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Time-resolved OCT-μPIV: a new microscopic PIV technique for noninvasive depth-resolved pulsatile flow profile acquisition

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An Erratum to this article was published on 10 February 2013

Abstract

In vivo acquisition of endothelial wall shear stress requires instantaneous depth-resolved whole-field pulsatile flow profile measurements in microcirculation. High-accuracy, quantitative and non-invasive velocimetry techniques are essential for emerging real-time mechano-genomic investigations. To address these research needs, a novel biological flow quantification technique, OCT-μPIV, was developed utilizing high-speed optical coherence tomography (OCT) integrated with microscopic Particle Image Velocimetry (μPIV). This technique offers the unique advantage of simultaneously acquiring blood flow profiles and vessel anatomy along arbitrarily oriented sagittal planes. The process is instantaneous and enables real-time 3D flow reconstruction without the need for computationally intensive image processing compared to state-of-the-art velocimetry techniques. To evaluate the line-scanning direction and speed, four sets of parametric synthetic OCT-μPIV data were generated using an in-house code. Based on this investigation, an in vitro experiment was designed at the fastest scan speed while preserving the region of interest providing the depth-resolved velocity profiles spanning across the width of a micro-fabricated channel. High-agreement with the analytical flow profiles was achieved for different flow rates and seed particle types and sizes. Finally, by employing blood cells as non-invasive seeding particles, in vivo embryonic vascular velocity profiles in multiple vessels were measured in the early chick embryo. The pulsatile flow frequency and peak velocity measurements were also acquired with OCT-μPIV, which agreed well with previous reported values. These results demonstrate the potential utility of this technique to conduct practical microfluidic and non-invasive in vivo studies for embryonic blood flows.

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References

  • Bogren HG, Buonocore MH, Valente RJ (2004) Four-dimensional magnetic resonance velocity mapping of blood flow patterns in the aorta in patients with atherosclerotic coronary artery disease compared to age-matched normal subjects. J Magn Reson Imaging 19(4):417–427

    Article  Google Scholar 

  • Boulnois J-L (1986) Photophysical processes in recent medical laser developments: a review. Lasers Med Sci 1:47–66

    Article  Google Scholar 

  • Brezinski ME (2006) Optical coherence tomography: principles and applications. Academic Press, London

    Google Scholar 

  • Chen J, Katz J (2005) Elimination of peak-locking error in PIV analysis using the correlation mapping method. Meas Sci Technol 16(8):1605–1618

    Article  Google Scholar 

  • Chen C-Y, Patrick MJ, Corti P, Kowalski W, Roman BL, Pekkan K (2011) Analysis of early embryonic great-vessel microcirculation in zebrafish using high-speed confocal μPIV. Biorheology 48:305–321

    Google Scholar 

  • Corti P, Young S, Chen CY, Patrick MJ, Rochon ER, Pekkan K, Roman BL (2011) Interaction between alk1 and blood flow in the development of arteriovenous malformations. Development 138(8):1573–1582

    Article  Google Scholar 

  • Davis A, Izatt J, Rothenberg F (2009) Quantitative measurement of blood flow dynamics in embryonic vasculature using spectral Doppler velocimetry. Anat Record (Hoboken) 292(3):311–319

    Article  Google Scholar 

  • Drexler W, Fujimoto JG (2008) Optical coherence tomography: technology and applications (biological and medical physics, biomedical engineering). Springer, Berlin

    Google Scholar 

  • Fercher AF, Drexler W, Hitzenberger CK, Lasser T (2003) Optical coherence tomography—principles and applications. Rep Prog Phys 66:239–303

    Article  Google Scholar 

  • Frakes DH, Pekkan K, Dasi LP, Kitajima HD, de Zelicourt D, Leo HL, Carberry J, Sundareswaran K, Simon H, Yoganathan AP (2008) Modified control grid interpolation for the volumetric reconstruction of fluid flows. Exp Fluids 45(6):987–997

    Article  Google Scholar 

  • Hahn C, Schwartz MA (2009) Mechanotransduction in vascular physiology and atherogenesis. Nat Rev Mol Cell Biol 10(1):53–62

    Article  Google Scholar 

  • Hove JR, Koster RW, Forouhar AS, Acevedo-Bolton G, Fraser SE, Gharib M (2003) Intracardiac fluid forces are an essential epigenetic factor for embryonic cardiogenesis. Nature 421(6919):172–177

