Parameter subset reduction for imaging-based digital twin generation of patients with left ventricular mechanical discoordination.

BACKGROUND: Integration of a patient's non-invasive imaging data in a digital twin (DT) of the heart can provide valuable insight into the myocardial disease substrates underlying left ventricular (LV) mechanical discoordination. However, when generating a DT, model parameters should be identifiable to obtain robust parameter estimations. In this study, we used the CircAdapt model of the human heart and circulation to find a subset of parameters which were identifiable from LV cavity volume and regional strain measurements of patients with different substrates of left bundle branch block (LBBB) and myocardial infarction (MI). To this end, we included seven patients with heart failure with reduced ejection fraction (HFrEF) and LBBB (study ID: 2018-0863, registration date: 2019-10-07), of which four were non-ischemic (LBBB-only) and three had previous MI (LBBB-MI), and six narrow QRS patients with MI (MI-only) (study ID: NL45241.041.13, registration date: 2013-11-12). Morris screening method (MSM) was applied first to find parameters which were important for LV volume, regional strain, and strain rate indices. Second, this parameter subset was iteratively reduced based on parameter identifiability and reproducibility. Parameter identifiability was based on the diaphony calculated from quasi-Monte Carlo simulations and reproducibility was based on the intraclass correlation coefficient ( ICC ) obtained from repeated parameter estimation using dynamic multi-swarm particle swarm optimization. Goodness-of-fit was defined as the mean squared error ( χ 2 ) of LV myocardial strain, strain rate, and cavity volume. RESULTS: A subset of 270 parameters remained after MSM which produced high-quality DTs of all patients ( χ 2 < 1.6), but minimum parameter reproducibility was poor ( ICC min = 0.01). Iterative reduction yielded a reproducible ( ICC min = 0.83) subset of 75 parameters, including cardiac output, global LV activation duration, regional mechanical activation delay, and regional LV myocardial constitutive properties. This reduced subset produced patient-resembling DTs ( χ 2 < 2.2), while septal-to-lateral wall workload imbalance was higher for the LBBB-only DTs than for the MI-only DTs (p < 0.05). CONCLUSIONS: By applying sensitivity and identifiability analysis, we successfully determined a parameter subset of the CircAdapt model which can be used to generate imaging-based DTs of patients with LV mechanical discoordination. Parameters were reproducibly estimated using particle swarm optimization, and derived LV myocardial work distribution was representative for the patient's underlying disease substrate. This DT technology enables patient-specific substrate characterization and can potentially be used to support clinical decision making.

Large vessels as a tree of transmission lines incorporated in the CircAdapt whole-heart model: A computational tool to examine heart-vessel interaction.

We developed a whole-circulation computational model by integrating a transmission line (TL) model describing vascular wave transmission into the established CircAdapt platform of whole-heart mechanics. In the present paper, we verify the numerical framework of our TL model by benchmark comparison to a previously validated pulse wave propagation (PWP) model. Additionally, we showcase the integrated CircAdapt-TL model, which now includes the heart as well as extensive arterial and venous trees with terminal impedances. We present CircAdapt-TL haemodynamics simulations of: 1) a systemic normotensive situation and 2) a systemic hypertensive situation. In the TL-PWP benchmark comparison we found good agreement regarding pressure and flow waveforms (relative errors ≤ 2.9% for pressure, and ≤ 5.6% for flow). CircAdapt-TL simulations reproduced the typically observed haemodynamic changes with hypertension, expressed by increases in mean and pulsatile blood pressures, and increased arterial pulse wave velocity. We observed a change in the timing of pressure augmentation (defined as a late-systolic boost in aortic pressure) from occurring after time of peak systolic pressure in the normotensive situation, to occurring prior to time of peak pressure in the hypertensive situation. The pressure augmentation could not be observed when the systemic circulation was lumped into a (non-linear) three-element windkessel model, instead of using our TL model. Wave intensity analysis at the carotid artery indicated earlier arrival of reflected waves with hypertension as compared to normotension, in good qualitative agreement with findings in patients. In conclusion, we successfully embedded a TL model as a vascular module into the CircAdapt platform. The integrated CircAdapt-TL model allows detailed studies on mechanistic studies on heart-vessel interaction.

