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Three-Dimensional Strain Measurements of a Tubular Elastic Model Using Tomographic Particle Image Velocimetry

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Abstract

The evaluation of strain induced in a blood vessel owing to contact with a medical device is of significance to examine the causes leading to vascular injury and rupture. The development of a method to assess strain in largely deformed elastic materials is expected. This study’s scope was to measure strain in deformed tubular elastic mock vessels using tomographic particle image velocimetry (tomo-PIV), and to show the applicability of this measurement method by comparing the results with data derived from a finite element analysis (FEA). Strain distribution was calculated from the displacement distribution, which in turn was measured by tracking fluorescent 13 μm particles in a transparent tubular elastic model using tomo-PIV. The von Mises strain distribution was calculated for a model whose inner diameter was subjected to a pressure load, because of which it expanded from 25 to 27.5 mm, adjusting to the diameter change of a human aorta during heartbeat. An FEA simulating the experiment was also conducted. Three-dimensional strain was successfully measured by using the tomo-PIV method. The radial strain distribution in the model linearly decreased outward (from the its inner to its outer side), and the result was consistent with the data obtained from the FEA. The mean von Mises strain measured using tomo-PIV was comparable with that obtained from the FEA (tomo-PIV: 0.155, FEA: 0.156). This study demonstrates the feasibility of utilizing tomo-PIV to quantitatively assess the three-dimensional strain induced in largely deformed elastic models.

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References

  1. Altngi, H. E., B. Bousaid, and H. W. Berre. Morphological and stent design risk factors to prevent migration phenomena for a thoracic aneurysm: a numerical analysis. Med. Eng. Phys. 37:23–33, 2015.

    Article  Google Scholar 

  2. Auricchio, F., M. Conti, M. D. Beule, G. D. Santis, and B. Verhegghe. Carotid artery stenting simulation: from patient-specific images to finite element analysis. Med. Eng. Phys. 33:281–289, 2011.

    Article  Google Scholar 

  3. Auricchio, F., M. Conti, S. Morganti, and A. Reali. Simulation of transcatheter aortic valve implantation: a patient-specific finite element approach. Comput. Methods Biomech. Biomed. Eng. 17(12):1–11, 2014.

    Article  Google Scholar 

  4. Bazilevs, Y., M. C. Hsu, Y. Zhang, W. Wang, T. Kvamsdal, S. Hentschel, and J. G. Isaksen. Computational vascular fluid–structure interaction: methodology and application to cerebral aneurysms. Biomech. Model Mechanobiol. 9:481–498, 2010.

    Article  Google Scholar 

  5. Benbarek, S., B. Bouiadjra, B. T. Achour, and B. Serier. Finite element analysis of the behavior of crack emanating from microvoid in cement of reconstructed acetabulum. Mat. Sci. Eng. A-Struct. 457:385–391, 2007.

    Article  Google Scholar 

  6. Benoit, A., S. Guerard, B. Gillet, G. Guillot, F. Hild, D. Mitton, J. N. Peire, and S. Roux. 3D analysis from micro-MRI during in situ compression on cancellous bone. J. Biomech. 42:2381–2386, 2009.

    Article  Google Scholar 

  7. Birjinjuk, J., J. M. Ruddy, E. Iffrig, T. S. Henry, B. G. Leshnower, J. N. Oshinski, D. N. Ku, and R. K. Veeraswamy. Development and testing of a silicone in vitro model of descending aortic dissection. J. Surg. Res. 198:502–507, 2015.

    Article  Google Scholar 

  8. Buchmann, N. A., C. Atkinson, M. C. Jeremy, and J. Soria. Tomographic particle image velocimetry investigation of the flow in a modeled human carotid artery bifurcation. Exp. Fluids 50(4):1131–1151, 2011.

    Article  Google Scholar 

  9. Burton, A. C. Relation of structure to function of the tissues of the wall of blood vessels. Physiol. Rev. 34:619–642, 1954.

    Article  Google Scholar 

  10. Cheng, Y. Y., J. Y. Li, S. L. Fok, W. L. Cheung, and T. W. Chow. 3D FEA of high-performance polyethylene fiber reinforced maxillary dentures. Dent. Mater. 26:e211–e219, 2010.

    Article  Google Scholar 

  11. Ducci, A., F. Pirisi, S. Tzamtzis, and G. Burriesci. Transcatheter aortic valves produce unphysiological flows which may contribute to thromboembolic events: an in vitro study. J. Biomech. 49:4080–4089, 2016.

