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This study sought to assess the predictive value of wall shear stress (WSS) for colocalized ascending aorta (AAo) growth rate (GR) in patients with bicuspid aortic valve (BAV).BAV is associated with AAo dilation, but there is limited knowledge about possible predictors of aortic dilation in patients with BAV. An increased WSS has been related to aortic wall damage in patients with BAV, but no previous prospective study tested its predictive value for dilation rate. Recently, a registration-based technique for the semiautomatic mapping of aortic GR has been presented and validated.Forty-seven patients with BAV free from valvular dysfunction prospectively underwent 4-dimensional flow cardiac magnetic resonance to compute WSS and subsequent follow-up with 2 electrocardiogram-gated high-resolution contrast-enhanced computed tomography angiograms for GR assessment.During a median follow-up duration of 43 months, mid AAo GR was 0.24 mm/year. WSS and its circumferential component showed statistically significant association with mid AAo GR in bivariate (P = 0.049 and P = 0.014, respectively) and in multivariate analysis corrected for stroke volume and either baseline AAo diameter (P = 0.046 and P = 0.014, respectively) or z-score (P = 0.036 and P = 0.012, respectively). GR mapping further detailed that GR was heterogeneous in the AAo and that circumferential WSS, but not WSS magnitude, showed statistically significant positive associations with GR in the regions with the fastest growth.4D flow cardiac magnetic resonance-derived WSS and, in particular, its circumferential component predict progressive dilation of the ascending aorta in patients with BAV. Thus, the assessment of WSS may be considered in the follow-up of these patients.

Objective Thoracic endovascular aortic repair (TEVAR) is widely used for the treatment of patients with blunt traumatic thoracic aortic injury (BTAI). However, aortic haemodynamic and biomechanical implications of this intervention are poorly investigated. This study aimed to assess whether patients treated by TEVAR following BTAI have thoracic aortic abnormalities in geometry, stiffness, and haemodynamics. Methods Patients with BTAI treated by TEVAR at Vall d’Hebron Hospital between 1999 and 2019 were compared with propensity score matched healthy volunteers (HVs). All subjects underwent cardiovascular magnetic resonance (CMR) comprising a 4D flow CMR sequence. Spatially resolved aortic diameter, length, volume, and curvature were assessed. Pulse wave velocity, distensibility, and longitudinal strain (all measurements of aortic stiffness) were determined regionally. Moreover, advanced haemodynamic descriptors were quantified: systolic flow reversal ratio (SFRR), quantifying backward flow during systole, and in plane rotational flow (IRF), measuring in plane strength of helical flow. Results Twenty-six BTAI patients treated by TEVAR were included and matched with 26 HVs. They did not differ in terms of age, sex, and body surface area. Patients with TEVAR had a larger and longer ascending aorta (AAo) and marked abnormalities in local curvature. Aortic stiffness was greater in the aortic segments proximal and distal to TEVAR compared with controls. Moreover, TEVAR patients presented strongly altered flow dynamics compared with controls: a reduced IRF from the distal AAo to the proximal descending aorta and an increased SFRR in the whole thoracic aorta. These differences persisted adjusting for cardiovascular risk factors and were independent of time elapsed since TEVAR implantation. Conclusion At long term follow up, previously healthy patients who underwent TEVAR implantation following BTAI had increased diameter, length and volume of the ascending aorta, and increased aortic stiffness and abnormal flow patterns in the whole thoracic aorta compared with matched controls. Further studies should address whether these alterations have clinical implications.

INTRODUCTION: Arterial tortuosity has emerged as a predictor of adverse outcomes in congenital aortopathies using 3D reconstructed images. We validated a new method to estimate aortic arch tortuosity on 2D CT. We hypothesize that arch tortuosity may identify bicuspid aortic valve (BAV) patients at high risk to develop thoracic aortic aneurysms or aortic dissections (TAD). METHODS: BAV subjects with chest CT scans were retrospectively identified in our clinical records and matched to tricuspid aortic valve (TAV) controls by age, gender, and presentation with TAD. Subjects with prior ascending aortic intervention were excluded. Measurements included aortic arch tortuosity, length, angle, width and height. Total aortic tortuosity was estimated in subjects with available abdominal images. RESULTS: 120 BAV and 234 TAV subjects were included. Our 2D measurements were highly correlated with 3D midline arch measurements and had high inter- and intra-observer reliability. Compared to TAV, BAV subjects had increased arch tortuosity (median 1.76 [Q1-Q3: 1.62-1.95] vs. 1.63 [1.53-1.78], P < 0.01), length (149 [136-160] vs. 135 [122-152] mm, P < 0.01),height (46 [41-53]vs. 39[34-7]mm, P < 0.01),and vertex acuity (70[61-77]vs.75 [68-81] degree, P < 0.01). In a multivariable analysis, arch tortuosity remained independently associated with BAV after adjusting for aortic diameter and other clinical characteristics. CONCLUSIONS: We found that aortic arch tortuosity is significantly increased in BAV and may identify BAV patients who are at increased risk for TAD. Further studies to evaluate the association between tortuosity and clinical outcomes are in progress.

