieving good results.

CONCLUSION

The method opens a door to deep-learning-driven methods in the simulations of complex coupled physical systems.

Reconstructing blood flow in data-poor regimes: a vasculature network kernel for Gaussian process regression

Blood flow reconstruction in the vasculature is important for many clinical applications. However, in clinical settings, the available data are often quite limited. For instance, transcranial Doppler ultrasound is a non-invasive clinical tool that is commonly used in clinical settings to measure blood velocity waveforms at several locations. This amount of data is grossly insufficient for training machine learning surrogate models, such as deep neural networks or Gaussian process regression. In this work, we propose a Gaussian process regression approach based on empirical kernels constructed by data generated from physics-based simulations-enabling near-real-time reconstruction of blood flow in data-poor regimes. We introduce a novel methodology to reconstruct the kernel within the vascular network. The proposed kernel encodes both spatiotemporal and vessel-to-vessel correlations, thus enabling blood flow reconstruction in vessels that lack direct measurements. We demonstrate that any prediction made with the proposed kernel satisfies the conservation of mass principle. The kernel is constructed by running stochastic one-dimensional blood flow simulations, where the stochasticity captures the epistemic uncertainties, such as lack of knowledge about boundary conditions and uncertainties in vasculature geometries. We demonstrate the performance of the model on three test cases, namely, a simple Y-shaped bifurcation, abdominal aorta and the circle of Willis in the brain.

Guidelines for mechanistic modeling and analysis in cardiovascular research

Computational, or in silico, models are an effective, noninvasive tool for investigating cardiovascular function. These models can be used in the analysis of experimental and clinical data to identify possible mechanisms of (ab)normal cardiovascular physiology. Recent advances in computing power and data management have led to innovative and complex modeling frameworks that simulate cardiovascular function across multiple scales. While commonly used in multiple disciplines, there is a lack of concise guidelines for the implementation of computer models in cardiovascular research. In line with recent calls for more reproducible research, it is imperative that scientists adhere to credible practices when developing and applying computational models to their research. The goal of this manuscript is to provide a consensus document that identifies best practices for in silico computational modeling in cardiovascular research. These guidelines provide the necessary methods for mechanistic model development, model analysis, and formal model calibration using fundamentals from statistics. We outline rigorous practices for computational, mechanistic modeling in cardiovascular research and discuss its synergistic value to experimental and clinical data.

Non-invasive fractional flow reserve estimation in coronary arteries using angiographic images

Coronary artery disease is the leading global cause of mortality and Fractional Flow Reserve (FFR) is widely regarded as the gold standard for assessing coronary artery stenosis severity. However, due to the limitations of invasive FFR measurements, there is a pressing need for a highly accurate virtual FFR calculation framework. Additionally, it's essential to consider local haemodynamic factors such as time-averaged wall shear stress (TAWSS), which play a critical role in advancement of atherosclerosis. This study introduces an innovative FFR computation method that involves creating five patient-specific geometries from two-dimensional coronary angiography images and conducting numerical simulations using computational fluid dynamics with a three-element Windkessel model boundary condition at the outlet to predict haemodynamic distribution. Furthermore, four distinct boundary condition methodologies are applied to each geometry for comprehensive analysis. Several haemodynamic features, including velocity, pressure, TAWSS, and oscillatory shear index are investigated and compared for each case. Results show that models with average boundary conditions can predict FFR values accurately and observed errors between invasive FFR and virtual FFR are found to be less than 5%.

DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model

Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introduce a blood pressure monitoring algorithm based on only photoplethysmography (PPG) signals using the deep neural network (DNN). The PPG signals are obtained from 125 unique subjects with 218 records and filtered using signal processing algorithms to reduce the effects of noise, such as baseline wandering, and motion artifacts. The proposed algorithm is based on pulse wave analysis of PPG signals, extracted various domain features from PPG signals, and mapped them to BP values. Four feature selection methods are applied and yielded four feature subsets. Therefore, an ensemble feature selection technique is proposed to obtain the optimal feature set based on major voting scores from four feature subsets. DNN models, along with the ensemble feature selection technique, outperformed in estimating the systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to previously reported approaches that rely only on the PPG signal. The coefficient of determination ( R 2 ) and mean absolute error (MAE) of the proposed algorithm are 0.962 and 2.480 mmHg, respectively, for SBP and 0.955 and 1.499 mmHg, respectively, for DBP. The proposed approach meets the Advancement of Medical Instrumentation standard for SBP and DBP estimations. Additionally, according to the British Hypertension Society standard, the results attained Grade A for both SBP and DBP estimations. It concludes that BP can be estimated more accurately using the optimal feature set and DNN models. The proposed algorithm has the potential ability to facilitate mobile healthcare devices to monitor continuous BP.

Convergence, sampling and total order estimator effects on parameter orthogonality in global sensitivity analysis

Dynamical system models typically involve numerous input parameters whose "effects" and orthogonality need to be quantified through sensitivity analysis, to identify inputs contributing the greatest uncertainty. Whilst prior art has compared total-order estimators' role in recovering "true" effects, assessing their ability to recover robust parameter orthogonality for use in identifiability metrics has not been investigated. In this paper, we perform: (i) an assessment using a different class of numerical models representing the cardiovascular system, (ii) a wider evaluation of sampling methodologies and their interactions with estimators, (iii) an investigation of the consequences of permuting estimators and sampling methodologies on input parameter orthogonality, (iv) a study of sample convergence through resampling, and (v) an assessment of whether positive outcomes are sustained when model input dimensionality increases. Our results indicate that Jansen or Janon estimators display efficient convergence with minimum uncertainty when coupled with Sobol and the lattice rule sampling methods, making them prime choices for calculating parameter orthogonality and influence. This study reveals that global sensitivity analysis is convergence driven. Unconverged indices are subject to error and therefore the true influence or orthogonality of the input parameters are not recovered. This investigation importantly clarifies the interactions of the estimator and the sampling methodology by reducing the associated ambiguities, defining novel practices for modelling in the life sciences.

