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%.

pyCEPS: A cross-platform electroanatomic mapping data to computational model conversion platform for the calibration of digital twin models of cardiac electrophysiology.

BACKGROUND AND OBJECTIVE: Data from electro-anatomical mapping (EAM) systems are playing an increasingly important role in computational modeling studies for the patient-specific calibration of digital twin models. However, data exported from commercial EAM systems are challenging to access and parse. Converting to data formats that are easily amenable to be viewed and analyzed with commonly used cardiac simulation software tools such as openCARP remains challenging. We therefore developed an open-source platform, pyCEPS, for parsing and converting clinical EAM data conveniently to standard formats widely adopted within the cardiac modeling community. METHODS AND RESULTS: pyCEPS is an open-source Python-based platform providing the following functions: (i) access and interrogate the EAM data exported from clinical mapping systems; (ii) efficient browsing of EAM data to preview mapping procedures, electrograms (EGMs), and electro-cardiograms (ECGs); (iii) conversion to modeling formats according to the openCARP standard, to be amenable to analysis with standard tools and advanced workflows as used for in silico EAM data. Documentation and training material to facilitate access to this complementary research tool for new users is provided. We describe the technological underpinnings and demonstrate the capabilities of pyCEPS first, and showcase its use in an exemplary modeling application where we use clinical imaging data to build a patient-specific anatomical model. CONCLUSION: With pyCEPS we offer an open-source framework for accessing EAM data, and converting these to cardiac modeling standard formats. pyCEPS provides the core functionality needed to integrate EAM data in cardiac modeling research. We detail how pyCEPS could be integrated into model calibration workflows facilitating the calibration of a computational model based on EAM data.

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%.

Influence of genetic mutations to atria vulnerability to atrial fibrillation: An in-silico 3D human atria study.

BACKGROUND AND OBJECTIVE: Personalized 3D computer models of atria have been extensively implemented in the last yearsas a tool to facilitate the understanding of the mechanisms underlying different forms of arrhythmia, such as atrial fibrillation (AF). Meanwhile, genetic mutations acting on potassium channel dynamics were demonstrated to induce fibrillatory episodes in asymptomatic patients. This research study aims at assessing the effects and the atrial susceptibility to AF of three gain-of-function mutations - namely, KCNH2 T895M, KCNH2 T436M, and KCNE3-V17M - associated with AF outbreaks, using highly detailed 3D atrial models with realistic wall thickness and heterogenous histological properties. METHODS: The 3D atrial model was generated by reconstructing segmented anatomical structures from CT scans of an AF patient. Modified versions of the Courtemanche human atrial myocyte model were used to reproduce the electrophysiological activity of the WT and of the three mutant cells. Ectopic foci (EF) were simulated in sixteen locations across the atrial mesh using an S1-S2 protocol with two S2 basic cycle lengths (BCL) and eleven coupling intervals in order to induce arrhythmias. RESULTS: The three genetic mutations at 3D level reduced the APD90. The KCNE3-V17M mutation provoked the highest shortening (55 % in RA and LA with respect to WT), followed by KCNH2 T895M (14 % in RA and 18 % LA with respect to WT)and KCNH2 T436M (7 % in RA and 9 % LA with respect to WT). The KCNE3-V17M mutation led to arrhythmia in 67 % of the cases simulated and in 94 % of ectopic foci considered, at S2 BCL equal to 100 ms. The KCNH2 T436M and KCNH2 T895M mutations increased the vulnerability to AF in a similar way, leading to arrhythmic episodes in 7 % of the simulated conditions, at S2 BCL set to 160 ms. Overall, 60 % of the arrhythmic events generated arise in the left atrium. Spiral waves, multiple rotors and disordered electrical pattern were elicited in the presence of the KCNE3-V17M mutation, exhibiting an instantaneous mean frequency of 7.6 Hz with a mean standard deviation of 1.12 Hz. The scroll waves induced in the presence of the KCNH2 T436M and KCNH2 T895M mutations showed steadiness and regularity with an instantaneous mean frequencies in the range of 4.9 - 5.1 Hz and a mean standard deviation within 0.19 - 0.53 Hz. CONCLUSIONS: The pro-arrhythmogenicity of the KCNE3-V17M, KCNH2 T895M and KCNH2 T436M mutations was studied and proved on personalized 3D cardiac models. The three genetic mutations were demonstrated to increase the predisposition of atrial tissue to the formation of AF-susceptible substrate in different ways based on their effects on electrophysiological properties of the atria.

