Patient-specific Computational Fluid Dynamics Simulations Research Articles

Optimizing distal and proximal splenic artery embolization with patient-specific computational fluid dynamics

Splenic artery embolization (SAE) has become a favored alternative to splenectomy, offering a less invasive intervention for injured spleens while preserving spleen function. However, our understanding of the role that hemodynamics plays during embolization remains limited. In this study, we utilized patient-specific computational fluid dynamics (CFD) simulations to study distal and proximal embolization strategies commonly used in SAE. Detailed 3D computer models were constructed considering the descending aorta, various major visceral arteries, and the iliac arteries. Subsequently, the blood flow and pressure associated with different coil placement locations in proximal embolization were studied considering the collateral vessels. Coil induced variations in pressure fields were quantified and compared to baseline. The coil induced flow stagnation was also quantified with particle residence time. Distal embolization was modeled with Lagrangian particle tracking and the effect of particle size, release location, and timing on embolization outcome was studied. Our findings highlight the crucial role of collateral vessels in maintaining blood supply to the spleen following proximal embolization. It was demonstrated that coil location can affect distal pressure and that strategic coil placement guided by patient-specific CFD simulations can further reduce this pressure as desired. Additionally, the results point to the critical roles that particle size, release timing, and location play in distal embolization. Our study provides an early attempt to use patient-specific computer modeling for optimizing embolization strategies and ultimately improving patient outcomes during SAE procedures.

Elevated atrial blood stasis in paroxysmal atrial fibrillation during sinus rhythm: a patient-specific computational fluid dynamics study.

Atrial fibrillation (AF) is associated with an increased risk of stroke, often caused by thrombi that form in the left atrium (LA), and especially in the left atrial appendage (LAA). The underlying mechanism is not fully understood but is thought to be related to stagnant blood flow, which might be present despite sinus rhythm. However, measuring blood flow and stasis in the LAA is challenging due to its small size and low velocities. We aimed to compare the blood flow and stasis in the left atrium of paroxysmal AF patients with controls using computational fluid dynamics (CFD) simulations. The CFD simulations were based on time-resolved computed tomography including the patient-specific cardiac motion. The pipeline allowed for analysis of 21 patients with paroxysmal AF and 8 controls. Stasis was estimated by computing the blood residence time. Residence time was elevated in the AF group (p < 0.001). Linear regression analysis revealed that stasis was strongest associated with LA ejection ratio (p < 0.001, R2 = 0.68) and the ratio of LA volume and left ventricular stroke volume (p < 0.001, R2 = 0.81). Stroke risk due to LA thrombi could already be elevated in AF patients during sinus rhythm. In the future, patient specific CFD simulations may add to the assessment of this risk and support diagnosis and treatment.

Patient-specific computational fluid dynamics for hypertrophic obstructive cardiomyopathy

BackgroundThe heterogeneous morphologic and functional expression of hypertrophic obstructive cardiomyopathy (HOCM) is evidenced by established imaging, multimodality imaging is essential for a comprehensive assessment but may remain uncertain. This study aimed to develop a patient-specific hemodynamics assessment with cardiac computed tomography angiography (CCTA) based computational fluid dynamics (CFD) and prove its usability in cohorts of HOCM patients. MethodsA retrospective study was performed on eight HOCM patients with septal myectomy who had both preoperative and postoperative CCTA as well as transthoracic echocardiography (TTE). The three-dimensional models were reconstructed from CCTA data, following which patient-specific CFD simulations were performed to estimate the blood velocity, pressure gradient, and wall shear stress. The simulation output was compared with TTE. Based on CFD simulations, retrospective and blinded virtual myectomy was also performed, to predict the minimum resected volume for improving obstruction in patients. ResultThe complex HOCM anatomy was successfully reconstructed for all 8 patients. The CFD simulation accurately assessed the pressure gradient, flow velocity. There was a good correlation between the peak pressure gradient measured by CFD and TTE in the pre- and post-operative assessments (r = 0.87 and 0.84, respectively), and the flow velocity (r = 0.87 and 0.90, respectively). The volumes of minimal resection myocardium predicted by CFD and virtual myectomy were consistent with the actual resection volumes. ConclusionCCTA-based CFD for HOCM patients may play a unique role in the assessment of patient-specific morphology and hemodynamics. Combination with virtual myectomy might allow for optimizing therapy planning in septal myectomy. Clinical perspectiveCFD based CCTA may emerge as a complement to established imaging strategies, with accurate three-dimensional reconstruction and hemodynamic simulation of the left ventricle in this retrospective study. Combined with virtual myectomy, CFD simulation might allow for predicting the volume of resected myocardium for septal myectomy. Moving forward, this technology may be used by clinicians to better assess the conditions of HOCM patients, and guide the extent and depth of resection during septal myectomy. Therefore, further prospective clinical evaluation is clearly warranted.

