Comprehensive 4-stage categorization of bicuspid aortic valve leaflet morphology by cardiac MRI in 386 patients

Unlocking insights in bicuspid aortic valve management in adult patients: the vital role of cardiac imaging

The bicuspid aortic valve (BAV) presents a multifaceted clinical challenge due to its diverse morphologies and associated complications. This review aims to elucidate the critical role of cardiac imaging in guiding optimal management strategies for BAV patients. BAV, with a prevalence of 1-2%, has genetic underpinnings linked to the NOTCH1 gene mutation. Variability in BAV morphology necessitates tailored surgical approaches. The three primary types of BAV morphology - right-left cusp fusion, right-noncoronary cusp fusion, and left-noncoronary cusp fusion - demand nuanced considerations due to their distinct implications. Valvular dysfunction results in aortic stenosis or regurgitation, attributed to altered valve structure and turbulent hemodynamics. Cardiac imaging modalities, including echocardiography, magnetic resonance imaging, and computerized tomography, are instrumental in assessing valve function, aortic dimensions, and associated complications. Imaging helps predict potential complications, enabling informed treatment decisions. Regular follow-up is crucial to detecting alterations early and intervening promptly. Surgical management options encompass aortic valve repair or replacement, with patient-specific factors guiding the choice. Post-surgical surveillance plays a vital role in preventing complications and optimizing patient outcomes. The review underscores the significance of advanced cardiac imaging techniques in understanding BAV's complexities, facilitating personalized management strategies, and improving patient care. By harnessing the power of multimodal imaging, clinicians can tailor interventions, monitor disease progression, and ultimately enhance the prognosis and quality of life for individuals with BAV.

Patients with Bicuspid Aortopathy and Aortic Dilatation

(1) Background: Bicuspid aortic valve (BAV) is the most frequent congenital cardiac disease. Alteration of ascending aorta diameter is a consequence of shear stress alterations due to haemodynamic abnormalities developed from inadequate valve cusp coaptation. (2) Objective: This narrative review aims to discuss anatomical, pathophysiological, genetical, ultrasound, and radiological aspects of BAV disease, focusing on BAV classification related to imaging patterns and flux models involved in the onset and developing vessel dilatation. (3) Methods: A comprehensive search strategy was implemented in PubMed from January to May 2022. English language articles were selected independently by two authors and screened according to the following criteria. (4) Key Contents and Findings: Ultrasound scan is the primary step in the diagnostic flowchart identifying structural and doppler patterns of the valve. Computed tomography determines aortic vessel dimensions according to the anatomo-pathology of the valve. Magnetic resonance identifies hemodynamic alterations. New classifications and surgical indications derive from these diagnostic features. Currently, indications correlate morphological results, dissection risk factors, and genetic alterations. Surgical options vary from aortic valve and aortic vessel substitution to aortic valve repair according to the morphology of the valve. In selected patients, transcatheter aortic valve replacement has an even more impact on the treatment choice. (5) Conclusions: Different imaging approaches are an essential part of BAV diagnosis. Morphological classifications influence the surgical outcome.

Clinical implications of the biomechanics of bicuspid aortic valve and bicuspid aortopathy

Bicuspid aortic valve (BAV), which affects up to 2% of the general population, results from the abnormal fusion of the cusps of the aortic valve. Patients with BAV are at a higher risk for developing aortic dilatation, a condition known as bicuspid aortopathy, which is associated with potentially life-threatening sequelae such as aortic dissection and aortic rupture. Although BAV biomechanics have been shown to contribute to aortopathy, their precise impact is yet to be delineated. Herein, we present the latest literature related to BAV biomechanics. We present the most recent definitions and classifications for BAV. We also summarize the current evidence pertaining to the mechanisms that drive bicuspid aortopathy. We highlight how aberrant flow patterns can contribute to the development of aortic dilatation. Finally, we discuss the role cardiac magnetic resonance imaging can have in assessing and managing patient with BAV and bicuspid aortopathy.

