Mancini, Viviana

Segers, Patrick

Valen-Sendstad, Kristian

W. Bergersen, Aslak

English

Ghent University Academic Bibliography

[] COMPARING APPLES TO ORANGES; MEASURED SKIN VIBRATIONS CORRELATE PHENOTYPICALLY WITH COMPUTED POST-STENOTIC FLOW INSTABILITIES. A PRAGMATIC BUT ROBUST TOOL FOR EARLY DETECTION OF CAROTID STENOSES?Viviana Mancini1, Aslak W. Bergersen2, Kristian Valen-Sendstad2, Patrick Segers11Ghent University2Simula Research Laboratory* Mancini and Bergersen contributed equally to this work. Abstract: Early detection of asymptomatic carotid artery stenosis is crucial for prevention of ischemic stroke. We aim to investigate the ability of Laser Doppler Vibrometry (LDV) to infer asymptomatic stenosis from the intensity of stenosis-induced flow instabilities (IFI), transmitting their energy into mechanical vibrations detectable at the skin. We therefore combined in-silico and in-vitro experiments to understand how the common carotid artery flow rate (QCCA), internal/external carotid flow split (QICA/QCCA), and degree of stenosis affected IFI. We used the 2nd order fluid-dynamical finite-elements solver Oasis [1] to in-silico simulate three cardiac cycles with stenosis severity of 56, 66, 76, 86, and 96%, in addition to a healthy-subject model. Geometries were obtained from patient-specific computer tomography angiography images [2,3] with an internal carotid artery (ICA) stenosis of 76%. Flow rates (QCCA: 145-529 ml/min) and flow splits (QICA/QCCA: 11.9 to 70.8%) were varied for a physiologically plausible range, which led to a total of 19 simulations [4,5]. Mesh element and time step sizes were set based on previous spatial and temporal sensitivity studies [6]. We computed IFI from 20Hz high-pass-filtered pressure traces, obtained downstream the stenosis, and found Restenosis to be the best predictor for the presence of instabilities (Figure 1-A). These results confirmed in-vitro experiments in a compliant replica of the 76% stenosis model where, similarly, Restenosis was related to an increase in IFI derived from LDV displacement (Figure 1-B) recorded on the skin-mimicking foil surrounding the tissue-mimicking gel in which the model was embedded [7]. The overall correlation between experimental and computational data was R2 = 0.9956. The absence of turbulence in a healthy-subject model allowed us to estimate that Restenosis can predict moderate and severe stenosis with 77% sensitivity. However, the severe stenosis models did not harbor flow instabilities because of limited QICA, and would hence remain undiagnosed using LDV. These findings are in agreement with clinical studies [8] on expertly operated carotid auscultation. We conclude that LDV has the potential to be used as diagnostic tool for asymptomatic carotid stenosis.Figure 1: While being largely insensitive to expectedly relevant factors such as stenosis severity, inlet flow rate and flow split (A), the instabilities of high-pass filtered pressure traces from stenosis-induced flow instabilities increased together with Restenosis, both computationally and experimentally (B). Acknowledgments: H2020 European funded project 644798. References: [1] Mortensen et al., Comput Phys Comm 2015;188:177-188. [2] Bergersen et al., JOSS 2019 – submitted. [3] Iannaccone et al., Int J Artif Organs 2014;37:928-939. [4] Likittanasombut et al., J Neuroimaging 2006;16:34-38. [5] Groen et al., J Biomech 2010,43:2332-8. [6] Mancini et al., Cardiovasc Eng Technol 2019 – submitted. [7] Mancini et al., PlosONE 2019 – submitted. [8] Johansson et al., BMC Neurology 2008;8:1-8.

Comparing apples to oranges : measured skin vibrations correlate phenotypically with computed post-stenotic flow instabilities : a pragmatic but robust tool for early detection of carotid stenoses?

https://biblio.ugent.be/publication/8623928/file/8623929.pdf

Comparing apples to oranges : measured skin vibrations correlate phenotypically with computed post-stenotic flow instabilities : a pragmatic but robust tool for early detection of carotid stenoses?

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