Natural Vascular Remodelling After Arteriovenous Fistula Creation in Dialysis Patients With and Without Previous Ipsilateral Vascular Access.

OBJECTIVE: The aim of the study was to observe the natural haemodynamic changes after arteriovenous fistula (AVF) creation in haemodialysis patients with and without a previous ipsilateral vascular access. METHODS: This was a retrospective, single centre cohort study. Patient demographics were registered and pre- and post-operative vessel ultrasound examinations were performed at regular follow up intervals. Arteriovenous fistula outcomes in terms of vessel diameter and access flow enhancement were determined for radiocephalic, brachiocephalic, and brachiobasilic AVFs. RESULTS: In total, 331 patients (median age 66 years, 60% male) with 366 new autologous AVFs were studied, of whom 112 patients had a previous ipsilateral vascular access (VA). Patients with a previous ipsilateral VA had a statistically significantly greater pre-operative brachial artery diameter (4.4 mm) and flow (106 mL/min), and basilic vein diameter (4.9 mm), compared with patients without a previous ipsilateral VA (4.0 mm, 54 mL/min, and 4.3 mm, respectively). For all AVF configurations these differences gradually disappeared over three months after AVF creation. The haemodynamic changes reached a plateau at three months, and were statistically significantly accelerated in patients with a previous ipsilateral VA. There were no differences in primary failure or high flow complications between both groups. CONCLUSION: Arteriovenous fistulae show haemodynamic and remodelling changes up to three months post-operatively. Previous ipsilateral VAs may initiate vessel preconditioning, and accelerate the observed haemodynamic changes after AVF creation. However, this preconditioning does not result in a beneficial or detrimental effect on VA function.

Computational Modelling Based Recommendation on Optimal Dialysis Needle Positioning and Dialysis Flow in Patients With Arteriovenous Grafts.

OBJECTIVE: Arteriovenous grafts (AVGs) typically lose patency within two years of creation due to venous neointimal hyperplasia, which is initiated by disturbed haemodynamics after AVG surgery. Haemodialysis needle flow can further disturb haemodynamics and thus impact AVG longevity. In this computational study it was assessed how dialysis flow and venous needle positioning impacts flow at the graft-vein anastomosis. Furthermore, it was studied how negative effects of dialysis needle flow could be mitigated. METHODS: Non-physiological wall shear stress and disturbed blood flow were assessed in an AVG model with and without dialysis needle flow. Needle distance to the venous anastomosis was set to 6.5, 10.0, or 13.5 cm, whereas dialysis needle flow was set to 200, 300 or 400 mL/min. Intraluminal needle tip depth was varied between superficial, central, or deep. The detrimental effects of dialysis needle flow were summarised by a haemodynamic score (HS), ranging from 0 (minimal) to 5 (severe). RESULTS: Dialysis needle flow resulted in increased disturbed flow and/or non-physiological wall shear stress in the venous peri-anastomotic region. Increasing cannulation distance from 6.5 to 13.5 cm reduced the HS by a factor 4.0, whereas a central rather than a deep or superficial needle tip depth reduced the HS by a maximum factor of 1.9. Lowering dialysis flow from 400 to 200 mL/min reduced the HS by a factor 7.4. CONCLUSION: Haemodialysis needle flow, cannulation location, and needle tip depth considerably increase the amount of disturbed flow and non-physiological wall shear stress in the venous anastomotic region of AVGs. Negative effects of haemodialysis needle flow could be minimised by more upstream cannulation, by lower dialysis flow and by ensuring a central needle tip depth. Since disturbed haemodynamics are associated with neointimal hyperplasia development, optimising dialysis flow and needle positioning during haemodialysis could play an important role in maintaining AVG patency.

Pre-operative Patient Specific Flow Predictions to Improve Haemodialysis Arteriovenous Fistula Maturation (Shunt Simulation Study): A Randomised Controlled Trial.

