Abstract

Noninvasive quantification of abnormal particles hidden in a granular mixture from deep tissue is still a challenge of medical examination. In this study, we have theoretically deduced the power spectrum of the photoacoustic signals from the random mixture of particles with non-uniform sizes. It is revealed that there is an approximate linear relationship between the content of abnormal particles and the spectral slope. This finding provides a parameter of equivalent diameter for the abnormal particle detection. The experimental studies sensitively differentiate and quantify a trace of big micro-particles mixed in small micro-particles. Since the abnormal particles are associated with many important physiological and pathological processes, this study might provide a noninvasive way to assess the related diseases, such as microthrombosis, through monitoring the abnormal particles.

© 2015 Optical Society of America

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    [Crossref] [PubMed]
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    [Crossref]
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    [Crossref] [PubMed]
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    [PubMed]
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    [PubMed]
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    [Crossref] [PubMed]
  7. A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
    [PubMed]
  8. J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
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  14. M. F. Beckmann, H. M. Schwab, and G. Schmitz, “Optimized SNR simultaneous multispectral photoacoustic imaging with laser diodes,” Opt. Express 23(2), 1816–1828 (2015).
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  15. Y. Sun, E. S. Sobel, and H. Jiang, “First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints,” Med. Phys. 38(7), 4009–4017 (2011).
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    [Crossref]
  18. F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
    [Crossref] [PubMed]
  19. F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
    [Crossref] [PubMed]
  20. M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
    [Crossref] [PubMed]
  21. R. E. Kumon, C. X. Deng, and X. Wang, “Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model,” Ultrasound Med. Biol. 37(5), 834–839 (2011).
    [Crossref] [PubMed]
  22. G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
    [Crossref] [PubMed]
  23. E. Hysi, R. K. Saha, and M. C. Kolios, “Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation,” J. Biomed. Opt. 17(12), 125006 (2012).
    [Crossref] [PubMed]
  24. S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
    [Crossref]
  25. G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
    [Crossref] [PubMed]
  26. R. K. Saha, “Computational modeling of photoacoustic signals from mixtures of melanoma and red blood cells,” J. Acoust. Soc. Am. 136(4), 2039–2049 (2014).
    [Crossref] [PubMed]
  27. R. K. Saha, “A simulation study on the quantitative assessment of tissue microstructure with photoacoustics,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(5), 881–895 (2015).
    [Crossref] [PubMed]
  28. S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
    [Crossref] [PubMed]

2015 (3)

R. K. Saha, “A simulation study on the quantitative assessment of tissue microstructure with photoacoustics,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(5), 881–895 (2015).
[Crossref] [PubMed]

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

M. F. Beckmann, H. M. Schwab, and G. Schmitz, “Optimized SNR simultaneous multispectral photoacoustic imaging with laser diodes,” Opt. Express 23(2), 1816–1828 (2015).
[Crossref] [PubMed]

2014 (3)

Y. Yamaoka, Y. Harada, M. Sakakura, T. Minamikawa, S. Nishino, S. Maehara, S. Hamano, H. Tanaka, and T. Takamatsu, “Photoacoustic microscopy using ultrashort pulses with two different pulse durations,” Opt. Express 22(14), 17063–17072 (2014).
[Crossref] [PubMed]

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

R. K. Saha, “Computational modeling of photoacoustic signals from mixtures of melanoma and red blood cells,” J. Acoust. Soc. Am. 136(4), 2039–2049 (2014).
[Crossref] [PubMed]

2013 (3)

S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
[Crossref]

Y. Sun and B. O’Neill, “Imaging high-intensity focused ultrasound-induced tissue denaturation by multispectral photoacoustic method: an ex vivo study,” Appl. Opt. 52(8), 1764–1770 (2013).
[Crossref] [PubMed]

P. M. Vlahovska, D. Barthes-Biesel, and C. Misbah, “Flow dynamics of red blood cells and their biomimetic counterparts,” C. R. Phys. 14(6), 451–458 (2013).
[Crossref]

2012 (3)

