Biology subjects

Crugnola, L.

Publications and source records attributed to Crugnola, L..

3 recordsLinked to original sources

bioRxiv2025

Personalized computational hemodynamic analysis in transcatheter aortic valve: investigation of long-term degeneration

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 relation 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 scenarios and we 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 (WDI), Leaflet Delamination Index (LDI), and Leaflet Permeability Index (LPI). 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 (WDI: p = 0.008, LDI: p = 0.001, LPI: 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.

bioengineering↗

bioRxiv2024

Computational analysis to assess hemodynamic forces in descending thoracic aortic aneurysms

Descending Thoracic Aortic Aneurysm (DTAA) is a life-threatening disorder, defined as a localized enlargement of the descending portion of the thoracic aorta. In this context, we develop a Fluid-Structure Interaction (FSI) computational framework, with the inclusion of a turbulence model and different material properties for the healthy and the aneurysmatic portions of the vessel, to study the hemodynamics and its relationship with DTAA. We first provide an analysis on nine ideal scenarios, accounting for different aortic arch types and DTAA ubications, to study changes in blood pressure, flow patterns, turbulence, wall shear stress, drag forces and internal wall stresses. Our findings demonstrate that the hemodynamics in DTAA is profoundly disturbed, with the presence of flow recirculation, formation of vortices and transition to turbulence. In particular, configurations with a more steep aortic arch exhibit a more chaotic hemodynamics. We notice also an increase of pressure values for configurations with less steep aortic arch and of drag forces for configurations with distal DTAA. Secondly, we replicate our analysis for three patient-specific cases (one for type of arch) obtaining conforting results in terms of accordance with the ideal scenarios. Finally, in a very preliminary way, we try to relate our findings to possible stent-graft migrations after TEVAR procedure to provide predictions on the post-operative state. KEY POINTSO_LIThis study employs computational methods to assess hemodynamic forces in descending thoracic aortic aneurysms; C_LIO_LIWe consider ideal cases by varying aortic arch type and aneurysm location; C_LIO_LIOur results show: chaotic hemodynamics for steep aortic arches; increase of pressure values for less steep aortic arches; high risk of plaque in the sac for proximal aneurysms and in the neck for distal aneurysms; C_LIO_LIWe analyse also 3 patient-specific cases, confirming the major outcomes found for the ideal cases; C_LIO_LIWe try to suggest how our pre-operative findings may be put in relation to assess the risk of stent-graft migration of a possible TEVAR procedure. C_LI

bioengineering↗

bioRxiv2024

Computational hemodynamic indices to identify Transcatheter Aortic Valve Implantation degeneration

PurposeStructural Valve Deterioration (SVD) is the main limiting factor to the long-term durability of bioprosthetic valves, which are used for Transcatheter Aortic Valve Implantation (TAVI). The aim of this study is to perform a patient-specific computational analysis of post-TAVI blood dynamics to identify hemodynamic indices that correlate with a premature onset of SVD. MethodsThe study population comprises two subgroups: patients with and without SVD at long-term follow-up exams. Starting from pre-operative CT images, we created reliable post-TAVI scenarios by virtually inserting the bioprosthetic valve (stent and leaflets), and we performed numerical simulations imposing realistic inlet conditions based on patient-specific data. The numerical results were post-processed to build suitable synthetic scores based on normalized hemodynamic indices. ResultsWe defined three synthetic scores, based on hemodynamic indices evaluated in different contexts: on the leaflets, in the ascending aorta, and in the whole domain. Our proposed synthetic scores are able to clearly isolate the SVD group. Notably, we found that leaflets OSI individually shows statistically significant differences between the two subgroups of patients. ConclusionThe results of this computational study suggest that blood dynamics may play an important role in creating the conditions that lead to SVD. More-over, the proposed synthetic scores could provide further indications for clinicians in assessing and predicting TAVI valves long-term performance.

bioengineering↗