Establishing the distribution of cerebrovascular resistance using computational fluid dynamics and 4D flow MRI

Cerebrovascular resistance (CVR) regulates blood flow in the brain, but little is known about the vascular resistances of the individual cerebral territories. We present a method to calculate these resistances and investigate how CVR varies in the hemodynamically disturbed brain. We included 48 patients with stroke/TIA (29 with symptomatic carotid stenosis). By combining flow rate (4D flow MRI) and structural computed tomography angiography (CTA) data with computational fluid dynamics (CFD) we computed the perfusion pressures out from the circle of Willis, with which CVR of the MCA, ACA, and PCA territories was estimated. 56 controls were included for comparison of total CVR (tCVR). CVR were 33.8 ± 10.5, 59.0 ± 30.6, and 77.8 ± 21.3 mmHg s/ml for the MCA, ACA, and PCA territories. We found no differences in tCVR between patients, 9.3 ± 1.9 mmHg s/ml, and controls, 9.3 ± 2.0 mmHg s/ml (p = 0.88), nor in territorial CVR in the carotid stenosis patients between ipsilateral and contralateral hemispheres. Territorial resistance associated inversely to territorial brain volume (p < 0.001). These resistances may work as reference values when modelling blood flow in the circle of Willis, and the method can be used when there is need for subject-specific analysis.

Whole body physiology model to simulate respiratory depression of fentanyl and associated naloxone reversal

BACKGROUND

Opioid use in the United States and abroad is an endemic part of society with yearly increases in overdose rates and deaths. In response, the use of the safe and effective reversal agent, naloxone, is being fielded and used by emergency medical technicians at a greater rate. There is evidence that repeated dosing of a naloxone nasal spray is becoming more common. Despite this we lack repeated dosing guidelines as a function of the amount of opiate the patient has taken.

METHODS

To measure repeat dosing guidelines, we construct a whole-body model of the pharmacokinetics and dynamics of an opiate, fentanyl on respiratory depression. We then construct a model of nasal deposition and administration of naloxone to investigate repeat dosing requirements for large overdose scenarios. We run a single patient through multiple goal directed resuscitation protocols and measure total naloxone administered.

RESULTS

Here we show that naloxone is highly effective at reversing the respiratory symptoms of the patient and recommend dosing requirements as a function of the fentanyl amount administered. We show that for increasing doses of fentanyl, naloxone requirements also increase. The rescue dose displays a nonlinear response to the initial opioid dose. This nonlinear response is largely logistic with three distinct phases: onset, rapid acceleration, and a plateau period for doses above 1.2 mg.

CONCLUSIONS

This paper investigates the total naloxone dose needed to properly reverse respiratory depression associated with fentanyl overdose. We show that the current guidelines for a rescue dose may be much lower than required.

Patient-Specific Haemodynamic Analysis of Virtual Grafting Strategies in Type-B Aortic Dissection: Impact of Compliance Mismatch

INTRODUCTION

Compliance mismatch between the aortic wall and Dacron Grafts is a clinical problem concerning aortic haemodynamics and morphological degeneration. The aortic stiffness introduced by grafts can lead to an increased left ventricular (LV) afterload. This study quantifies the impact of compliance mismatch by virtually testing different Type-B aortic dissection (TBAD) surgical grafting strategies in patient-specific, compliant computational fluid dynamics (CFD) simulations.

MATERIALS AND METHODS

A post-operative case of TBAD was segmented from computed tomography angiography data. Three virtual surgeries were generated using different grafts; two additional cases with compliant grafts were assessed. Compliant CFD simulations were performed using a patient-specific inlet flow rate and three-element Windkessel outlet boundary conditions informed by 2D-Flow MRI data. The wall compliance was calibrated using Cine-MRI images. Pressure, wall shear stress (WSS) indices and energy loss (EL) were computed.

RESULTS

Increased aortic stiffness and longer grafts increased aortic pressure and EL. Implementing a compliant graft matching the aortic compliance of the patient reduced the pulse pressure by 11% and EL by 4%. The endothelial cell activation potential (ECAP) differed the most within the aneurysm, where the maximum percentage difference between the reference case and the mid (MDA) and complete (CDA) descending aorta replacements increased by 16% and 20%, respectively.

CONCLUSION

This study suggests that by minimising graft length and matching its compliance to the native aorta whilst aligning with surgical requirements, the risk of LV hypertrophy may be reduced. This provides evidence that compliance-matching grafts may enhance patient outcomes.

Hemodynamics of ventricular-arterial coupling under enhanced external counterpulsation: An optimized dual-source lumped parameter model

BACKGROUND AND OBJECTIVE

Enhanced external counterpulsation (EECP) is a mechanically assisted circulation technique widely used in the rehabilitation and management of ischemic cardiovascular diseases. It contributes to cardiovascular functions by regulating the afterload of ventricle to improve hemodynamic effects, including increased diastolic blood pressure at aortic root, increased cardiac output and enhanced blood perfusion to multiple organs including coronary circulation. However, the effects of EECP on the coupling of the ventricle and the arterial system, termed ventricular-arterial coupling (VAC), remain elusive. We aimed to investigate the acute effect of EECP on the dynamic interaction between the left ventricle and its afterload of the arterial system from the perspective of ventricular output work.

