Characterization of hemodynamics in anomalous aortic origin of coronary arteries using patient-specific modeling

Chidyagwai, Simbarashe G.; Vardhan, Madhurima; Kaplan, Melvin H.; Chamberlain, Reid C.; Barker, Piers; Randles, Amanda

doi:10.1016/j.jbiomech.2021.110919

Cited by 9 publications

(12 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 9 , 31 Meanwhile, computational fluid dynamics simulations with rigid geometries showed how the narrowed intramural course caused significant hemodynamic abnormalities. 19 , 20 , 32 A 3D-printed model of an intramural AAORCA had an abnormally low FFR that normalized in a separate model of the postoperative geometry. 33 A cine CTA of an interarterial (but not intramural) anomalous left coronary found no luminal compression nor perfusion defect during dobutamine-stress.…”

Section: Discussionmentioning

confidence: 99%

“… 16 , 17 More recently, computational fluid dynamics has also been used to model the FFR and hemodynamics in AAOCA, but such methods have yet to be validated with direct measurements for anomalous coronaries. 18 , 19 , 20 Also, computational fluid dynamics modeling fails to simulate the coronary lumen compression that may occur during exercise. Meanwhile, advancements in fluid–structure interaction (FSI) modeling enable simultaneous modeling of blood flow and tissue deformation, but to our knowledge, this approach has not been applied to AAOCA.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Patient-specific fluid–structure simulations of anomalous aortic origin of right coronary arteries

et al. 2022

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Patient-specific fluid–structure simulations of anomalous aortic origin of right coronary arteries

et al. 2022

View full text Add to dashboard Cite

“…They also observed that SCD cases in young trained patients are primarily caused by ALCA while older patients exhibit equivalent or even higher incidence rates for ARCA-related SCD [ 11 ]. Chidyagwai et al reported that although RCA patients have lower likelihoods of experiencing exercise-induced SCD, certain studies indicate increased incidence of ventricular fibrosis [ 23 ]. However, an observational study by Clark et al found no association between AAOCA detected in CTA and sudden death [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

“…There is limited literature exploring the relationship between coronary artery disease (CAD) and AAOCA, and as of now, there is no consensus on this matter. The elevated time-averaged wall shear stress found in AAOCA patients could potentially lead to premature atherosclerosis and coronary spasm [ 23 ]. Click et al reported a significantly greater degree of stenosis in anomalous circumflex arteries compared to normal ones in the control group [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Anomalous origin of the coronary artery: prevalence and coronary artery disease in adults undergoing coronary tomographic angiography

Li,

Hu,

Luo

et al. 2024

BMC Cardiovasc Disord

View full text Add to dashboard Cite

Background Anomalous aortic origin of a coronary artery (AAOCA) is a rare congenital coronary anomaly with the potential to cause adverse cardiac events. However, there is limited data on the association between AAOCA and coronary artery disease (CAD). Therefore, the aim of this study is to determine the prevalence and symptoms of patients with AAOCA, as well as investigate the correlation between AAOCA and CAD in a population referred for coronary computed tomographic angiography (CTA). Methods and results All consecutive patients who underwent CTA from 2010 to 2021 were included. Characteristics, symptoms, coronary related adverse events and CTA information were reviewed by medical records. Separate multivariable cumulative logistic regressions were performed, using the stenosis severity in each of the four coronaries as individual responses and as a combined patient clustered response. Finally, we identified 207 adult patients with AAOCA, the prevalence of AAOCA is 0.23% (207/90,501). Moreover, this study found no significant association between AAOCA and CAD. AAOCA did not contribute to higher rates of hospitalization or adverse cardiac events, including calcification. Conclusion AAOCA is a rare congenital disease that is not associated with increased presence of obstructive CAD in adults.

show abstract

“…Quantitative analysis of AAOCA from CTA is used in different contexts, such as diagnosis and risk profiling, surgical planning, and numerical biomechanical simulations [ 9 – 12 ]. Recently, deep learning techniques have shown promising performance in the medical field, addressing classification, segmentation, and detection tasks [ 13 – 15 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic 3D Segmentation and Identification of Anomalous Aortic Origin of the Coronary Arteries Combining Multi-view 2D Convolutional Neural Networks

Pascaner,

Rosato,

Fantazzini

et al. 2024

J Digit Imaging. Inform. med.

View full text Add to dashboard Cite

This work aimed to automatically segment and classify the coronary arteries with either normal or anomalous origin from the aorta (AAOCA) using convolutional neural networks (CNNs), seeking to enhance and fasten clinician diagnosis. We implemented three single-view 2D Attention U-Nets with 3D view integration and trained them to automatically segment the aortic root and coronary arteries of 124 computed tomography angiographies (CTAs), with normal coronaries or AAOCA. Furthermore, we automatically classified the segmented geometries as normal or AAOCA using a decision tree model. For CTAs in the test set (n = 13), we obtained median Dice score coefficients of 0.95 and 0.84 for the aortic root and the coronary arteries, respectively. Moreover, the classification between normal and AAOCA showed excellent performance with accuracy, precision, and recall all equal to 1 in the test set. We developed a deep learning-based method to automatically segment and classify normal coronary and AAOCA. Our results represent a step towards an automatic screening and risk profiling of patients with AAOCA, based on CTA.

show abstract

Characterization of hemodynamics in anomalous aortic origin of coronary arteries using patient-specific modeling

Cited by 9 publications

References 36 publications

Patient-specific fluid–structure simulations of anomalous aortic origin of right coronary arteries

Patient-specific fluid–structure simulations of anomalous aortic origin of right coronary arteries

Anomalous origin of the coronary artery: prevalence and coronary artery disease in adults undergoing coronary tomographic angiography

Automatic 3D Segmentation and Identification of Anomalous Aortic Origin of the Coronary Arteries Combining Multi-view 2D Convolutional Neural Networks

Contact Info

Product

Resources

About