Patient-specific Boundary Conditions Research Articles

Computational Lower Limb Simulator Boundary Conditions to Reproduce Measured TKA Loading in a Cohort of Telemetric Implant Patients.

Recent advancements in computational modeling offer opportunities to refine total knee arthroplasty (TKA) design and treatment strategies. This study developed patient-specific simulator external boundary conditions (EBCs) using a PID-controlled lower limb finite element (FE) model. Calibration of the external actuation required to achieve measured patient-specific joint loading and motion was completed for nine patients with telemetric implants during gait, stair descent, and deep knee bend. The study also compared two EBC scenarios: activity-specific hip AP motion and pelvic rotation (that was averaged across all patients for an activity) and patient-specific hip AP motion and pelvic rotation. Including patient-specific data significantly improved reproduction of joint-level loading, reducing root mean squared error between the target and achieved loading by 28.7% and highlighting the importance of detailed patient data in replicating joint kinematics and kinetics. The principal component analysis (PCA) of the EBCs for the patient dataset showed that one component represented 77.8% of the overall variation, while the first three components represented 97.8%. Given the significant loading variability within the patient cohort, this group of patient-specific models can be run individually to provide insight into expected TKA mechanics variability, and the PCA can be utilized to further create reasonable EBCs that expand the variability evaluated.

Using DFT on ultrasound measurements to determine patient-specific blood flow boundary conditions for computational hemodynamics of intracranial aneurysms

Boundary conditions (BCs) is one pivotal factor influencing the accuracy of hemodynamic predictions on intracranial aneurysms (IAs) using computational fluid dynamics (CFD) modeling. Unfortunately, a standard procedure to secure accurate BCs for hemodynamic modeling does not exist. To bridge such a knowledge gap, two representative patient-specific IA models (Case-I and Case-II) were reconstructed and their blood flow velocity waveforms in the internal carotid artery (ICA) were measured by ultrasonic techniques and modeled by discrete Fourier transform (DFT). Then, numerical investigations were conducted to explore the appropriate number of samples (N) for DFT modeling to secure the accurate BC by comparing a series of hemodynamic parameters using in-vitro validated CFD modeling. Subsequently, a comprehensive comparison in hemodynamic characteristics under patient-specific BCs and a generalized BC based on a one-dimensional (1D) model was conducted to reinforce the understanding that a patient-specific BC is pivotal for accurate hemodynamic risk evaluations on IA pathophysiology. In addition, the influence of the variance of heart rate/cardiac pulsatile period on hemodynamic characteristics in IA models was studied preliminarily. The results showed that N ≥ 16 for DFT model is a decent choice to secure the proper BC profile to calculate time-averaged hemodynamic parameters, while more data points such as N ≥ 36 can ensure the accuracy of instantaneous hemodynamic predictions. In addition, results revealed the generalized BC could overestimate or underestimate the hemodynamic risks on IAs significantly; thus, patient-specific BCs are highly recommended for hemodynamic modeling for IA risk evaluation. Furthermore, this study discovered the variance of heart rate has rare influences on hemodynamic characteristics in both instantaneous and time-averaged parameters under the assumption of an identical blood flow rate.

Are hemodynamics responsible for inflammatory changes in venous vessel walls? A quantitative study of wall-enhancing intracranial arteriovenous malformation draining veins.

Signal enhancement of vascular walls on vessel wall MRI might be a biomarker for inflammation. It has been theorized that contrast enhancement on vessel wall imaging (VWI) in draining veins of intracranial arteriovenous malformations (AVMs) may be associated with disease progression and development of venous stenosis. The aim of this study was to investigate the relationship between vessel wall enhancement and hemodynamic stressors along AVM draining veins. Eight AVM patients with 15 draining veins visualized on VWI were included. Based on MR venography data, patient-specific 3D surface models of the venous anatomy distal to the nidus were segmented. The enhanced vascular wall regions were manually extracted and mapped onto the venous surface models after registration of image data. Using image-based blood flow simulations applying patient-specific boundary conditions based on phase-contrast quantitative MR angiography, hemodynamics were investigated in the enhanced vasculature. For the shear-related parameters, time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT) were calculated. Velocity, oscillatory velocity index (OVI), and vorticity were extracted for the intraluminal flow-related hemodynamics. Visual observations demonstrated overlap of enhancement with local lower shear stresses resulting from decreased velocities. Thus, higher RRT values were measured in the enhanced areas. Furthermore, nonenhancing draining veins showed on average slightly higher flow velocities and TAWSS. Significant decreases of 55% (p = 0.03) for TAWSS and of 24% (p = 0.03) for vorticity were identified in enhanced areas compared with near distal and proximal domains. Velocity magnitude in the enhanced region showed a nonsignificant decrease of 14% (p = 0.06). Furthermore, increases were present in the OSI (32%, p = 0.3), RRT (25%, p = 0.15), and OVI (26%, p = 0.3) in enhanced vessel sections, although the differences were not significant. This novel multimodal investigation of hemodynamics in AVM draining veins allows for precise prediction of occurring shear- and flow-related phenomena in enhanced vessel walls. These findings may suggest low shear to be a local predisposing factor for venous stenosis in AVMs.

