Annals of Biomedical Engineering

, Volume 47, Issue 5, pp 1250–1264 | Cite as

Non-Destructive Reflectance Mapping of Collagen Fiber Alignment in Heart Valve Leaflets

  • Will Goth
  • Sam Potter
  • Alicia C. B. Allen
  • Janet Zoldan
  • Michael S. Sacks
  • James W. TunnellEmail author


Collagen fibers are the primary structural elements that define many soft-tissue structure and mechanical function relationships, so that quantification of collagen organization is essential to many disciplines. Current tissue-level collagen fiber imaging techniques remain limited in their ability to quantify fiber organization at macroscopic spatial scales and multiple time points, especially in a non-contacting manner, requiring no modifications to the tissue, and in near real-time. Our group has previously developed polarized spatial frequency domain imaging (pSFDI), a reflectance imaging technique that rapidly and non-destructively quantifies planar collagen fiber orientation in superficial layers of soft tissues over large fields-of-view. In this current work, we extend the light scattering models and image processing techniques to extract a critical measure of the degree of collagen fiber alignment, the normalized orientation index (NOI), directly from pSFDI data. Electrospun fiber samples with architectures similar to many collagenous soft tissues and known NOI were used for validation. An inverse model was then used to extract NOI from pSFDI measurements of aortic heart valve leaflets and clearly demonstrated changes in degree of fiber alignment between opposing sides of the sample. These results show that our model was capable of extracting absolute measures of degree of fiber alignment in superficial layers of heart valve leaflets with only general a priori knowledge of fiber properties, providing a novel approach to rapid, non-destructive study of microstructure in heart valve leaflets using a reflectance geometry.


Polarized light imaging Structured illumination Collagen fiber structure Cylindrical scattering Optical sectioning Wide-field reflectance imaging 



This work was supported by funding from the National Heart, Lung, and Blood Institute of the National Institutes of Health (awards RO1-HL108330 and RO1-HL129077), the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award T32-EB007505), and the Cancer Prevention and Research Institute of Texas (Award RP-130702). The authors would also like to thank Mason Dana for his contributions to data collection and instrumentation troubleshooting, and acknowledge the Microscopy and Imaging Facility of the Institute for Cellular and Molecular Biology at The University of Texas at Austin for use of their electron microscope facilities. There are no conflicts of interest from financial or other commercial benefits related to the development of this manuscript.