OBJECTIVE: An arteriovenous fistula (AVF) needs to mature before it becomes suitable to cannulate for haemodialysis treatment. Maturation importantly depends on the post-operative flow increase. Unfortunately, 20-40% of AVFs fail to mature (FTM). A patient specific computational model that predicts immediate post-operative flow was developed, and it was hypothesised that providing information from this model for planning of fistula creation might reduce FTM rates. METHODS: A multicentre, randomised controlled trial in nine Dutch hospitals was conducted in which patients with renal failure who were referred for AVF creation, were recruited. Patients were randomly assigned (1:1) to the control or computer simulation group. Both groups underwent a work up, with physical and duplex ultrasonography (DUS) examination. In the simulation group the data from the DUS examination were used for model simulations, and based on the immediate post-operative flow prediction, the ideal AVF configuration was recommended. The primary endpoint was AVF maturation defined as an AVF flow ≥500 mL/min and a vein inner diameter of ≥4 mm six weeks post-operatively. The secondary endpoint was model performance (i.e. comparisons between measured and predicted flows, and (multivariable) regression analysis for maturation probability with accompanying area under the receiver operator characteristic curve [AUC]). RESULTS: A total of 236 patients were randomly assigned (116 in the control and 120 in the simulation group), of whom 205 (100 and 105 respectively) were analysed for the primary endpoint. There was no difference in FTM rates between the groups (29% and 32% respectively). Immediate post-operative flow prediction had an OR of 1.15 (1.06-1.26; p < .001) per 100 mL/min for maturation, and the accompanying AUC was 0.67 (0.59-0.75). CONCLUSION: Providing pre-operative patient specific flow simulations during surgical planning does not result in improved maturation rates. Further study is needed to improve the predictive power of these simulations in order to render the computational model an adjunct to surgical planning.

Parameter subset reduction for patient-specific modelling of arrhythmogenic cardiomyopathy-related mutation carriers in the CircAdapt model.

Arrhythmogenic cardiomyopathy (AC) is an inherited cardiac disease, clinically characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. Patient-specific computational models could help understand the disease progression and may help in clinical decision-making. We propose an inverse modelling approach using the CircAdapt model to estimate patient-specific regional abnormalities in tissue properties in AC subjects. However, the number of parameters (n = 110) and their complex interactions make personalized parameter estimation challenging. The goal of this study is to develop a framework for parameter reduction and estimation combining Morris screening, quasi-Monte Carlo (qMC) simulations and particle swarm optimization (PSO). This framework identifies the best subset of tissue properties based on clinical measurements allowing patient-specific identification of right ventricular tissue abnormalities. We applied this framework on 15 AC genotype-positive subjects with varying degrees of myocardial disease. Cohort studies have shown that atypical regional right ventricular (RV) deformation patterns reveal an early-stage AC disease. The CircAdapt model of cardiovascular mechanics and haemodynamics has already demonstrated its ability to capture typical deformation patterns of AC subjects. We, therefore, use clinically measured cardiac deformation patterns to estimate model parameters describing myocardial disease substrates underlying these AC-related RV deformation abnormalities. Morris screening reduced the subset to 48 parameters. qMC and PSO further reduced the subset to a final selection of 16 parameters, including regional tissue contractility, passive stiffness, activation delay and wall reference area. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

An audit of uncertainty in multi-scale cardiac electrophysiology models.

Models of electrical activation and recovery in cardiac cells and tissue have become valuable research tools, and are beginning to be used in safety-critical applications including guidance for clinical procedures and for drug safety assessment. As a consequence, there is an urgent need for a more detailed and quantitative understanding of the ways that uncertainty and variability influence model predictions. In this paper, we review the sources of uncertainty in these models at different spatial scales, discuss how uncertainties are communicated across scales, and begin to assess their relative importance. We conclude by highlighting important challenges that continue to face the cardiac modelling community, identifying open questions, and making recommendations for future studies. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

A comparative study of geometry-based methods and intra-arterial pressure measurements to assess the hemodynamic significance of equivocal iliac artery stenoses.