METHODS

A neural network assisted optimization algorithm was proposed to identify the ordinary differential equation (ODE) relation between aortic root blood pressure and flow rate. Based on the optimized order of ODE, a lumped parameter model (LPM) under EECP was developed taking into consideration of the simultaneous action of cardiac and EECP pressure sources. The ventricular output work, in terms of aortic pressure and flow rate cooperated with the LPM, was used to characterize the VAC of ventricle and its afterload. The VAC subjected to the principle of minimal ventricular output work was validated by solving the Euler-Poisson equation of cost function, ultimately determining the waveforms of aortic pressure and flow rate.

RESULTS

A third-order ODE can precisely describe the hemodynamic relationship between aortic pressure and flow rate. An optimized dual-source LPM with three energy-storage elements has been constructed, showing the potential in probing VAC under EECP. The LPM simulation results demonstrated that the VAC in terms of aortic pressure and flow rate yielded to the minimal ventricular output work under different EECP pressures.

CONCLUSIONS

The ventricular-arterial coupling under EECP is subjected to the minimal ventricular output work, which can serve as a criterion for determining aortic pressure and flow rate. This study provides insight for the understanding of VAC and has the potential in characterizing the performance of the ventricular and arterial system under EECP.

Cell-Driven Fluid Dynamics: A Physical Model of Active Systemic Circulation

Active fluid circulation and transport are key functions of living organisms, which drive efficient delivery of oxygen and nutrients to various physiological compartments. Because fluid circulation occurs in a network, the systemic flux and pressure are not simple outcomes of any given component. Rather, they are emergent properties of network elements and network topology. Moreover, consistent pressure and osmolarity gradients across compartments such as the kidney, interstitium, and vessels are known. How these gradients and network properties are established and maintained is an unanswered question in systems physiology. Previous studies have shown that epithelial cells are fluid pumps that actively generate pressure and osmolarity gradients. Polarization and activity of ion exchangers that drive fluid flux in epithelial cells are affected by pressure and osmolarity gradients. Therefore, there is an unexplored coupling between the pressure and osmolarity in the circulating network. Here we develop a mathematical theory that integrates the influence of pressure and osmolarity on solute transport and explores both cell fluid transport and systemic circulation. This model naturally generates pressure and osmolarity gradients across physiological compartments, and demonstrates how systemic transport properties can depend on cell properties, and how the cell state can depend on systemic properties. When epithelial and endothelial pumps are considered together, we predict how pressures at various points in the network depend on the overall osmolarity of the system. The model can be improved by including physiological geometries and expanding solute species, and highlights the interplay of fluid properties with cell function in living organisms.

A lumped parameter model for evaluating coronary artery blood supply capacity

The coronary artery constitutes a vital vascular system that sustains cardiac function, with its primary role being the conveyance of indispensable nutrients to the myocardial tissue. When coronary artery disease occurs, it will affect the blood supply of the heart and induce myocardial ischemia. Therefore, it is of great significance to numerically simulate the coronary artery and evaluate its blood supply capacity. In this article, the coronary artery lumped parameter model was derived based on the relationship between circuit system parameters and cardiovascular system parameters, and the blood supply capacity of the coronary artery in healthy and stenosis states was studied. The aortic root pressure calculated by the aortic valve fluid-structure interaction (AV FSI) simulator was employed as the inlet boundary condition. To emulate the physiological phenomenon of sudden pressure drops resulting from an abrupt reduction in blood vessel radius, a head loss model was connected at the coronary artery's entrance. For each coronary artery outlet, the symmetric structured tree model was appended to simulate the terminal impedance of the missing downstream coronary arteries. The particle swarm optimization (PSO) algorithm was used to optimize the blood flow viscous resistance, blood flow inertia, and vascular compliance of the coronary artery model. In the stenosis states, the relative flow and fractional flow reserve (FFR) calculated by numerical simulation corresponded to the published literature data. It was anticipated that the proposed model can be readily adapted for clinical application, serving as a valuable reference for diagnosing and treating patients.

The interactive effect of intra-beat and inter-beat blood pressure variability on neurodegeneration in older adults

Blood pressure variability (BPV) and arterial stiffness are age-related hemodynamic risk factors for neurodegenerative disease, but it remains unclear whether they exert independent or interactive effects on brain health. When combined with high inter-beat BPV, increased intra-beat BPV indicative of arterial stiffness could convey greater pressure wave fluctuations deeper into the cerebrovasculature, exacerbating neurodegeneration. This interactive effect was studied in older adults using multiple markers of neurodegeneration, including medial temporal lobe (MTL) volume, plasma neurofilament light (NfL) and glial fibrillary acidic protein (GFAP). Older adults (N=105) without major neurological or systemic disease were recruited and underwent brain MRI and continuous BP monitoring to quantify inter-beat BPV through systolic average real variability (ARV) and intra-beat variability through arterial stiffness index (ASI). Plasma NfL and GFAP were assessed. The interactive effect of ARV and ASI on MTL atrophy, plasma NfL, and GFAP was studied using hierarchical linear regression. Voxel-based morphometry (VBM) was used to confirm region-of-interest analysis findings. The interaction between higher ARV and higher ASI was significantly associated with left-sided MTL atrophy in both the region-of-interest and false discovery rate-corrected VBM analysis. The interactive effect was also significantly associated with increased plasma NfL, but not GFAP. The interaction between higher ARV and higher ASI is independently associated with increased neurodegenerative markers, including MTL atrophy and plasma NfL, in independently living older adults. Findings could suggest the increased risk for neurodegeneration associated with higher inter-beat BPV may be compounded by increased intra-beat variability due to arterial stiffness.

Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements

Blood pressure gradient ( Δ P ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. Δ P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. The 0D simulations were extremely efficient ( ∼ 15 s computation time) compared to 3D simulations ( ∼ 30 h computation time on a cluster). However, the 0D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Numerical study of hemodynamic flow in the aortic vessel of Williams syndrome patient with congenital heart disease

Congenital arterial stenosis such as supravalvar aortic stenosis (SVAS) are highly prevalent in Williams syndrome (WS) and other arteriopathies pose a substantial health risk. Conventional tools for severity assessment, including clinical findings and pressure gradient estimations, often fall short due to their susceptibility to transient physiological changes and disease stage influences. Moreover, in the pediatric population, the severity of these and other congenital heart defects (CHDs) often restricts the applicability of invasive techniques for obtaining crucial physiological data. Conversely, evaluating CHDs and their progression requires a comprehensive understanding of intracardiac blood flow. Current imaging modalities, such as blood speckle imaging (BSI) and four-dimensional magnetic resonance imaging (4D MRI) face limitations in resolving flow data, especially in cases of elevated flow velocities. To address these challenges, we devised a computational framework employing zero-dimensional (0D) lumped parameter models coupled with patient-specific reconstructed geometries pre- and post-surgical intervention to execute computational fluid dynamic (CFD) simulations. This framework facilitates the analysis and visualization of intricate blood flow patterns, offering insights into geometry and flow dynamics alterations impacting cardiac function. In this study, we aim to assess the efficacy of surgical intervention in correcting an extreme aortic defect in a patient with WS, leading to reductions in wall shear stress (WSS), maximum velocity magnitude, pressure drop, and ultimately a decrease in cardiac workload.

Patient-specific non-invasive estimation of the aortic blood pressure waveform by ultrasound and tonometry

BACKGROUND AND OBJECTIVE

Aortic blood pressure (ABP) is a more effective prognostic indicator of cardiovascular disease than peripheral blood pressure. A highly accurate algorithm for non-invasively deriving the ABP wave, based on ultrasonic measurement of aortic flow combined with peripheral pulse wave measurements, has been proposed elsewhere. However, it has remained at the proof-of-concept stage because it requires a priori knowledge of the ABP waveform to calculate aortic pulse wave velocity (PWV). The objective of this study is to transform this proof-of-concept algorithm into a clinically feasible technique.

METHODS

We used the Bramwell-Hill equation to non-invasively calculate aortic PWV which was then used to reconstruct the ABP waveform from non-invasively determined aortic blood flow velocity, aortic diameter, and radial pressure. The two aortic variables were acquired by an ultrasound system from 90 subjects, followed by recordings of radial pressure using a SphygmoCor device. The ABPs estimated by the new algorithm were compared with reference values obtained by cardiac catheterization (invasive validation, 8 subjects aged 62.3 ± 12.7 years) and a SphygmoCor device (non-invasive validation, 82 subjects aged 45.0 ± 17.8 years).

RESULTS

In the invasive comparison, there was good agreement between the estimated and directly measured pressures: the mean error in systolic blood pressure (SBP) was 1.4 ± 0.8 mmHg; diastolic blood pressure (DBP), 0.9 ± 0.8 mmHg; mean blood pressure (MBP), 1.8 ± 1.2 mmHg and pulse pressure (PP), 1.4 ± 1.1 mmHg. In the non-invasive comparison, the estimated and directly measured pressures also agreed well: the errors being: SBP, 2.0 ± 1.4 mmHg; DBP, 0.8 ± 0.1 mmHg; MBP, 0.1 ± 0.1 mmHg and PP, 2.3 ± 1.6 mmHg. The significance of the differences in mean errors between calculated and reference values for SBP, DBP, MBP and PP were assessed by paired t-tests. The agreement between the reference methods and those obtained by applying the new approach was also expressed by correlation and Bland-Altman plots.

CONCLUSION

The new method proposed here can accurately estimate ABP, allowing this important variable to be obtained non-invasively, using standard, well validated measurement techniques. It thus has the potential to relocate ABP estimation from a research environment to more routine use in the cardiac clinic.

SHORT ABSTRACT

A highly accurate algorithm for non-invasively deriving the ABP wave has been proposed elsewhere. However, it has remained at the proof-of-concept stage because it requires a priori knowledge of the ABP waveform to calculate aortic pulse wave velocity (PWV). This study aims to transform this proof-of-concept algorithm into a clinically feasible technique. We used the Bramwell-Hill equation to non-invasively calculate aortic PWV which was then used to reconstruct the ABP waveform. The ABPs estimated by the new algorithm were compared with reference values obtained by cardiac catheterization or a SphygmoCor device. The results showed that there was good agreement between the estimated and directly measured pressures. The new method proposed can accurately estimate ABP, allowing this important variable to be obtained non-invasively, using standard, well validated measurement techniques. It thus has the potential to relocate ABP estimation from a research environment to more routine use in the cardiac clinic.

Aortic Cellular Heterogeneity in Health and Disease: Novel Insights Into Aortic Diseases From Single-Cell RNA Transcriptomic Data Sets

Aortic diseases such as atherosclerosis, aortic aneurysms, and aortic stiffening are significant complications that can have significant impact on end-stage cardiovascular disease. With limited pharmacological therapeutic strategies that target the structural changes in the aorta, surgical intervention remains the only option for some patients with these diseases. Although there have been significant contributions to our understanding of the cellular architecture of the diseased aorta, particularly in the context of atherosclerosis, furthering our insight into the cellular drivers of disease is required. The major cell types of the aorta are well defined; however, the advent of single-cell RNA sequencing provides unrivaled insights into the cellular heterogeneity of each aortic cell type and the inferred biological processes associated with each cell in health and disease. This review discusses previous concepts that have now been enhanced with recent advances made by single-cell RNA sequencing with a focus on aortic cellular heterogeneity.