    Article  Google Scholar 

  12. Elsinga, G. E., F. Scarano, B. Wieneke, and B. W. V. Oudheusden. Tomographic particle image velocimetry. Exp. Fluids 41(6):933–947, 2006.

    Article  Google Scholar 

  13. Elsinga, G. E., and S. Togoz. Ghost hunting: an assessment of ghost particle detection and removal methods for tomo-PIV. Meas. Sci. Technol. 25:084004, 2014.

    Article  Google Scholar 

  14. Gahagnon, S., Y. Mofid, G. Josse, and F. Ossant. Skin anisotropy in vivo and initial natural stress effect: a quantitative study using high-frequency static elastography. J. Biomech. 45:2860–2865, 2012.

    Article  Google Scholar 

  15. Germaneau, A., P. Doumalin, and J. C. Dupre. 3D strain field measurement by correlation of volume images using scattered light: recording of images and choice of marks. Strain 43(3):207–218, 2007.

    Article  Google Scholar 

  16. Gillard, F., R. Boardman, M. Mavrogordato, D. Hollis, I. Sinclair, F. Pierron, and M. Browne. The application of digital volume correlation (DVC) to study the microstructural behaviour of trabecular bone during compression. J. Mech. Behav. Biomed. Mater. 29:480–499, 2014.

    Article  Google Scholar 

  17. Gutowski, V., L. Russell, and A. Cerra. New tests for adhesion of silicone sealants. Constr. Build. Mater. 7(1):19–25, 1993.

    Article  Google Scholar 

  18. Hasler, D., A. Landolt, and D. Obrist. Tomographic PIV behind a prosthetic heart valve. Exp. Fluids 57:80, 2016.

    Article  Google Scholar 

  19. Herman, G. T., and A. Lent. Iterative reconstruction algorithms. Comput. Biol. Med. 6:273–294, 1976.

    Article  Google Scholar 

  20. Hussein, A. I., P. E. Barbone, and E. F. Morgan. Digital volume correlation for study of the mechanics of whole bones. Procedia IUTAM. 4:116–125, 2012.

    Article  Google Scholar 

  21. Itoh, H., and Y. Yamada. Measurement of silicone rubber using impedance change of a quartz-crystal tuning-fork tactile sensor. J. Appl. Phys. 45:4643–4646, 2006.

    Article  Google Scholar 

  22. Kono, K., and T. Terada. In vitro experiments of vessel wall apposition between the enterprise and enterprise 2 stents for treatment of cerebral aneurysms. Acta Neurochir. 158:241–245, 2016.

    Article  Google Scholar 

  23. Liang, D. K., D. Z. Yang, M. Qi, and W. Q. Wang. Finite element analysis of the implantation of a balloon-expandable stent in a stenosed artery. Int. J. Cardiol. 104:314–318, 2005.

    Article  Google Scholar 

  24. Madi, K., G. Tozzi, Q. H. Zhang, J. Tong, A. Cossey, A. Au, D. Hollis, and F. Hild. Computation of full-field displacements in a scaffold implant using digital volume correlation and finite element analysis. Med. Eng. Phys. 35:1298–1312, 2013.

    Article  Google Scholar 

  25. Maier, A., M. W. Gee, C. Reeps, J. Pongratz, H. H. Eckstein, and W. A. Wall. A comparison of diameter, wall stress, and rupture potential index for abdominal aortic aneurysm rupture risk prediction. Ann. Biomed. Eng. 38(10):3124–3134, 2010.

    Article  Google Scholar 

  26. Martin, D., and F. Boyle. Finite element analysis of balloon-expandable coronary stent deployment: influence of angioplasty balloon configuration. Int. J. Numer. Method Biomed. Eng. 29:1161–1175, 2013.

    Article  Google Scholar 

  27. Mucke, T., L. M. Ritschl, A. B. Dipl, K. D. Wolff, D. A. Mitchell, and D. Liepsch. Opened end-to-side technique for end-to-side anastomosis and analyses by an elastic true-to-scale silicone rubber model. Microsurgery 34(1):28–36, 2013.

    Article  Google Scholar 

  28. Nikanorov, A., H. B. Smouse, K. Osman, M. Bialas, S. Shrivastava, and L. B. Schwartz. Fracture of self-expanding nitinol stents stressed in vitro under simulated intravascular conditions. J. Vasc. Surg. 48(2):435–440, 2008.

    Article  Google Scholar 

  29. Novara, M., K. J. Batenburg, and F. Scarano. Motion tracking enhanced MART for tomo-PIV. Meas. Sci. Technol. 21:035401, 2010.