Turbulent blood flow in a cerebral artery with an aneurysm.

Unruptured intracranial aneurysms are common in the general population, and many uncertainties remain when predicting rupture risks and treatment outcomes. One of the cutting-edge tools used to investigate this condition is computational fluid dynamics (CFD). However, CFD is not yet mature enough to guide the clinical management of this disease. In addition, recent studies have reported significant flow instabilities when refined numerical methods are used. Questions remain as to how to properly simulate and evaluate this flow, and whether these instabilities are really turbulence. The purpose of the present study is to evaluate the impact of the simulation setup on the results and investigate the occurrence of turbulence in a cerebral artery with an aneurysm. For this purpose, direct numerical simulations were performed with up to 200 cardiac cycles and with data sampling rates of up to 100,000 times per cardiac cycle. Through phase-averaging or triple decomposition, the contributions of turbulence and of laminar pulsatile waves to the velocity, pressure and wall shear stress fluctuations were distinguished. For example, the commonly used oscillatory shear index was found to be closely related to the laminar waves introduced at the inlet, rather than turbulence. The turbulence energy cascade was evaluated through energy spectrum estimates, revealing that, despite the low flow rates and Reynolds number, the flow is turbulent near the aneurysm. Phase-averaging was shown to be an approach that can help researchers better understand this flow, although the results are highly dependent on simulation setup and post-processing choices.

Optimizing the compression resistance of low-nickel stainless steel coronary stents using finite element and response surface methodology.

Considering the high strength and excellent biocompatibility of low-nickel stainless steel, this paper focused on optimizing the design of a vascular stent made from this material using finite element analysis (FEA) combined with the response surface methodology (RSM). The aim is to achieve the desired compressive resistance for the stent while maintaining a thin stent wall thickness. The parameters of the stent's support unit width (H), strut width (W), and thickness (T) were selected as input parameters, while the output parameters obtained from FEA included the compressive load, the equivalent plastic strain (PEEQ), axial shortening rate, radial recoil rate, and metal coverage rate. The mathematical models of input parameters and output parameters were established by using the Box Behnken design (BBD) of RSM. The model equations were solved under constrained conditions, and the optimal structural parameters, namely H, W, and T, were finally determined as 0.770 mm, 0.100 mm, and 0.075 mm respectively. In this situation, the compression load of the stent reached the target value of 0.38 N/mm; the PEEQ resulting from the stent expansion was small; the axial shortening, radial recoil, and metal coverage index were all minimized within the required range.

Examining temporal changes in model-optimized parameters using longitudinal hemodynamic measurements.

BACKGROUND: We previously applied hemodynamic data to personalize a mathematical model of the circulation expressed as physically interpretable parameters. The aim of this study was to identify patterns in the data that could potentially explain the estimated parameter changes. This included investigating whether the parameters could be used to track the effect of physical activity on high blood pressure. Clinical trials have repeatedly detected beneficial changes in blood pressure after physical activity and uncovered changes in lower level phenotypes (such as stiffened or high-resistance blood vessels). These phenotypes can be characterized by parameters describing the mechanical properties of the circulatory system. These parameters can be incorporated in and contextualized by physics-based cardiovascular models of the circulation, which in combination can become tools for monitoring cardiovascular disease progression and management in the future. METHODS: Closed-loop and open-loop models of the left ventricle and systemic circulation were previously optimized to data from a pilot study with a 12-week exercise intervention period. Basal characteristics and hemodynamic data such as blood pressure in the carotid, brachial and finger arteries, as well as left-ventricular outflow tract flow traces were collected in the trial. Model parameters estimated for measurements made on separate days during the trial were used to compute parameter changes for total peripheral resistance, systemic arterial compliance, and maximal left-ventricular elastance. We compared the changes in these cardiovascular model-based estimates to changes from more conventional estimates made without the use of physics-based models by correlation analysis. Additionally, ordinary linear regression and linear mixed-effects models were applied to determine the most informative measurements for the selected parameters. We applied maximal aerobic capacity (measured as VO2max ) data to examine if exercise had any impact on parameters through regression analysis and case studies. RESULTS AND CONCLUSIONS: Parameter changes in arterial parameters estimated using the cardiovascular models correlated moderately well with conventional estimates. Estimates based on carotid pressure waveforms gave higher correlations (0.59 and above when p < 0.05 ) than those for finger arterial pressure. Parameter changes over the 12-week study duration were of similar magnitude when compared to short-term changes after a bout of intensive exercise in the same parameters. The short-term changes were computed from measurements made immediately before and 24 h after a cardiopulmonary exercise test used to measure VO2max . Regression analysis indicated that changes in VO2max did not account for any substantial amount of variability in total peripheral resistance, systemic arterial compliance, or maximal left-ventricular elastance. On the contrary, changes in stroke volume contributed to far more explained variability. The results suggest that more research is required to be able to accurately track exercise-induced changes in the vasculature for people with pre-hypertension and hypertension using lumped-parameter models.

