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.

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.

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.

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.

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.

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.

A review study of fetal circulatory models to develop a digital twin of a fetus in a perinatal life support system.

Background: Preterm birth is the main cause of neonatal deaths with increasing mortality and morbidity rates with decreasing GA at time of birth. Currently, premature infants are treated in neonatal intensive care units to support further development. However, the organs of, especially, extremely premature infants (born before 28 weeks of GA) are not mature enough to function optimally outside the womb. This is seen as the main cause of the high morbidity and mortality rates in this group. A liquid-filled incubator, a so-called PLS system, could potentially improve these numbers for extremely premature infants, since this system is designed to mimic the environment of the natural womb. To support the development and implementation of such a complex system and to interpret vital signals of the fetus during a PLS system operation, a digital twin is proposed. This mathematical model is connected with a manikin representing the digital and physical twin of the real-life PLS system. Before developing a digital twin of a fetus in a PLS system, its functional and technical requirements are defined and existing mathematical models are evaluated. Method and results: This review summarizes existing 0D and 1D fetal circulatory models that potentially could be (partly) adopted for integration in a digital twin of a fetus in a PLS system based on predefined requirements. The 0D models typically describe hemodynamics and/or oxygen transport during specific events, such as the transition from fetus to neonate. Furthermore, these models can be used to find hemodynamic differences between healthy and pathological physiological states. Rather than giving a global description of an entire cardiovascular system, some studies focus on specific organs or vessels. In order to analyze pressure and flow wave profiles in the cardiovascular system, transmission line or 1D models are used. As for now, these models do not include oxygen transport. Conclusion: This study shows that none of the models identified in literature meet all the requirements relevant for a digital twin of a fetus in a PLS system. Nevertheless, it does show the potential to develop this digital twin by integrating (parts) of models into a single model.

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.

From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy.

Survivors of myocardial infarction are at risk of life-threatening ventricular tachycardias (VTs) later in their lives. Current guidelines for implantable cardioverter defibrillators (ICDs) implantation to prevent VT-related sudden cardiac death is solely based on symptoms and left ventricular ejection fraction. Catheter ablation of scar-related VTs is performed following ICD therapy, reducing VTs, painful shocks, anxiety, depression and worsening heart failure. We postulate that better prediction of the occurrence and circuit of VT, will improve identification of patients at risk for VT and boost preventive ablation, reducing mortality and morbidity. For this purpose, multiple time-evolving aspects of the underlying pathophysiology, including the anatomical substrate, triggers and modulators, should be part of VT prediction models. We envision digital twins as a solution combining clinical expertise with three prediction approaches: evidence-based medicine (clinical practice), data-driven models (data science) and mechanistic models (biomedical engineering). This paper aims to create a mutual understanding between experts in the different fields by providing a comprehensive description of the clinical problem and the three approaches in an understandable manner, leveraging future collaborations and technological innovations for clinical decision support. Moreover, it defines open challenges and gains for digital twin solutions and discusses the potential of hybrid modelling.

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.

Uncertainty Quantification of Regional Cardiac Tissue Properties in Arrhythmogenic Cardiomyopathy Using Adaptive Multiple Importance Sampling.

