Personalized computational hemodynamic analysis in transcatheter aortic valve: investigation of long-term degeneration
Abstract
Introduced as an alternative to open-heart surgery for elderly patients, Transcatheter Aortic Valve Implantation (TAVI) has recently been extended to younger patients due to comparable performance with the gold-standard. However, the long-term durability of the bio-prosthetic TAVI valves is limited by Structural Valve Deterioration (SVD), an inevitable degenerative process whose pathogenesis is still unclear. In this study, we aim to computationally investigate a possible relationship between aortic hemodynamics and SVD development. To this aim, we collect data from twelve patients with and without SVD at long-term follow-up exams. Starting from pre-operative clinical images, we build early post-operative virtual geometries and perform Computational Fluid Dynamics simulations by prescribing a personalized flow rate based on Echo Doppler data. In order to identify a premature onset of SVD, we propose three computational hemodynamic indices: Wall Damage Index ( W D I ), Leaflet Delamination Index ( L D I ), and Leaflet Permeability Index ( L P I ). Additionally, to each index we associate a score and, using the Wilcoxon rank-sum test, we find that each score individually shows a statistically greater median value in the SVD sub-population ( W D I : p = 0.008 , L D I : p = 0.001 , L P I : p = 0.020 ). Finally, we define a synthetic scoring system that clearly separates between SVD and non-SVD patients. Our results suggest that aortic hemodynamics may drive a premature onset of SVD, and the synthetic score could potentially assist clinicians in a patient-specific planning of follow-up exams to closely monitor those patients at high SVD risk. • Personalized flow rate boundary conditions using Echo Doppler data. • Efficient Computational Fluid Dynamics after Transcatheter Aortic Valve Implantation. • Influence of hemodynamics on the degeneration of transcatheter bio-prosthetic valves. • Computational hemodynamic risk scores for Structural Valve Deterioration.
Fields of Study & Subjects
Cardiac Valve Diseases and Treatments
Cardiovascular Function and Risk Factors
Aortic Disease and Treatment Approaches
Publication details
- Journal / source
- Computers in Biology and Medicine
- Publisher
- Elsevier BV
- Volume
- 202
- Pages
- 111435–111435
- Publication date
- 5 January 2026
- Language
- EN