Computational Modeling for Coarctation of the Aorta: State of the Art and Novel Considerations

Coarctation of the aorta (CoA) is a congenital cardiovascular defect characterized by a narrowing of the aortic arch, leading to significant hemodynamic disturbances. Computational modeling has emerged as a powerful tool for understanding this pathophysiology, guiding diagnosis, and optimizing treatment strategies. This study provides a systematic review of current computational approaches — (i) computational fluid dynamics (CFD), for simulating the altered hemodynamics caused by the narrowed aortic segment; (ii) finite element analysis (FEA), for analyzing the mechanical behavior of the aortic wall; (iii) fluid–structure interaction, which integrates fluid dynamics and structural mechanics to evaluate the interplay between blood flow and vessel wall deformation; and (iv) artificial intelligence, used to interpret large clinical and simulation datasets — emphasizing their clinical applicability and limitations. Additionally, we present a case study of a pediatric patient as an exemplification of new computational possibilities. Specifically, we discuss the use of clinical data in CFD models for CoA diagnosis and propose the application of FEA in CoA treatment to refine mechanical property estimations based on treatment outcomes. Our findings demonstrate the potential of computational tools in improving diagnostic accuracy while underscoring the need for more precise clinical data collection. By bridging engineering methodologies with clinical practice, this research aims to enhance the integration of computational modeling into routine care, ultimately contributing to personalized and optimized management of CoA. Future studies should focus on the creation of an integrated patient-specific clinical pipeline, including refined patient-specific modeling approaches aimed at improving predictive capabilities and streamlining clinical decision-making.