    Article  Google Scholar 

  • Hu N, Clark EB (1989) Hemodynamics of the stage 12 to stage 29 chick embryo. Circ Res 65(6):1665–1670

    Article  Google Scholar 

  • Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, Hee MR, Flotte T, Gregory K, Puliafito CA et al (1991) Optical coherence tomography. Science 254(5035):1178–1181

    Article  Google Scholar 

  • Kim GB, Lee SJ (2006) X-ray PIV measurements of blood flows without tracer particles. Exp Fluids 41(2):195–200

    Article  Google Scholar 

  • Kim HB, Hertzberg JR, Shandas R (2004) Development and validation of echo PIV. Exp Fluids 36(3):455–462

    Article  Google Scholar 

  • Kowalski WJ, Teslovich NC, Dur O, Keller BB, Pekkan K (2012) Computational hemodynamic optimization predicts dominant aortic arch selection is driven by embryonic outflow tract orientation in the chick embryo. Biomech Model Mechanobiol 11(7):1057–1073

    Article  Google Scholar 

  • Lara M, Chen CY, Mannor P, Dur O, Menon PG, Yoganathan AP, Pekkan K (2011) Hemodynamics of the hepatic venous three-vessel confluences using particle image velocimetry. Ann Biomed Eng 39(9):2398–2416

    Article  Google Scholar 

  • Lee JY, Ji HS, Lee SJ (2007) Micro-PIV measurements of blood flow in extraembryonic blood vessels of chicken embryos. Physiol Meas 28(10):1149–1162

    Article  Google Scholar 

  • Lima R, Wada S, Tsubota K, Yamaguchi T (2006) Confocal micro-PIV measurements of three-dimensional profiles of cell suspension flow in a square microchannel. Meas Sci Technol 17(4):797–808

    Article  Google Scholar 

  • Lindken R, Westerweel J, Wieneke B (2006) Stereoscopic micro particle image velocimetry. Exp Fluids 41(2):161–171

    Article  Google Scholar 

  • Lindken R, Rossi M, Grosse S, Westerweel J (2009) Micro-particle image velocimetry (microPIV): recent developments, applications, and guidelines. Lab Chip 9(17):2551–2567

    Article  Google Scholar 

  • Markl M, Harloff A, Bley TA, Zaitsev M, Jung B, Weigang E, Langer M, Hennig J, Frydrychowicz A (2007) Time-resolved 3D MR velocity mapping at 3T: improved navigator-gated assessment of vascular anatomy and blood flow. J Magn Reson Imaging 25(4):824–831

    Article  Google Scholar 

  • Oosterbaan AM, Ursem NT, Struijk PC, Bosch JG, van der Steen AF, Steegers EA (2009) Doppler flow velocity waveforms in the embryonic chicken heart at developmental stages corresponding to 5–8 weeks of human gestation. Ultrasound Obstet Gynecol 33(6):638–644

    Article  Google Scholar 

  • Park JS, Kihm KD (2006) Three-dimensional micro-PTV using deconvolution microscopy. Exp Fluids 40(3):491–499

    Article  Google Scholar 

  • Park JS, Choi CK, Kihm KD (2004) Optically sliced micro-PIV using confocal laser scanning microscopy (CLSM). Exp Fluids 37(1):105–119

    Article  Google Scholar 

  • Parrish JA (1981) New concepts in therapeutic photomedicine: photochemistry, optical targeting and the therapeutic window. J Investig Dermatol 1:45–50

    Article  Google Scholar 

  • Patrick MJ, Chen CY, Frakes D, Dur O, Pekkan K (2011) Cellular-level near-wall unsteadiness of high-hematocrit erythrocyte flow using confocal μPIV. Exp Fluids 50:887–904

    Article  Google Scholar 

  • Poelma C, Vennemann LindkenR, Westerweel J (2008) In vivo blood flow and wall shear stress measurements in the vitelline network. Exp Fluids 45(4):703–713

    Article  Google Scholar 

  • Roman BL, Pekkan K (2012) Mechanotransduction in embryonic vascular development. Biomech Model Mechanobiol

