Characterisation of Elastic and Acoustic Properties of an Agar-Based Tissue Mimicking Material

Brewin, M.P.; Birch, Malcolm; Mehta, Deepak; Reeves, Jonathan; Shaw, Sylvie; Kruse, Carola; Whiteman,; Hu, Shiqi; Kenz, Zackary R.; Banks, H. T.; Greenwald, Stephen E.

doi:10.1007/s10439-015-1294-7

Cited by 7 publications

(5 citation statements)

References 26 publications

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“…Therefore, anticipating how this might affect the results are challenging. Moreover, the soft tissue embedding the carotid arteries would further dampen the instabilities that would present on the skin surface, generally with a lower amplitude relative to the fluctuations induced by the turbulent-like post-stenotic flow 5…”

Section: Discussionmentioning

confidence: 99%

High-Frequency Fluctuations in Post-stenotic Patient Specific Carotid Stenosis Fluid Dynamics: A Computational Fluid Dynamics Strategy Study

Mancini

Bergersen

Vierendeels

et al. 2019

Cardiovasc Eng Tech

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Purpose Screening of asymptomatic carotid stenoses is performed by auscultation of the carotid bruit, but the sensitivity is poor. Instead, it has been suggested to detect carotid bruit as neck’s skin vibrations. We here take a first step towards a computational fluid dynamics proof-of-concept study, and investigate the robustness of our numerical approach for capturing high-frequent fluctuations in the post-stenotic flow. The aim was to find an ideal solution strategy from a pragmatic point of view, balancing accuracy with computational cost comparing an under-resolved direct numerical simulation (DNS) approach vs. three common large eddy simulation (LES) models (static/dynamic Smagorinsky and Sigma). Method We found a reference solution by performing a spatial and temporal refinement study of a stenosed carotid bifurcation with constant flow rate. The reference solution was compared against LES for both a constant and pulsatile flow. Results Only the Sigma and Dynamic Smagorinsky models were able to replicate the flow field of the reference solution for a pulsatile simulation, however the computational cost of the Sigma model was lower. However, none of the sub-grid scale models were able to replicate the high-frequent flow in the peak-systolic constant flow rate simulations, which had a higher mean Reynolds number. Conclusions The Sigma model was the best combination between accuracy and cost for simulating the pulsatile post-stenotic flow field, whereas for the constant flow rate, the under-resolved DNS approach was better. These results can be used as a reference for future studies investigating high-frequent flow features.

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Section: Discussionmentioning

confidence: 99%

High-Frequency Fluctuations in Post-stenotic Patient Specific Carotid Stenosis Fluid Dynamics: A Computational Fluid Dynamics Strategy Study

Mancini

Bergersen

Vierendeels

et al. 2019

Cardiovasc Eng Tech

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“…Therefore, the vertical strain related to the compression was estimated based on σ compression and the bulk modulus ( K ) definition: , where and is the vertical compression-related thickness change. Furthermore, is defined using the initial absolute shear modulus of the explant matrix: , where is the Poisson’s ratio of agarose: = 0.44 is based on 66 . The, the effective elastic modulus of the compressed explant-culture matrix is .…”

Section: Methodsmentioning

confidence: 99%

Compressive stress-mediated p38 activation required for ERα + phenotype in breast cancer

et al. 2021

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Breast cancer is now globally the most frequent cancer and leading cause of women’s death. Two thirds of breast cancers express the luminal estrogen receptor-positive (ERα + ) phenotype that is initially responsive to antihormonal therapies, but drug resistance emerges. A major barrier to the understanding of the ERα-pathway biology and therapeutic discoveries is the restricted repertoire of luminal ERα + breast cancer models. The ERα + phenotype is not stable in cultured cells for reasons not fully understood. We examine 400 patient-derived breast epithelial and breast cancer explant cultures (PDECs) grown in various three-dimensional matrix scaffolds, finding that ERα is primarily regulated by the matrix stiffness. Matrix stiffness upregulates the ERα signaling via stress-mediated p38 activation and H3K27me3-mediated epigenetic regulation. The finding that the matrix stiffness is a central cue to the ERα phenotype reveals a mechanobiological component in breast tissue hormonal signaling and enables the development of novel therapeutic interventions. Subject terms: ER-positive (ER + ), breast cancer, ex vivo model, preclinical model, PDEC, stiffness, p38 SAPK.

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“…The key pieces that will be modeled are the loading profile (loading begins at t = Γ 1 and lasts until the weight begins to be released at t = Γ 3 ), which we will model as instantaneous loading to position A , and the oscillations after weight release (free oscillations begin at t = Γ 4 = 0) which are the main object of investigations here. For more information on the experimental setup, interested readers may refer to [27]. …”

Section: Methodsmentioning

confidence: 99%

Model validation for a noninvasive arterial stenosis detection problem

Banks

Hu²,

Kenz³

et al. 2014

Mathematical Biosciences and Engineering

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A current thrust in medical research is the development of a non-invasive method for detection, localization, and characterization of an arterial stenosis (a blockage or partial blockage in an artery). A method has been proposed to detect shear waves in the chest cavity which have been generated by disturbances in the blood flow resulting from a stenosis. In order to develop this methodology further, we use one-dimensional shear wave experimental data from novel acoustic phantoms to validate a corresponding viscoelastic mathematical model. We estimate model parameters which give a good fit (in a sense to be precisely defined) to the experimental data, and use asymptotic error theory to provide confidence intervals for parameter estimates. Finally, since a robust error model is necessary for accurate parameter estimates and confidence analysis, we include a comparison of absolute and relative models for measurement error.

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Characterisation of Elastic and Acoustic Properties of an Agar-Based Tissue Mimicking Material

Cited by 7 publications

References 26 publications

High-Frequency Fluctuations in Post-stenotic Patient Specific Carotid Stenosis Fluid Dynamics: A Computational Fluid Dynamics Strategy Study

High-Frequency Fluctuations in Post-stenotic Patient Specific Carotid Stenosis Fluid Dynamics: A Computational Fluid Dynamics Strategy Study

Compressive stress-mediated p38 activation required for ERα + phenotype in breast cancer

Model validation for a noninvasive arterial stenosis detection problem

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