OBJECTIVES: To date, the ultimate decision to treat iliac artery stenoses in patients suffering from symptomatic peripheral arterial disease is based on the patient's symptoms and on visual inspection of angiographical images. The primary aim of this study was to investigate the accuracy of geometry-based methods (i.e. visual inspection and quantitative vascular analysis (Viewforum version R7.2v1 Advanced vessel analysis, Philips Healthcare, Best, The Netherlands) of 3D rotational angiography) to identify the severity of equivocal iliac artery stenosis in peripheral arterial disease patients with intra-arterial hyperemic pressure measurements (gold standard) as a reference. METHODS: Twenty patients with symptomatic iliac artery stenoses were subjected to 3D rotational angiography. Intra-arterial pressure measurements under hyperemic conditions were performed across 24 visually identified iliac artery stenoses. Three experienced interventional-radiologists retrospectively estimated the lumen diameter reduction by visual inspection. Furthermore, quantitative vascular analysis was performed on the 3D rotational angiography data. Geometry-based estimates were classified into two groups: lumen diameter reduction of <50% (non-significant) and diameter reduction ≥ 50% (significant), and compared to the intra-arterial hyperemic pressure gradients. A stenosis causing a pressure gradient (Δp) ≥10 mmHg was considered hemodynamically significant. RESULTS: Visual inspection and quantitative vascular analysis correctly identified hemodynamically significant stenoses in, respectively, 83% and 67% of the 24 iliac artery stenoses. Quantitative vascular analysis-based identification of hemodynamic significant stenoses (Δp ≥ 10 mmHg) could be optimized by lowering the threshold to a 42% lumen diameter reduction which improved the accuracy from 67% to 83%. CONCLUSIONS: Visual inspection of 3D rotational angiography by experienced interventional-radiologists has an 83% accuracy to identify hemodynamic significant iliac artery stenoses (Δ p ≥10 mmHg). The use of quantitative vascular analysis software did not improve accuracy.

Pre-operative Duplex Ultrasonography in Arteriovenous Fistula Creation: Intra- and Inter-observer Agreement.

OBJECTIVE: Although clinical guidelines on arteriovenous fistula (AVF) creation advocate minimum luminal arterial and venous diameters, assessed by duplex ultrasonography (DUS), the clinical value of routine DUS examination is under debate. DUS might be an insufficiently repeatable and/or reproducible imaging modality because of its operator dependency. The present study aimed to assess intra- and inter-observer agreement of DUS examination in support of AVF surgery planning. METHODS: Ten end stage renal disease patients were included, to assess intra- and inter-observer agreement of pre-operative DUS measurements. All measurements were performed by two trained and experienced vascular technicians, blinded to measurement readings. From the routine DUS protocol, representative measurements (venous diameters, and arterial diameters and volume flow in the upper arm and forearm) were selected. For intra-observer agreement the measurements were performed in triplicate, with the probe released from the skin between each. Intraclass correlation coefficients were calculated for intra- and inter-observer agreement, and Bland-Altman plots used to graphically display mean measurement differences and limits of agreement. RESULTS: Ten patients (6 male, 59.4±19.7 years) consented to participate, and all predefined measurements were obtained. Intraclass correlation coefficients for intra-observer agreement of diameter measurements were at least 0.90 (95% CI 0.74-0.97; radial artery). Inter-observer agreement was at least 0.83 (0.46-0.96; lateral diameter upper arm cephalic vein). The Bland-Altman plots showed acceptable mean measurement differences and limits of agreement. CONCLUSION: In experienced hands, excellent intra- and inter-observer agreement can be reached for the discrete pre-operative DUS measurements advocated in clinical guidelines. DUS is therefore a reliable imaging modality to support AVF surgery planning. The content of DUS protocols, however, needs further standardisation.

Application of an Adaptive Polynomial Chaos Expansion on Computationally Expensive Three-Dimensional Cardiovascular Models for Uncertainty Quantification and Sensitivity Analysis.