Effects of preoperative aortic tortuosity and postoperative hypertension on patient-specific hemodynamics of abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a serious dilated vascular disease. The risk factors of aneurysm rupture and postoperative blood pressure are the major clinical concerns. The purpose of this work is to analyze the hemodynamic difference between preoperative and postoperative AAA using patient-specific boundary conditions and explore the rupture risk of AAA with different torsion and to simulate the blood flow of different degrees of hypertension. A three-element Windkessel model is utilized as the outlet boundary condition. 20-sim software and self-developed user-defined functions are used to calibrate the parameters. To analyze the influence of aortic tortuosity on hemodynamics, five AAA geometries with different torsion degrees are modified and obtained. We also grade the hypertension and explore the effect of hypertension after operation. The analysis results are consistent with the patient-specific situation. The results show that stent implantation for aneurysms reduces the pressure at the lesion site and increase the speed and wall shear stress. Vessels with high torsion have lower time-averaged wall shear stress (TAWSS), higher oscillatory shear stress index (OSI) and relative retention time, and more disordered blood flow. After stent implantation, with the increase in blood pressure, TAWSS and OSI continue to increase, and the blood flow speed is also faster. AAA with high torsion is more likely to rupture. In clinical practice, attention should be paid to the degree of torsion of the lesion site. Furthermore, blood pressure should be monitored and controlled in time to prevent postoperative complications.

Multi-Dimensional Modeling of Cerebral Hemodynamics: A Systematic Review.

The Circle of Willis (CoW) describes the arterial system in the human brain enabling the neurovascular blood supply. Neurovascular diseases like intracranial aneurysms (IAs) can occur within the CoW and carry the risk of rupture, which can lead to subarachnoid hemorrhage. The assessment of hemodynamic information in these pathologies is crucial for their understanding regarding detection, diagnosis and treatment. Multi-dimensional in silico approaches exist to evaluate these hemodynamics based on patient-specific input data. The approaches comprise low-scale (zero-dimensional, one-dimensional) and high-scale (three-dimensional) models as well as multi-scale coupled models. The input data can be derived from medical imaging, numerical models, literature-based assumptions or from measurements within healthy subjects. Thus, the most realistic description of neurovascular hemodynamics is still controversial. Within this systematic review, first, the models of the three scales (0D, 1D, 3D) and second, the multi-scale models, which are coupled versions of the three scales, were discussed. Current best practices in describing neurovascular hemodynamics most realistically and their clinical applicablility were elucidated. The performance of 3D simulation entails high computational expenses, which could be reduced by analyzing solely the region of interest in detail. Medical imaging to establish patient-specific boundary conditions is usually rare, and thus, lower dimensional models provide a realistic mimicking of the surrounding hemodynamics. Multi-scale coupling, however, is computationally expensive as well, especially when taking all dimensions into account. In conclusion, the 0D-1D-3D multi-scale approach provides the most realistic outcome; nevertheless, it is least applicable. A 1D-3D multi-scale model can be considered regarding a beneficial trade-off between realistic results and applicable performance.

Standardized viscosity as a source of error in computational fluid dynamic simulations of cerebral aneurysms.

