Patterns of ascending aortic dilatation and predictors of surgical replacement of the aorta: A comparison of bicuspid and tricuspid aortic valve patients over eight years of follow-up

The Prevalence of Coronary Artery Disease in Bicuspid Aortic Valve Patients: An Overview of the Literature

The prevalence of coronary artery disease (CAD) in bicuspid aortic valve (BAV) patients is a debatable topic. Several studies have indicated that BAV patients have a lower prevalence of CAD compared with patients with a tricuspid aortic valve (TAV), but the effects of age and gender have not always been considered. This systematic review provides an overview of articles which report on CAD in BAV and TAV patients. Searches were executed in April 2021 and January 2022 according to the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) guidelines in three online databases: Medline, Embase, and Scopus. Screening and data extraction was done by two investigators separately. Primary and secondary outcomes were compared between BAV and TAV patients; a fixed effects model was used for correcting on confounders. Literature search yielded 1,529 articles with 44 being eligible for inclusion. BAV patients were younger (56.4 ± 8.3 years) than TAV patients (64 ± 10.3 years, p < 0.001). All CAD risk factors and CAD were more prevalent in TAV patients. No significant difference remained after correcting for age and gender as confounders. BAV patients have a lower prevalence of CAD and CAD risk factors compared with TAV patients. However, when the age differences between both groups are considered in the analyses, a similar prevalence of both CAD and CAD risk factors is found.

Analysis of Prevalence and Clinical Features of Aortic Stenosis in Patients with and without Bicuspid Aortic Valve Using Machine Learning Methods

Aortic stenosis (AS) is the most commonly diagnosed valvular heart disease, and its prevalence increases with the aging of the general population. However, AS is often diagnosed at a severe stage, necessitating surgical treatment, due to its long asymptomatic period. The objective of this study was to analyze the frequency of AS in a population of cardiovascular patients using echocardiography (ECHO) and to identify clinical factors and features associated with these patient groups. We utilized machine learning methods to analyze 84,851 echocardiograms performed between 2010 and 2018 at the National Medical Research Center named after V.A. Almazov. The primary indications for ECHO were coronary artery disease (CAD) and hypertension (HP), accounting for 33.5% and 14.2% of the cases, respectively. The frequency of AS was found to be 13.26% among the patients (n = 11,252). Within our study, 1544 patients had a bicuspid aortic valve (BAV), while 83,316 patients had a tricuspid aortic valve (TAV). BAV patients were observed to be younger compared to TAV patients. AS was more prevalent in the BAV group (59%) compared to the TAV group (12%), with a p-value of <0.0001. By employing a machine learning algorithm, we randomly identified significant features present in AS patients, including age, hypertension (HP), aortic regurgitation (AR), ascending aortic dilatation (AscAD), and BAV. These findings could serve as additional indications for earlier observation and more frequent ECHO in specific patient groups for the earlier detection of developing AS.

Adventitial adaptive immune cells are associated with ascending aortic dilatation in patients with a bicuspid aortic valve

Background

Bicuspid aortic valve (BAV) is associated with ascending aorta aneurysms and dissections. Presently, genetic factors and pathological flow patterns are considered responsible for aneurysm formation in BAV while the exact role of inflammatory processes remains unknown.

Methods

In order to objectify inflammation, we employ a highly sensitive, quantitative immunohistochemistry approach. Whole slides of dissected, dilated and non-dilated ascending aortas from BAV patients were quantitatively analyzed.

Results

Dilated aortas show a 4-fold increase of lymphocytes and a 25-fold increase in B lymphocytes in the adventitia compared to non-dilated aortas. Tertiary lymphoid structures with B cell follicles and helper T cell expansion were identified in dilated and dissected aortas. Dilated aortas were associated with an increase in M1-like macrophages in the aorta media, in contrast the number of M2-like macrophages did not change significantly.

Conclusion

This study finds unexpected large numbers of immune cells in dilating aortas of BAV patients. These findings raise the question whether immune cells in BAV aortopathy are innocent bystanders or contribute to the deterioration of the aortic wall.