Noninvasive, patient-specific computational fluid dynamics simulations of dural venous sinus pressures in idiopathic intracranial hypertension

BackgroundThe pathophysiology of Idiopathic Intracranial Hypertension (IIH) is poorly understood, making the disease difficult to properly diagnose and treat. Endovascular venous stenting has emerged as an effective non-invasive treatment option for a select cohort of IIH patients with venous sinus stenosis and elevated venous sinus pressure gradient. Unfortunately, current methods of determining patient eligibility for stenting treatment depend on highly invasive and insufficient measurement methods such as venous manometry, which can only measure pressure gradients and not other components of the complex 3D hemodynamic environment. Thus, there is a need for a non-invasive methodology for determining the 3D flow environment of the dural venous sinuses. ObjectiveTo develop a novel method of non-invasive, patient-specific computational fluid dynamic (CFD) simulation of venous sinus hemodynamics for evaluating stenting eligibility. MethodA patient with IIH and elevated sinus pressure gradient underwent MR venography, phase-contrast MR venography, and venous manometry. Patient-specific dural venous anatomy was segmented from the MR venography to construct 3D models of the venous sinuses. 3D transient patient-specific computational fluid dynamic simulations were conducted using flow velocities measured with phase-contrast MR venography as boundary conditions. ResultsSuccessful computational simulations were completed, allowing for the calculation of the spatio-temporal evolution of blood flow through the dural venous sinuses, and the quantitative examination of pressure gradients. Calculated pressure gradients from CFD were validated against venous manometry with an error of only ∼5%. ConclusionsWe have successfully developed time-resolved, patient-specific 3D computational simulations of the dural venous sinuses without assumptions at the boundary conditions for the first time. The methodology can accurately and non-invasively measure venous pressure gradients. This preliminary study serves as a proof of concept for our method to be used as a diagnostic tool for determining venous stenting eligibility, as well as a tool for advancing the general understanding of IIH pathophysiology. Statement of SignificanceThe pathophysiology of Idiopathic Intracranial Hypertension (IIH) is poorly understood making the disease difficult to properly diagnose and treat. Endovascular venous stenting has emerged as an effective non-invasive treatment option for a select cohort of IIH patients with venous sinus stenosis and elevated venous sinus pressure gradient. Our work provides a method for noninvasively determining eligibility for venous sinus stenting, avoiding costly and invasive venous manometry.

Improving the accuracy of computational fluid dynamics simulations of coiled cerebral aneurysms using finite element modeling

Cerebral aneurysms are a serious clinical challenge, with ∼half resulting in death or disability. Treatment via endovascular coiling significantly reduces the chances of rupture, but the techniquehas failure rates of ∼20 %. This presents a pressing need to develop a method fordetermining optimal coildeploymentstrategies. Quantification of the hemodynamics of coiled aneurysms using computational fluid dynamics (CFD) has the potential to predict post-treatment outcomes, but representing the coil mass in CFD simulations remains a challenge. We use the Finite Element Method (FEM) for simulating patient-specific coil deployment for n = 4 ICA aneurysms for which 3D printed in vitro models were also generated, coiled, and scanned using ultra-high resolution synchrotron micro-CT. The physical and virtual coil geometries were voxelized onto a binary structured grid and porosity maps were generated for geometric comparison. The average binary accuracy score is 0.8623 and the average error in porosity map is 4.94 %. We then conduct patient-specific CFD simulations of the aneurysm hemodynamics using virtual coils geometries, micro-CT generated oil geometries, and using the porous medium method to represent the coil mass. Hemodynamic parameters including Neck Inflow Rate (Qneck) and Wall Shear Stress (WSS) were calculated for each of the CFD simulations. The average relative error in Qneck and WSS from CFD using FEM geometry were 6.6 % and 21.8 % respectively, while the error from CFD using a porous media approximation resulted in errors of 55.1 % and 36.3 % respectively; demonstrating a marked improvement in the accuracy of CFD simulations using FEM generated coil geometries.

