In silico modelling of aortic annuloplasty: hemodynamic assessment through in vitro experiments and in vivo MRI

Aortic annuloplasty (AA) is an innovative surgical technique for aortic root (AR) enlargement. It is performed by implanting sutures, bands, or rings, either externally or internally the AR, hereby reducing its diameter. This study evaluates the impact of AA approaches on AR hemodynamic by employing a porcine-specific workflow combining in vivo magnetic resonance imaging (MRI), in vitro experiments and in silico fluid-structure interaction (FSI) simulations investigating external single ring AA. CAD models of native and post-annuloplasty ARs were segmented from in vivo porcine MRI data and served as the basis for fabricating 3D-printed resin phantoms and implementing computational digital twins. The former were tested on a pulsatile flow-loop, whereas the latter were integrated in FSI simulations, with time-dependent boundary conditions based on the resultant experimental pressure waveforms. Additionally, a proof-of-concept validation of the in silico model against in vivo data is proposed. Computational results of the two cases were compared in terms of fluid velocity, vorticity, helicity, and wall shear stresses, providing a step towards understanding the complex interactions between the AR and blood flow dynamics. Results suggested that the presence of the ring increased the systolic jet flow and post-valve velocities (three-fold increase), reduced the backward, vortical flow during diastole (∼ 9% decrease), and induced modifications in bulk flow and wall shear stresses distribution. Furthermore, the development of an animal-specific digital twin of a post-AA AR represents a significant advancement in the field, providing a valuable tool for future research and for clinical applications to aid AA decision-making process.

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Publication Details

Journal
Computer Methods and Programs in Biomedicine
Published
2026-01-09
DOI
https://doi.org/10.1016/j.cmpb.2026.109246
Primary Topic
Aortic Disease and Treatment Approaches
Type
article
Field-Weighted Citation Impact
0.00

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article

In silico modelling of aortic annuloplasty: hemodynamic assessment through in vitro experiments and in vivo MRI

Monika Colombo, Luca Bontempi, Preben Johansen, Marta Zattoni et al.
Computer Methods and Programs in Biomedicine
Aortic Disease and Treatment Approaches
article

In silico modelling of aortic annuloplasty: hemodynamic assessment through in vitro experiments and in vivo MRI

Monika Colombo, Luca Bontempi, Preben Johansen, Marta Zattoni, Giulia Luraghi, Leila Louise Benhassen
article en

Abstract

Aortic annuloplasty (AA) is an innovative surgical technique for aortic root (AR) enlargement. It is performed by implanting sutures, bands, or rings, either externally or internally the AR, hereby reducing its diameter. This study evaluates the impact of AA approaches on AR hemodynamic by employing a porcine-specific workflow combining in vivo magnetic resonance imaging (MRI), in vitro experiments and in silico fluid-structure interaction (FSI) simulations investigating external single ring AA. CAD models of native and post-annuloplasty ARs were segmented from in vivo porcine MRI data and served as the basis for fabricating 3D-printed resin phantoms and implementing computational digital twins. The former were tested on a pulsatile flow-loop, whereas the latter were integrated in FSI simulations, with time-dependent boundary conditions based on the resultant experimental pressure waveforms. Additionally, a proof-of-concept validation of the in silico model against in vivo data is proposed. Computational results of the two cases were compared in terms of fluid velocity, vorticity, helicity, and wall shear stresses, providing a step towards understanding the complex interactions between the AR and blood flow dynamics. Results suggested that the presence of the ring increased the systolic jet flow and post-valve velocities (three-fold increase), reduced the backward, vortical flow during diastole (∼ 9% decrease), and induced modifications in bulk flow and wall shear stresses distribution. Furthermore, the development of an animal-specific digital twin of a post-AA AR represents a significant advancement in the field, providing a valuable tool for future research and for clinical applications to aid AA decision-making process.

Computer Methods and Programs in BiomedicineVol. 277
Aarhus University (DK), Erasmus MC (NL), Aarhus University Hospital (DK), Erasmus University Rotterdam (NL), Politecnico di Milano (IT)
Aarhus Universitet
Peace, Justice and strong institutions
Openalex Percentile: Top 93%
Aortic Disease and Treatment Approaches
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