  1. 1.
    Allen, A. C., E. Barone, O. Cody, K. Crosby, L. J. Suggs, and J. Zoldan. Electrospun poly(N-isopropyl acrylamide)/poly(caprolactone) fibers for the generation of anisotropic cell sheets. Biomater. Sci. 5:1661–1669, 2017.CrossRefGoogle Scholar
  2. 2.
    Amoroso, N. J., A. D’Amore, Y. Hong, W. R. Wagner, and M. S. Sacks. Elastomeric electrospun polyurethane scaffolds: the interrelationship between fabrication conditions, fiber topology, and mechanical properties. Adv. Mater. 23:106–111, 2011.CrossRefGoogle Scholar
  3. 3.
    Ayoub, S., K. C. Tsai, A. H. Khalighi, and M. S. Sacks. The three-dimensional microenvironment of the mitral valve: insights into the effects of physiological loads. Cell. Mol. Bioeng. 11:291–306, 2018.CrossRefGoogle Scholar
  4. 4.
    Bodenschatz, N., P. Krauter, A. Liemert, J. Wiest, and A. Kienle. Model-based analysis on the influence of spatial frequency selection in spatial frequency domain imaging. Appl. Opt. 54:6725–6731, 2015.CrossRefGoogle Scholar
  5. 5.
    Bohren, C. F., and D. R. Huffman. Absorption and Scattering of Light by Small Particles. New York: Wiley, 2008.Google Scholar
  6. 6.
    Chenault, D. B., and R. A. Chipman. Measurements of linear diattenuation and linear retardance spectra with a rotating sample spectropolarimeter. Appl. Opt. 32:3513–3519, 1993.CrossRefGoogle Scholar
  7. 7.
    Courtney, T., M. S. Sacks, J. Stankus, J. Guan, and W. R. Wagner. Design and analysis of tissue engineering scaffolds that mimic soft tissue mechanical anisotropy. Biomaterials 27:3631–3638, 2006.Google Scholar
  8. 8.
    Cuccia, D. J., F. Bevilacqua, A. J. Durkin, F. R. Ayers, and B. J. Tromberg. Quantitation and mapping of tissue optical properties using modulated imaging. J. Biomed. Opt. 14:024012–024013, 2009.CrossRefGoogle Scholar
  9. 9.
    Cuccia, D. J., F. Bevilacqua, A. J. Durkin, and B. J. Tromberg. Modulated imaging: quantitative analysis and tomography of turbid media in the spatial-frequency domain. Opt. Lett. 30:1354–1356, 2005.CrossRefGoogle Scholar
  10. 10.
    Cuccia, D. J., F. Bevilacqua, A. J. Durkin, and B. J. Tromberg. Depth-sectioned imaging and quantitative analysis in turbid media using spatially modulated illumination. In: Biomedical Topical Meeting. Optical Society of America, 2004, p. FF5.Google Scholar
  11. 11.
    D’Amore, A., J. A. Stella, W. R. Wagner, and M. S. Sacks. Characterization of the complete fiber network topology of planar fibrous tissues and scaffolds. Biomaterials 31:5345–5354, 2010.CrossRefGoogle Scholar
  12. 12.
    Deitzel, J., J. Kleinmeyer, D. Harris, and N. B. Tan. The effect of processing variables on the morphology of electrospun nanofibers and textiles. Polymer 42:261–272, 2001.CrossRefGoogle Scholar
  13. 13.
    Doshi, J., and D. H. Reneker. Electrospinning process and applications of electrospun fibers. In: Industry Applications Society Annual Meeting, 1993. Conference Record of the 1993 IEEE. IEEE, 1993, pp. 1698–1703.Google Scholar
  14. 14.
    Eckert, C. E., R. Fan, B. Mikulis, M. Barron, C. A. Carruthers, V. M. Friebe, N. R. Vyavahare, and M. S. Sacks. On the biomechanical role of glycosaminoglycans in the aortic heart valve leaflet. Acta biomater. 9:4653–4660, 2013.CrossRefGoogle Scholar
  15. 15.
    Fratzl, P. Collagen: structure and mechanics, an introduction. In: Collagen. New York: Springer, 2008, pp. 1–13.Google Scholar
  16. 16.
    Gelse, K., E. Pöschl, and T. Aigner. Collagens—structure, function, and biosynthesis. Adv. Drug Deliv. Rev. 55:1531–1546, 2003.CrossRefGoogle Scholar
  17. 17.
