Patient-specific analysis of the hemodynamic performance of surgical and transcatheter aortic valve replacements

Aortic valve (AV) diseases are life-threatening conditions which affect millions of people worldwide and, if left untreated, can lead to death a few years after symptom onset. Patients affected by AV diseases are commonly referred to surgical AV replacement (SAVR). However, more than 30% of patients are not suitable for SAVR. For this reason, transcatheter aortic valve implantation (TAVI) has been attracting growing interest. Several clinical studies compared the outcomes of these techniques, showing that TAVI could be a valid alternative to SAVR. However, there is a lack of detailed knowledge about changes in the aortic hemodynamic conditions following these procedures. The main aim of this thesis is to develop efficient and robust methodologies to study and compare the influences of different AV replacement procedures on aortic hemodynamics. An image-based patient-specific computational model has been developed, which uses magnetic resonance images (MRI) acquired from patients to obtain realistic geometry and boundary conditions (BCs) for computational fluid dynamics (CFD) analysis. The implemented physiological BCs were compared with the most commonly used inlet and outlet BCs, and showed the best agreement with in vivo data. The model was then applied to study and compare SAVR, TAVI and aortic root replacement using a variety of prostheses. In addition, an experimental set-up was designed to further study TAVI hemodynamics by combining 3D-printing, 4D flow MRI and CFD. Finally, a preliminary analysis of valve leaflet thrombosis was conducted. It has been shown that both TAVI and SAVR are able to greatly improve the aortic hemodynamics, but this often deviates from conditions in healthy volunteers, with the extent of abnormalities strongly dependent on the type of prostheses or valve disease. The work also demonstrated the feasibility of predicting valve leaflet thrombosis using a shear-driven model for thrombus formation and growth.Open Acces

Qualitative and quantitative assessments of blood flow on tears in type B aortic dissection with different morphologies

Objective: The interactions between aortic morphology and hemodynamics play a key role in determining type B aortic dissection (TBAD) progression and remodeling. The study aimed to provide qualitative and quantitative hemodynamic assessment in four different TBAD morphologies based on 4D flow MRI analysis. Materials and Methods: Four patients with different TBAD morphologies underwent CT and 4D flow MRI scans. Qualitative blood flow evaluation was performed by visualizing velocity streamlines and flow directionality near the tears. Quantitative analysis included flow rate, velocity and reverse flow index (RFI) measurements. Statistical analysis was performed to evaluate hemodynamic differences between the true lumen (TL) and false lumen (FL) of patients. Results: Qualitative analysis revealed blood flow splitting near the primary entry tears (PETs), often causing the formation of vortices in the FL. All patients exhibited clear hemodynamic differences between TL and FL, with the TL generally showing higher velocities and flow rates, and lower RFIs. Average velocity magnitude measurements were significantly different for Patient 1 (t = 5.61, p = 0.001), Patient 2 (t = 3.09, p = 0.02) and Patient 4 (t = 2.81, p = 0.03). At follow-up, Patient three suffered from left renal ischemia because of FL collapse. This patient presented a complex morphology with two FLs and marked flow differences between TL and FLs. In Patient 4, left renal artery malperfusion was observed at the 32-months follow-up, due to FL thrombosis growing after PET repair. Conclusion: The study demonstrates the clinical feasibility of using 4D flow MRI in the context of TBAD. Detailed patient-specific hemodynamics assessment before treatment may provide useful insights to better understand this pathology in the future

Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta

Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoracic aortic aneurysms (ATAA). To accurately reproduce hemodynamics, computational fluid dynamics (CFD) models must employ realistic inflow boundary conditions (BCs). However, the limited availability of in vivo velocity measurements still makes researchers resort to idealized BCs. In this study we generated and thoroughly characterized a large dataset of synthetic 4D aortic velocity profiles suitable to be used as BCs for CFD simulations. 4D flow MRI scans of 30 subjects with ATAA were processed to extract cross-sectional planes along the ascending aorta, ensuring spatial alignment among all planes and interpolating all velocity fields to a reference configuration. Velocity profiles of the clinical cohort were extensively characterized by computing flow morphology descriptors of both spatial and temporal features. By exploiting principal component analysis (PCA), a statistical shape model (SSM) of 4D aortic velocity profiles was built and a dataset of 437 synthetic cases with realistic properties was generated. Comparison between clinical and synthetic datasets showed that the synthetic data presented similar characteristics as the clinical population in terms of key morphological parameters. The average velocity profile qualitatively resembled a parabolic-shaped profile, but was quantitatively characterized by more complex flow patterns which an idealized profile would not replicate. Statistically significant correlations were found between PCA principal modes of variation and flow descriptors. We built a data-driven generative model of 4D aortic velocity profiles, suitable to be used in computational studies of blood flow. The proposed software system also allows to map any of the generated velocity profiles to the inlet plane of any virtual subject given its coordinate set.Comment: 21 pages, 5 figures, 2 tables To be submitted to "Computer methods and programs in biomedicine" Scripts: https://github.com/saitta-s/flow4D Synthetic velocity profiles: //doi.org/10.5281/zenodo.725198

