Research on Aneurysm Growth Prediction in Vascular Dilation Caused by Bicuspid Aortic Valve Based on VDM and CFD

Research on Aneurysm Growth Prediction in Vascular Dilation Caused by Bicuspid Aortic Valve Based on VDM and CFD

Bicuspid aortic valve (BAV) is the most common congenital valvular malformation, characterized by heterogeneous phenotypic subtypes that predispose patients to secondary aortic pathologies, including valvular dysfunction and ascending aortic dilation. With approximately 50% of BAV patients developing aortic dilation, a prevalence that continues to rise, accurate assessment of postoperative aortic remodeling remains a critical unmet clinical need for early risk stratification and optimized therapeutic decision-making. Currently, clinical surveillance relies heavily on periodic manual measurement of the maximum aortic diameter on follow-up computed tomography angiography (CTA), yet this approach suffers from several inherent limitations. It is a lagging indicator that detects irreversible wall damage only after significant enlargement has occurred. It oversimplifies complex three-dimensional morphological changes into a single linear dimension. It exhibits substantial intra- and inter-observer variability. It is also inefficient for large-scale longitudinal data management. Although alternative metrics such as computational fluid dynamics (CFD) derived hemodynamic parameters and morphological geometric features have been explored, existing methods remain constrained by static single-time-point analyses that fail to capture the dynamic biomechanical evolution driving aneurysm progression, high technical barriers that preclude routine clinical integration, and a lack of comprehensive models that systematically integrate dynamic deformation, static anatomy, and hemodynamic information. To address these gaps, this study aims to develop a fully automated, quantitative, and dynamic risk prediction system that leverages vascular deformation mapping (VDM) for noninvasive early detection of regional aortic deformation, integrates multiparameter features including dynamic deformational, static anatomical, and hemodynamic characteristics through an artificial intelligence model, and delivers intuitive structured reports to directly support clinical decision-making, thereby enabling earlier intervention and improved patient outcomes.

Inclusion Criteria:

Patients are eligible for inclusion if they are male or non-pregnant female aged 18 to 85 years, diagnosed with Bicuspid Aortic Valve (BAV) by CTA, and have successfully undergone Transcatheter Aortic Valve Replacement (TAVR) with available pre-operative, post-operative (1-3 months), and follow-up (6-12 months) CTA imaging. The CTA scan range must cover cranially at least the origin of the brachiocephalic trunk, left common carotid artery, and left subclavian artery, and caudally at least the origin of the internal and external iliac arteries.

Exclusion Criteria:

Patients are excluded if they have traumatic or iatrogenic aortic dissection, isolated aortic aneurysm without BAV, connective tissue disorders such as Marfan syndrome or Ehlers-Danlos syndrome, or prior cardiac or aortic surgery including surgical aortic valve replacement or aortic repair. Additional exclusions include insufficient number of CTA scans or inadequate scan range, poor CTA image quality due to motion artifacts or inadequate contrast enhancement precluding accurate segmentation, or image registration failure precluding completion of VDM analysis.