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

E. Hysi, R. K. Saha, and M. C. Kolios, “Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation,” J. Biomed. Opt. 17(12), 125006 (2012).
[Crossref] [PubMed]

2011 (2)

Y. Sun, E. S. Sobel, and H. Jiang, “First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints,” Med. Phys. 38(7), 4009–4017 (2011).
[Crossref] [PubMed]

R. E. Kumon, C. X. Deng, and X. Wang, “Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model,” Ultrasound Med. Biol. 37(5), 834–839 (2011).
[Crossref] [PubMed]

2010 (1)

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

2009 (2)

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3(9), 503–509 (2009).
[Crossref] [PubMed]

2007 (2)

F. T. Yu and G. Cloutier, “Experimental ultrasound characterization of red blood cell aggregation using the structure factor size estimator,” J. Acoust. Soc. Am. 122(1), 645–656 (2007).
[Crossref] [PubMed]

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

2006 (1)

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[Crossref]

2004 (1)

J. K. Armstrong, R. B. Wenby, H. J. Meiselman, and T. C. Fisher, “The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation,” Biophys. J. 87(6), 4259–4270 (2004).
[Crossref] [PubMed]

2003 (2)

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

1990 (2)

M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
[Crossref] [PubMed]

C. Le Devehat, M. Vimeux, G. Bondoux, and T. Khodabandehlou, “Red blood cell aggregation in diabetes mellitus,” Int. Angiol. 9(1), 11–15 (1990).
[PubMed]

1987 (1)

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

1984 (1)

O. Linderkamp, P. Ozanne, P. Y. K. Wu, and H. J. Meiselman, “Red blood cell aggregation in preterm and term neonates and adults,” Pediatr. Res. 18(12), 1356–1360 (1984).
[Crossref] [PubMed]

1983 (1)

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

Armstrong, J. K.

J. K. Armstrong, R. B. Wenby, H. J. Meiselman, and T. C. Fisher, “The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation,” Biophys. J. 87(6), 4259–4270 (2004).
[Crossref] [PubMed]

Barthes-Biesel, D.

P. M. Vlahovska, D. Barthes-Biesel, and C. Misbah, “Flow dynamics of red blood cells and their biomimetic counterparts,” C. R. Phys. 14(6), 451–458 (2013).
[Crossref]

Beckmann, M. F.

Bondoux, G.

C. Le Devehat, M. Vimeux, G. Bondoux, and T. Khodabandehlou, “Red blood cell aggregation in diabetes mellitus,” Int. Angiol. 9(1), 11–15 (1990).
[PubMed]

Box, F. M.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Brown, D. G.

M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
[Crossref] [PubMed]

Carson, P. L.

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

Chan, W. S.

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Chunilal, S.

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Cloutier, G.

F. T. Yu and G. Cloutier, “Experimental ultrasound characterization of red blood cell aggregation using the structure factor size estimator,” J. Acoust. Soc. Am. 122(1), 645–656 (2007).
[Crossref] [PubMed]

Coleman, D. J.

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

Crowther, M.

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Dar, I. A.

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

Deng, C. X.

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

R. E. Kumon, C. X. Deng, and X. Wang, “Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model,” Ultrasound Med. Biol. 37(5), 834–839 (2011).
[Crossref] [PubMed]

Dobbe, J. G.

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

Elbaum, M.

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

Feleppa, E. J.

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

Fisher, T. C.

J. K. Armstrong, R. B. Wenby, H. J. Meiselman, and T. C. Fisher, “The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation,” Biophys. J. 87(6), 4259–4270 (2004).
[Crossref] [PubMed]

Gennaro, A. M.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Ginsberg, J. S.

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Goedhart, P. T.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Greenebaum, M.

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

Grimbergen, C. A.

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

Hall, T. J.

M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
[Crossref] [PubMed]

Hamano, S.

Harada, Y.

Hardeman, M. R.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Hysi, E.