Aortic haemodynamics and wall stress analysis following arch aneurysm repair using a single-branched endograft

IntroductionThoracic endovascular aortic repair (TEVAR) of the arch is challenging given its complex geometry and the involvement of supra-aortic arteries. Different branched endografts have been designed for use in this region, but their haemodynamic performance and the risk for post-intervention complications are not yet clear. This study aims to examine aortic haemodynamics and biomechanical conditions following TVAR treatment of an aortic arch aneurysm with a two-component single-branched endograft.MethodsComputational fluid dynamics and finite element analysis were applied to a patient-specific case at different stages: pre-intervention, post-intervention and follow-up. Physiologically accurate boundary conditions were used based on available clinical information.ResultsComputational results obtained from the post-intervention model confirmed technical success of the procedure in restoring normal flow to the arch. Simulations of the follow-up model, where boundary conditions were modified to reflect change in supra-aortic vessel perfusion observed on the follow-up scan, predicted normal flow patterns but high levels of wall stress (up to 1.3M MPa) and increased displacement forces in regions at risk of compromising device stability. This might have contributed to the suspected endoleaks or device migration identified at the final follow up.DiscussionOur study demonstrated that detailed haemodynamic and biomechanical analysis can help identify possible causes for post-TEVAR complications in a patient-specific setting. Further refinement and validation of the computational workflow will allow personalised assessment to aid in surgical planning and clinical decision making

4-D Flow MRI-Based Computational Analysis of Blood Flow in Patient-Specific Aortic Dissection

Computational hemodynamic studies of aortic dissections usually combine patient-specific geometries with idealized or generic boundary conditions. In this study, we present a comprehensive methodology for the simulation of hemodynamics in type B aortic dissection (TBAD), based on fully patient-specific boundary conditions

Aortic flow and morphology adaptation to deconditioning after 21-days of head-down bed-rest assessed by phase contrast MRI

Our aim was to assess the effects of 21-days head-down (-6 degrees) bed-rest (BR) and effectiveness of sledge jump countermeasure (CM), on aortic flow and morphology by Phase Contrast (PC) MRI. Male subjects were enrolled at :envihub (DLR, Germany) in control (CTRL, N=12) or countermeasure (CM, N=12) groups. PC-MRI images were obtained before and after 21-days of BR, and analyzed with custom software. Semi-automated region growing and thresholding were applied to segment the aortic lumen, and to compute parameters from velocity images: area lumen (AL), flow velocity, stroke volume (SV), flow rate (Qpeak), time-to-peak flow, systolic duration and heart beat duration (RR). After 21 days, in CTRL significant decreases in SV (14%), Qpeak (5%) and AL (4%) were observed compared to baseline values. Conversely, for CM no changes were observed in these parameters, but only in RR (-8%). Cardiac adaptation to deconditioning due to immobilization resulted in a reduction of SV and Qpeak that might have induced a remodeling process in the ascending aorta, by shrinking of its lumen. The applied CM seemed to counteract at least partially these effects.SCOPUS: cp.pinfo:eu-repo/semantics/publishe

Hemodynamic evaluation using four-dimensional flow magnetic resonance imaging for a patient with multichanneled aortic dissection

The hemodynamic function of multichanneled aortic dissection (MCAD) requires close monitoring and effective management to avoid potentially catastrophic sequelae. This report describes a 47-year-old man who underwent endovascular repair based on findings from four-dimensional (4D) flow magnetic resonance imaging of an MCAD. The acquired 4D flow data revealed complex, bidirectional flow patterns in the false lumens and accelerated blood flow in the compressed true lumen. The collapsed abdominal true lumen expanded unsatisfactorily after primary tear repair, which required further remodeling with bare stents. This case study demonstrates that hemodynamic analysis using 4D flow magnetic resonance imaging can help understand the complex pathologic changes of MCAD

Effect of Vessel Tortuosity on Stress Concentration at the Distal Stent–Vessel Interface: Possible Link With New Entry Formation Through Biomechanical Simulation

A computational approach is used to investigate potential risk factors for distal stent graft-induced new entry (dSINE) in aortic dissection (AD) patients. Patient-specific simulations were performed based on computed tomography images acquired from six AD patients (three dSINE and three non-dSINE) to analyze the correlation between anatomical characteristics and stress/strain distributions. Sensitivity analysis was carried out using idealized models to independently assess the effect of stent graft length, stent tortuosity and wedge apposition angle at the landing zone on key biomechanical variables. Mismatch of biomechanical properties between the stented and nonstented regions led to high stress at the distal stent graft–vessel interface in all patients, as well as shear strain in the neighboring region, which coincides with the location of tear formation. Stress was observed to increase with the increase of stent tortuosity (from 263 kPa at a tortuosity angle of 50 deg to 313 kPa at 30 deg). It was further amplified by stent graft landing at the inflection point of a curve. Malapposition of the stent graft led to an asymmetrical segment within the aorta, therefore changing the location and magnitude of the maximum von Mises stress substantially (up to +25.9% with a +25 deg change in the distal wedge apposition angle). In conclusion, stent tortuosity and wedge apposition angle serve as important risk predictors for dSINE formation in AD patients