Numerical analysis of blood flow in the abdominal aorta under simulated weightlessness and earth conditions.

Blood flow through the abdominal aorta and iliac arteries is a crucial area of research in hemodynamics and cardiovascular diseases. To get in to the problem, this study presents detailed analyses of blood flow through the abdominal aorta, together with left and right iliac arteries, under Earth gravity and weightless conditions, both at the rest stage, and during physical activity. The analysis were conducted using ANSYS Fluent software. The results indicate, that there is significantly less variation in blood flow velocity under weightless conditions, compared to measurement taken under Earth Gravity conditions. Study presents, that the maximum and minimum blood flow velocities decrease and increase, respectively, under weightless conditions. Our model for the left iliac artery revealed higher blood flow velocities during the peak of the systolic phase (systole) and lower velocities during the early diastolic phase (diastole). Furthermore, we analyzed the shear stress of the vessel wall and the mean shear stress over time. Additionally, the distribution of oscillatory shear rate, commonly used in hemodynamic analyses, was examined to assess the effects of blood flow on the blood vessels. Countermeasures to mitigate the negative effects of weightlessness on astronauts health are discussed, including exercises performed on the equipment aboard the space station. These exercises aim to maintain optimal blood flow, prevent the formation of atherosclerotic plaques, and reduce the risk of cardiovascular complications.

Transmural APD heterogeneity determines ventricular arrhythmogenesis in LQT8 syndrome: Insights from Bidomain computational modeling.

Long QT Syndrome type 8 (LQT8) is a cardiac arrhythmic disorder associated with Timothy Syndrome, stemming from mutations in the CACNA1C gene, particularly the G406R mutation. While prior studies hint at CACNA1C mutations' role in ventricular arrhythmia genesis, the mechanisms, especially in G406R presence, are not fully understood. This computational study explores how the G406R mutation, causing increased transmural dispersion of repolarization, induces and sustains reentrant ventricular arrhythmias. Using three-dimensional numerical simulations on an idealized left-ventricular model, integrating the Bidomain equations with the ten Tusscher-Panfilov ionic model, we observe that G406R mutation with 11% and 50% heterozygosis significantly increases transmural dispersion of repolarization. During S1-S4 stimulation protocols, these gradients facilitate conduction blocks, triggering reentrant ventricular tachycardia. Sustained reentry pathways occur only with G406R mutation at 50% heterozygosis, while neglecting transmural heterogeneities of action potential duration prevents stable reentry, regardless of G406R mutation presence.

Fabrication, characterization and numerical validation of a novel thin-wall hydrogel vessel model for cardiovascular research based on a patient-specific stenotic carotid artery bifurcation.