When applying models to patient-specific situations, the impact of model input uncertainty on the model output uncertainty has to be assessed. Proper uncertainty quantification (UQ) and sensitivity analysis (SA) techniques are indispensable for this purpose. An efficient approach for UQ and SA is the generalized polynomial chaos expansion (gPCE) method, where model response is expanded into a finite series of polynomials that depend on the model input (i.e., a meta-model). However, because of the intrinsic high computational cost of three-dimensional (3D) cardiovascular models, performing the number of model evaluations required for the gPCE is often computationally prohibitively expensive. Recently, Blatman and Sudret (2010, "An Adaptive Algorithm to Build Up Sparse Polynomial Chaos Expansions for Stochastic Finite Element Analysis," Probab. Eng. Mech., 25(2), pp. 183-197) introduced the adaptive sparse gPCE (agPCE) in the field of structural engineering. This approach reduces the computational cost with respect to the gPCE, by only including polynomials that significantly increase the meta-model's quality. In this study, we demonstrate the agPCE by applying it to a 3D abdominal aortic aneurysm (AAA) wall mechanics model and a 3D model of flow through an arteriovenous fistula (AVF). The agPCE method was indeed able to perform UQ and SA at a significantly lower computational cost than the gPCE, while still retaining accurate results. Cost reductions ranged between 70-80% and 50-90% for the AAA and AVF model, respectively.

Explainable Machine Learning Based Prediction of Severity of Heart Failure Using Primary Electronic Health Records.

Heart Failure (HF) is a life-threatening condition. It affects more than 64 million people worldwide. Early diagnosis of HF is extremely crucial. In this study, we propose utilization of machine learning (ML) models to predict severity of HF from primary Electronic Health Records (EHRs). We used a public dataset of 2008 HF patients for the study. Gaussian Naive Bayes, Random Forest and CatBoost methods were used for prediction. The study shows that CatBoost works best for the goal. In addition to that, the largest contributors for tree-based models harmonize well with clinically important parameters, which exhibits the trustworthiness of these models. Hence, we conclude that utilization of ML methods on primary EHRs is a promising step for time-efficient diagnosis of HF patients.

Generation of synthetic aortic valve stenosis geometries for in silico trials.

In silico trials are a promising way to increase the efficiency of the development, and the time to market of cardiovascular implantable devices. The development of transcatheter aortic valve implantation (TAVI) devices, could benefit from in silico trials to overcome frequently occurring complications such as paravalvular leakage and conduction problems. To be able to perform in silico TAVI trials virtual cohorts of TAVI patients are required. In a virtual cohort, individual patients are represented by computer models that usually require patient-specific aortic valve geometries. This study aimed to develop a virtual cohort generator that generates anatomically plausible, synthetic aortic valve stenosis geometries for in silico TAVI trials and allows for the selection of specific anatomical features that influence the occurrence of complications. To build the generator, a combination of non-parametrical statistical shape modeling and sampling from a copula distribution was used. The developed virtual cohort generator successfully generated synthetic aortic valve stenosis geometries that are comparable with a real cohort, and therefore, are considered as being anatomically plausible. Furthermore, we were able to select specific anatomical features with a sensitivity of around 90%. The virtual cohort generator has the potential to be used by TAVI manufacturers to test their devices. Future work will involve including calcifications to the synthetic geometries, and applying high-fidelity fluid-structure-interaction models to perform in silico trials.

Significance of Dynamic Axial Stretching on Estimating Biomechanical Behavior and Properties of the Human Ascending Aorta.