Objectives This study sought to ascertain whether patients with a bicuspid aortic valve (BAV) have an intrinsic alteration in regional aortic stiffness compared with patients with tricuspid aortic valve (TAV) and Marfan syndrome (MFS) patients with similar aortic sizes, as well as to assess the influence of ascending aorta (AAo) dilation on regional stiffness parameters in BAV patients. Background Imaging biomarkers as predictors of BAV, MFS, and degenerative AAo aneurysms in TAV patients (DA-TAV) are lacking. Biomechanical characterization has been proposed as a possible tool for further aneurysm stratification. Methods A total 234 subjects (136 BAV, 44 MFS, and 18 DA-TAV patients and 36 healthy control subjects) were included. The cardiac magnetic resonance protocol comprised 4-dimensional flow to assess AAo and descending aorta (DAo) pulse wave velocities (PWVs) and double-oblique, 2-dimensional, steady-state free-precession cine cardiac magnetic resonance to compute aortic distensibility (AD). Results On adjusted analysis, nondilated BAV patients had similar PWV and AD as healthy control subjects in both AAo and DAo, whereas dilated BAV did not differ from DA-TAV. In contrast, AAo and DAo stiffness in MFS patients was markedly greater than in BAV patients, increasing slightly with dilation severity. AAo PWV showed a biphasic pattern in BAV patients: it first decreased and then increased throughout AAo dilation, with a clear turning point at 50 mm, whereas distensibility did not discern mildly dilated aorta. In multivariate analysis adjusted for clinical and demographic characteristics, only PWV was related to AAo dilation in BAV patients. Conclusions The mechanical properties of AAo aneurysms are similar in BAV and TAV patients, whereas MFS patients have a stiffer aorta. Aortic stiffness strongly depends on dilation severity. AAo PWV resulted in a potentially clinically useful biphasic trend with respect to aneurysm diameter, whereas distensibility did not discern mildly dilated aorta. Beyond clinical risk factors, PWV but not AD was independently related to AAo dilation in BAV patients.

Recent advances in medical imaging have confirmed the presence of altered hemodynamics in bicuspid aortic valve (BAV) patients. Therefore, there is a need for new hemodynamic biomarkers to refine disease monitoring and improve patient risk stratification. This research aims to analyze and extract multiple correlation patterns of hemodynamic parameters from 4D Flow MRI data and find which parameters allow an accurate classification between healthy volunteers (HV) and BAV patients with dilated and non-dilated ascending aorta using machine learning. Sixteen hemodynamic parameters were calculated in the ascending aorta (AAo) and aortic arch (AArch) at peak systole from 4D Flow MRI. We used sequential forward selection (SFS) and principal component analysis (PCA) as feature selection algorithms. Then, eleven machine-learning classifiers were implemented to separate HV and BAV patients (non- and dilated ascending aorta). Multiple correlation patterns from hemodynamic parameters were extracted using hierarchical clustering. The linear discriminant analysis and random forest are the best performing classifiers, using five hemodynamic parameters selected with SFS (velocity angle, forward velocity, vorticity, and backward velocity in AAo; and helicity density in AArch) a 96.31 ± 1.76% and 96.00 ± 0.83% accuracy, respectively. Hierarchical clustering revealed three groups of correlated features. According to this analysis, we observed that features selected by SFS have a better performance than those selected by PCA because the five selected parameters were distributed according to 3 different clusters. Based on the proposed method, we concluded that the feature selection method found five potentially hemodynamic biomarkers related to this disease.