In vitro vascular models, primarily made of silicone, have been utilized for decades for studying hemodynamics and supporting the development of implants for catheter-based treatments of diseases such as stenoses and aneurysms. Hydrogels have emerged as prominent materials in tissue-engineering applications, offering distinct advantages over silicone models for fabricating vascular models owing to their viscoelasticity, low friction, and tunable mechanical properties. Our study evaluated the feasibility of fabricating thin-wall, anatomical vessel models made of polyvinyl alcohol hydrogel (PVA-H) based on a patient-specific carotid artery bifurcation using a combination of 3D printing and molding technologies. The model's geometry, elastic modulus, volumetric compliance, and diameter distensibility were characterized experimentally and numerically simulated. Moreover, a comparison with silicone models with the same anatomy was performed. A PVA-H vessel model was integrated into a mock circulatory loop for a preliminary ultrasound-based assessment of fluid dynamics. The vascular model's geometry was successfully replicated, and the elastic moduli amounted to 0.31 ± 0.007 MPa and 0.29 ± 0.007 MPa for PVA-H and silicone, respectively. Both materials exhibited nearly identical volumetric compliance (0.346 and 0.342% mmHg-1), which was higher compared to numerical simulation (0.248 and 0.290% mmHg-1). The diameter distensibility ranged from 0.09 to 0.20% mmHg-1 in the experiments and between 0.10 and 0.18% mmHg-1 in the numerical model at different positions along the vessel model, highlighting the influence of vessel geometry on local deformation. In conclusion, our study presents a method and provides insights into the manufacturing and mechanical characterization of hydrogel-based thin-wall vessel models, potentially allowing for a combination of fluid dynamics and tissue engineering studies in future cardio- and neurovascular research.

Functional consequences of changes in the distribution of Ca2+ extrusion pathways between t-tubular and surface membranes in a model of human ventricular cardiomyocyte.

The sarcolemmal Ca2+ efflux pathways, Na+-Ca2+-exchanger (NCX) and Ca2+-ATPase (PMCA), play a crucial role in the regulation of intracellular Ca2+ load and Ca2+ transient in cardiomyocytes. The distribution of these pathways between the t-tubular and surface membrane of ventricular cardiomyocytes varies between species and is not clear in human. Moreover, several studies suggest that this distribution changes during the development and heart diseases. However, the consequences of NCX and PMCA redistribution in human ventricular cardiomyocytes have not yet been elucidated. In this study, we aimed to address this point by using a mathematical model of the human ventricular myocyte incorporating t-tubules, dyadic spaces, and subsarcolemmal spaces. Effects of various combinations of t-tubular fractions of NCX and PMCA were explored, using values between 0.2 and 1 as reported in animal experiments under normal and pathological conditions. Small variations in the action potential duration (≤ 2%), but significant changes in the peak value of cytosolic Ca2+ transient (up to 17%) were observed at stimulation frequencies corresponding to the human heart rate at rest and during activity. The analysis of model results revealed that the changes in Ca2+ transient induced by redistribution of NCX and PMCA were mainly caused by alterations in Ca2+ concentrations in the subsarcolemmal spaces and cytosol during the diastolic phase of the stimulation cycle. The results suggest that redistribution of both transporters between the t-tubular and surface membranes contributes to changes in contractility in human ventricular cardiomyocytes during their development and heart disease and may promote arrhythmogenesis.

A possible path to persistent re-entry waves at the outlet of the left pulmonary vein.

Atrial fibrillation (AF) is the most common form of cardiac arrhythmia, often evolving from paroxysmal episodes to persistent stages over an extended timeframe. While various factors contribute to this progression, the precise biophysical mechanisms driving it remain unclear. Here we explore how rapid firing of cardiomyocytes at the outlet of the pulmonary vein of the left atria can create a substrate for a persistent re-entry wave. This is grounded in a recently formulated mathematical model of the regulation of calcium ion channel density by intracellular calcium concentration. According to the model, the number of calcium channels is controlled by the intracellular calcium concentration. In particular, if the concentration increases above a certain target level, the calcium current is weakened to restore the target level of calcium. During rapid pacing, the intracellular calcium concentration of the cardiomyocytes increases leading to a substantial reduction of the calcium current across the membrane of the myocytes, which again reduces the action potential duration. In a spatially resolved cell-based model of the outlet of the pulmonary vein of the left atria, we show that the reduced action potential duration can lead to re-entry. Initiated by rapid pacing, often stemming from paroxysmal AF episodes lasting several days, the reduction in calcium current is a critical factor. Our findings illustrate how such episodes can foster a conducive environment for persistent AF through electrical remodeling, characterized by diminished calcium currents. This underscores the importance of promptly addressing early AF episodes to prevent their progression to chronic stages.

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue.

Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model's applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.