A fast approach to estimating Windkessel model parameters for patient-specific multi-scale CFD simulations of aortic flow

Computational fluid dynamics (CFD) study of hemodynamics in the aorta can provide a comprehensive analysis of relevant cardiovascular diseases. One trending approach is to couple the three-element Windkessel model with patient-specific CFD simulations to form a multi-scale model that captures more realistic flow fields. However, case-specific parameters (e.g., Rc, Rp, and C) for the Windkessel model must be tuned to reflect patient-specific flow conditions. In this study, we propose a fast approach to estimate these parameters under both physiological and pathological conditions. The approach consists of the following steps: (1) finding geometric resistances for each branch using steady CFD simulation; (2) using the pattern search algorithm from Matlab toolbox to search the parameter spaces by solving the flow circuit system with the consideration of geometric resistances; (3) performing the multi-scale modeling of aortic flow with the optimized Windkessel model parameters. The method was validated through a series of numerical experiments to show flexibility and robustness, including physiological and pathological flow distributions at each downstream branch from healthy or stenosed aortic geometries. This study demonstrates a flexible and computationally efficient way to capture patient-specific hemodynamics in the aorta, facilitating personalized biomechanical analysis of aortic flow.

Irregular anatomical features can alter hemodynamics in Takayasu arteritis

ObjectiveTakayasu arteritis (TA) is a difficult disease to deal with because there are neither reliable clinical signs, laboratory biomarkers, nor a single noninvasive imaging technique that can be used for early diagnosis and disease activity monitoring. Knowledge of aortic hemodynamics in TA is lacking. This study aimed to fill this gap by assessing hemodynamics in patients with TA using image-based computational fluid dynamics (CFD) simulations. MethodsEleven patients with TA were included in the present study. Patient-specific geometries were reconstructed from either clinical aortic computed tomography angiography or magnetic resonance angiography studies and coupled with physiological boundary conditions for CFD simulations. Key anatomical and hemodynamic parameters were compared with a control group consisting of 18 age- and sex-matched adults without TA who had healthy aortas. ResultsCompared with controls, patients with TA had significantly higher aortic velocities (0.9 m/s [0.7, 1.1 m/s] vs 0.6 m/s [0.5, 0.7 m/s]; P = .002), maximum time-averaged wall shear stress (14.2 Pa [9.8, 20.9 Pa] vs 8.0 Pa [6.2, 10.3 Pa]; P = .004), and maximum pressure drops between the ascending and descending aorta (36.9 mm Hg [29.0, 49.3 mm Hg] vs 28.5 mm Hg [25.8, 31.5 mm Hg]; P = .004). These significant hemodynamic alterations in patients with TA might result from abnormal anatomical features including smaller arch diameter (20.0 mm [13.8, 23.3 mm] vs 25.2 mm [23.3, 26.8 mm]; P = .003), supra-aortic branch diameters (21.9 mm [18.5, 24.6 mm] vs 25.7 mm [24.3, 28.3 mm]; P = .003) and descending aorta diameter (14.7 mm [12.2, 16.8 mm] vs 22.5 mm [19.8, 24.0 mm]; P < .001). ConclusionsCFD analysis reveals hemodynamic changes in the aorta of patients with TA. The applicability of CFD technique coupled with standard imaging assessments in predicting disease progression of such patients will be explored in future studies. Future large cohort study with outcome correlation is also warranted. Clinical RelevanceBased on patient-specific computational fluid dynamics simulations, the present retrospective study revealed significant difference in aortic hemodynamics between the patients with and without Takayasu arteritis (TA). To the best of our knowledge, this study is the first to evaluate hemodynamic conditions within TA, demonstrating the potential of computational flow modeling in capturing abnormal hemodynamic forces, such as high wall shear stress, resulted from irregular morphological changes. In the future, assessing the hemodynamic parameters within patients with TA during the prestenotic period, together with longitudinal computational fluid dynamics studies may allow better monitoring and management of TA.