Contrary to most vessels, the ascending thoracic aorta (ATA) not only distends but also elongates in the axial direction. The purpose of this study is to investigate the biomechanical behavior of the ascending thoracic aorta (ATA) in response to dynamic axial stretching during the cardiac cycle. In addition, the implications of neglecting this dynamic axial stretching when estimating the constitutive model parameters of the ATA are investigated. The investigations were performed through in silico simulations by assuming a Gasser-Ogden-Holzapfel (GOH) constitutive model representative of ATA tissue material. The GOH model parameters were obtained from biaxial tests performed on four human ATA tissues in a previous study. Pressure-diameter curves were simulated as synthetic data to assess the effect of neglecting dynamic axial stretching on estimating constitutive model parameters. Our findings reveal a significant increase in axial stress (~ 16%) and stored strain energy (~ 18%) in the vessel when dynamic axial stretching is considered, as opposed to assuming a fixed axial stretch. All but one artery showed increased volume compliance while considering a dynamic axial stretching condition. Furthermore, we observe a notable difference in the estimated constitutive model parameters when dynamic axial stretching of the ATA is neglected, compared to the ground truth model parameters. These results underscore the critical importance of accounting for axial deformations when conducting in vivo biomechanical characterization of the ascending thoracic aorta.

Efficient sensitivity analysis for biomechanical models with correlated inputs.

In most variance-based sensitivity analysis (SA) approaches applied to biomechanical models, statistical independence of the model input is assumed. However, often the model inputs are correlated. This might alter the interpretation of the SA results, which may severely impact the guidance provided during model development and personalization. Potential reasons for the infrequent usage of SA techniques that account for input correlation are the associated high computational costs, especially for models with many parameters, and the fact that the input correlation structure is often unknown. The aim of this study was to propose an efficient correlated global sensitivity analysis method by applying a surrogate model-based approach. Furthermore, this article demonstrates how correlated SA should be interpreted and how the applied method can guide the modeler during model development and personalization, even when the correlation structure is not entirely known beforehand. The proposed methodology was applied to a typical example of a pulse wave propagation model and resulted in accurate SA results that could be obtained at a theoretically 27,000× lower computational cost compared to the correlated SA approach without employing a surrogate model. Furthermore, our results demonstrate that input correlations can significantly affect SA results, which emphasizes the need to thoroughly investigate the effect of input correlations during model development. We conclude that our proposed surrogate-based SA approach allows modelers to efficiently perform correlated SA to complex biomechanical models and allows modelers to focus on input prioritization, input fixing and model reduction, or assessing the dependency structure between parameters.

Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans.

In this study, we propose a Convolutional Neural Network (CNN) with an assembly of non-linear fully connected layers for estimating body height and weight using a limited amount of data. This method can predict the parameters within acceptable clinical limits for most of the cases even when trained with limited data.

Biomechanical Characterisation of Thoracic Ascending Aorta with Preserved Pre-Stresses.

Mechanical properties of an aneurysmatic thoracic aorta are potential markers of future growth and remodelling and can help to estimate the risk of rupture. Aortic geometries obtained from routine medical imaging do not display wall stress distribution and mechanical properties. Mechanical properties for a given vessel may be determined from medical images at different physiological pressures using inverse finite element analysis. However, without considering pre-stresses, the estimation of mechanical properties will lack accuracy. In the present paper, we propose and evaluate a mechanical parameter identification technique, which recovers pre-stresses by determining the zero-pressure configuration of the aortic geometry. We first validated the method on a cylindrical geometry and subsequently applied it to a realistic aortic geometry. The verification of the assessed parameters was performed using synthetically generated reference data for both geometries. The method was able to estimate the true mechanical properties with an accuracy ranging from 98% to 99%.

Guideline recommendations on minimal blood vessel diameters and arteriovenous fistula outcomes.