Introduction: Computational models of the cardiovascular system are widely used to simulate cardiac (dys)function. Personalization of such models for patient-specific simulation of cardiac function remains challenging. Measurement uncertainty affects accuracy of parameter estimations. In this study, we present a methodology for patient-specific estimation and uncertainty quantification of parameters in the closed-loop CircAdapt model of the human heart and circulation using echocardiographic deformation imaging. Based on patient-specific estimated parameters we aim to reveal the mechanical substrate underlying deformation abnormalities in patients with arrhythmogenic cardiomyopathy (AC). Methods: We used adaptive multiple importance sampling to estimate the posterior distribution of regional myocardial tissue properties. This methodology is implemented in the CircAdapt cardiovascular modeling platform and applied to estimate active and passive tissue properties underlying regional deformation patterns, left ventricular volumes, and right ventricular diameter. First, we tested the accuracy of this method and its inter- and intraobserver variability using nine datasets obtained in AC patients. Second, we tested the trueness of the estimation using nine in silico generated virtual patient datasets representative for various stages of AC. Finally, we applied this method to two longitudinal series of echocardiograms of two pathogenic mutation carriers without established myocardial disease at baseline. Results: Tissue characteristics of virtual patients were accurately estimated with a highest density interval containing the true parameter value of 9% (95% CI [0-79]). Variances of estimated posterior distributions in patient data and virtual data were comparable, supporting the reliability of the patient estimations. Estimations were highly reproducible with an overlap in posterior distributions of 89.9% (95% CI [60.1-95.9]). Clinically measured deformation, ejection fraction, and end-diastolic volume were accurately simulated. In presence of worsening of deformation over time, estimated tissue properties also revealed functional deterioration. Conclusion: This method facilitates patient-specific simulation-based estimation of regional ventricular tissue properties from non-invasive imaging data, taking into account both measurement and model uncertainties. Two proof-of-principle case studies suggested that this cardiac digital twin technology enables quantitative monitoring of AC disease progression in early stages of disease.

Optic nerve sheath diameter assessment by neurosonology: A review of methodologic discrepancies.

BACKGROUND AND PURPOSE: Reported cutoff values of the optic nerve sheath diameter (ONSD) for the diagnosis of elevated intracranial pressure (ICP) are inconsistent. This hampers ONSD as a possible noninvasive bedside monitoring tool for ICP. Because the influence of methodological differences on variations in cutoff values is unknown, we performed a narrative review to identify discrepancies in ONSD assessment methodologies and to investigate their effect on reported ONSD values. METHODS: We used a structured and quantitative approach in which each ONSD methodology found in the reviewed articles was categorized based on the characteristic appearance of the ultrasound images and ultrasound marker placement. Subsequently, we investigated the influence of the different methodologies on ONSD values by organizing the ONSDs with respect to these categories. RESULTS: In a total of 63 eligible articles, we could determine the applied ONSD assessment methodology. Reported ultrasound images either showed the optic nerve and its sheath as a dark region with hyperechoic striped band at its edges or as a single dark region surrounded by lighter retrobulbar fat. Four different ultrasound marker positions were used to delineate the optic nerve sheath, which resulted in different ONSD values and more importantly, different sensitivities to changes in ICP. CONCLUSIONS: Based on our observations, we recommend to place ultrasound markers at the outer edges of the hyperechoic striped bands or at the transitions from the single dark region to the hyperechoic retrobulbar fat because these locations yielded the highest sensitivity of ONSD measurements for increased ICP.

Intra-Operative Video-Based Measurement of Biaxial Strains of the Ascending Thoracic Aorta.

Local biaxial deformation measurements are essential for the in-depth investigation of tissue properties and remodeling of the ascending thoracic aorta, particularly in aneurysm formation. Current clinical imaging modalities pose limitations around the resolution and tracking of anatomical markers. We evaluated a new intra-operative video-based method to assess local biaxial strains of the ascending thoracic aorta. In 30 patients undergoing open-chest surgery, we obtained repeated biaxial strain measurements, at low- and high-pressure conditions. Precision was very acceptable, with coefficients of variation for biaxial strains remaining below 20%. With our four-marker arrangement, we were able to detect significant local differences in the longitudinal strain as well as in circumferential strain. Overall, the magnitude of strains we obtained (range: 0.02-0.05) was in line with previous reports using other modalities. The proposed method enables the assessment of local aortic biaxial strains and may enable new, clinically informed mechanistic studies using biomechanical modeling as well as mechanobiological profiling.

Computationally guided in-vitro vascular growth model reveals causal link between flow oscillations and disorganized neotissue.

