Ascending thoracic aorta aneurysm repair induces positive hemodynamic outcomes in a patient with unchanged bicuspid aortic valve

Pathophysiology of the ascending aorta: Impact of dilation and valve phenotype on large-scale blood flow coherence detected by 4D flow MRI

BACKGROUND AND OBJECTIVE

The evidence on the role of hemodynamics in aorta pathophysiology has yet to be robustly translated into clinical applications, to improve risk stratification of aortic diseases. Motivated by the need to enrich the current understanding of the pathophysiology of the ascending aorta (AAo), this study evaluates in vivo how large-scale aortic flow coherence is affected by AAo dilation and aortic valve phenotype.

METHODS

A complex networks-based approach is applied to 4D flow MRI data to quantify subject-specific AAo flow coherence in terms of correlation between axial velocity waveforms and the aortic flow rate waveform along the cardiac cycle. The anatomical length of persistence of such correlation is quantified using the recently proposed network metric average weighted curvilinear distance (AWCD). The analysis considers 107 subjects selected to allow an ample stratification in terms of aortic valve morphology, absence/presence of AAo dilation and of aortic valve stenosis.

RESULTS

The analysis highlights that the presence of AAo dilation as well as of bicuspid aortic valve phenotype breaks the physiological AAo flow coherence, quantified in terms of AWCD. Of notice, it emerges that cycle-average blood flow rate and relative AAo dilation are main determinants of AWCD, playing opposite roles in promoting and hampering the persistence of large-scale flow coherence in AAo, respectively.

CONCLUSIONS

The findings of this study can contribute to broaden the current mechanistic link between large-scale blood flow coherence and aortic pathophysiology, with the prospect of enriching the existing tools for the in vivo non-invasive hemodynamic risk assessment for aortic diseases onset and progression.

Non-invasive diagnostics of blockage growth in the descending aorta-computational approach

Atherosclerosis causes blockages to the main arteries such as the aorta preventing blood flow from delivering oxygen to the organs. Non-invasive diagnosis of these blockages is difficult, particularly in primary healthcare. In this paper, the effect of arterial blockage development and growth is investigated at the descending aorta on some possible non-invasive assessment parameters including the blood pressure waveform, wall shear stress (WSS), time-average WSS (TAWSS) and the oscillation shear index (OSI). Blockage severity growth is introduced in a simulation model as 25%, 35%, 50% and 65% stenosis at the descending aorta based on specific healthy control aorta data clinically obtained. A 3D aorta model with invasive pulsatile waveforms (blood flow and pressure) is used in the CFD simulation. Blockage severity is assessed by using blood pressure measurements at the left subclavian artery. An arterial blockage growth more than 35% of the lumen diameter significantly affects the pressure. A strong correlation is also observed between the ascending aorta pressure values, pressure at the left subclavian artery and the relative residence time (RRT). An increase of RRT downstream from the stenosis indicates a 35% stenosis at the descending aorta which results in high systolic and diastolic pressure readings. The findings of this study could be further extended by transferring the waveform reading from the left subclavian artery to the brachial artery.

Graphical abstract

Interaction of the Blood Components with Ascending Thoracic Aortic Aneurysm Wall: Biomechanical and Fluid Analyses

BACKGROUND

Ascending thoracic aortic aneurysm (ATAA) is an asymptomatic localized dilation of the aorta that is prone to rupture with a high rate of mortality. While diameter is the main risk factor for rupture assessment, it has been shown that the peak wall stress from finite element (FE) simulations may contribute to refinement of clinical decisions. In FE simulations, the intraluminal boundary condition is a single-phase blood flow that interacts with the thoracic aorta (TA). However, the blood is consisted of red blood cells (RBCs), white blood cells (WBCs), and plasma that interacts with the TA wall, so it may affect the resultant stresses and strains in the TA, as well as hemodynamics of the blood.

METHODS

In this study, discrete elements were distributed in the TA lumen to represent the blood components and mechanically coupled using fluid-structure interaction (FSI). Healthy and aneurysmal human TA tissues were subjected to axial and circumferential tensile loadings, and the hyperelastic mechanical properties were assigned to the TA and ATAA FE models.

RESULTS

The ATAA showed larger tensile and shear stresses but smaller fluid velocity compared to the ATA. The blood components experienced smaller shear stress in interaction with the ATAA wall compared to TA. The computational fluid dynamics showed smaller blood velocity and wall shear stress compared to the FSI.

