Skip to main content
SpringerLink
Log in

Probing Different Biological Length Scales Using Photoacoustics: From 1 to 1000 MHz

  • Reference work entry
  • First Online:
Handbook of Photonics for Biomedical Engineering

Abstract

Photoacoustics (PA) is proving to be a versatile imaging modality combining features of ultrasonic and optical imaging such as the high resolution of ultrasound (US) with the contrast of optical imaging, reducing the fundamental depth limitation of the photon mean free path. This chapter focuses on using PA as a tool for probing various biological length scales by adjusting the frequency of the detected PA signals. As the frequency increases, the PA imaging resolution increases allowing for the examination of smaller length scales. More specifically, the ability of PA to characterize red blood cells (RBCs) is explored by analysis of the frequency-domain content of the PA signals rather than the PA signal strength typically used. RBCs are one of the most dominant sources of endogenous contrast in PA imaging, and the presented research has focused on probing the effect of RBC orientation, morphology, and pathology at various length scales. Finite element models were developed investigating the effect of cell orientation and morphology on the features of the PA power spectra over 100 MHz, where significant differences in the simulated and measured power spectra for various RBC orientations have been observed. The shape used to model RBCs (biconcave, oblate ellipsoid, and sphere) was found to also significantly affect the features of the power spectra. Using clinically relevant US detection frequencies (<10 MHz), aggregation of RBCs, a pathological condition, could be characterized using quantitative parameters adapted from US tissue characterization techniques. The formation of aggregates was shown to impair the release of oxygen into the surrounding environment and this change could be quantified using PA at multiple optical irradiation wavelengths.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 849.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 899.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Xu M, Wang LV (2006) Photoacoustic imaging in biomedicine. Rev Sci Instrum 77:041101-1-22

    Google Scholar 

  2. Kreuzer LB (1971) Ultralow gas concentration infrared absorption spectroscopy. J Appl Phys 42:2934–2943

    Article  Google Scholar 

  3. Rosencwaig A, Gersho A (1976) Theory of the photoacoustic effect with solids. J Appl Phys 47:64–69

    Article  Google Scholar 

  4. Wang LV, Hu S (2012) Photoacoustic tomography: in vivo imaging from organelles to organs. Science 335:1458–1462

    Article  Google Scholar 

  5. Ma R, Taruttis A, Ntziachristos V, Razansky D (2009) Multispectral optoacoustic tomography (MSOT) scanner for whole-body small animal imaging. Opt Express 17:21414–21426

    Article  Google Scholar 

  6. Emelianov SY, Li P, O’Donnell M (2009) Photoacoustics for molecular imaging and therapy. Phys Today 62:34–39

    Article  Google Scholar 

  7. Bowen T (1981) Radiation-induced thermoacoustic soft tissue imaging. Proc IEEE Ultrason Symp 2:817–822

    Google Scholar 

  8. Zhang HF, Maslov K, Stoica G, Wang LV (2006) Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging. Nat Biotechnol 24:848–851

    Article  Google Scholar 

  9. Lao Y, Xing D, Yang S, Xiang L (2008) Noninvasive photoacoustic imaging of the developing vasculature during early tumor growth. Phys Med Biol 53:4203–4212

    Article  Google Scholar 

  10. Siphanto RI et al (2005) Serial noninvasive photoacoustic imaging of neovascularization in tumor angiogenesis. Opt Express 13:89–95

    Article  Google Scholar 

  11. Wang X, Xie X, Ku G, Wang LV, Stoica G (2006) Noninvasive imaging of hemoglobin concentration and oxygenation in rat brain using high-resolution photoacoustic tomography. J Biomed Opt 11:024015-1-9

    Google Scholar 

  12. Esenaliev RO, Larina IV, Larin KV, Deyo DJ, Motamedi M, Prough DS (2002) Optoacoustic technique for noninvasive monitoring of blood oxygenation: a feasibility study. Appl Optics 41:4722–4731

    Article  Google Scholar 

  13. Esenaliev RO, Petrov YY, Hartrumpf O, Deyo DJ, Prough DS (2004) Continuous, noninvasive monitoring of total hemoglobin concentration by an optoacoustic technique. Appl Optics 43:3401–3407

    Article  Google Scholar 

  14. Mallidi S, Luke GP, Emelianov S (2011) Photoacoustic imaging in cancer detection, diagnosis and treatement guidance. Trends Biotechnol 29:213–221

    Article  Google Scholar 

  15. Zalev J, Kolios MC (2011) Detecting abnormal vasculature from photoacoustic signals using wavelet-packet features. Proc SPIE 7899:78992M-1-15