Disturbed shear stress is thought to be the driving factor of neointimal hyperplasia in blood vessels and grafts, for example in hemodialysis conduits. Despite the common occurrence of neointimal hyperplasia, however, the mechanistic role of shear stress is unclear. This is especially problematic in the context of in situ scaffold-guided vascular regeneration, a process strongly driven by the scaffold mechanical environment. To address this issue, we herein introduce an integrated numerical-experimental approach to reconstruct the graft-host response and interrogate the mechanoregulation in dialysis grafts. Starting from patient data, we numerically analyze the biomechanics at the vein-graft anastomosis of a hemodialysis conduit. Using this biomechanical data, we show in an in vitro vascular growth model that oscillatory shear stress, in the presence of cyclic strain, favors neotissue development by reducing the secretion of remodeling markers by vascular cells and promoting the formation of a dense and disorganized collagen network. These findings identify scaffold-based shielding of cells from oscillatory shear stress as a potential handle to inhibit neointimal hyperplasia in grafts.

An Automated Algorithm for Optic Nerve Sheath Diameter Assessment from B-mode Ultrasound Images.

BACKGROUND AND PURPOSE: The optic nerve sheath diameter (ONSD) is a promising surrogate marker for the detection of raised intracranial pressure (ICP). However, inconsistencies in manual ONSD assessment are thought to affect ONSD and the corresponding ONSD cutoff values for the diagnosis of elevated ICP, hereby hampering the full potential of ONSD. In this study, we developed an image intensity-invariant algorithm to automatically estimate ONSD from B-mode ultrasound images at multiple depths. METHODS: The outcomes of the algorithm were validated against manual ONSD measurements by two human experts. Each expert analyzed the images twice (M1 and M2) in unknown order. RESULTS: The algorithm proved capable of segmenting the ONSD in 39 of 42 images, hereby showing mean differences of -.08 ± .45 and -.05 ± .41 mm compared to averaged ONSD values (M1 + M2/2) of Operator 1 and Operator 2, respectively, whereas the mean difference between the two experts was .03 ± .26 mm. Moreover, differences between algorithm-derived and expert-derived ONSD values were found to be much smaller than the 1 mm difference that is expected between patients with normal and elevated ICP, making it likely that our algorithm can distinguish between these patient groups. CONCLUSIONS: Our algorithm has the potential to improve the accuracy of ONSD as a surrogate marker for elevated ICP because it has no intrinsic variability. However, future research should be performed to validate if the algorithm does indeed result in more accurate noninvasive ICP predictions.

Improved Quantification of Cell Density in the Arterial Wall-A Novel Nucleus Splitting Approach Applied to 3D Two-Photon Laser-Scanning Microscopy.

Accurate information on vascular smooth muscle cell (VSMC) content, orientation, and distribution in blood vessels is indispensable to increase understanding of arterial remodeling and to improve modeling of vascular biomechanics. We have previously proposed an analysis method to automatically characterize VSMC orientation and transmural distribution in murine carotid arteries under well-controlled biomechanical conditions. However, coincident nuclei, erroneously detected as one large nucleus, were excluded from the analysis, hampering accurate VSMC content characterization and distorting transmural distributions. In the present study, therefore, we aim to (1) improve the previous method by adding a "nucleus splitting" procedure to split coinciding nuclei, (2) evaluate the accuracy of this novel method, and (3) test this method in a mouse model of VSMC apoptosis. After euthanasia, carotid arteries from SM22α-hDTR Apoe -/- and control Apoe -/- mice were bluntly dissected, excised, mounted in a biaxial biomechanical tester and brought to in vivo axial stretch and a pressure of 100 mmHg. Nuclei and elastin fibers were then stained using Syto-41 and Eosin-Y, respectively, and imaged using 3D two-photon laser scanning microscopy. Nuclei were segmented from images and coincident nuclei were split. The nucleus splitting procedure determines the likelihood that voxel pairs within coincident nuclei belong to the same nucleus and utilizes these likelihoods to identify individual nuclei using spectral clustering. Manual nucleus counts were used as a reference to assess the performance of our splitting procedure. Before and after splitting, automatic nucleus counts differed -26.6 ± 9.90% (p < 0.001) and -1.44 ± 7.05% (p = 0.467) from the manual reference, respectively. Whereas the slope of the relative difference between the manual and automated counts as a function of the manual count was significantly negative before splitting (p = 0.008), this slope became insignificant after splitting (p = 0.653). Smooth muscle apoptosis led to a 33.7% decrease in VSMC density (p = 0.008). Nucleus splitting improves the accuracy of automated cell content quantification in murine carotid arteries and overcomes the progressively worsening problem of coincident nuclei with increasing cell content in vessels. The presented image analysis framework provides a robust tool to quantify cell content, orientation, shape, and distribution in vessels to inform experimental and advanced computational studies on vascular structure and function.