A Novel Patient-Specific Computational Fluid Dynamics Study of the Activation of Primary Collateral Pathways in the Circle of Willis During Vasospasm.

The Circle of Willis (CoW) is a redundant network of blood vessels that perfuses the brain. The ringlike anatomy mitigates the negative effects of stroke by activating collateral pathways that help maintain physiological perfusion. Previous studies have investigated the activation of these pathways during embolic stroke and internal carotid artery occlusion. However, the role of collateral pathways during cerebral vasospasm-an involuntary constriction of blood vessels after subarachnoid hemorrhage-is not well-documented. This study presents a novel technique to create patient-specific computational fluid dynamics (CFD) simulations of the Circle of Willis before and during vasospasm. Computed tomographic angiography (CTA) scans are segmented to model the vasculature, and transcranial Doppler ultrasound (TCD) measurements of blood flow velocity are applied as boundary conditions. Bayesian analysis leverages information about the uncertainty in the measurements of vessel diameters and velocities to find an optimized parameter set that satisfies mass conservation and that is applied in the final simulation. With this optimized parameter set, the diameters, velocities, and flow rates fall within typical literature values. Virtual angiograms modeled using passive scalar transport agree closely with clinical angiography. A sensitivity analysis quantifies the changes in collateral flow rates with respect to changes in the inlet and outlet flow rates. This analysis can be applied in the future to a cohort of patients to investigate the relationship between the locations and severities of vasospasm, the patient-to-patient anatomical variability in the Circle of Willis, and the activation of collateral pathways.

The impact of 4D-Flow MRI spatial resolution on patient-specific CFD simulations of the thoracic aorta

Magnetic Resonance Imaging (MRI) is considered the gold standard of medical imaging technologies as it allows for accurate imaging of blood vessels. 4-Dimensional Flow Magnetic Resonance Imaging (4D-Flow MRI) is built on conventional MRI, and provides flow data in the three vector directions and a time resolved magnitude data set. As such it can be used to retrospectively calculate haemodynamic parameters of interest, such as Wall Shear Stress (WSS). However, multiple studies have indicated that a significant limitation of the imaging technique is the spatiotemporal resolution that is currently available. Recent advances have proposed and successfully integrated 4D-Flow MRI imaging techniques with Computational Fluid Dynamics (CFD) to produce patient-specific simulations that have the potential to aid in treatments,surgical decision making, and risk stratification. However, the consequences of using insufficient 4D-Flow MRI spatial resolutions on any patient-specific CFD simulations is currently unclear, despite being a recognised limitation. The research presented in this study aims to quantify the inaccuracies in patient-specific 4D-Flow MRI based CFD simulations that can be attributed to insufficient spatial resolutions when acquiring 4D-Flow MRI data. For this research, a patient has undergone four 4D-Flow MRI scans acquired at various isotropic spatial resolutions and patient-specific CFD simulations have subsequently been run using geometry and velocity data produced from each scan. It was found that compared to CFD simulations based on a 1.5,{text {mm}} times 1.5,{text {mm}} times 1.5,{text {mm}}, using a spatial resolution of 4,{text {mm}} times 4,{text {mm}} times 4,{text {mm}} substantially underestimated the maximum velocity magnitude at peak systole by 110.55%. The impacts of 4D-Flow MRI spatial resolution on WSS calculated from CFD simulations have been investigated and it has been shown that WSS is underestimated in CFD simulations that are based on a coarse 4D-Flow MRI spatial resolution. The authors have concluded that a minimum 4D-Flow MRI spatial resolution of 1.5,{text {mm}} times 1.5,{text {mm}} times 1.5,{text {mm}} must be used when acquiring 4D-Flow MRI data to perform patient-specific CFD simulations. A coarser spatial resolution will produce substantial differences within the flow field and geometry.