    Ghosh, N., and I. A. Vitkin. Tissue polarimetry: concepts, challenges, applications, and outlook. J. Biomed. Opt. 16:110801–11080129, 2011.CrossRefGoogle Scholar
  18. 18.
    Ghosh, N. , I. A. Vitkin, and M. F. Wood. Mueller matrix decomposition for extraction of individual polarization parameters from complex turbid media exhibiting multiple scattering, optical activity, and linear birefringence. J. Biomed. Opt. 13:044014–044036, 2008.CrossRefGoogle Scholar
  19. 19.
    Gilbert, T. W., S. Wognum, E. M. Joyce, D. O. Freytes, M. S. Sacks, and S. F. Badylak. Collagen fiber alignment and biaxial mechanical behavior of porcine urinary bladder derived extracellular matrix. Biomaterials 29:4775–4782, 2008.CrossRefGoogle Scholar
  20. 20.
    Gioux, S., A. Mazhar, D. J. Cuccia, A. J. Durkin, B. J. Tromberg, and J. V. Frangioni. Three-dimensional surface profile intensity correction for spatially modulated imaging. J. Biomed. Opt. 14:034045, 2009.CrossRefGoogle Scholar
  21. 21.
    Goth, W., J. Lesicko, M. S. Sacks, and J. W. Tunnell. Optical-based analysis of soft tissue structures. Annu. Rev. Biomed. Eng. 2016. Scholar
  22. 22.
    Guo, X., M. F. Wood, and A. Vitkin. A Monte Carlo study of penetration depth and sampling volume of polarized light in turbid media. Opt. Commun. 281:380–387, 2008.CrossRefGoogle Scholar
  23. 23.
    Holzapfel, G. A. Biomechanics of soft tissue. Handb. Mater. Behav. Models 3:1049–1063, 2001.Google Scholar
  24. 24.
    Hotaling, N. A., K. Bharti, H. Kriel, and C. G. Simon. DiameterJ: a validated open source nanofiber diameter measurement tool. Biomaterials 61:327–338, 2015.CrossRefGoogle Scholar
  25. 25.
    Hulst, H. C., and H. Van De Hulst. Light Scattering by Small Particles. Mineola: Courier Dover Publications, 1957.Google Scholar
  26. 26.
    Jacques, S. L., and J. C. Ramella-Roman. Polarized Light Imaging of Tissues. Royal Society of Chemistry, 2004, pp. 591–607.Google Scholar
  27. 27.
    Jammalamadaka, S. R., and A. Sengupta. Topics in Circular Statistics. Singapore: World Scientific, 2001.CrossRefGoogle Scholar
  28. 28.
    Joyce, E. M., J. Liao, F. J. Schoen, J. E. Mayer, Jr., and M. S. Sacks. Functional collagen fiber architecture of the pulmonary heart valve cusp. Ann. Thorac. Surg. 87:1240–1249, 2009.CrossRefGoogle Scholar
  29. 29.
    Kemp, N., H. Zaatari, J. Park, H. G. Rylander, III, and T. Milner. Form-biattenuance in fibrous tissues measured with polarization-sensitive optical coherence tomography (PS-OCT). Opt. Express 13:4611–4628, 2005.CrossRefGoogle Scholar
  30. 30.
    Liu, B., M. Harman, S. Giattina, D. L. Stamper, C. Demakis, M. Chilek, S. Raby, and M. E. Brezinski. Characterizing of tissue microstructure with single-detector polarization-sensitive optical coherence tomography. Appl. Opt. 45:4464–4479, 2006.CrossRefGoogle Scholar
  31. 31.
    Lu, S.-Y., and R. A. Chipman. Interpretation of Mueller matrices based on polar decomposition. JOSA A 13:1106–1113, 1996.CrossRefGoogle Scholar
  32. 32.
    Mark, J. E. Physical Properties of Polymers Handbook. New York: Springer, 2007.CrossRefGoogle Scholar
  33. 33.
    Martin, C., and W. Sun. Biomechanical characterization of aortic valve tissue in humans and common animal models. J. Biomed. Mater. Res. A 100:1591–1599, 2012.CrossRefGoogle Scholar
  34. 34.
    Mega, Y., M. Robitaille, R. Zareian, J. McLean, J. Ruberti, and C. DiMarzio. Quantification of lamellar orientation in corneal collagen using second harmonic generation images. Opt. Lett. 37:3312–3314, 2012.CrossRefGoogle Scholar
  35. 35.
