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

Mini-sternotomy vs right anterior thoracotomy for aortic valve replacement.

BACKGROUND: While minimally invasive techniques for aortic valve replacement (AVR) have been shown to be safe, limited data exist comparing the varying approaches. This study aimed to compare the outcomes between two minimally invasive approaches for AVR: mini-sternotomy (MS) and right anterior thoracotomy (RAT). MATERIALS AND METHODS: A systematic search of MEDLINE, EMBASE, and OVID was conducted for the period 1990-2019. Nine observational studies (n = 2926 patients) met the inclusion criteria. RESULTS: There was no difference in operative mortality between MS and RAT (odds ratio [OR]: 0.87, 95% confidence interval [CI]: 0.41-1.85; P = .709). Meta-analyses favored MS over RAT in reoperation for bleeding (OR: 0.42, 95% CI: 0.28-0.63; P < .001), aortic cross-clamp time (standardized mean difference [SMD]: -0.12, 95% CI: -0.20 to 0.029; P = .009), and the rate of conversion to sternotomy (OR: 0.32, 95% CI: 0.11-0.93; P = .036). The rate of permanent pacemaker insertion approached borderline significance in favor of MS (OR: 0.54, 95% CI: 0.26-1.12; P = .097). In-hospital outcomes of stroke, atrial fibrillation, and surgical site infection were similar between the two groups. The length of hospital stay was shorter for RAT (SMD: 0.12, 95% CI: 0.027-0.22; P = .012) and the length of postoperative ventilation was borderline significant in favor of RAT (SMD: 0.16, 95% CI: -0.027 to 0.34; P = .095). CONCLUSIONS: This study highlights important differences in short-term outcomes between MS and RAT as approaches for AVR. This has important implications for patient selection, especially in the elderly, where such approaches are becoming more common-place

Consensus statement on aortic valve replacement via an anterior right minithoracotomy in the UK healthcare setting

The wide uptake of anterior right thoracotomy (ART) as an approach for aortic valve replacement (AVR) has been limited despite initial reports of its use in 1993. Compared with median sternotomy, and even ministernotomy, ART is considered to be less traumatic to the chest wall and to help facilitate quicker patient recovery. In this statement, a consensus agreement is outlined that describes the potential benefits of the ART AVR. The technical considerations that require specific attention are described and the initiation of an ART programme at a UK centre is recommended through simulation and/or use of specialist instruments in conventional cases. The use of soft tissue retractors, peripheral cannulation, modified aortic clamping and the use of intraoperative adjuncts, such as sutureless valves and/or automated knot fasteners, are important to consider in order to circumvent the challenges of minimal the altered exposure via an ART.A coordinated team-based approach that encourages ownership of the programme by team members is critical. A designated proctor/mentor is also recommended. The organisation of structured training and simulation, as well as planning the initial cases are important steps to consider

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

Background and Objective: Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoratic aortic aneurysms (ATAA). To accurately reproduce in vivo 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. The aim of this study was to generate and thoroughly characterize a large dataset of synthetic 4D aortic velocity profiles sampled on a 2D cross-section along the ascending aorta with features similar to clinical cohorts of patients with ATAA. Methods: Time-resolved 3D phase contrast magnetic resonance (4D flow MRI) scans of 30 subjects with ATAA were processed through in-house code to extract anatomically consistent 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. Results: 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. Conclusions: We built a data-driven generative model of 4D aortic inlet 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.</p