Effect of Aortic Wall Deformation with Healthy and Calcified Annulus on Hemodynamic Performance of Implanted On-X Valve

Sadipour, Masod; Hanafizadeh, Pedram; Sadeghy, Kayvan; Sattari, Amirmohammad

doi:10.1007/s13239-019-00453-y

Cited by 7 publications

(14 citation statements)

References 37 publications

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“…Concerning the geometrical modelling of the BMAV, in the majority of FSI studies the device’s geometry was reconstructed to replicate commercially available designs, such as the Bicarbon valve (Corcym Srl, Milan, IT) ( 58 , 59 , 67 , 71 ), the ATS Open Pivot valve (Medtronic, Dublin, IR) ( 54 – 56 , 63 , 75 , 79 ), the On-X valve (Artivion, Kennesaw, GA, USA) ( 38 , 45 ) and valves from St. Jude series (Abbott Laboratories, Chicago, IL, USA) ( 27 , 28 , 31 , 33 , 35 , 37 , 49 – 53 , 57 , 60 – 62 , 64 – 66 , 68 – 70 , 72 – 77 , 81 – 85 ). Nevertheless, idealized valve models, which do not refer to specific commercial designs, are sometimes considered ( Figure 2C ) ( 42 ).…”

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

“…Additionally, different levels of detail can be adopted to model the hinges connecting valve leaflets and the housing. The hinge recess of the housing can be reproduced with a realistic geometry, featuring a characteristic butterfly shape ( 28 , 33 , 37 , 38 , 45 , 47 , 48 , 60 , 75 ). Alternatively, the coupling between the leaflets and the housing can be simplified, for example, by replacing the hinge with a peripheral gap ( 27 , 46 , 58 , 67 ) or modelling a simplified pin ( 41 ) or spherical ( 72 , 81 ) hinge.…”

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

“…Simplified hinge geometry typically results in leaflet rotation being limited by angular constraints rather than by the blocking mechanism of the hinge. Additionally, the friction in the hinge is usually neglected ( 33 , 35 , 38 , 41 , 49 , 55 , 56 , 58 , 61 – 63 , 67 , 69 ), since it is much smaller than fluid forces and reliable coefficients are difficult to retrieve ( 49 , 67 ).…”

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

“…Straight geometries with or without aortic sinuses may also be designed to replicate experimental set-ups ( 28 , 33 , 37 , 41 , 48 , 66 , 67 , 71 , 72 , 76 , 81 ) or aortic prostheses designs ( 53 , 58 , 59 ) ( Table 1 ). Patient-specific geometries, usually reconstructed from magnetic resonance ( 34 , 35 , 47 , 49 , 50 , 61 , 62 ) or computed tomography ( 38 , 45 ) images, consider the actual curvature and tortuosity of the ascending aorta, ensuring a higher level of similarity between simulated blood flow and in vivo conditions downstream of the valve. In the majority of idealized and patient-specific geometrical models, no structural component was included in the model downstream of the valve ( Table 1 ), except in some studies where deformable aortic walls ( 38 , 80 ) or deformable aortic valved prostheses ( 53 , 59 ) were incorporated ( Figure 2F ).…”

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

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Fluid-structure interaction simulation of mechanical aortic valves: a narrative review exploring its role in total product life cycle

Arminio,

Carbonaro,

Morbiducci

et al. 2024

Front. Med. Technol.

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Over the last years computer modelling and simulation has emerged as an effective tool to support the total product life cycle of cardiovascular devices, particularly in the device preclinical evaluation and post-market assessment. Computational modelling is particularly relevant for heart valve prostheses, which require an extensive assessment of their hydrodynamic performance and of risks of hemolysis and thromboembolic complications associated with mechanically-induced blood damage. These biomechanical aspects are typically evaluated through a fluid-structure interaction (FSI) approach, which enables valve fluid dynamics evaluation accounting for leaflets movement. In this context, the present narrative review focuses on the computational modelling of bileaflet mechanical aortic valves through FSI approach, aiming to foster and guide the use of simulations in device total product life cycle. The state of the art of FSI simulation of heart valve prostheses is reviewed to highlight the variety of modelling strategies adopted in the literature. Furthermore, the integration of FSI simulations in the total product life cycle of bileaflet aortic valves is discussed, with particular emphasis on the role of simulations in complementing and potentially replacing the experimental tests suggested by international standards. Simulations credibility assessment is also discussed in the light of recently published guidelines, thus paving the way for a broader inclusion of in silico evidence in regulatory submissions. The present narrative review highlights that FSI simulations can be successfully framed within the total product life cycle of bileaflet mechanical aortic valves, emphasizing that credible in silico models evaluating the performance of implantable devices can (at least) partially replace preclinical in vitro experimentation and support post-market biomechanical evaluation, leading to a reduction in both time and cost required for device development.

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Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

Section: State Of the Art Of Fsi Simulation Of Mechanical Aortic Valvesmentioning

confidence: 99%

See 2 more Smart Citations

Fluid-structure interaction simulation of mechanical aortic valves: a narrative review exploring its role in total product life cycle

Arminio,

Carbonaro,

Morbiducci

et al. 2024

Front. Med. Technol.

View full text Add to dashboard Cite

show abstract

“…Smart Materials can reform from their temporary shape to their original one in response to an external stimulus such as temperature, light, magnetic field, electrical potential, and pH (Janbaz et al, 2016;Abdolahi et al, 2017;Roudbarian et al, 2019a). These materials have myriad applications in different fields, such as aerospace engineering (Liu et al, 2014), robotics (Jebellat et al, 2021;Jin et al, 2018), textile engineering (Zhang et al, 2018;Udhayaraman and Mulay, 2019), medical devices (Zhao et al, 2019;Sadipour et al, 2020), drug delivery (Gharehnazifam et al, 2021(Gharehnazifam et al, , 2022Bayat et al, 2020), and biomaterials (Janbaz et al, 2016;Asadzadeh et al, 2020). Among them, shape-memory polymer (SMP) is a type of smart material that can intake shape-memory effect (SME).…”

Section: Introductionmentioning

confidence: 99%