CONCLUSIONS

This study is a first proof of concept, and future investigations will aim at validating the novel methodology to derive a more reliable ATAA rupture risk assessment considering the interaction of the blood components with the TA wall.

Experimental and Mouse-Specific Computational Models of the Fbln4SMKO Mouse to Identify Potential Biomarkers for Ascending Thoracic Aortic Aneurysm

PURPOSE

To use computational methods to explore geometric, mechanical, and fluidic biomarkers that could correlate with mouse lifespan in the Fbln4SMKO mouse. Mouse lifespan was used as a surrogate for risk of a severe cardiovascular event in cases of ascending thoracic aortic aneurysm.

METHODS

Image-based, mouse-specific fluid-structure-interaction models were developed for Fbln4SMKO mice (n = 10) at ages two and six months. The results of the simulations were used to quantify potential biofluidic biomarkers, complementing the geometrical biomarkers obtained directly from the images.

RESULTS

Comparing the different geometrical and biofluidic biomarkers to the mouse lifespan, it was found that mean oscillatory shear index (OSImin) and minimum time-averaged wall shear stress (TAWSSmin) at six months showed the largest correlation with lifespan (r2 = 0.70, 0.56), with both correlations being positive (i.e., mice with high OSImean and high TAWSSmin tended to live longer). When change between two and six months was considered, the change in TAWSSmin showed a much stronger correlation than OSImean (r2 = 0.75 vs. 0.24), and the correlation was negative (i.e., mice with increasing TAWSSmin over this period tended to live less long).

CONCLUSION

The results highlight potential biomarkers of ATAA outcomes that can be obtained through noninvasive imaging and computational simulations, and they illustrate the potential synergy between small-animal and computational models.

Computational analysis of aortic haemodynamics in the presence of ascending aortic aneurysm

BACKGROUND

The usefulness of numerical modelling of a patient's cardiovascular system is growing in clinical treatment. Understanding blood flow mechanics can be crucial in identifying connections between haemodynamic factors and aortic wall pathologies.

OBJECTIVE

This work investigates the haemodynamic parameters of an ascending aorta and ascending aortic aneurysm in humans.

METHODS

Two aortic models were constructed from medical images using the SimVascular software. FEM blood flow modelling of cardiac cycle was performed using CFD and CMM-FSI at different vascular wall parameters.

RESULTS

The results showed that highest blood velocity was 1.18 m/s in aorta with the aneurysm and 1.9 m/s in healthy aorta model. The largest displacements ware in the aorta with the aneurysm (0.73 mm). In the aorta with the aneurysm, time averaged WSS values throughout the artery range from 0 Pa to 1 Pa. In the healthy aorta, distribution of WSS values changes from 0.3 Pa to 0.6 Pa.

CONCLUSIONS

In the case of an ascending aortic aneurysm, the maximum blood velocity was found to be 1.6 times lower than in the healthy aorta. The aneurysm-based model demonstrates a 45% greater wall displacement, while the oscillatory shear index decreased by 30% compared to healthy aortic results.

Significance of Hemodynamics Biomarkers, Tissue Biomechanics and Numerical Simulations in the Pathogenesis of Ascending Thoracic Aortic Aneurysms

Guidelines for the treatment of aortic wall diseases are based on measurements of maximum aortic diameter. However, aortic rupture or dissections do occur for small aortic diameters. Growing scientific evidence underlines the importance of biomechanics and hemodynamics in aortic disease development and progression. Wall shear stress (WWS) is an important hemodynamics marker that depends on aortic wall morphology and on the aortic valve function. WSS could be helpful to interpret aortic wall remodeling and define personalized risk criteria. The complementarity of Computational Fluid Dynamics and 4D Magnetic Resonance Imaging as tools for WSS assessment is a promising reality. The potentiality of these innovative technologies will provide maps or atlases of hemodynamics biomarkers to predict aortic tissue dysfunction. Ongoing efforts should focus on the correlation between these non-invasive imaging biomarkers and clinico-pathologic situations for the implementation of personalized medicine in current clinical practice.

Combining 4D Flow MRI and Complex Networks Theory to Characterize the Hemodynamic Heterogeneity in Dilated and Non-dilated Human Ascending Aortas

Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria.

