Application of Patient-Specific Computational Fluid Dynamics in Anomalous Aortic Origin of Coronary Artery: A Systematic Review.
Anselm W StarkAndreas A GiannopoulosAlexander PugachevIsaac ShiriAndreas HaeberlinLorenz RäberDominik ObristChristoph GräniPublished in: Journal of cardiovascular development and disease (2023)
Anomalous aortic origin of a coronary artery (AAOCA) is a rare congenital heart condition with fixed and dynamic stenotic elements, potentially causing ischemia. Invasive coronary angiography under stress is the established method for assessing hemodynamics in AAOCA, yet it is costly, technically intricate, and uncomfortable. Computational fluid dynamics (CFD) simulations offer a noninvasive alternative for patient-specific hemodynamic analysis in AAOCA. This systematic review examines the role of CFD simulations in AAOCA, encompassing patient-specific modeling, noninvasive imaging-based boundary conditions, and flow characteristics. Screening articles using AAOCA and CFD-related terms prior to February 2023 yielded 19 publications, covering 370 patients. Over the past four years, 12 (63%) publications (259 patients) employed dedicated CFD models, whereas 7 (37%) publications (111 patients) used general-purpose CFD models. Dedicated CFD models were validated for fixed stenosis but lacked dynamic component representation. General-purpose CFD models exhibited variability and limitations, with fluid-solid interaction models showing promise. Interest in CFD modeling of AAOCA has surged recently, mainly utilizing dedicated models. However, these models inadequately replicate hemodynamics, necessitating novel CFD approaches to accurately simulate pathophysiological changes in AAOCA under stress conditions.
Keyphrases
- end stage renal disease
- coronary artery
- systematic review
- chronic kidney disease
- newly diagnosed
- ejection fraction
- pulmonary artery
- peritoneal dialysis
- prognostic factors
- randomized controlled trial
- aortic valve
- mass spectrometry
- machine learning
- pulmonary arterial hypertension
- pulmonary hypertension
- artificial intelligence
- meta analyses
- fluorescence imaging