Computational fluid dynamics simulation to evaluate aortic coarctation gradient with contrast-enhanced CT

Application feasibility of virtual models and computational fluid dynamics for the planning and evaluation of aortic repair surgery for Williams syndrome

BACKGROUND

Accurate diagnosis and evaluation of Williams Syndrome (WS) are essential yet challenging for effective surgical management. This study aimed to quantify the hemodynamic changes of surgical repair for WS through virtual surgery and computational fluid dynamics (CFD) for surgical guidance and postoperative evaluation.

METHODS

A patient preliminarily diagnosed with WS was included in this study. 3D model alongside hemodynamic analysis was used to guide and evaluate the surgical procedure. Preoperative, predictive and postoperative models were created and analyzed using CFD. Key parameters, including blood flow velocity, pressure differences, wall shear stress, and other critical factors, were assessed to evaluate the surgery's effectiveness.

RESULTS

In the hemodynamics analysis, the CFD results of predictive model and postoperative model demonstrated a high level of consistency, and showed significant differences compared to the preoperative model. The velocity at the stenosis on the aorta decreased from 5.6 m/s before the operation to 1.6 m/s in the virtual model and 1.5 m/s in the postoperative model. Surgical repair increased the proportion of outlet flow of the descending aorta (dAo) from 28.7% to 35.5%.

CONCLUSIONS

Virtual surgery and CFD can predict surgical outcomes, enabling doctors to optimize and rehearse the procedure before the actual surgery. The method of predicting surgery through virtual surgery and CFD is accurate and feasible.

TRIAL REGISTRATION

Registered by the Ethics Committee of Peking University International Hospital (No. IRB2019-062).

Assessment of turbulent blood flow and wall shear stress in aortic coarctation using image-based simulations

In this study, we analyzed turbulent flows through a phantom (a 180[Formula: see text] bend with narrowing) at peak systole and a patient-specific coarctation of the aorta (CoA), with a pulsating flow, using magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). For MRI, a 4D-flow MRI is performed using a 3T scanner. For CFD, the standard [Formula: see text], shear stress transport [Formula: see text], and Reynolds stress (RSM) models are applied. A good agreement between measured and simulated velocity is obtained for the phantom, especially for CFD with RSM. The wall shear stress (WSS) shows significant differences between CFD and MRI in absolute values, due to the limited near-wall resolution of MRI. However, normalized WSS shows qualitatively very similar distributions of the local values between MRI and CFD. Finally, a direct comparison between in vivo 4D-flow MRI and CFD with the RSM turbulence model is performed in the CoA. MRI can properly identify regions with locally elevated or suppressed WSS. If the exact values of the WSS are necessary, CFD is the preferred method. For future applications, we recommend the use of the combined MRI/CFD method for analysis and evaluation of the local flow patterns and WSS in the aorta.

Accelerated Estimation of Pulmonary Artery Stenosis Pressure Gradients with Distributed Lumped Parameter Modeling vs. 3D CFD with Instantaneous Adaptive Mesh Refinement: Experimental Validation in Swine

Branch pulmonary artery stenosis (PAS) commonly occurs in congenital heart disease and the pressure gradient over a stenotic PA lesion is an important marker for re-intervention. Image based computational fluid dynamics (CFD) has shown promise for non-invasively estimating pressure gradients but one limitation of CFD is long simulation times. The goal of this study was to compare accelerated predictions of PAS pressure gradients from 3D CFD with instantaneous adaptive mesh refinement (AMR) versus a recently developed 0D distributed lumped parameter CFD model. Predictions were then experimentally validated using a swine PAS model (n = 13). 3D CFD simulations with AMR improved efficiency by 5 times compared to fixed grid CFD simulations. 0D simulations further improved efficiency by 6 times compared to the 3D simulations with AMR. Both 0D and 3D simulations underestimated the pressure gradients measured by catheterization (- 1.87 ± 4.20 and - 1.78 ± 3.70 mmHg respectively). This was partially due to simulations neglecting the effects of a catheter in the stenosis. There was good agreement between 0D and 3D simulations (ICC 0.88 [0.66-0.96]) but only moderate agreement between simulations and experimental measurements (0D ICC 0.60 [0.11-0.86] and 3D ICC 0.66 [0.21-0.88]). Uncertainty assessment indicates that this was likely due to limited medical imaging resolution causing uncertainty in the segmented stenosis diameter in addition to uncertainty in the outlet resistances. This study showed that 0D lumped parameter models and 3D CFD with instantaneous AMR both improve the efficiency of hemodynamic modeling, but uncertainty from medical imaging resolution will limit the accuracy of pressure gradient estimations.