Computational fluid dynamics (CFD) simulations are a powerful tool for studying cerebral aneurysms, capable of evaluating hemodynamics in a way that is infeasible with imaging alone. However, the difficulty of incorporating patient-specific information and inherent obstacles of in vivo validation have limited the clinical usefulness of CFD of cerebral aneurysms. In this work we investigate the effect of using standardized blood viscosity values in CFD simulations of cerebral aneurysms when compared to simulations of the same aneurysms using patient-specific viscosity values derived from hematocrit measurements. The objective of this work is to determine the level of error, on average, that is, caused by using standardized values of viscosity in CFD simulations of cerebral aneurysms. By quantifying this error, we demonstrate the need for incorporating patient-specific viscosity in future CFD investigations of cerebral aneurysms. CFD simulations of forty-one cerebral aneurysms were conducted using patient-specific boundary conditions. For each aneurysm two simulations were conducted, one utilizing patient-specific blood viscosity derived from hematocrit measurements and another using a standardized value for blood viscosity. Hemodynamic parameters such as wall shear stress (WSS), wall shear stress gradient (WSSG), and the oscillatory shear index (OSI) were calculated for each of the simulations for each aneurysm. Paired t-tests for differences in the time-averaged maps of these hemodynamic parameters between standardized and patient-specific viscosity simulations were conducted for each aneurysm. Bland-Altman analysis was used to examine the cohort-wide changes in the hemodynamic parameters. Subjects were broken into two groups, those with higher than standard viscosity and those with lower than standard viscosity. An unpaired t-test was used to compare the percent change in WSS, WSSG, and OSI between patient-specific and standardized viscosity simulations for the two cohorts. The percent changes in hemodynamic parameters were correlated against the direction and magnitude of percent change in viscosity, aneurysm size, and aneurysm location. For all t-tests, a Bonferroni-corrected significance level of 0.0167 was used. 63.2%, 41.5%, and 48.7% of aneurysms showed statistically significant differences between patient-specific and standardized viscosity simulations for WSS, WSSG, and OSI respectively. No statistically significant difference was found in the percent changes in WSS, WSSG, and OSI between the group with higher than standard viscosity and those with lower than standard viscosity, indicating an increase in viscosity can cause either an increase or decrease in each of the hemodynamic parameters. On a study-wide level no significant bias was found in either direction for WSS, WSSG, or OSI between the simulation groups due to the bidirectional effect of changing viscosity. No correlation was found between percent change of viscosity and percent change of WSS, WSSG, or OSI, meaning an after-the-fact correction for patient-specific viscosity is not feasible. Standardizing viscosity values in CFD of cerebral aneurysms has a large and unpredictable impact on the calculated WSS, WSSG, and OSI when compared to CFD simulations of the same aneurysms using a patient-specific viscosity. We recommend implementing hematocrit-based patient-specific blood viscosity values for all CFD simulations of cerebral aneurysms.

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

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

Numerical investigation of unruptured middle cerebral artery bifurcation aneurysms: influence of aspect ratio

An aneurysm is a disease condition, which is due to the pathological weakening of an arterial wall. These aneurysms are often found in various branch points and bifurcations of an artery in the cerebral circulation. Most aneurysms come to medical attention, either due to brain hemorrhages caused by rupture or found unruptured. To consider surgically invasive treatment modalities, clinicians need scientific methods such as, hemodynamic analysis to assess rupture risk. The arterial wall loses its structural integrity when wall shear stress (WSS) and other hemodynamic parameters exceed a certain threshold. In the present study, numerical simulations are carried out for unruptured middle cerebral artery (MCA) aneurysms. Three distinct representative sizes are chosen from a larger patient pool of 26 MCA aneurysms. Logically, these aneurysms represent three growth stages of any patient with similar anatomical structure. Simulations are performed to compare the three growth phases (with different aspect ratios) of an aneurysm and correlate their hemodynamic parameters. Simulations with patient specific boundary conditions reveal that, aneurysms with a higher aspect ratio (AR) correspond to an attendant decrease in both time-averaged wall shear stress (TAWSS) and spatial wall shear stress gradients (WSSG). Smaller MCAs were observed to have higher positive wall shear stress divergence (WSSD), exemplifying the tensile nature of arterial wall stretching. Present study identifies positive wall shear stress divergence (PWSSD) to be a potential biomarker for evaluating the growth of an aneurysm.

Hemodynamics in AVF over time: A protective role of vascular remodeling toward flow stabilization.