Unraveling Bicuspid Aortic Valve Enigmas by Multimodality Imaging: Clinical Implications

Multimodality imaging is the basis of the diagnosis, follow-up, and surgical management of bicuspid aortic valve (BAV) patients. Transthoracic echocardiography (TTE) is used in our clinical routine practice as a first line imaging for BAV diagnosis, valvular phenotyping and function, measurement of thoracic aorta, exclusion of other aortic malformations, and for the assessment of complications such are infective endocarditis and aortic. Nevertheless, TTE is less useful if we want to assess accurately other aortic segments such as mid-distal ascending aorta, where computed tomography (CT) and magnetic resonance (CMR) could improve the precision of aorta size measurement by multiplanar reconstructions. A major advantage of CT is its superior spatial resolution, which affords a better definition of valve morphology and calcification, accuracy, and reproducibility of ascending aorta size, and allows for coronary artery assessment. Moreover, CMR offers the opportunity of being able to evaluate aortic functional properties and blood flow patterns. In this setting, new developed sequences such as 4D-flow may provide new parameters to predict events during follow up. The integration of all multimodality information facilitates a comprehensive evaluation of morphologic and dynamic features, stratification of the risk, and therapy guidance of this cohort of patients.

International Consensus Statement on Nomenclature and Classification of the Congenital Bicuspid Aortic Valve and Its Aortopathy, for Clinical, Surgical, Interventional and Research Purposes

This International Consensus Classification and Nomenclature for the congenital bicuspid aortic valve condition recognizes 3 types of bicuspid valves: 1. The fused type (right-left cusp fusion, right-non-coronary cusp fusion and left-non-coronary cusp fusion phenotypes); 2. The 2-sinus type (latero-lateral and antero-posterior phenotypes); and 3. The partial-fusion (forme fruste) type. The presence of raphe and the symmetry of the fused type phenotypes are critical aspects to describe. The International Consensus also recognizes 3 types of bicuspid valve-associated aortopathy: 1. The ascending phenotype; 2. The root phenotype; and 3. Extended phenotypes. ©  2021 Jointly between the RSNA, the European Association for Cardio-Thoracic Surgery, The Society of Thoracic Surgeons, and the American Association for Thoracic Surgery. The articles are identical except for minor stylistic and spelling differences in keeping with each journal's style. All rights reserved. Keywords: Bicuspid Aortic Valve, Aortopathy, Nomenclature, Classification.

International consensus statement on nomenclature and classification of the congenital bicuspid aortic valve and its aortopathy, for clinical, surgical, interventional and research purposes

This International Consensus Classification and Nomenclature for the congenital bicuspid aortic valve condition recognizes 3 types of bicuspid valves: 1. The fused type (right-left cusp fusion, right-non-coronary cusp fusion and left-non-coronary cusp fusion phenotypes); 2. The 2-sinus type (latero-lateral and antero-posterior phenotypes); and 3. The partial-fusion (forme fruste) type. The presence of raphe and the symmetry of the fused type phenotypes are critical aspects to describe. The International Consensus also recognizes 3 types of bicuspid valve-associated aortopathy: 1. The ascending phenotype; 2. The root phenotype; and 3. Extended phenotypes.

International consensus statement on nomenclature and classification of the congenital bicuspid aortic valve and its aortopathy, for clinical, surgical, interventional and research purposes

This International Consensus Classification and Nomenclature for the congenital bicuspid aortic valve condition recognizes 3 types of bicuspid valves: 1. The fused type (right-left cusp fusion, right-non-coronary cusp fusion and left-non-coronary cusp fusion phenotypes); 2. The 2-sinus type (latero-lateral and antero-posterior phenotypes); and 3. The partial-fusion (forme fruste) type. The presence of raphe and the symmetry of the fused type phenotypes are critical aspects to describe. The International Consensus also recognizes 3 types of bicuspid valve-associated aortopathy: 1. The ascending phenotype; 2. The root phenotype; and 3. Extended phenotypes.

International Consensus Statement on Nomenclature and Classification of the Congenital Bicuspid Aortic Valve and Its Aortopathy, for Clinical, Surgical, Interventional and Research Purposes

This International Consensus Classification and Nomenclature for the congenital bicuspid aortic valve condition recognizes 3 types of bicuspid valves: 1. The fused type (right-left cusp fusion, right-non-coronary cusp fusion and left-non-coronary cusp fusion phenotypes); 2. The 2-sinus type (latero-lateral and antero-posterior phenotypes); and 3. The partial-fusion (forme fruste) type. The presence of raphe and the symmetry of the fused type phenotypes are critical aspects to describe. The International Consensus also recognizes 3 types of bicuspid valve-associated aortopathy: 1. The ascending phenotype; 2. The root phenotype; and 3. Extended phenotypes.