    Article  Google Scholar 

  30. Novara, M., and F. Scarano. Performances of motion tracking enhanced tomo-PIV on turbulent shear flows. Exp. Fluids 52:1027–1041, 2012.

    Article  Google Scholar 

  31. Pericevic, I., L. Caitriona, D. Toner, and D. J. Kelly. The influence of plaque composition on underlying arterial wall stress during stent expansion: the case for lesion-specific stents. Med. Eng. Phys. 31:428–433, 2009.

    Article  Google Scholar 

  32. Roberts, B. C., E. Perilli, and K. J. Reynolds. Application of the digital volume correlation technique for the measurement of displacement and strain fields in bone: a literature review. J. Biomech. 47:923–934, 2014.

    Article  Google Scholar 

  33. Scarano, F. Tomo-PIV: principles and practice. Meas. Sci. Technol. 24:012001, 2013.

    Article  Google Scholar 

  34. Scarano, F., and M. Riethmuller. Advances in iterative multigrid PIV image processing. Exp. Fluids 29(7):51–60, 2000.

    Article  Google Scholar 

  35. Tanaka, Y., S. Saito, S. Sasuga, A. Takahashi, Y. Aoyama, K. Obama, M. Umezu, and K. Iwasaki. Quantitative assessment of paravalvular leakage after transcatheter aortic valve replacement using a patient-specific pulsatile flow model. Int. J. Cardiol. 258:313–320, 2018.

    Article  Google Scholar 

  36. Verhulp, E., B. V. Rietbergen, and R. Huiskes. A three-dimensional digital image correlation technique for strain measurements in microstructures. J. Biomech. 37:1313–1320, 2004.

    Article  Google Scholar 

  37. Wang, Y., Y. Hu, X. Gong, W. Jiang, P. Zhang, and Z. Chen. Preparation and properties of magnetorheological elastomers based on silicone rubber/polystyrene blend matrix. J. Appl. Polym. Sci. 103:3143–3149, 2007.

    Article  Google Scholar 

  38. Wang, Q., S. Kodali, C. Primiano, and W. Sun. Simulations of transcatheter aortic valve implantation: implications for aortic root rupture. Biomech. Model Mechanobiol. 14(1):29–38, 2015.

    Article  Google Scholar 

  39. Wells, P. N. T., and H. D. Liang. Medical ultrasound: imaging of soft tissue strain and elasticity. J. R. Soc. Interface 8:1521–1549, 2011.

    Article  Google Scholar 

  40. Wernet, M. P., and J. A. Hadley. A high temperature seeding technique for particle image velocimetry. Meas. Sci. Technol. 27:125201, 2016.

    Article  Google Scholar 

  41. Wieneke, B. Volume self-calibration for 3D particle image velocimetry. Exp. Fluids 45:549–556, 2008.

    Article  Google Scholar 

Download references

Acknowledgments

This research was partially supported by the Research on Regulatory Science of Pharmaceuticals and Medical Devices from the Japan Agency for Medical Research and Development, AMED (No. 17mk0102042h0003) and the Japan Society for Promotion of Science (15J07145).

Conflict of interest

All authors declare that they have no conflicts of interest.

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

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Authors and Affiliations

  1. Department of Integrative Bioscience and Biomedical Engineering, Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, Japan

    Azuma Takahashi, Yusuke Aoyama, Mitsuo Umezu & Kiyotaka Iwasaki

  2. Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan

    Xiaodong Zhu, Mitsuo Umezu & Kiyotaka Iwasaki

  3. Cooperative Major in Advanced Biomedical Sciences, Graduate School of Advanced Science and Engineering, Waseda University, Tokyo, Japan

    Mitsuo Umezu & Kiyotaka Iwasaki

  4. 2-2 Wakamatsu-cho, Shinjuku, Tokyo, 162-8480, Japan

    Kiyotaka Iwasaki

Authors
  1. Azuma Takahashi
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Correspondence to Kiyotaka Iwasaki.

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Associate Editors Ulrich Steinseifer and Ajit P. Yoganathan oversaw the review of this article.

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Takahashi, A., Zhu, X., Aoyama, Y. et al. Three-Dimensional Strain Measurements of a Tubular Elastic Model Using Tomographic Particle Image Velocimetry. Cardiovasc Eng Tech 9, 395–404 (2018). https://doi.org/10.1007/s13239-018-0350-5

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  • DOI: https://doi.org/10.1007/s13239-018-0350-5

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