E. Hysi, R. K. Saha, and M. C. Kolios, “Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation,” J. Biomed. Opt. 17(12), 125006 (2012).
[Crossref] [PubMed]

Ince, C.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Insana, M. F.

M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
[Crossref] [PubMed]

Jiang, H.

Y. Sun, E. S. Sobel, and H. Jiang, “First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints,” Med. Phys. 38(7), 4009–4017 (2011).
[Crossref] [PubMed]

Joshi, B.

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

Khodabandehlou, T.

C. Le Devehat, M. Vimeux, G. Bondoux, and T. Khodabandehlou, “Red blood cell aggregation in diabetes mellitus,” Int. Angiol. 9(1), 11–15 (1990).
[PubMed]

Kolios, M. C.

E. Hysi, R. K. Saha, and M. C. Kolios, “Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation,” J. Biomed. Opt. 17(12), 125006 (2012).
[Crossref] [PubMed]

Ku, G.

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Kumon, R. E.

R. E. Kumon, C. X. Deng, and X. Wang, “Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model,” Ultrasound Med. Biol. 37(5), 834–839 (2011).
[Crossref] [PubMed]

Le Devehat, C.

C. Le Devehat, M. Vimeux, G. Bondoux, and T. Khodabandehlou, “Red blood cell aggregation in diabetes mellitus,” Int. Angiol. 9(1), 11–15 (1990).
[PubMed]

Lee, A.

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Lin, J. D.

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

Linderkamp, O.

O. Linderkamp, P. Ozanne, P. Y. K. Wu, and H. J. Meiselman, “Red blood cell aggregation in preterm and term neonates and adults,” Pediatr. Res. 18(12), 1356–1360 (1984).
[Crossref] [PubMed]

Liu, X.

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
[Crossref]

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

Lizzi, F. L.

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

Luquita, A.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Maehara, S.

Meiselman, H. J.

J. K. Armstrong, R. B. Wenby, H. J. Meiselman, and T. C. Fisher, “The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation,” Biophys. J. 87(6), 4259–4270 (2004).
[Crossref] [PubMed]

O. Linderkamp, P. Ozanne, P. Y. K. Wu, and H. J. Meiselman, “Red blood cell aggregation in preterm and term neonates and adults,” Pediatr. Res. 18(12), 1356–1360 (1984).
[Crossref] [PubMed]

Meng, Z. X.

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

Minamikawa, T.

Misbah, C.

P. M. Vlahovska, D. Barthes-Biesel, and C. Misbah, “Flow dynamics of red blood cells and their biomimetic counterparts,” C. R. Phys. 14(6), 451–458 (2013).
[Crossref]

Mutsaerts, H. J.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Nishino, S.

O’Neill, B.

Ostromogilsky, M.

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

Out, M.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Ozanne, P.

O. Linderkamp, P. Ozanne, P. Y. K. Wu, and H. J. Meiselman, “Red blood cell aggregation in preterm and term neonates and adults,” Pediatr. Res. 18(12), 1356–1360 (1984).
[Crossref] [PubMed]

Palatnik, S.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Pang, Y.

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Rabelink, T. J.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Rasia, M.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Reiber, J. H.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Rodger, M.

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Romijn, J. A.

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

Rorke, M. C.

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

Rutten, M. C.

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

Saha, R. K.

R. K. Saha, “A simulation study on the quantitative assessment of tissue microstructure with photoacoustics,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(5), 881–895 (2015).
[Crossref] [PubMed]

R. K. Saha, “Computational modeling of photoacoustic signals from mixtures of melanoma and red blood cells,” J. Acoust. Soc. Am. 136(4), 2039–2049 (2014).
[Crossref] [PubMed]

E. Hysi, R. K. Saha, and M. C. Kolios, “Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation,” J. Biomed. Opt. 17(12), 125006 (2012).
[Crossref] [PubMed]

Sakakura, M.

Schmitz, G.

Schwab, H. M.

Sobel, E. S.

Y. Sun, E. S. Sobel, and H. Jiang, “First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints,” Med. Phys. 38(7), 4009–4017 (2011).
[Crossref] [PubMed]

Stijnen, J. M.