  • Srinivasan S, Baldwin HS, Aristizabal O, Kwee L, Labow M, Artman M, Turnbull DH (1998) Noninvasive, in utero imaging of mouse embryonic heart development with 40-MHz echocardiography. Circulation 98(9):912–918

    Article  Google Scholar 

  • Sundareswaran KS, Haggerty CM, de Zelicourt D, Dasi LP, Pekkan K, Frakes DH, Powell AJ, Kanter KR, Fogel MA, Yoganathan AP (2011) Visualization of flow structures in Fontan patients using 3-dimensional phase contrast magnetic resonance imaging. J Thorac Cardiovasc Surg 143(5):1108–1116

    Article  Google Scholar 

  • Wang Y, Dur O, Patrick MJ, Tinney JP, Tobita K, Keller BB, Pekkan K (2009) Aortic arch morphogenesis and flow modeling in the chick embryo. Ann Biomed Eng 37(6):1069–1081

    Article  Google Scholar 

  • Weinbaum S, Tarbell JM, Damiano ER (2007) The structure and function of the endothelial glycocalyx layer. Annu Rev Biomed Eng 9:121–167

    Article  Google Scholar 

  • Weissmann-Brenner A, Pretorius DH, Achiron R, Gindes L (2012) Fetal echocardiography: the four-chamber view, the outflow tracts, and the contribution of the cardiac arches. Ultrasound Clin 7(1):1–13

    Article  Google Scholar 

  • Zheng H, Liu L, Williams L, Hertzberg R, Lanning C, Shandas R (2006) Real time multicomponent echo particle image velocimetry technique for opaque flow imaging. Appl Phys Lett 88(26):261915

    Article  Google Scholar 

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Acknowledgments

This work was supported by NSF CAREER 0954465 and ERC Consolidator Grants.

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan

    Chia-Yuan Chen

  2. Departments of Biomedical and Mechanical Engineering, Carnegie Mellon University, 700 Technology Drive, Pittsburgh, PA, 15219, USA

    Prahlad G. Menon, William Kowalski & Kerem Pekkan

  3. Department of Mechanical Engineering, Koc University, Rumelifeneri, Istanbul, Turkey

    Kerem Pekkan

Authors
  1. Chia-Yuan Chen
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  2. Prahlad G. Menon
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  3. William Kowalski
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  4. Kerem Pekkan
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Correspondence to Kerem Pekkan.

Appendix

Appendix

In PIV, a significant portion of measurement error can be caused by the tracer particle size. This error have been well established for a standard μPIV experiment (Lindken et al. 2009) but needs to be quantified for the new OCT-μPIV technique. In order to investigate particle size effect on the OCT-μPIV velocity measurements, three different types of particles were tested that range from 1 to 12 μm. The resultant velocity profiles obtained with these particles were plotted in Fig. 6 along with corresponding analytical solution comparison and the raw OCT-μPIV images. Through this comparison, the optimal ratio of particle size to the relevant fluid dynamic length scale should be in the range of 0.03 (12/400 μm) and 0.003 (1/400 μm). In this work, the channel width was fabricated to be 400 μm, and therefore, the particle size of 3.2 μm was selected to ensure that the particle response time is smaller than the smallest time scale in the flow and free of Brownian motion effects. The calculated interparticular distance values for 12, 3.2, and 1.0 μm particles are 94, 38, and 16.7 μm, respectively.

Fig. 6
figure 6

Depth-resolved velocity profiles acquired at the center of the microchannel with three different types of particles compared with the corresponding analytical solutions. Error bars indicate one standard deviation values for each particle type. Red: hollow glass beads with 8–12 μm in diameter (TSI, Inc., MN) at concentration of 0.6 % (mg/mL); Blue: fluorescent particles with 3.2 μm in diameter (Microgenics, Inc., CA) at concentration of 0.2 %; Green: fluorescent particles with 1.0 μm in diameter (Microgenics, Inc., CA) at concentration of 0.1 %

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Chen, CY., Menon, P.G., Kowalski, W. et al. Time-resolved OCT-μPIV: a new microscopic PIV technique for noninvasive depth-resolved pulsatile flow profile acquisition. Exp Fluids 54, 1426 (2013). https://doi.org/10.1007/s00348-012-1426-x

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  • DOI: https://doi.org/10.1007/s00348-012-1426-x

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