The mechanisms underlying vascular stenosis formation in the arteriovenous fistula (AVF) for hemodialysis (HD) remain mostly unknown. Several computational fluid dynamics (CFD) studies have suggested a potential role for unsteady flow in inducing intimal hyperplasia and AVF stenosis, but the majority of these observations have been limited to a single time point after surgical creation. The aim of the present study was to investigate the relation between hemodynamic conditions and AVF vascular remodeling through a CFD longitudinal study. Non contrast-enhanced MR images and Doppler Ultrasound (US) examinations were acquired at 3 days, 40 days, 6 months, 1 year, and 1.5 years after surgery in a 72-year male referred for native radio-cephalic AVF. Three-dimensional AVF models were generated and high fidelity CFD simulations were performed using pimpleFoam, setting patient-specific boundary conditions derived from US. Morphological and hemodynamic changes over time were then analyzed. Analysis of vessel morphology and hemodynamics during follow-up showed that the AVF had a successful maturation process, characterized by a massive arterial and venous dilatation within the 6 months after surgery, a corresponding increase in blood flow volume and important flow instabilities. Between 6 months and 1 year, a stenosis developed in the juxta-anastomotic vein and caused AVF failure at 1.5 years. The development of stenosis was paralleled by the regularization of blood flow velocity pattern and consequent decrease in the near-wall disturbed flow metrics. These results suggest that development of intimal hyperplasia and vessel stenosis, triggered by unsteady flow, could be the result of vascular inward remodeling toward regularization of turbulent-like flow.

Assessing the impact of turbulent kinetic energy boundary conditions on turbulent flow simulations using computational fluid dynamics

Computational fluid dynamics has been widely used to study hemodynamics, but accurately determining boundary conditions for turbulent blood flow remains challenging. This study aims to investigate the effect of patient-specific turbulence boundary conditions on the accuracy of turbulent flow simulation. Using a stenosis model with 50% severity in diameter, the post-stenosis turbulence flow region was simulated with different planes to obtain inlet boundary conditions and simulate downstream flows. The errors of simulated flow fields obtained with turbulence kinetic energy (TKE) boundary data and arbitrary turbulence intensity were compared. Additionally, the study tested various TKE data resolutions and noise levels to simulate experimental environments. The mean absolute error of velocity and TKE was investigated with various turbulence intensities and TKE mapping. While voxel size and signal-to-noise ratio of the TKE data affected the results, simulation with SNR > 5 and voxel size < 10% resulted in better accuracy than simulations with turbulence intensities. The simulation with appropriate TKE boundary data resulted in a more accurate velocity and turbulence field than those with arbitrary turbulence intensity boundary conditions. The study demonstrated the potential improvement of turbulent blood flow simulation with patient-specific turbulence boundary conditions, which can be obtained from recent measurement techniques.

Mechanism of blood flow energy loss in real healthy aorta using computational fluid-structure interaction framework

Blood flow energy loss may correlate with the occurrence of vascular diseases. However, the mechanism of blood flow energy loss is still not fully explored. The objective of the present study is to reveal the mechanism of energy loss of blood flow in the healthy aorta. Two patients without aortic diseases are retrospectively screened from a clinical hospital. The computed tomography image is used to inversely reconstruct a three-dimensional geometric model of the healthy aorta. Non-invasive clinical measurements are applied to determine patient-specific boundary conditions. The fluid-structure interaction method is adopted to acquire high-resolution hemodynamics. A novel method is proposed to calculate the blood flow energy loss caused by aortic wall deformation. The distribution of blood flow validates the accuracy of the above computational framework, which could capture more than 90% of blood flow energy loss. Viscous friction of blood flow is the primary cause of energy loss, followed by aortic wall deformation, and finally turbulent dissipation. Energy loss due to viscous friction and wall deformation mainly occurs on the aortic vessel wall. The sum of these two energy losses approximates the total energy loss and may be associated with the initiation of aortic lesions. Besides, we find that the buffering efficiency of the real healthy aorta is about 80%. The mechanism of aortic blood flow energy loss is uncovered and these findings would inform the new hemodynamic markers and clinical assessment tool for the vascular wall.