Application of Machine Learning Methods to Analyze Occurrence and Clinical Features of Ascending Aortic Dilatation in Patients with and without Bicuspid Aortic Valve

Aortic aneurysm (AA) rapture is one of the leading causes of death worldwide. Unfortunately, the diagnosis of AA is often verified after the onset of complications, in most cases after aortic rupture. The aim of this study was to evaluate the frequency of ascending aortic aneurysm (AscAA) and aortic dilatation (AD) in patients with cardiovascular diseases undergoing echocardiography, and to identify the main risk factors depending on the morphology of the aortic valve. We processed 84,851 echocardiographic (ECHO) records of 13,050 patients with aortic dilatation (AD) in the Almazov National Medical Research Centre from 2010 to 2018, using machine learning methodologies. Despite a high prevalence of AD, the main reason for the performed ECHO was coronary artery disease (CAD) and hypertension (HP) in 33.5% and 14.2% of the patient groups, respectively. The prevalence of ascending AD (>40 mm) was 15.4% (13,050 patients; 78.3% (10,212 patients) in men and 21.7% (2838 patients) in women). Only 1.6% (n = 212) of the 13,050 patients with AD knew about AD before undergoing ECHO in our center. Among all the patients who underwent ECHO, we identified 1544 (1.8%) with bicuspid aortic valve (BAV) and 635 with BAV had AD (only 4.8% of all AD patients). According to the results of the random forest feature importance analysis, we identified the eight main factors of AD: age, male sex, vmax aortic valve (AV), aortic stenosis (AS), blood pressure, aortic regurgitation (AR), diabetes mellitus, and heart failure (HF). The known factors of AD-like HP, CAD, hyperlipidemia, BAV, and obesity, were also AD risk factors, but were not as important. Our study showed a high frequency of AscAA and dilation. Standard risk factors of AscAA such as HP, hyperlipidemia, or obesity are significantly more common in patients with AD, but the main factors in the formation of AD are age, male sex, vmax AV, blood pressure, AS, AR, HF, and diabetes mellitus. In males with BAV, AD incidence did not differ significantly, but the presence of congenital heart disease was one of the 12 main risk factors for the formation of AD and association with more significant aortic dilatation in AscAA groups.

Atlas-Based Evaluation of Hemodynamic in Ascending Thoracic Aortic Aneurysms

Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models obtained by the deformation of the mean template for specific shape boundaries (i.e., ±1.5 standard deviation, σ). Simulations demonstrated remarkable changes in the velocity streamlines, blood pressure, and fluid shear stress with the principal shape modes such as the aortic size (Mode 1), vessel tortuosity (Mode 2), and aortic valve morphologies (Mode 3). The atlas-based disease assessment can represent a powerful tool to reveal important insights on ATAA-derived hemodynamic, especially for aneurysms which are considered to have borderline anatomies, and thus challenging decision-making. The utilization of SSMs for creating probabilistic patient cohorts can facilitate the understanding of the heterogenous nature of the dilated ascending aorta.

Comparative evaluation of coronary disease burden: bicuspid valve disease is not atheroprotective

OBJECTIVE

Bicuspid aortic valve (BAV) has been associated with less atherosclerosis as compared with tricuspid aortic valve (TAV) patients. It, however, remains unclear whether this reflects the older age of TAV patients and/or accumulation of atherosclerotic risk factors or that the BAV phenotype is atheroprotective. Therefore, we compared the atherosclerotic disease burden of BAV and TAV patients, with that of the general (age-matched) population.

METHODS

The prevalence of coronary artery disease (CAD) and CAD risk factors in BAV and TAV patients who underwent aortic valve surgery were compared with the Dutch general practitioners registry data. BAV (n=454) and TAV (n=1101) patients were divided into four groups: BAV with aortic valve stenosis (BAV-AoS), BAV with aortic valve regurgitation (BAV-AR), TAV with AoS (TAV-AoS) and TAV with AR (TAV-AR). The atherosclerotic disease burden of each group was compared with that of the corresponding age cohort for the general population.