Review of Systemic Mock Circulation Loops for Evaluation of Implantable Cardiovascular Devices and Biological Tissues

CLINICAL IMPACT

On needs-based ex vivo monitoring of implantable devices or tissues/organs in cardiovascular simulators provides new insights and paves new paths for device prototypes. The insights gained could not only support the needs of patients, but also inform engineers, scientists and clinicians about undiscovered aspects of diseases (during routine monitoring). We analyze seminal and current work and highlight a variety of opportunities for developing preclinical tools that would improve strategies for future implantable devices. Holistically, mock circulation loop studies can bridge the gap between in vivo and in vitro approaches, as well as clinical and laboratory settings, in a mutually beneficial manner.

Hemodynamic simulation of complete transposition of the great arteries for optimal treatment strategies based on its circulatory physiology

Our study aimed to elucidate the role of different shunts and provide novel insights into optimal treatment approaches for complete transposition of the great arteries (TGA), which is characterized by unique and complicated circulatory dynamics. We constructed a computational cardiovascular TGA model and manipulated cardiovascular parameters, such as atrial septal defect (ASD) and patent ductus arteriosus (PDA) sizes, to quantify their effects on oxygenation and hemodynamics. In addition, ASD flow patterns were investigated as innovative indications for balloon atrial septostomy (BAS). Our model of TGA with an intact ventricular septum (TGA-IVS) showed that a large ASD can achieve sufficient mixing for survival without PDA, and the presence of PDA is detrimental to oxygen delivery. A treatment strategy for TGA-IVS that enlarges the ASD as much as possible by BAS and PDA closure would be desirable. In TGA with a ventricular septal defect (TGA-VSD), the VSD allows for higher oxygenation and reduces the detrimental effects of PDA on systemic circulation. In TGA-VSD, both strategies of enlarging the ASD by BAS with a closed PDA and adjusting the PDA in response to pulmonary vascular resistance (PVR) reduction without BAS may be effective. The simulated ASD flow patterns showed that the sharp peak left-to-right flow pattern in systole (σ-wave) reflected the hemodynamically significant ASD size, independent of PDA, VSD, and PVR. The ASD flow pattern visualized by Doppler echocardiography provides clinical insights into the significance of an ASD and indications for BAS, which are not readily apparent through morphological assessment.NEW & NOTEWORTHY Complete transposition of the great arteries (TGA) represents complex and unique circulation that is dependent on blood mixing through multiple interacting shunts. Consequently, the role of each shunt and the treatment strategy remain unclear. We developed a mathematical model of TGA circulation, revealing the significant influence of atrial septal defect (ASD) on oxygenation and hemodynamics. The blood flow pattern through the ASD reflects its hemodynamic impact and helps determine treatment strategies.

A 3D scaling law for supravalvular aortic stenosis suited for stethoscopic auscultations

In this study a frequency scaling law for 3D anatomically representative supravalvular aortic stenosis (SVAS) cases is proposed. The law is uncovered for stethoscopy's preferred auscultation range (70-120 Hz). LES simulations are performed on the CFD solver Fluent, leveraging Simulia's Living Heart Human Model (LHHM), modified to feature hourglass stenoses that range between 30 to 80 percent (mild to severe) in addition to the descending aorta. For physiological hemodynamic boundary conditions the Windkessel model is implemented via a UDF subroutine. The flow-generated acoustic signal is then extracted using the FW-H model and analyzed using FFT. A preferred receiver location that matches clinical practice is confirmed (right intercostal space) and a correlation between the degree of stenosis and a corresponding acoustic frequency is obtained. Five clinical auscultation signals are tested against the scaling law, with the findings interpreted in relation to the NHS classification of stenosis and to the assessments of experienced cardiologists. The scaling law is thus shown to succeed as a potential quantitative decision-support tool for clinicians, enabling them to reliably interpret stethoscopic auscultations for all degrees of stenosis, which is especially useful for moderate degrees of SVAS. Computational investigation of more complex stenotic cases would enhance the clinical relevance of this proposed scaling law, and will be explored in future research.

Modeling and evaluation of biomechanics and hemodynamic based on patient-specific small intracranial aneurysm using fluid-structure interaction

BACKGROUND AND OBJECTIVE

Rupture of small intracranial aneurysm (IA) often leads to the development of highly fatal clinical syndromes such as subarachnoid hemorrhage. Due to the patient specificity of small IA, there are many difficulties in evaluating the rupture risk of small IA such as multiple influencing factors, high clinical experience requirements and poor reusability.

METHODS

In this study, clinical methods such as transcranial doppler (TCD) and magnetic resonance imaging (MRI) are used to obtain patient-specific parameters, and the fluid-structure interaction method (FSI) is used to model and evaluate the biomechanics and hemodynamics of patient-specific small IA.

RESULTS

The results show that a spiral vortex stably exists in the patient-specific small IA. Due to the small size of the patient-specific small IA, the blood flow velocity still maintains a high value with maximum reaching 3 m/s. The inertial impact of blood flow and vortex convection have certain influence on hemodynamic and biomechanics parameters. They cause three high value areas of WSSM on the patient-specific small IA with maximum of 180 Pa, 130 Pa and 110 Pa, respectively. They also cause two types of WSS concentration points, positive normal stress peak value areas and negative normal stress peak value areas to appear.

CONCLUSION

This paper found that the factors affecting hemodynamic parameters and biomechanical parameters are different. Unlike hemodynamic parameters, biomechanical parameters are also affected by blood pressure in addition to blood flow velocity. This study reveals the relationship between the flow field distribution and changes of patient-specific small IA, biomechanics and hemodynamics.