Abstract P1048: Lattice-Boltzmann Method Achieves Feasible Hemodynamic Analysis In Carotid Atherosclerosis With Low Computational Cost

Introduction: Atherosclerosis is a common cardiovascular pathophysiology that can lead to plaque-related complications, including stroke and myocardial infarction. Non-invasive hemodynamic analysis can provide valuable insights into the plaque's rupture vulnerability and growth progression. Computational fluid dynamics is widely studied to understand hemodynamic pathophysiology further; however, traditional computational fluid dynamics methods often require daily-based analysis time to visualize hemodynamic parameters. This study investigated the feasibility of using the lattice Boltzmann method (LBM) for hemodynamic analysis of atherosclerosis lesions. Methods: From ten carotid artery stenosis patients, 20 carotid artery models were generated and analyzed using LBM. Hemodynamic parameters, including time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT), were compared between the stenotic lesion and contralateral control sides. The patient-specific boundary conditions were applied. Their cardiac cycle was subdivided into three periods: systolic acceleration, systolic deceleration, and diastolic, and analyzed to investigate their relationship with the hemodynamic parameters. Results: LBM effectively captured the hemodynamic parameters associated with carotid atherosclerosis with an hourly-based computational cost (2.765 [2.435-3.233] hours). The analysis visualized high TAWSS and low RRT distribution at stenotic areas during the systolic deceleration period and low TAWSS and high RRT distribution at the post-stenotic distal lesion during the diastolic period. These findings were reproducible among the ten patients. Conclusion: LBM-based hemodynamic analysis has the potential to serve as a non-invasive diagnostic tool that can help understand atherosclerosis pathophysiology with low computational cost.

Computational modeling of hemodynamics and risk of thrombosis in the left atrial appendage using patient-specific blood viscosity and boundary conditions at the mitral valve.

Hemodynamics play a vital role for the risk of thrombosis in the left atrial appendage (LAA) and left atrium (LA) for patients with atrial fibrillation. Accurate prediction of hemodynamics in the LA can provide important guidance for assessing the risk of thrombosis in the LAA. Patient specificity is a crucial factor in representing the true hemodynamic fields. In this study, we investigated the effects of blood rheology (as a function of hematocrit and shear rate), as well as patient-specific mitral valve (MV) boundary conditions (MV area and velocity profiles measured by ultrasound) on the hemodynamics and thrombosis potential of the LAA. Four scenarios were setup with different degrees of patient specificity. Though using a constant blood viscosity can classify the thrombus and non-thrombus patients for all the hemodynamic indicators, the risk of thrombosis was underestimated for all patients compared with patient-specific viscosities. The results with least patient specificities showed that patients prone to thrombosis predicted by three hemodynamic indicators were inconsistent with clinical observations. Moreover, though patients had the same MV inlet flow rate, different MV models lead to different trends in the risk of thrombosis in different patients. We also found that endothelial cell activation potential and relative residence time can effectively distinguish thrombus and non-thrombus patients for all the scenarios, relatively insensitive to patient specificities. Overall, the findings of this study provide useful insights on patients-specific hemodynamic simulations of the LA.

Calibration of patient-specific boundary conditions for coupled CFD models of the aorta derived from 4D Flow-MRI.

Introduction: Patient-specific computational fluid dynamics (CFD) models permit analysis of complex intra-aortic hemodynamics in patients with aortic dissection (AD), where vessel morphology and disease severity are highly individualized. The simulated blood flow regime within these models is sensitive to the prescribed boundary conditions (BCs), so accurate BC selection is fundamental to achieve clinically relevant results. Methods: This study presents a novel reduced-order computational framework for the iterative flow-based calibration of 3-Element Windkessel Model (3EWM) parameters to generate patient-specific BCs. These parameters were calibrated using time-resolved flow information derived from retrospective four-dimensional flow magnetic resonance imaging (4D Flow-MRI). For a healthy and dissected case, blood flow was then investigated numerically in a fully coupled zero dimensional-three dimensional (0D-3D) numerical framework, where the vessel geometries were reconstructed from medical images. Calibration of the 3EWM parameters was automated and required ~3.5 min per branch. Results: With prescription of the calibrated BCs, the computed near-wall hemodynamics (time-averaged wall shear stress, oscillatory shear index) and perfusion distribution were consistent with clinical measurements and previous literature, yielding physiologically relevant results. BC calibration was particularly important in the AD case, where the complex flow regime was captured only after BC calibration. Discussion: This calibration methodology can therefore be applied in clinical cases where branch flow rates are known, for example, via 4D Flow-MRI or ultrasound, to generate patient-specific BCs for CFD models. It is then possible to elucidate, on a case-by-case basis, the highly individualized hemodynamics which occur due to geometric variations in aortic pathology high spatiotemporal resolution through CFD.

Use of high-speed angiography HSA-derived boundary conditions and Physics Informed Neural Networks (PINNs) for comprehensive estimation of neurovascular hemodynamics.