Deep Learning for Computational Hemodynamics: A Brief Review of Recent Advances

Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better understanding various medical conditions, designing more effective drug delivery systems, and developing novel diagnostic methods and treatments. However, despite significant advances in computational technology and resources, the expensive computational cost of these simulations still hinders their transformation from a research interest to a clinical tool. This bottleneck is even more severe for image-based, patient-specific CFD simulations with realistic boundary conditions and complex computational domains, which make such simulations excessively expensive. To address this issue, deep learning approaches have been recently explored to accelerate computational hemodynamics simulations. In this study, we review recent efforts to integrate deep learning with CFD and discuss the applications of this approach in solving hemodynamics problems, such as blood flow behavior in aorta and cerebral arteries. We also discuss potential future directions in the field. In this review, we suggest that incorporating physiologic understandings and underlying fluid mechanics laws in deep learning models will soon lead to a paradigm shift in the development novel non-invasive computational medical decisions.

Patient-specific computational fluid dynamic simulation of cerebrospinal fluid flow in the intracranial space

BackgroundAbnormal cerebrospinal fluid (CSF) flow is associated with a variety of poorly understood neurological disorders such as Alzheimer’s Disease and hydrocephalus. The lack of comprehensive understanding of the fluid and solid mechanics of CSF flow remains a critical barrier in the development of diagnostic assessment and potential treatment options for these diseases. We have developed a whole brain, patient-specific computational fluid dynamics (CFD) simulation of CSF flow in the cranial cavity as a step towards comprehensive understanding of CSF dynamics and how they relate to neurodegenerative diseases. MethodsA patient-specific 3D geometry of the CSF filled spaces was segmented from structural MRI. Patient-specific boundary conditions were measured using phase contrast MRI. A rigid wall three-dimensional CFD simulation was conducted using only patient-specific waveforms as boundary conditions. Deformation of brain tissue is accounted for using volumetric flowrate boundary conditions calculated via the conservation of mass. Phase contrast MRI measurement of maximum velocity at the cerebral aqueduct was used to validate the simulation with excellent agreement. ResultsThe CSF dynamics across the cardiac cycle are presented, illustrating the relationship between arterial flow and CSF flow. Flow in and out of the ventricles was shown to have a slight phase delay (∼20 % of the cardiac cycle) from flow in the subarachnoid space. Intracranial pressure dynamics are presented, with pressure in the Lateral Ventricles demonstrating less significant transient effects than pressure in the subarachnoid space. ConclusionsThis work presents a quantitatively validated whole-brain simulation of CSF flow for a single healthy subject. The computational methodology improves over the state of the art by eliminating non-physiological boundary conditions and unnecessary assumptions about the mechanical properties of brain tissue, providing an essential step towards clinically useful tools for assessing the development of neurodegenerative disorders.

Computational Investigation of Anastomosis Options of a Right-Heart Pump to Patient Specific Pulmonary Arteries.

Patients with Fontan circulation have increased risk of heart failure, but are not always candidates for heart transplant, leading to the development of the subpulmonic Penn State Fontan Circulation Assist Device. The aim of this study was to use patient-specific computational fluid dynamics simulations to evaluate anastomosis options for implanting this device. Simulations were performed of the pre-surgical anatomy as well as four surgical options: a T-junction and three Y-grafts. Cases were evaluated based on several fluid-dynamic quantities. The impact of imbalanced left-right pulmonary flow distribution was also investigated. Results showed that a 12-mm Y-graft was the most energy efficient. However, an 8-mm graft showed more favorable wall shear stress distribution, indicating lower risk of thrombosis and endothelial damage. The 8-mm Y-grafts also showed a more balanced pulmonary flow split, and lower residence time, also indicating lower thrombosis risk. The relative performance of the surgical options was largely unchanged whether or not the pulmonary vascular resistance remained imbalanced post-implantation.

A New Method for Quantifying Abdominal Aortic Wall Shear Stress Using Phase Contrast Magnetic Resonance Imaging and the Womersley Solution.