    Google Scholar 

  16. Patterson MP, Riley CP, Kolios MC, Whelan WM (2011) Optoacoustic signal amplitude and frequency spectrum analysis laser heated bovine liver ex-vivo. In: Proceedings IEEE ultrasonics symposium, Orlando, FL, pp 300–303

    Google Scholar 

  17. Strohm E, Rui M, Gorelikov I, Matsuura N, Kolios MC (2011) Vaporization of perfluorocarbon droplets using optical irradiation. Biomed Opt Express 2:1432–1442

    Article  Google Scholar 

  18. Wilson K, Homan K, Emelianov S (2012) Biomedical photoacoustics beyond thermal expansion using triggered nanodroplet vaporization for contrast-enhanced imaging. Nat Commun 3:618–629

    Article  Google Scholar 

  19. Li C, Wang LV (2009) Photoacoustic tomography and sensing in biomedicine. Phys Med Biol 54:R59–R97

    Article  Google Scholar 

  20. Diebold GJ (2009) Photoacoustic monopole radiation: waves from objects with symmetry in one, two and three dimensions. In: Wang LV (ed) Photoacoustic imaging and spectroscopy. CRC Press, Boca Raton, pp 3–17

    Chapter  Google Scholar 

  21. Diebold GJ, Khan MI, Park SM (1990) Photoacoustic signatures of particulate matter: optical production of acoustic monopole radiation. Science 250:101–104

    Article  Google Scholar 

  22. Zagzebski JA (1996) Essentials of ultrasound physics. Mosby, St. Louis

    Google Scholar 

  23. Szabo TL (2004) Diagnostic ultrasound imaging: inside out. Elsevier Academic, New York

    Google Scholar 

  24. Lizzi FL (1997) Ultrasonic scatter-property images of the eye and prostate. Proc IEEE Ultrason Symp 17:1109–1117

    Google Scholar 

  25. Lizzi FL, Greenbaum M, Feleppa EJ, Elbaum M, Coleman DJ (1983) Theoretical framework for spectrum analysis in ultrasound tissue characterization. J Acoust Soc Am 73:1366–1373

    Article  Google Scholar 

  26. Lizzi FL, Ostromogilsky M, Feleppa EJ, Rorke MC, Yaremko MM (1987) Relationship of ultrasonic spectral parameters to features of tissue microstructure. IEEE Trans Ultrason Ferroelectr Freq Control 34:319–329

    Google Scholar 

  27. Feleppa EJ, Lizzi FL, Coleman DJ, Yaremko MM (1986) Diagnostic spectrum analysis in ophthalmology: a physical perspective. Ultrasound Med Biol 12:623–631

    Article  Google Scholar 

  28. Feleppa EJ (2008) Ultrasonic tissue-type imaging of the prostate: implications for biopsy and treatment guidance. Cancer Biomark 4:201–212

    Article  Google Scholar 

  29. Kolios MC, Czarnota GJ (2009) Potential use of ultrasound for the detection of cell changes in cancer treatment. Future Oncol 5:1527–1532

    Article  Google Scholar 

  30. Hall JE (2011) Guyton and Hall textbook of medical physiology: twelfth edition. Sanders/Elsevier, Philadelphia

    Google Scholar 

  31. Rogers K (2011) Blood physiology and circulation. Brittanica Education Publishing, New York

    Google Scholar 

  32. Prahl S (2001) Optical properties spectra. Oregon medical laser center. http://omlc.ogi.edu/spectra. Accessed 27 Mar 2013

  33. Chien S (1987) Red cell deformability and its relevance to blood flow. Annu Rev Physiol 49:177–192

    Article  Google Scholar 

  34. Canham PB, Burton AC (1968) Distribution of size and shape in populations of normal human red cells. Circ Res 22:405–422

    Article  Google Scholar 

  35. Park Y et al (2008) Refractive index maps and membrane dynamics of human red blood cells parasitized by Plasmodium falciparum. Proc Natl Acad Sci U S A 105:13730–13735

    Article  Google Scholar 

  36. Baskurt OK, Neu B, Meiselman HJ (2011) Red blood cell aggregation. CRC Press, Boca Raton

    Book  Google Scholar 

  37. Tateishi N, Suzuki Y, Cicha I, Maeda N (2001) O2 release from erthrocytes flowing in narrow O2-permeable tube: effects of erythrocyte aggregation. Am J Physiol Heart Circ Physiol 281:H448–H456

    Google Scholar 

  38. Arbel Y et al (2012) Erythrocyte aggregation as a cause of slow flow in patients of acute coronary syndromes. Int J Cardiol 154:322–327