Physics-informed neural networks (PINNs) and computational fluid dynamics (CFD) have both demonstrated an ability to derive accurate hemodynamics if boundary conditions (BCs) are known. Unfortunately, patient-specific BCs are often unknown, and assumptions based upon previous investigations are used instead. High speed angiography (HSA) may allow extraction of these BCs due to the high temporal fidelity of the modality. We propose to investigate whether PINNs using convection and Navier-Stokes equations with BCs derived from HSA data may allow for extraction of accurate hemodynamics in the vasculature. Imaging data generated from in vitro 1000 fps HSA, as well as simulated 1000 fps angiograms generated using CFD were utilized for this study. Calculations were performed on a 3D lattice comprised of 2D projections temporally stacked over the angiographic sequence. A PINN based on an objective function comprised of the Navier-Stokes equation, the convection equation, and angiography-based BCs was used for estimation of velocity, pressure and contrast flow at every point in the lattice. Imaging-based PINNs show an ability to capture such hemodynamic phenomena as vortices in aneurysms and regions of rapid transience, such as outlet vessel blood flow within a carotid artery bifurcation phantom. These networks work best with small solution spaces and high temporal resolution of the input angiographic data, meaning HSA image sequences represent an ideal medium for such solution spaces. The study shows the feasibility of obtaining patient-specific velocity and pressure fields using an assumption-free data driven approach based purely on governing physical equations and imaging data.

Influence of abdominal aortic aneurysm shape on hemodynamics in human aortofemoral arteries: A transient open-loop study

New imaging methods have enabled the detection of unruptured abdominal aortic aneurysms (AAA). It is necessary to develop appropriate mathematical models for rupture prediction to allow a proper patient treatment plan. To provide valid hemodynamic parameters, high-fidelity numerical models with patient-specific boundary conditions are needed. Researchers have pointed out in recent research articles and reviews that those morphological parameters, such as shape, dilation ratio, neck angle, common iliac bifurcation angle, and AAA type, consistently correlate with the rupture mechanism. However, it is unclear how morphological indicators affect hemodynamics-based computational fluid dynamics predictions. The present work investigates the influence of AAA shape on local and global hemodynamics parameters and rupture predictions. Five cases of magnetic resonance imaging scan-based data for patient-specific aortofemoral artery modeling are explored. The inflow conditions are patient-specific, and an open loop system has been considered to model all five cases. Hemodynamics parameters in pulsating conditions, such as wall shear stress (WSS), velocity contour, time average WSS (TAWSS), oscillatory shear index (OSI), vorticity, and streamlines, are computed and investigated. Both maximum dilation diameter and aneurysm neck angle are found to have substantial effects on local hemodynamics parameters. The magnitude of WSS, TAWSS, and OSI increases and decreases non-linearly with a change in maximum diameter during the cardiac process. Also, aneurysms with doubly titled and completely saccular shape show complex streamlines, low WSS, and high residence time in the sac area of the wall.

The Influence of Minor Aortic Branches in Patient-Specific Flow Simulations of Type-B Aortic Dissection

Type-B aortic dissection (TBAD) is a disease in which a tear develops in the intimal layer of the descending aorta forming a true lumen and false lumen (FL). Because disease outcomes are thought to be influenced by haemodynamic quantities such as pressure and wall shear stress (WSS), their analysis via numerical simulations may provide valuable clinical insights. Major aortic branches are routinely included in simulations but minor branches are virtually always neglected, despite being implicated in TBAD progression and the development of complications. As minor branches are estimated to carry about 7–21% of cardiac output, neglecting them may affect simulation accuracy. We present the first simulation of TBAD with all pairs of intercostal, subcostal and lumbar arteries, using 4D-flow MRI (4DMR) to inform patient-specific boundary conditions. Compared to an equivalent case without minor branches, their inclusion improved agreement with 4DMR velocities, reduced time-averaged WSS (TAWSS) and transmural pressure and elevated oscillatory shear in regions where FL dilatation and calcification were observed in vivo. Minor branch inclusion resulted in differences of 60-75% in these metrics of potential clinical relevance, indicating a need to account for minor branch flow loss if simulation accuracy is sought.