Cardiac Imaging of Aortic Valve Area From 34 287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes

Background:

The aortic valve is an important determinant of cardiovascular physiology and anatomic location of common human diseases.

Methods:

From a sample of 34 287 white British ancestry participants, we estimated functional aortic valve area by planimetry from prospectively obtained cardiac magnetic resonance imaging sequences of the aortic valve. Aortic valve area measurements were submitted to genome-wide association testing, followed by polygenic risk scoring and phenome-wide screening, to identify genetic comorbidities.

Results:

A genome-wide association study of aortic valve area in these UK Biobank participants showed 3 significant associations, indexed by rs71190365 (chr13:50764607, DLEU1 , P =1.8×10 −9 ), rs35991305 (chr12:94191968, CRADD , P =3.4×10 −8 ), and chr17:45013271:C:T ( GOSR2 , P =5.6×10 −8 ). Replication on an independent set of 8145 unrelated European ancestry participants showed consistent effect sizes in all 3 loci, although rs35991305 did not meet nominal significance. We constructed a polygenic risk score for aortic valve area, which in a separate cohort of 311 728 individuals without imaging demonstrated that smaller aortic valve area is predictive of increased risk for aortic valve disease (odds ratio, 1.14; P =2.3×10 −6 ). After excluding subjects with a medical diagnosis of aortic valve stenosis (remaining n=308 683 individuals), phenome-wide association of >10 000 traits showed multiple links between the polygenic score for aortic valve disease and key health-related comorbidities involving the cardiovascular system and autoimmune disease. Genetic correlation analysis supports a shared genetic etiology with between aortic valve area and birth weight along with other cardiovascular conditions.

Conclusions:

These results illustrate the use of automated phenotyping of cardiac imaging data from the general population to investigate the genetic etiology of aortic valve disease, perform clinical prediction, and uncover new clinical and genetic correlates of cardiac anatomy.

Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences

Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled, which creates barriers to their use in supervised machine learning. We develop a weakly supervised deep learning model for classification of aortic valve malformations using up to 4,000 unlabeled cardiac MRI sequences. Instead of requiring highly curated training data, weak supervision relies on noisy heuristics defined by domain experts to programmatically generate large-scale, imperfect training labels. For aortic valve classification, models trained with imperfect labels substantially outperform a supervised model trained on hand-labeled MRIs. In an orthogonal validation experiment using health outcomes data, our model identifies individuals with a 1.8-fold increase in risk of a major adverse cardiac event. This work formalizes a deep learning baseline for aortic valve classification and outlines a general strategy for using weak supervision to train machine learning models using unlabeled medical images at scale.

Misclassification of bicuspid aortic valves is common and varies by imaging modality and patient characteristics

BACKGROUND

Bicuspid aortic valve (BAV) is the most prevalent adult congenital heart defect. BAV causes lifelong progressive disease that can be prevented by early diagnosis and long-term surveillance, but may be compromised by misclassification of valve morphology.

METHODS

The study population was derived from the UTHealth Bicuspid Aortic Valve Registry, which includes serial images on more than 200 participants over a mean follow-up interval of 2.8 years. We abstracted descriptions of aortic valve morphology from transthoracic or transesophageal echocardiography, computed tomography angiography, and magnetic resonance angiography reports. We used chi-square and t tests to determine associations between reported valve morphologies (definitely bicuspid, possibly bicuspid, tricuspid, or uncertain) and clinical characteristics and assessed image quality using a validated tool.

RESULTS

About 40% of participants were misclassified in at least one imaging report. The mean interval between misclassification and correct diagnosis was 22 months. TEE, MR and CT were more sensitive than TTE and successfully reclassified 20% of participants, but were only used in 14% of patients. Misclassification was associated with age, the extent of valve calcification and image quality, but was not significantly associated with aortic regurgitation, gender, or cusp configuration.

CONCLUSION

Misclassification of BAV is prevalent, frequently leads to delayed diagnosis, and is more likely to occur in the most severely affected cases. TEE, CT and MR may increase diagnostic accuracy in up to half of BAV cases but are underutilized. Additional studies are needed to determine if misclassification of BAV patients leads to increased long-term morbidity and mortality.