Haemodynamic optimisation of a dialysis graft design using a global optimisation approach.

Disturbed flow and the resulting non-physiological wall shear stress (WSS) at the graft-vein anastomosis play an important role in arteriovenous graft (AVG) patency loss. Modifying graft geometry with helical features is a popular approach to minimise the occurrence of detrimental haemodynamics and to potentially increase graft longevity. Haemodynamic optimisation of AVGs typically requires many computationally expensive computational fluid dynamics (CFD) simulations to evaluate haemodynamic performance of different graft designs. In this study, we aimed to develop a haemodynamically optimised AVG by using an efficient meta-modelling approach. A training dataset containing CFD evaluations of 103 graft designs with helical features was used to develop computationally low-cost meta-models for haemodynamic metrics related to graft dysfunction. During optimisation, the meta-models replaced CFD simulations that were otherwise needed to evaluate the haemodynamic performance of possible graft designs. After optimisation, haemodynamic performance of the optimised graft design was verified using a CFD simulation. The obtained optimised graft design contained both a helical graft centreline and helical ridge. Using the optimised design, the magnitude of flow disturbances and the size of the anastomotic areas exposed to non-physiological WSS was successfully reduced compared to a regular straight graft. Our meta-modelling approach allowed to reduce the total number of CFD model evaluations required for our design optimisation by approximately a factor 2000. The applied efficient meta-modelling technique was successful in identifying an optimal, helical graft design at relatively low computational costs. Future studies should evaluate the in vivo benefits of the developed graft design.

Complementing sparse vascular imaging data by physiological adaptation rules.

Mathematical modeling of pressure and flow waveforms in blood vessels using pulse wave propagation (PWP) models has tremendous potential to support clinical decision making. For a personalized model outcome, measurements of all modeled vessel radii and wall thicknesses are required. In clinical practice, however, data sets are often incomplete. To overcome this problem, we hypothesized that the adaptive capacity of vessels in response to mechanical load could be utilized to fill in the gaps of incomplete patient-specific data sets. We implemented homeostatic feedback loops in a validated PWP model to allow adaptation of vessel geometry to maintain physiological values of wall stress and wall shear stress. To evaluate our approach, we gathered vascular MRI and ultrasound data sets of wall thicknesses and radii of central and arm arterial segments of 10 healthy subjects. Reference models (i.e., termed RefModel, n = 10) were simulated using complete data, whereas adapted models (AdaptModel, n = 10) used data of one carotid artery segment only, and the remaining geometries in this model were estimated using adaptation. We evaluated agreement between RefModel and AdaptModel geometries, as well as that between pressure and flow waveforms of both models. Limits of agreement (bias ± 2 SD of difference) between AdaptModel and RefModel radii and wall thicknesses were 0.2 ± 2.6 mm and -140 ± 557 µm, respectively. Pressure and flow waveform characteristics of the AdaptModel better resembled those of the RefModels as compared with the model in which the vessels were not adapted. Our adaptation-based PWP model enables personalization of vascular geometries even when not all required data are available.NEW & NOTEWORTHY To benefit personalized pulse wave propagation (PWP) modeling, we propose a novel method that, instead of relying on extensive data sets on vascular geometries, incorporates physiological adaptation rules. The developed vascular adaptation model adequately predicted arterial radius and wall thickness compared with ultrasound and MRI estimates, obtained in humans. Our approach could be used as a tool to facilitate personalized modeling, notably in case of missing data, as routinely found in clinical settings.