Workflow Comparison for Combined 4D MRI/CFD Patient-Specific Cardiovascular Flow Simulations of the Thoracic Aorta

AbstractComputational fluid dynamics (CFD) has been widely used to predict and understand cardiovascular flows. However, the accuracy of CFD predictions depends on faithful reconstruction of patient vascular anatomy and accurate patient-specific inlet and outlet boundary conditions. 4-Dimensional magnetic resonance imaging (4D MRI) can provide patient-specific data to obtain the required geometry and time-dependent flow boundary conditions for CFD simulations, and can further be used to validate CFD predictions. This work presents a framework to combine both spatiotemporal 4D MRI data and patient monitoring data with CFD simulation workflows. To assist practitioners, all aspects of the modeling workflow, from geometry reconstruction to results postprocessing, are illustrated and compared using three software packages (ansys, comsol, SimVascular) to predict hemodynamics in the thoracic aorta. A sensitivity analysis with respect to inlet boundary condition is presented. Results highlight the importance of 4D MRI data for improving the accuracy of flow predictions on the ascending aorta and the aortic arch. In contrast, simulation results for the descending aorta are less sensitive to the patient-specific inlet boundary conditions.

Non-invasive estimation of the parameters of a three-element windkessel model of aortic arch arteries in patients undergoing thoracic endovascular aortic repair.

Background: Image-based computational hemodynamic modeling and simulations are important for personalized diagnosis and treatment of cardiovascular diseases. However, the required patient-specific boundary conditions are often not available and need to be estimated. Methods: We propose a pipeline for estimating the parameters of the popular three-element Windkessel (WK3) models (a proximal resistor in series with a parallel combination of a distal resistor and a capacitor) of the aortic arch arteries in patients receiving thoracic endovascular aortic repair of aneurysms. Pre-operative and post-operative 1-week duplex ultrasound scans were performed to obtain blood flow rates, and intra-operative pressure measurements were also performed invasively using a pressure transducer pre- and post-stent graft deployment in arch arteries. The patient-specific WK3 model parameters were derived from the flow rate and pressure waveforms using an optimization algorithm reducing the error between simulated and measured pressure data. The resistors were normalized by total resistance, and the capacitor was normalized by total resistance and heart rate. The normalized WK3 parameters can be combined with readily available vessel diameter, brachial blood pressure, and heart rate data to estimate WK3 parameters of other patients non-invasively. Results: Ten patients were studied. The medians (interquartile range) of the normalized proximal resistor, distal resistor, and capacitor parameters are 0.10 (0.07-0.15), 0.90 (0.84-0.93), and 0.46 (0.33-0.58), respectively, for common carotid artery; 0.03 (0.02-0.04), 0.97 (0.96-0.98), and 1.91 (1.63-2.26) for subclavian artery; 0.18 (0.08-0.41), 0.82 (0.59-0.92), and 0.47 (0.32-0.85) for vertebral artery. The estimated pressure showed fairly high tolerance to patient-specific inlet flow rate waveforms using the WK3 parameters estimated from the medians of the normalized parameters. Conclusion: When patient-specific outflow boundary conditions are not available, our proposed pipeline can be used to estimate the WK3 parameters of arch arteries.

A hybrid hierarchical strategy for registration of 7T TOF-MRI to 7T PC-MRI intracranial vessel data

Purpose7T time-of-flight (TOF) MRI provides high resolution for the evaluation of cerebrovascular vessels and pathologies. In combination with 4D flow fields acquired with phase-contrast (PC) MRI, hemodynamic information can be extracted to enhance the analysis by providing direct measurements in the larger arteries or patient-specific boundary conditions. Hence, a registration between both modalities is required.MethodsTo combine TOF and PC-MRI data, we developed a hybrid registration approach. Vessels and their centerlines are segmented from the TOF data. The centerline is fit to the intensity ridges of the lower resolved PC-MRI data, which provides temporal information. We used a metric that utilizes a scaled sum of weighted intensities and gradients on the normal plane. The registration is then guided by decoupled local affine transformations. It is applied hierarchically following the branching order of the vessel tree.ResultsA landmark validation over Monte Carlo simulations yielded an average mean squared error of 184.73 mm and an average Hausdorff distance of 15.20 mm. The hierarchical traversal that transforms child vessels with their parents registers even small vessels not detectable in the PC-MRI.ConclusionThe presented work combines high-resolution tomographic information from 7T TOF-MRI and measured flow data from 4D 7T PC-MRI scan for the arteries of the brain. This enables usage of patient-specific flow parameters for realistic simulations, thus supporting research in areas such as cerebral small vessel disease. Automatization and free deformations can help address the limiting error measures in the future.