Wall shear stress (WSS) is an important mediator of cardiovascular pathologies and there is a need for its reliable evaluation as a potential prognostic indicator. The purpose of this work was to develop a method that quantifies WSS from two-dimensional (2D) phase contrast magnetic resonance (PCMR) imaging derived flow waveforms, apply this method to PCMR data acquired in the abdominal aorta of healthy volunteers, and to compare PCMR-derived WSS values to values predicted from a computational fluid dynamics (CFD) simulation. The method uses PCMR-derived flow versus time waveforms constrained by the Womersley solution for pulsatile flow in a cylindrical tube. The method was evaluated for sensitivity to input parameters, intrastudy repeatability and was compared with results from a patient-specific CFD simulation. 2D-PCMR data were acquired in the aortas of healthy men (n = 12) and women (n = 15) and time-averaged WSS (TAWSS) was compared. Agreement was observed when comparing TAWSS between CFD and the PCMR flow-based method with a correlation coefficient of 0.88 (CFD: 15.0 ± 1.9 versus MRI: 13.5 ± 2.4 dyn/cm2) though comparison of WSS values between the PCMR-based method and CFD predictions indicate that the PCMR method underestimated instantaneous WSS by 3.7 ± 7.6 dyn/cm2. We found no significant difference in TAWSS magnitude between the sexes; 8.19 ± 2.25 versus 8.07 ± 1.71 dyn/cm2, p = 0.16 for men and women, respectively.

Wall shear stress gradient is independently associated with middle cerebral artery aneurysm development: a case-control CFD patient-specific study based on 77 patients

BackgroundPreviously published computational fluid dynamics (CFD) studies regarding intracranial aneurysm (IA) formation present conflicting results. Our study analysed the involvement of the combination of high wall shear stress (WSS) and a positive WSS gradient (WSSG) in IA formation.MethodsWe designed a case-control study with a selection of 38 patients with an unruptured middle cerebral artery (MCA) aneurysm and 39 non-aneurysmal controls to determine the involvement of WSS, oscillatory shear index (OSI), the WSSG and its absolute value (absWSSG) in aneurysm formation based on patient-specific CFD simulations using velocity profiles obtained from transcranial colour-coded sonography.ResultsAmong the analysed parameters, only the WSSG had significantly higher values compared to the controls (11.05 vs − 14.76 [Pa/mm], P = 0.020). The WSS, absWSSG and OSI values were not significantly different between the analysed groups. Logistic regression analysis identified WSS and WSSG as significant co-predictors for MCA aneurysm formation, but only the WSSG turned out to be a significant independent prognosticator (OR: 1.009; 95% CI: 1.001–1.017; P = 0.025). Significantly more patients (23/38) in the case group had haemodynamic regions of high WSS combined with a positive WSSG near the bifurcation apex, while in the control group, high WSS was usually accompanied by a negative WSSG (14/39). From the analysis of the ROC curve for WSSG, the area under the curve (AUC) was 0.654, with the optimal cut-off value −0.37 Pa/mm. The largest AUC was recognised for combined WSS and WSSG (AUC = 0.671). Our data confirmed that aneurysms tend to form near the bifurcation apices in regions of high WSS values accompanied by positive WSSG.ConclusionsThe development of IAs is determined by an independent effect of haemodynamic factors. High WSS impacts MCA aneurysm formation, while a positive WSSG mainly promotes this process.

Patient-Specific Computational Fluid Dynamics Reveal Localized Flow Patterns Predictive of Post-Left Ventricular Assist Device Aortic Incompetence.