A Patient-Specific CFD Pipeline Using Doppler Echocardiography for Application in Coarctation of the Aorta in a Limited Resource Clinical Context

Congenital heart disease (CHD) is the most common birth defect globally and coarctation of the aorta (CoA) is one of the commoner CHD conditions, affecting around 1/1800 live births. CoA is considered a CHD of critical severity. Unfortunately, the prognosis for a child born in a low and lower-middle income country (LLMICs) with CoA is far worse than in a high-income country. Reduced diagnostic and interventional capacities of specialists in these regions lead to delayed diagnosis and treatment, which in turn lead to more cases presenting at an advanced stage. Computational fluid dynamics (CFD) is an important tool in this context since it can provide additional diagnostic data in the form of hemodynamic parameters. It also provides an in silico framework, both to test potential procedures and to assess the risk of further complications arising post-repair. Although this concept is already in practice in high income countries, the clinical infrastructure in LLMICs can be sparse, and access to advanced imaging modalities such as phase contrast magnetic resonance imaging (PC-MRI) is limited, if not impossible. In this study, a pipeline was developed in conjunction with clinicians at the Red Cross War Memorial Children’s Hospital, Cape Town and was applied to perform a patient-specific CFD study of CoA. The pipeline uses data acquired from CT angiography and Doppler transthoracic echocardiography (both much more clinically available than MRI in LLMICs), while segmentation is conducted via SimVascular and simulation is realized using OpenFOAM. The reduction in cost through use of open-source software and the use of broadly available imaging modalities makes the methodology clinically feasible and repeatable within resource-constrained environments. The project identifies the key role of Doppler echocardiography, despite its disadvantages, as an intrinsic component of the pipeline if it is to be used routinely in LLMICs.

HEMODYNAMIC STUDY OF CORONARY ARTERY ANEURYSMS

Background: When the coronary artery expands more than two times its diameter, it will form a coronary artery aneurysm (CAA). CAA can lead to myocardial ischemia. In this paper, the mechanism of myocardial ischemia induced by CAA was studied by geometric multiscale method. Methods: Four kinds of three-dimensional models of CAA with different dilation diameters were established on the basis of normal three-dimensional models. The dilation diameters were 2, 3, 5 and 7 times, capacitance was added after the CAA to simulate the elasticity of the vascular wall. Results:A large number of eddies exist in CAA. 2–7 times model: 1.1–14.4% reduction of blood flow downstream of CAA and 5, 7 times model showed upstream diastolic backward flow, the backward flow rate was 1.1% and 5.6%, respectively. The aveWSS at the CAA was 1.76–0.35[Formula: see text]Pa; the relative retention time was 1.1–14.6[Formula: see text]Pa[Formula: see text]; the average vorticity was 0.0085–231.7[Formula: see text]s[Formula: see text]. Conclusion:CAA can store blood, and the elasticity of the wall of CAA results in the flow of blood upstream. These two reasons make the downstream flow of CAA decrease and easily form intratumoral thrombosis, which may lead to myocardial ischemia.