OBJECTIVE: Clinical guidelines provide recommendations on the minimal blood vessel diameters required for arteriovenous fistula creation but the evidence for these recommendations is limited. We compared vascular access outcomes of fistulas created in agreement with the ESVS Clinical Practice Guidelines (i.e. arteries and veins >2 mm for forearm fistulas and >3 mm for upper arm fistulas) with fistulas created outside these recommendations. METHODS: The multicenter Shunt Simulation Study cohort contains 211 hemodialysis patients who received a first radiocephalic, brachiocephalic, or brachiobasilic fistula before publication of the ESVS Clinical Practice Guidelines. All patients had preoperative duplex ultrasound measurements according to a standardized protocol. Outcomes included duplex ultrasound findings at 6 weeks after surgery, vascular access function, and intervention rates until 1 year after surgery. RESULTS: In 55% of patients, fistulas were created in agreement with the ESVS Clinical Practice Guidelines recommendations on minimal blood vessel diameters. Concordance with the guideline recommendations was more frequent for forearm fistulas than for upper arm fistulas (65% vs 46%, p = 0.01). In the entire cohort, agreement with the guideline recommendations was not associated with an increased proportion of functional vascular accesses (70% vs 66% for fistulas created within and outside guideline recommendations, respectively; p = 0.61) or with decreased access-related intervention rates (1.45 vs 1.68 per patient-year, p = 0.20). In forearm fistulas, however, only 52% of arteriovenous fistulas created outside these recommendations developed into a timely functional vascular access. CONCLUSIONS: Whereas upper arm arteriovenous fistulas with preoperative blood vessel diameters <3 mm had similar vascular access function as fistulas created with larger blood vessels, forearm arteriovenous fistulas with preoperative blood vessel diameters <2 mm had poor clinical outcomes. These results support that clinical decision-making should be guided by an individual approach.

A realistic arteriovenous dialysis graft model for hemodynamic simulations.

OBJECTIVE: The hemodynamic benefit of novel arteriovenous graft (AVG) designs is typically assessed using computational models that assume highly idealized graft configurations and/or simplified boundary conditions representing the peripheral vasculature. The objective of this study is to evaluate whether idealized AVG models are suitable for hemodynamic evaluation of new graft designs, or whether more realistic models are required. METHODS: An idealized and a realistic, clinical imaging based, parametrized AVG geometry were created. Furthermore, two physiological boundary condition models were developed to represent the peripheral vasculature. We assessed how graft geometry (idealized or realistic) and applied boundary condition models of the peripheral vasculature (physiological or distal zero-flow) impacted hemodynamic metrics related to AVG dysfunction. RESULTS: Anastomotic regions exposed to high WSS (>7, ≤40 Pa), very high WSS (>40 Pa) and highly oscillatory WSS were larger in the simulations using the realistic AVG geometry. The magnitude of velocity perturbations in the venous segment was up to 1.7 times larger in the realistic AVG geometry compared to the idealized one. When applying a (non-physiological zero-flow) boundary condition that neglected blood flow to and from the peripheral vasculature, we observed large regions exposed to highly oscillatory WSS. These regions could not be observed when using either of the newly developed distal boundary condition models. CONCLUSION: Hemodynamic metrics related to AVG dysfunction are highly dependent on the geometry and the distal boundary condition model used. Consequently, the hemodynamic benefit of a novel graft design can be misrepresented when using idealized AVG modelling setups.

Hemodynamics-driven mathematical model of third heart sound generation.

The proto-diastolic third heart sound (S3) is observed in various hemodynamic conditions in both normal and diseased hearts. We propose a novel, one-degree of freedom mathematical model of mechanical vibrations of heart and blood that generates the third heart sound, implemented in a real-time model of the cardiovascular system (CircAdapt). To examine model functionality, S3 simulations were performed for conditions mimicking the normal heart as well as heart failure with preserved ejection fraction (HFpEF), atrioventricular valve regurgitation (AVR), atrioventricular valve stenosis (AVS) and septal shunts (SS). Simulated S3 showed both qualitative and quantitative agreements with measured S3 in terms of morphology, frequency, and timing. It was shown that ventricular mass, ventricular viscoelastic properties as well as inflow momentum play a key role in the generation of S3. The model indicated that irrespective of cardiac conditions, S3 vibrations are always generated, in both the left and right sides of the heart, albeit at different levels of audibility. S3 intensities increased in HFpEF, AVR and SS, but the changes of acoustic S3 features in AVS were not significant, as compared with the reference simulation. S3 loudness in all simulated conditions was proportional to the level of cardiac output and severity of cardiac conditions. In conclusion, our hemodynamics-driven mathematical model provides a fast and realistic simulation of S3 under various conditions which may be helpful to find new indicators for diagnosis and prognosis of cardiac diseases.