    Misfeld, M., and H.-H. Sievers. Heart valve macro- and microstructure. Philos. Trans. R. Soc. Lond. B 362:1421–1436, 2007.CrossRefGoogle Scholar
  36. 36.
    Oppenheim, A. V., and R. W. Schafer. Discrete-Time Signal Processing. Upper Saddle River: Prentice Hall, pp. 86–87, 1989.Google Scholar
  37. 37.
    Parry, D. A. The molecular fibrillar structure of collagen and its relationship to the mechanical properties of connective tissue. Biophys. Chem. 29:195–209, 1988.CrossRefGoogle Scholar
  38. 38.
    Qi, J., and D. S. Elson. Mueller polarimetric imaging for surgical and diagnostic applications: a review. J. Biophotonics 10:950–982, 2017.CrossRefGoogle Scholar
  39. 39.
    Sacks, M. S. Incorporation of experimentally-derived fiber orientation into a structural constitutive model for planar collagenous tissues. J. Biomech. Eng. 125:280–287, 2003.CrossRefGoogle Scholar
  40. 40.
    Sacks, M. S., D. B. Smith, and E. D. Hiester. A small angle light scattering device for planar connective tissue microstructural analysis. Ann. Biomed. Eng. 25:678–689, 1997.CrossRefGoogle Scholar
  41. 41.
    Samuels, R. J. Small angle light scattering from deformed spherulites. Theory and its experimental verification. J. Polym. Sci. C 1966. Scholar
  42. 42.
    Stella, J. A., and M. S. Sacks. On the biaxial mechanical properties of the layers of the aortic valve leaflet. J. Biomech. Eng. 129:757–766, 2007.CrossRefGoogle Scholar
  43. 43.
    Stoller, P., K. M. Reiser, P. M. Celliers, and A. M. Rubenchik. Polarization-modulated second harmonic generation in collagen. Biophys. J. 82:3330–3342, 2002.CrossRefGoogle Scholar
  44. 44.
    Sun, M., H. He, N. Zeng, E. Du, Y. Guo, S. Liu, J. Wu, Y. He, and H. Ma. Characterizing the microstructures of biological tissues using Mueller matrix and transformed polarization parameters. Biomed. Opt. Express 5:4223–4234, 2014.CrossRefGoogle Scholar
  45. 45.
    Tower, T. T., M. R. Neidert, and R. T. Tranquillo. Fiber alignment imaging during mechanical testing of soft tissues. Ann. Biomed. Eng. 30:1221–1233, 2002.CrossRefGoogle Scholar
  46. 46.
    Van Krevelen, D. W., and K. Te Nijenhuis. Properties of Polymers: Their Correlation with Chemical Structure; Their Numerical Estimation and Prediction from Additive Group Contributions. Amsterdam: Elsevier, 2009.CrossRefGoogle Scholar
  47. 47.
    Wiest, J., N. Bodenschatz, A. Brandes, A. Liemert, and A. Kienle. Polarization influence on reflectance measurements in the spatial frequency domain. Phys. Med. Biol. 60:5717, 2015.CrossRefGoogle Scholar
  48. 48.
    Yang, B., J. Lesicko, M. Sharma, M. Hill, M. S. Sacks, and J. W. Tunnell. Polarized light spatial frequency domain imaging for non-destructive quantification of soft tissue fibrous structures. Biomed. Opt. Express 6:1520–1533, 2015.CrossRefGoogle Scholar
  49. 49.
    York, T., L. Kahan, S. P. Lake, and V. Gruev. Real-time high-resolution measurement of collagen alignment in dynamically loaded soft tissue. J. Biomed. Opt. 19:066011, 2014.CrossRefGoogle Scholar
  50. 50.
    Zhou, W.-S., and X.-Y. Su. A direct mapping algorithm for phase-measuring profilometry. J. Mod. Opt. 41:89–94, 1994.CrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2019

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringThe University of Texas at AustinAustinUSA
  2. 2.Department of Mechanical EngineeringThe University of Texas at AustinAustinUSA
  3. 3.James T. Willerson Center for Cardiovascular Modeling and Simulation, Institute for Computational Engineering and Sciences, Department of Biomedical EngineeringThe University of Texas at AustinAustinUSA

Personalised recommendations