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Inverse Finite Element Framework Combining Ultrasound Imaging and Inflation Testing of PVA Artery Phantoms

Guendouz, Y.; Razif, N. A. M.; Bernasconi, F.; Johnston, R. D.; Lally, C.

2024-05-03 bioengineering
10.1101/2024.05.01.591942 bioRxiv
Show abstract

The clinical decision to establish if a patient with carotid disease should undergo surgical intervention is primarily based on the percent stenosis. Whilst this applies for high-grade stenosed vessels (>70%), it falls short for other cases. Due to the heterogeneity of plaque tissue, probing the mechanics of the tissue would likely provide further insights into why some plaques are more prone to rupture. Mechanical characterisation of such tissue is nontrivial, however, due to the difficulties in collecting fresh, intact plaque tissue and using physiologically relevant mechanical testing of such material. The use of polyvinyl alcohol (PVA) is thus highly convenient because of its acoustic properties and tuneable mechanical properties. MethodsThe aim of this study is to demonstrate the potential of polyvinyl alcohol phantoms to simulate atherosclerotic features. In addition, a testing and simulation framework is developed for full PVA vessel material characterization using ring tensile testing and inflation testing combined with non-invasive ultrasound imaging and computational modelling. ResultsStrain stiffening behaviour was observed in PVA through ring tensile tests, particularly at high freeze-thaw cycles. Inflation testing of bi-layered phantoms featuring lipid pool inclusions demonstrated high strains at shoulder regions. The application of an inverse finite element framework successfully recovered boundaries and determined the shear moduli for the PVA wall to lie within the range 27 kPa to 53 kPa. ConclusionThe imaging-modelling framework presented facilitates the use and characterisation of arterial mimicking phantoms to further explore plaque rupture. It also shows translational potential for non-invasive mechanical characterisation of atherosclerotic plaques to improve the identification of clinically relevant metrics of plaque vulnerability.

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