Towards the personalization of septic shock resuscitation: the fundamentals of ANDROMEDA-SHOCK-2 trial

Septic shock is a highly lethal and prevalent disease. Progressive circulatory dysfunction leads to tissue hypoperfusion and hypoxia, eventually evolving to multiorgan dysfunction and death. Prompt resuscitation may revert these pathogenic mechanisms, restoring oxygen delivery and organ function. High heterogeneity exists among the determinants of circulatory dysfunction in septic shock, and current algorithms provide a stepwise and standardized approach to conduct resuscitation. This review provides the pathophysiological and clinical rationale behind ANDROMEDA-SHOCK-2, an ongoing multicenter randomized controlled trial that aims to compare a personalized resuscitation strategy based on clinical phenotyping and peripheral perfusion assessment, versus standard of care, in early septic shock resuscitation.

Learning reduced-order models for cardiovascular simulations with graph neural networks

Reduced-order models based on physics are a popular choice in cardiovascular modeling due to their efficiency, but they may experience loss in accuracy when working with anatomies that contain numerous junctions or pathological conditions. We develop one-dimensional reduced-order models that simulate blood flow dynamics using a graph neural network trained on three-dimensional hemodynamic simulation data. Given the initial condition of the system, the network iteratively predicts the pressure and flow rate at the vessel centerline nodes. Our numerical results demonstrate the accuracy and generalizability of our method in physiological geometries comprising a variety of anatomies and boundary conditions. Our findings demonstrate that our approach can achieve errors below 3% for pressure and flow rate, provided there is adequate training data. As a result, our method exhibits superior performance compared to physics-based one-dimensional models while maintaining high efficiency at inference time.

Modelling coronary flow and myocardial perfusion by integrating a structured-tree coronary flow model and a hyperelastic left ventricle model

BACKGROUND AND OBJECTIVE

There is an increasing demand to establish integrated computational models that facilitate the exploration of coronary circulation in physiological and pathological contexts, particularly concerning interactions between coronary flow dynamics and myocardial motion. The field of cardiology has also demonstrated a trend toward personalised medicine, where these integrated models can be instrumental in integrating patient-specific data to improve therapeutic outcomes. Notably, incorporating a structured-tree model into such integrated models is currently absent in the literature, which presents a promising prospect. Thus, the goal here is to develop a novel computational framework that combines a 1D structured-tree model of coronary flow in human coronary vasculature with a 3D left ventricle model utilising a hyperelastic constitutive law, enabling the physiologically accurate simulation of coronary flow dynamics.

METHODS

We adopted detailed geometric information from previous studies of both coronary vasculature and left ventricle to construct the coronary flow model and the left ventricle model. The structured-tree model for coronary flow was expanded to encompass the effect of time-varying intramyocardial pressure on intramyocardial blood vessels. Simultaneously, the left ventricle model served as a robust foundation for the calculation of intramyocardial pressure and subsequent quantitative evaluation of myocardial perfusion. A one-way coupling framework between the two models was established to enable the evaluation and examination of coronary flow dynamics and myocardial perfusion.

RESULTS

Our predicted coronary flow waveforms aligned well with published experimental data. Our model precisely captured the phasic pattern of coronary flow, including impeded or even reversed flow during systole. Moreover, our assessment of coronary flow, considering both globally and regionally averaged intramyocardial pressure, demonstrated that elevated intramyocardial pressure corresponds to increased impeding effects on coronary flow. Furthermore, myocardial blood flow simulated from our model was comparable with MRI perfusion data at rest, showcasing the capability of our model to predict myocardial perfusion.

CONCLUSIONS

The integrated model introduced in this study presents a novel approach to achieving physiologically accurate simulations of coronary flow and myocardial perfusion. It holds promise for its clinical applicability in diagnosing insufficient myocardial perfusion.

A multi-dimensional CFD framework for fast patient-specific fractional flow reserve prediction

Fractional flow reserve (FFR) is considered as the gold standard for diagnosing coronary myocardial ischemia. Existing 3D computational fluid dynamics (CFD) methods attempt to predict FFR noninvasively using coronary computed tomography angiography (CTA). However, the accuracy and efficiency of the 3D CFD methods in coronary arteries are considerably limited. In this work, we introduce a multi-dimensional CFD framework that improves the accuracy of FFR prediction by estimating 0D patient-specific boundary conditions, and increases the efficiency by generating 3D initial conditions. The multi-dimensional CFD models contain the 3D vascular model for coronary simulation, the 1D vascular model for iterative optimization, and the 0D vascular model for boundary conditions expression. To improve the accuracy, we utilize clinical parameters to derive 0D patient-specific boundary conditions with an optimization algorithm. To improve the efficiency, we evaluate the convergence state using the 1D vascular model and obtain the convergence parameters to generate appropriate 3D initial conditions. The 0D patient-specific boundary conditions and the 3D initial conditions are used to predict FFR (FFRC). We conducted a retrospective study involving 40 patients (61 diseased vessels) with invasive FFR and their corresponding CTA images. The results demonstrate that the FFRC and the invasive FFR have a strong linear correlation (r = 0.80, p < 0.001) and high consistency (mean difference: 0.014 ±0.071). After applying the cut-off value of FFR (0.8), the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of FFRC were 88.5%, 93.3%, 83.9%, 84.8%, and 92.9%, respectively. Compared with the conventional zero initial conditions method, our method improves prediction efficiency by 71.3% per case. Therefore, our multi-dimensional CFD framework is capable of improving the accuracy and efficiency of FFR prediction significantly.