Image quality and radiation dose of ECG-triggered High-Pitch Dual-Source cardiac computed tomography angiography in children for the evaluation of central vascular stents

Assess image quality and radiation dose of ECG-triggered High-Pitch Dual-Source CTA for the evaluation central vascular stents in children. We included all children ≤ 21 years old with one or more central vascular stents and available prospective ECG-triggered High-Pitch Dual-Source CTA performed at our institution between January 2015 and August 2017. Demographic and scanner information was retrieved. Two board-certified pediatric radiologists blinded to the clinical data, independently reviewed and scored each case using a four-point quality score. Scores 1, 2 and 3 were considered of diagnostic image quality. Inter-observer agreement and non-parametric test were used. 18 patients (10 girls, 8 boys) with a mean age of 9.47 ± 7.38 years (mean ± SD) met inclusion criteria. Thirty-two central vascular stents were evaluated. Mean quality score was 2.07 ± 0.94 with 12.5% (4/32) of the cases classified as unevaluable. Interobserver agreement was excellent (k = 0.86). There is no significant difference between quality score and stent location (p = 0.07). There is a significant difference with stent material as all non-diagnostic scores were only seen in covered stents made of platinum-iridium (p < 0.001). There was no association between image quality and age, height, weight, BSA, heart rate, radiation dose or stent lumen size (p > 0.05). ECG-triggered high-pitch spiral DS-CTA offers appropriate image quality for assessment of central vascular stents in children.

Virtual medicine: Utilization of the advanced cardiac imaging patient avatar for procedural planning and facilitation

Advances in imaging technology have led to a paradigm shift from planning of cardiovascular procedures and surgeries requiring the actual patient in a "brick and mortar" hospital to utilization of the digitalized patient in the virtual hospital. Cardiovascular computed tomographic angiography (CCTA) and cardiovascular magnetic resonance (CMR) digitalized 3-D patient representation of individual patient anatomy and physiology serves as an avatar allowing for virtual delineation of the most optimal approaches to cardiovascular procedures and surgeries prior to actual hospitalization. Pre-hospitalization reconstruction and analysis of anatomy and pathophysiology previously only accessible during the actual procedure could potentially limit the intrinsic risks related to time in the operating room, cardiac procedural laboratory and overall hospital environment. Although applications are specific to areas of cardiovascular specialty focus, there are unifying themes related to the utilization of technologies. The virtual patient avatar computer can also be used for procedural planning, computational modeling of anatomy, simulation of predicted therapeutic result, printing of 3-D models, and augmentation of real time procedural performance. Examples of the above techniques are at various stages of development for application to the spectrum of cardiovascular disease processes, including percutaneous, surgical and hybrid minimally invasive interventions. A multidisciplinary approach within medicine and engineering is necessary for creation of robust algorithms for maximal utilization of the virtual patient avatar in the digital medical center. Utilization of the virtual advanced cardiac imaging patient avatar will play an important role in the virtual health care system. Although there has been a rapid proliferation of early data, advanced imaging applications require further assessment and validation of accuracy, reproducibility, standardization, safety, efficacy, quality, cost effectiveness, and overall value to medical care.

Model-Based Therapy Planning Allows Prediction of Haemodynamic Outcome after Aortic Valve Replacement

Optimizing treatment planning is essential for advances in patient care and outcomes. Precisely tailored therapy for each patient remains a yearned-for goal. Cardiovascular modelling has the potential to simulate and predict the functional response before the actual intervention is performed. The objective of this study was to proof the validity of model-based prediction of haemodynamic outcome after aortic valve replacement. In a prospective study design virtual (model-based) treatment of the valve and the surrounding vasculature were performed alongside the actual surgical procedure (control group). The resulting predictions of anatomic and haemodynamic outcome based on information from magnetic resonance imaging before the procedure were compared to post-operative imaging assessment of the surgical control group in ten patients. Predicted vs. post-operative peak velocities across the valve were comparable (2.97 ± 1.12 vs. 2.68 ± 0.67 m/s; p = 0.362). In wall shear stress (17.3 ± 12.3 Pa vs. 16.7 ± 16.84 Pa; p = 0.803) and secondary flow degree (0.44 ± 0.32 vs. 0.49 ± 0.23; p = 0.277) significant linear correlations (p < 0.001) were found between predicted and post-operative outcomes. Between groups blood flow patterns showed good agreement (helicity p = 0.852, vorticity p = 0.185, eccentricity p = 0.333). Model-based therapy planning is able to accurately predict post-operative haemodynamics after aortic valve replacement. These validated virtual treatment procedures open up promising opportunities for individually targeted interventions.