Progressive aortic valve disease has remained a persistent cause of concern in patients with left ventricular assist devices. Aortic incompetence (AI) is a known predictor of both mortality and readmissions in this patient population and remains a challenging clinical problem. Ten left ventricular assist device patients with de novo aortic regurgitation and 19 control left ventricular assist device patients were identified. Three-dimensional models of patients' aortas were created from their computed tomography scans, following which large-scale patient-specific computational fluid dynamics simulations were performed with physiologically accurate boundary conditions using the SimVascular flow solver. The spatial distributions of time-averaged wall shear stress and oscillatory shear index show no significant differences in the aortic root in patients with and without AI (mean difference, 0.67 dyne/cm2 [95% CI, -0.51 to 1.85]; P=0.23). Oscillatory shear index was also not significantly different between both groups of patients (mean difference, 0.03 [95% CI, -0.07 to 0.019]; P=0.22). The localized wall shear stress on the leaflet tips was significantly higher in the AI group than the non-AI group (1.62 versus 1.35 dyne/cm2; mean difference [95% CI, 0.15-0.39]; P<0.001), whereas oscillatory shear index was not significantly different between both groups (95% CI, -0.009 to 0.001; P=0.17). Computational fluid dynamics serves a unique role in studying the hemodynamic features in left ventricular assist device patients where 4-dimensional magnetic resonance imaging remains unfeasible. Contrary to the widely accepted notions of highly disturbed flow, in this study, we demonstrate that the aortic root is a region of relatively stagnant flow. We further identified localized hemodynamic features in the aortic root that challenge our understanding of how AI develops in this patient population.

Patient-specific computational fluid dynamic simulation for assessing hemodynamic changes following branched endovascular aneurysm repair: A pilot study

Abstract Objective This pilot study assessed the hypothesis that patient-specific computational fluid dynamic (CFD) modelling can detect aortic branch hemodynamic changes following branched endovascular aneurysm repair (bEVAR). Methods Patients who underwent bEVAR with the Jotec E-xtra Design for thoracoabdominal aortic aneurysms were retrospectively selected. Using open-source SimVascular software, pre- and post-operative aortic finite element volume meshes were constructed from CT imaging. Pulsatile in-flow conditions were derived and adjusted for patient-specific clinical variables. Outlet boundary conditions consisted of Windkessel models approximated from physiologic flow splits. Rigid wall flow simulations were then performed on pre- and post-operative models with equivalent boundary conditions. Computations were performed with an incompressible Navier-Stokes flow solver on a 72-core cluster. Results Pre- and post-operative flow simulations were performed on 10 patients undergoing bEVAR with a total of 40 target vessels (10 celiac, 20 superior mesenteric, 20 renal stents). Compared to pre-operative values, bEVAR was associated with a decrease in peak renal artery pressure (116.8 ± 11.5 vs 112.8 ± 11.6 mmHg, p&amp;lt;.001) and flow rate (13.7 ± 2.3 vs 12.9 ± 2.4 ml/s, p&amp;lt;.001). No post-operative differences were observed in pressure or flow rates in the celiac or mesenteric arteries (p=.10-.55). Representative perfusion waveforms from a single patient are shown in Figure 1. bEVAR resulted in a significant increase in aortic (1.4 ± 0.5 vs 4.3 ± 2.9 dynes/cm2, p=.009) and renal artery (24.3 ± 7.1 vs 35.4 ± 12.4 dynes/cm2, p=.23) wall shear stress; however, these values remained within the physiologic range. In certain graft configurations, 3D visualization of blood flow streamlines revealed areas of turbulent flow at the origin of external branches which were associated with decreased target artery perfusion (Figure 2). Conclusion Changes in para-visceral aortic geometry after bEVAR is associated with a decrease in computationally estimated renal perfusion, without significant changes to celiac or mesenteric hemodynamics. Further CFD simulation-based studies are needed to assess whether changes in branch configuration or hemodynamics after bEVAR can predict loss of branch patency.

In-Stent Restenosis Progression in Human Superficial Femoral Arteries: Dynamics of Lumen Remodeling and Impact of Local Hemodynamics

In-stent restenosis (ISR) represents a major drawback of stented superficial femoral arteries (SFAs). Motivated by the high incidence and limited knowledge of ISR onset and development in human SFAs, this study aims to (i) analyze the lumen remodeling trajectory over 1-year follow-up period in human stented SFAs and (ii) investigate the impact of altered hemodynamics on ISR initiation and progression. Ten SFA lesions were reconstructed at four follow-ups from computed tomography to quantify the lumen area change occurring within 1-year post-intervention. Patient-specific computational fluid dynamics simulations were performed at each follow-up to relate wall shear stress (WSS) based descriptors with lumen remodeling. The largest lumen remodeling was found in the first post-operative month, with slight regional-specific differences (larger inward remodeling in the fringe segments, p < 0.05). Focal re-narrowing frequently occurred after 6 months. Slight differences in the lumen area change emerged between long and short stents, and between segments upstream and downstream from stent overlapping portions, at specific time intervals. Abnormal patterns of multidirectional WSS were associated with lumen remodeling within 1-year post-intervention. This longitudinal study gave important insights into the dynamics of ISR and the impact of hemodynamics on ISR progression in human SFAs.