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as those based on the finite element method, provide valuable information on the cardiac mechanical function, accurate numerical results can be obtained at the price of very fine spatio-temporal discretizations. As a matter of fact, simulating even just a few heartbeats can require up to hours of wall time on high-performance computing architectures. In addition, cardiac models usually depend on a set of input parameters that are calibrated in order to explore multiple virtual scenarios. To compute reliable solutions at a greatly reduced computational cost, we rely on a reduced basis method empowered with a new deep learning-based operator approximation, which we refer to as Deep-HyROMnet technique. Our strategy combines a projection-based POD-Galerkin method with deep neural networks for the approximation of (reduced) nonlinear operators, overcoming the typical computational bottleneck associated with standard hyper-reduction techniques employed in reduced-order models (ROMs) for nonlinear parametrized systems. This method can provide extremely accurate approximations to parametrized cardiac mechanics problems, such as in the case of the complete cardiac cycle in a patient-specific left ventricle geometry. In this respect, a 3D model for tissue mechanics is coupled with a 0D model for external blood circulation; active force generation is provided through an adjustable parameter-dependent surrogate model as input to the tissue 3D model. The proposed strategy is shown to outperform classical projection-based ROMs, in terms of orders of magnitude of computational speed-up, and to return accurate pressure-volume loops in both physiological and pathological cases. Finally, an application to a forward uncertainty quantification analysis, unaffordable if relying on a FOM, is considered, involving output quantities of interest such as, for example, the ejection fraction or the maximal rate of change in pressure in the left ventricle.

Exercise and pulsatile pulmonary vascular loading in chronic thromboembolic pulmonary disease

Chronic thromboembolic pulmonary disease (CTEPD) is characterized by organized nonresolving thrombi in pulmonary arteries (PA). In CTEPD with pulmonary hypertension (PH), chronic thromboembolic PH (CTEPH), early wave reflection results in abnormalities of pulsatile afterload and augmented PA pressures. We hypothesized that exercise during right heart catheterization (RHC) would elicit more frequent elevations of pulsatile vascular afterload than resistive elevations in patients with CTEPD without PH. The interdependent physiology of pulmonary venous and PA hemodynamics was also evaluated. Consecutive patients with CTEPD without PH (resting mean PA pressure ≤20 mmHg) undergoing an exercise RHC were identified. Latent resistive and pulsatile abnormalities of pulmonary vascular afterload were defined as an exercise mean PA pressure/cardiac output >3 WU, and PA pulse pressure to PA wedge pressure (PA PP/PAWP) ratio >2.5, respectively. Forty-five patients (29% female, 53 ± 14 years) with CTEPD without PH were analyzed. With exercise, 19 patients had no abnormalities (ExNOR), 26 patients had abnormalities (ExABN) of pulsatile (20), resistive (2), or both (4) elements of pulmonary vascular afterload. Exercise elicited elevations of pulsatile afterload (53%) more commonly than resistive afterload (13%) (p < 0.001). ExABN patients had lower PA compliance and higher pulmonary vascular resistance at rest and exercise and prolonged resistance-compliance time product at rest. The physiological relationship between changes in PA pressures relative to PAWP was disrupted in the ExABN group. In CTEPD without PH, exercise RHC revealed latent pulmonary vascular afterload elevations in 58% of patients with more frequent augmentation of pulsatile than resistive pulmonary vascular afterload.

Ex Vivo Working Porcine Heart Model

Ex vivo working porcine heart models allow for the study of a heart's function and physiology outside the living organism. These models are particularly useful due to the anatomical and physiological similarities between porcine and human hearts, providing an experimental platform to investigate cardiac disease or assess donor heart viability for transplantation. This chapter presents an in-depth discussion of the model's components, including the perfusate, preload, and afterload. We explore the challenges of emulating cardiac afterload and present a historical perspective on afterload modeling, discussing various methodologies and their respective limitations. An actively controlled afterload device is introduced to enhance the model's ability to rapidly adjust pressure in the large arteries, thereby providing a more accurate and dynamic experimental model. Finally, we provide a comprehensive experimental protocol for the ex vivo working porcine heart model.

Aortic arch shape after arch repair predicts exercise capacity: a multicentre analysis

Aims

Coarctation of the aorta is associated with long-term morbidity including decreased exercise capacity, despite successful repair. In the absence of discrete recoarctation, the haemodynamic mechanism remains unknown. This multicentre study evaluated the relationship between aorta shape, flow, and exercise capacity in patients after arch repair, specifically through the lens of aortic size mismatch and descending aortic (DAo) flow and their association with exercise.

Methods and results

Cardiac magnetic resonance, cardiopulmonary exercise test, and echocardiogram data within 1 year were analysed from 58 patients (age 28 ± 10 years, 48% male) across four centres with history of isolated arch repair. Aortic arch measurements were correlated with % predicted VO2max with subgroup analyses of those with residual arch obstruction, bicuspid aortic valve, and hypertension. Ascending aorta (AAo) to DAo diameter ratio (DAAo/DDAo) was negatively correlated with % predicted VO2max. %DAo flow positively correlated with VO2max. Sub-analyses demonstrated that the negative correlation of DAAo/DDAo with VO2max was maintained only in patients without arch obstruction and with a bicuspid aortic valve. Smaller aortic arch measurements were associated with both hypertension and exercise-induced hypertension.

Conclusion

Aorta size mismatch, due to AAo dilation or small DAo, and associated decreased %DAo flow, correlated significantly with decreased exercise capacity after aortic arch repair. These correlations were stronger in patients without arch obstruction and with a bicuspid aortic valve. Aorta size mismatch and %DAo flow capture multiple mechanisms of altered haemodynamics beyond blood pressure gradient or discrete obstruction and can inform the definition of a successful repair.