Hemodynamic Profiles Before and After Surgery in Bicuspid Aortic Valve Disease-A Systematic Review of the Literature

Bicuspid aortic valve (BAV) disease presents a unique management challenge both pre- and post-operatively. 4D flow MRI offers multiple tools for the assessment of the thoracic aorta in aortic valve disease. In particular, its assessment of flow patterns and wall shear stress have led to new understandings around the mechanisms of aneurysm development in BAV disease. Novel parameters have now been developed that have the potential to predict pathological aortic dilatation and may help to risk stratify BAV patients in future. This systematic review analyses the current 4D flow MRI literature after aortic valve and/or ascending aortic replacement in bicuspid aortic valve disease. 4D flow MRI has also identified distinct challenges posed by this cohort at the time of valve replacement compared to standard management of tri-leaflet disorders, and may help tailor the type and timing of replacement. Eccentric pathological flow patterns seen after bioprosthetic valve implantation, but not with mechanical prostheses, might be an important future consideration in intervention planning. 4D flow MRI also has promising potential in supporting the development of artificial valve prostheses and aortic conduits with more physiological flow patterns.

Patient-Specific CT-Based Fluid-Structure-Interaction Aorta Model to Quantify Mechanical Conditions for the Investigation of Ascending Aortic Dilation in TOF Patients

Background

Some adult patients with Tetralogy of Fallot (TOF) were found to simultaneously develop ascending aortic dilation. Severe aortic dilation would lead to several aortic diseases, including aortic aneurysm and dissection, which seriously affect patients' living quality and even cause patients' death. Current practice guidelines of aortic-dilation-related diseases mainly focus on aortic diameter, which has been found not always a good indicator. Therefore, it may be clinically useful to identify some other factors that can potentially better predict aortic response to dilation.

Methods

20 TOF patients scheduled for TOF repair surgery were recruited in this study and were divided into dilated and nondilated groups according to the Z scores of ascending aorta diameters. Patient-specific aortic CT images, pressure, and flow rates were used in the construction of computational biomechanical models.

Results

Simulation results demonstrated a good coincidence between numerical mean flow rate at inlet and the one obtained from color Doppler ultrasonography, which implied that computational models were able to simulate the movement of the aorta and blood inside accurately. Our results indicated that aortic stress can effectively differentiate patients of the dilated group from the ones of the nondilated group. Mean ascending aortic stress-P1 (maximal principal stress) from the dilated group was 54% higher than that from the nondilated group (97.97 kPa vs. 63.47 kPa, p value = 0.044) under systolic pressure. Velocity magnitude in the aorta and aortic wall displacement of the dilated group were also greater than those of the nondilated group with p value < 0.1.

Conclusion

Computational modeling and ascending aortic biomechanical factors may be used as a potential tool to identify and analyze aortic response to dilation. Large-scale clinical studies are needed to validate these preliminary findings.

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

Arterial aneurysms are pathological dilations of blood vessels, which can be of clinical concern due to thrombosis, dissection, or rupture. Aneurysms can form throughout the arterial system, including intracranial, thoracic, abdominal, visceral, peripheral, or coronary arteries. Currently, aneurysm diameter and expansion rates are the most commonly used metrics to assess rupture risk. Surgical or endovascular interventions are clinical treatment options, but are invasive and associated with risk for the patient. For aneurysms in locations where thrombosis is the primary concern, diameter is also used to determine the level of therapeutic anticoagulation, a treatment that increases the possibility of internal bleeding. Since simple diameter is often insufficient to reliably determine rupture and thrombosis risk, computational hemodynamic simulations are being developed to help assess when an intervention is warranted. Created from subject-specific data, computational models have the potential to be used to predict growth, dissection, rupture, and thrombus-formation risk based on hemodynamic parameters, including wall shear stress, oscillatory shear index, residence time, and anomalous blood flow patterns. Generally, endothelial damage and flow stagnation within aneurysms can lead to coagulation, inflammation, and the release of proteases, which alter extracellular matrix composition, increasing risk of rupture. In this review, we highlight recent work that investigates aneurysm geometry, model parameter assumptions, and other specific considerations that influence computational aneurysm simulations. By highlighting modeling validation and verification approaches, we hope to inspire future computational efforts aimed at improving our understanding of aneurysm pathology and treatment risk stratification.