Identification of intra-individual variation in intracranial arterial flow by MRI and the effect on computed hemodynamic descriptors.

To determine the intra-individual flow variation in serially acquired studies, and the influence of this variation on subsequent hemodynamic simulations using the inlet flow as a boundary condition. Author: Kindly check and confirm whether the corresponding authors are correctly identified.Confirmed. This prospective study included 51 patients (37 females and 14 males) with unruptured intracranial aneurysms who have received more than three times follow-up of 2D phase-contrast MR. The flow and velocity parameters were extracted to calculate the reproducibility and variation. Patient-specific computational fluid dynamics simulations were performed using the measured flows. Intraclass correlation coefficients for mean and maximum velocity and flow parameters ranged from 0.77 to 0.90. A 10% CV of mean flow was identified. Variations of 10% in inlet flow resulted in hemodynamic changes including 41.41% of peak systolic wall shear stress; 39.13% of end-diastolic wall shear stress; 2.79% of low shear area at peak systole; 2.12% of low shear area at end diastole: 47.57% of time-averaged wall shear stress; and 0.17% of oscillatory shear index. This study identified 10% of intra-individual mean flow variation on phase-contrast MR. Intra-individual flow variation resulted in a non-negligible variation in wall shear stress, but relatively small variation in low shear area in hemodynamic calculations.

Patient-specific CFD simulation of aerodynamics for nasal pathology: a combined computational and experimental study

ABSTRACT The aim of this study was to develop and verify a personalised approach for simulating the aerodynamic flow patterns using patient-specific data of a severe form of nasal obstruction during inspiration. The reconstruction of the 3D geometry of the nasal cavity based on the computer images of a patient diagnosed with the unilateral nasal valve collapse and S-shaped septum deviation was used to perform the Computational Fluid Dynamics (CFD) simulation of airflow. A comparative study of the airflow with standard data (SD) and personal input data (PD) of mass flow rate was carried out. In both cases, the air streamlines went straight along the lower and middle nasal passages on the non-deviated septum side. The peak velocity increased in two cavities, mostly on the septum deviation side, while the peak pressure inversely dropped. . With personal data, the peak velocity and pressure values varied greatly in different parts of the nasal cavity, depending on the particular local anatomy. In a patient with unilateral nasal valve collapse and S-shaped septum deviation, the use of personal data does not have an impact on the streamline’s direction, longitudinal velocity, and pressure distributions but it significantly changed the local velocity and pressure in the nasal cavity.

Baseline local hemodynamics as predictor of lumen remodeling at 1-year follow-up in stented superficial femoral arteries

In-stent restenosis (ISR) is the major drawback of superficial femoral artery (SFA) stenting. Abnormal hemodynamics after stent implantation seems to promote the development of ISR. Accordingly, this study aims to investigate the impact of local hemodynamics on lumen remodeling in human stented SFA lesions. Ten SFA models were reconstructed at 1-week and 1-year follow-up from computed tomography images. Patient-specific computational fluid dynamics simulations were performed to relate the local hemodynamics at 1-week, expressed in terms of time-averaged wall shear stress (TAWSS), oscillatory shear index and relative residence time, with the lumen remodeling at 1-year, quantified as the change of lumen area between 1-week and 1-year. The TAWSS was negatively associated with the lumen area change (ρ = − 0.75, p = 0.013). The surface area exposed to low TAWSS was positively correlated with the lumen area change (ρ = 0.69, p = 0.026). No significant correlations were present between the other hemodynamic descriptors and lumen area change. The low TAWSS was the best predictive marker of lumen remodeling (positive predictive value of 44.8%). Moreover, stent length and overlapping were predictor of ISR at follow-up. Despite the limited number of analyzed lesions, the overall findings suggest an association between abnormal patterns of WSS after stenting and lumen remodeling.