    Article  Google Scholar 

  39. Ahuja AS, Hendee WR (1977) Effects of red cell shape and orientation on propagation of sound in blood. Med Phys 4:516–520

    Article  Google Scholar 

  40. Yu FTH, Cloutier G (2007) Experimental ultrasound characterization of red blood cell aggregation using the structure factor size estimator. J Acoust Soc Am 22:645–656

    Article  Google Scholar 

  41. Fontaine I, Bertrand M, Cloutier G (1999) A system-based approach to modeling the ultrasound signal backscattered by red blood cells. Biophys J 77:2387–2399

    Article  Google Scholar 

  42. Strohm EM, Hysi E, Kolios MC (2012) Photoacoustic measurements of single red blood cells. In: Proceedings IEEE IUS, Orlando, FL, pp 1406–1409

    Google Scholar 

  43. Evans E, Fung YC (1972) Improved measurements of the erythrocyte geometry. Microvasc Res 4:335–347

    Article  Google Scholar 

  44. Baddour RE, Sherar MD, Hunt JW, Czarnota GJ, Kolios MC (2005) High-frequency ultrasound scattering from microspheres and single cells. J Acoust Soc Am 117:934–943

    Article  Google Scholar 

  45. Hysi E, Dopsa D, Kolios MC (2013) Photoacoustic radio-frequency spectroscopy (PA-RFS) for monitoring absorber size and concentration. Proc SPIE 8585:85813W

    Google Scholar 

  46. Strohm EM, Berndl EL, Kolios MC (2013) A photoacoustic technique to measure the properties of single cells. Proc SPIE 8581:85814D

    Google Scholar 

  47. PiagnerellI M et al (2007) Assessment of erythrocyte shape by flow cytometry techniques. J Clin Pathol 60:549–554

    Article  Google Scholar 

  48. Saha RK, Kolios MC (2011) A simulation study on photoacoustic signals from red blood cells. J Acoust Soc Am 129:2935–2943

    Article  Google Scholar 

  49. Hysi E, Saha RK, Kolios MC (2012) On the use of photoacoustics to detect red blood cell aggregation. Biomed Opt Express 3:2326–2338

    Article  Google Scholar 

  50. Hysi E, Saha RK, Kolios MC (2012) Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation. J Biomed Phys 17:125006-1-10

    Google Scholar 

  51. Saha RK, Karmakar S, Hysi E, Roy M, Kolios MC (2012) Validity of a theoretical model to examine blood oxygenation dependent photoacoustics. J Biomed Opt 17:055002

    Article  Google Scholar 

  52. Kolios MC, Czarnota GJ, Lee M, Hunt JW, Sherar MD (2002) Ultrasonic spectral parameter imaging of apoptosis. Ultrasound Med Biol 28:589–597

    Article  Google Scholar 

  53. Saha RK, Kolios MC (2011) Effects of cell spatial organization and size distribution on ultrasound backscattering. IEEE Trans Ultrason Ferroelectr Freq Control 58:2118–2131

    Article  Google Scholar 

  54. Baskurt OK, Farley RA, Meiselman HJ (1997) Erythrocyte aggregation tendency and cellular properties in horse, human and rat a comparative study. Am J Physiol Heart Circ Physiol 273:H2604–H2612

    Google Scholar 

  55. Plebani M, Piva E (2002) Erythrocyte sedimentation rate: use of fresh blood for quality control. Am J Clin Pathol 117:621–626

    Article  Google Scholar 

  56. Strohm EM, Berndl ESL, Kolios MC (2013) Probing red blood cell morphology using high frequency photoacoustics. Biophys J 105:59–67

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physics, Ryerson University, 350 Victoria Street, M5B 2K3, Toronto, ON, Canada

    Eno Hysi MSc, Eric M. Strohm Phd & Michael C. Kolios Phd

Authors
  1. Eno Hysi MSc
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eric M. Strohm Phd
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael C. Kolios Phd
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael C. Kolios Phd .

Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

    Aaron Ho-Pui Ho

  2. School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea (Republic of)

    Donghyun Kim

  3. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

    Michael G. Somekh

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media Dordrecht

About this entry

Cite this entry

Hysi, E., Strohm, E.M., Kolios, M.C. (2017). Probing Different Biological Length Scales Using Photoacoustics: From 1 to 1000 MHz. In: Ho, AP., Kim, D., Somekh, M. (eds) Handbook of Photonics for Biomedical Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5052-4_29

Download citation

Publish with us

Policies and ethics

Search

Navigation