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Inverse identification of local stiffness across ascending thoracic aortic aneurysms

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Abstract

Aortic dissection is the most common catastrophe of the thoracic aorta, with a very high rate of mortality. Type A dissection is often associated with an ascending thoracic aortic aneurysm (ATAA). However, it is widely acknowledged that the risk of type A dissection cannot be reliably predicted simply by measuring the ATAA diameter and there is a pressing need for more reliable risk predictors. It was previously shown that there is a significant correlation between a rupture criterion based on the ultimate stretch of the ATAA and the local extensional stiffness of the aorta. Therefore, reconstructing regional variations of the extensional stiffness across the aorta appears highly important. In this paper, we present a novel noninvasive inverse method to identify the patient-specific local extensional stiffness of aortic walls based on preoperative gated CT scans. Using these scans, a structural mesh is defined across the aorta with a set of nodes attached to the same material points at different time steps throughout the cardiac cycle. For each node, time variations of the position are analyzed using Fourier series, permitting the reconstruction of the local strain distribution (fundamental term). Relating these strains to tensions with the extensional stiffness, and writing the local equilibrium satisfied by the tensions, the local extensional stiffness is finally derived at every position. The methodology is applied onto the ascending and descending aorta of three patients. Interestingly, the regional distribution of identified stiffness properties appears heterogeneous across the ATAA. Averagely, the identified stiffness is also compared with values obtained using other nonlocal methodologies. The results support the possible noninvasive prediction of stretch-based rupture criteria in clinical practice using local stiffness reconstruction.

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Acknowledgements

The authors are grateful to the European Research Council for Grant ERC-2014-CoG BIOLOCHANICS.

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Authors and Affiliations

  1. Mines Saint-Étienne, CIS-EMSE, 42023, Saint-Étienne, France

    Solmaz Farzaneh, Olfa Trabelsi & Stéphane Avril

  2. INSERM, U1059, SAINBIOSE, 42023, Saint-Étienne, France

    Solmaz Farzaneh, Olfa Trabelsi & Stéphane Avril

  3. Université de Lyon, 69000, Lyon, France

    Solmaz Farzaneh, Olfa Trabelsi & Stéphane Avril

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  1. Solmaz Farzaneh
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Correspondence to Stéphane Avril.

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Farzaneh, S., Trabelsi, O. & Avril, S. Inverse identification of local stiffness across ascending thoracic aortic aneurysms. Biomech Model Mechanobiol 18, 137–153 (2019). https://doi.org/10.1007/s10237-018-1073-0

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