The heart, a secondary organ in the control of blood circulation

Circulation of the blood is a fundamental physiological function traditionally ascribed to the pressure-generating function of the heart. However, over the past century the 'cardiocentric' view has been challenged by August Krogh, Ernst Starling, Arthur Guyton and others, based on haemodynamic data obtained from isolated heart preparations and organ perfusion. Their research brought forth experimental evidence and phenomenological observations supporting the concept that cardiac output occurs primarily in response to the metabolic demands of the tissues. The basic tenets of Guyton's venous return model are presented and juxtaposed with their critiques. Developmental biology of the cardiovascular system shows that the blood circulates before the heart has achieved functional integrity and that its movement is intricately connected with the metabolic demands of the tissues. Long discovered, but as yet overlooked, negative interstitial pressure may play a role in assisting the flow returning to the heart. Based on these phenomena, an alternative circulation model has been proposed in which the heart functions like a hydraulic ram and maintains a dynamic equilibrium between the arterial (centrifugal) and venous (centripetal) forces which define the blood's circular movement. In this focused review we introduce some of the salient arguments in support of the proposed circulation model. Finally, we present evidence that exercising muscle blood flow is subject to local metabolic control which upholds optimal perfusion in the face of a substantive rise in muscle vascular conductance, thus lending further support to the permissive role of the heart in the overall control of blood circulation.

Differential sensitivities to blood pressure variations in internal carotid and intracranial arteries: a numerical approach to stroke prediction

Stroke remains a global health concern, necessitating early prediction for effective management. Atherosclerosis-induced internal carotid and intra cranial stenosis contributes significantly to stroke risk. This study explores the relationship between blood pressure and stroke prediction, focusing on internal carotid artery (ICA) branches: middle cerebral artery (MCA), anterior cerebral artery (ACA), and their role in hemodynamics. Computational fluid dynamics (CFD) informed by the Windkessel model were employed to simulate patient-specific ICA models with introduced stenosis. Central to our investigation is the impact of stenosis on blood pressure, flow velocity, and flow rate across these branches, incorporating Fractional Flow Reserve (FFR) analysis. Results highlight differential sensitivities to blood pressure variations, with M1 branch showing high sensitivity, ACA moderate, and M2 minimal. Comparing blood pressure fluctuations between ICA and MCA revealed heightened sensitivity to potential reverse flow compared to ICA and ACA comparisons, emphasizing MCA's role. Blood flow adjustments due to stenosis demonstrated intricate compensatory mechanisms. FFR emerged as a robust predictor of stenosis severity, particularly in the M2 branch. In conclusion, this study provides comprehensive insights into hemodynamic complexities within major intracranial arteries, elucidating the significance of blood pressure variations, flow attributes, and FFR in stenosis contexts. Subject-specific data integration enhances model reliability, aiding stroke risk assessment and advancing cerebrovascular disease understanding.

Fractional-Order Modeling of Arterial Compliance in Vascular Aging: A Computational Biomechanical Approach for Investigating Cardiovascular Dynamics

Goal: The goal of this study is to investigate the application of fractional-order calculus in modeling arterial compliance in human vascular aging. Methods: A novel fractional-order modified arterial Windkessel model that incorporates a fractional-order capacitor (FOC) element is proposed to capture the complex and frequency-dependent properties of arterial compliance. The model's performance is evaluated by verifying it using data collected from three different human subjects, with a specific focus on aortic pressure and flow rates. Results: The results show that the FOC model accurately captures the dynamics of arterial compliance, providing a flexible means to estimate central blood pressure distribution and arterial stiffness. Conclusions: This study demonstrates the potential of fractional-order calculus in advancing the modeling and characterization of arterial compliance in human vascular aging. The proposed FOC model can improve our understanding of the physiological changes in arterial compliance associated with aging and help to identify potential interventions for age-related cardiovascular diseases.

Cerebral microcirculatory pulse wave propagation and pulse wave amplitude mapping in retrospectively gated MRI

To analyze cerebral arteriovenous pulse propagation and to generate phase-resolved pulse amplitude maps from a fast gradient-echo sequence offering flow-related enhancement (FREE). Brain MRI was performed using a balanced steady-state free precession sequence at 3T followed by retrospective k-space gating. The time interval of the pulse wave between anterior-, middle- and posterior cerebral artery territories and the superior sagittal sinus were calculated and compared between and older and younger groups within 24 healthy volunteers. Pulse amplitude maps were generated and compared to pseudo-Continuous Arterial Spin Labeling (pCASL) MRI maps by voxel-wise Pearson correlation, Sørensen-Dice maps and in regards to signal contrast. The arteriovenous delays between all vascular territories and the superior sagittal sinus were significantly shorter in the older age group (11 individuals, ≥ 31 years) ranging between 169 ± 112 and 246 ± 299 ms versus 286 ± 244 to 419 ± 299 ms in the younger age group (13 individuals) (P ≤ 0.04). The voxel-wise pulse wave amplitude values and perfusion-weighted pCASL values correlated significantly (Pearson-r = 0.33, P < 0.01). Mean Dice overlaps of high (gray) and low (white matter) regions were 73 ± 3% and 59 ± 5%. No differences in image contrast were seen in the whole brain and the white matter, but significantly higher mean contrast of 0.73 ± 0.23% in cortical gray matter in FREE-MRI compared to 0.52 ± 0.12% in pCASL-MRI (P = 0.01). The dynamic information of flow-related enhancement allows analysis of the cerebral pulse wave propagation potentially providing information about the (micro)circulation on a regional level. However, the pulse wave amplitude reveals weaknesses in comparison to true perfusion-weighting and could rather be used to calculate a pulsatility index.