RESULTS

CAD risk factors hypertension and hypercholesterolaemia were more prevalent in the surgery groups than the age-matched general population (all p<0.001). All BAVs (BAV-AoS and BAV-AR) and TAV-AR had a similar incidence of CAD history as compared to the age-matched general populations (p=0.689, p=0.325 and p=0.617 respectively), whereas TAV-AoS had a higher incidence (21.6% versus 14.9% in the age-matched general population, p<0.001).

CONCLUSIONS

Stenotic TAV disease is part of the atherosclerotic disease spectrum, while regurgitant TAV and all BAVs are not. Although the prevalence of cardiovascular risk factors is higher in all BAV patients, the prevalence of CAD is similar to the general population.

Patient-specific computational evaluation of stiffness distribution in ascending thoracic aortic aneurysm

Quantifying local aortic stiffness properties in vivo is acknowledged as essential to assess the severity of an ascending thoracic aortic aneurysm (ATAA). Recently, the LESI (local extensional stiffness identification) methodology has been established to quantify non-invasively local stiffness properties of ATAAs using electrocardiographic-gated computed tomography (ECG-gated CT) scans. The aim of the current study was to determine the most sensitive markers of local ATAA stiffness estimation with the hypothesis that direct measures of local ATAA stiffness could better detect the high-risk patients. A cohort of 30 patients (12 BAV and 18 TAV) referred for aortic size evaluation by ECG-gated CT were recruited. For each patient, the extensional stiffness Q was evaluated by the LESI methodology whilst computational flow analyses were also performed to derive hemodynamics markers such as the wall shear stress (WSS). A strong positive correlation was found between the extensional stiffness and the aortic pulse pressure (R = 0.644 and p < 0.001). Interestingly, a significant positive correlation was also found between the extensional stiffness and patients age for BAV ATAAs (R = 0.619 and p = 0.032), but not for TAV ATAAs (R = -0.117 and p = 0.645). No significant correlation was found between the extensional stiffness and WSS evaluated locally. There was no significant difference either in the extensional stiffness between BAV ATAAs and TAV ATAAs (Q = 3.6 ± 2.5 MPa.mm for BAV ATAAs vs Q = 5.3 ± 3.1 MPa.mm for TAV ATAAs, p = 0.094). Future work will focus on relating the extensional stiffness to the patient-specific rupture risk of ATAAs on larger cohorts to confirm the promising interest of the LESI methodology.

Statistical Shape Analysis of Ascending Thoracic Aortic Aneurysm: Correlation between Shape and Biomechanical Descriptors

An ascending thoracic aortic aneurysm (ATAA) is a heterogeneous disease showing different patterns of aortic dilatation and valve morphologies, each with distinct clinical course. This study aimed to explore the aortic morphology and the associations between shape and function in a population of ATAA, while further assessing novel risk models of aortic surgery not based on aortic size. Shape variability of n = 106 patients with ATAA and different valve morphologies (i.e., bicuspid versus tricuspid aortic valve) was estimated by statistical shape analysis (SSA) to compute a mean aortic shape and its deformation. Once the computational atlas was built, principal component analysis (PCA) allowed to reduce the complex ATAA anatomy to a few shape modes, which were correlated to shear stress and aortic strain, as determined by computational analysis. Findings demonstrated that shape modes are associated to specific morphological features of aneurysmal aorta as the vessel tortuosity and local bulging of the ATAA. A predictive model, built with principal shape modes of the ATAA wall, achieved better performance in stratifying surgically operated ATAAs versus monitored ATAAs, with respect to a baseline model using the maximum aortic diameter. Using current imaging resources, this study demonstrated the potential of SSA to investigate the association between shape and function in ATAAs, with the goal of developing a personalized approach for the treatment of the severity of aneurysmal aorta.