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

Stoica, G.

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Strackee, J.

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

Streekstra, G. J.

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

Sun, Y.

Y. Sun and B. O’Neill, “Imaging high-intensity focused ultrasound-induced tissue denaturation by multispectral photoacoustic method: an ex vivo study,” Appl. Opt. 52(8), 1764–1770 (2013).
[Crossref] [PubMed]

Y. Sun, E. S. Sobel, and H. Jiang, “First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints,” Med. Phys. 38(7), 4009–4017 (2011).
[Crossref] [PubMed]

Svetaz, M. J.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Takamatsu, T.

Tanaka, H.

Tao, C.

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
[Crossref]

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

Urli, L.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Vimeux, M.

C. Le Devehat, M. Vimeux, G. Bondoux, and T. Khodabandehlou, “Red blood cell aggregation in diabetes mellitus,” Int. Angiol. 9(1), 11–15 (1990).
[PubMed]

Vlahovska, P. M.

P. M. Vlahovska, D. Barthes-Biesel, and C. Misbah, “Flow dynamics of red blood cells and their biomimetic counterparts,” C. R. Phys. 14(6), 451–458 (2013).
[Crossref]

Volpintesta, R.

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

Wagner, R. F.

M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
[Crossref] [PubMed]

Wang, L. V.

L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3(9), 503–509 (2009).
[Crossref] [PubMed]

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[Crossref]

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Wang, S.

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
[Crossref]

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

Wang, X.

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
[Crossref]

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

R. E. Kumon, C. X. Deng, and X. Wang, “Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model,” Ultrasound Med. Biol. 37(5), 834–839 (2011).
[Crossref] [PubMed]

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Wenby, R. B.

J. K. Armstrong, R. B. Wenby, H. J. Meiselman, and T. C. Fisher, “The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation,” Biophys. J. 87(6), 4259–4270 (2004).
[Crossref] [PubMed]

Wu, P. Y. K.

O. Linderkamp, P. Ozanne, P. Y. K. Wu, and H. J. Meiselman, “Red blood cell aggregation in preterm and term neonates and adults,” Pediatr. Res. 18(12), 1356–1360 (1984).
[Crossref] [PubMed]

Xie, X.

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Xu, G.

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

Xu, M.

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[Crossref]

Yamaoka, Y.

Yang, Y.

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

Yaremko, M. M.

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

Yu, F. T.

F. T. Yu and G. Cloutier, “Experimental ultrasound characterization of red blood cell aggregation using the structure factor size estimator,” J. Acoust. Soc. Am. 122(1), 645–656 (2007).
[Crossref] [PubMed]

Yuan, J.

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

Ann. Intern. Med. (1)

W. S. Chan, S. Chunilal, A. Lee, M. Crowther, M. Rodger, and J. S. Ginsberg, “A red blood cell agglutination D-dimer test to exclude deep venous thrombosis in pregnancy,” Ann. Intern. Med. 147(3), 165–170 (2007).
[Crossref] [PubMed]

Appl. Opt. (1)

Appl. Phys. Lett. (3)

Y. Yang, S. Wang, C. Tao, X. Wang, and X. Liu, “Photoacoustic tomography of tissue subwavelength microstructure with a narrowband and low frequency system,” Appl. Phys. Lett. 101(3), 034105 (2012).
[Crossref]

G. Xu, I. A. Dar, C. Tao, X. Liu, C. X. Deng, and X. Wang, “Photoacoustic spectrum analysis for microstructure characterization in biological tissue: A feasibility study,” Appl. Phys. Lett. 101(22), 221102 (2012).
[Crossref] [PubMed]

S. Wang, C. Tao, X. Wang, and X. Liu, “Quantitative detection of stochastic microstructure in turbid media by photoacoustic spectral matching,” Appl. Phys. Lett. 102(11), 114102 (2013).
[Crossref]

Biophys. J. (1)

J. K. Armstrong, R. B. Wenby, H. J. Meiselman, and T. C. Fisher, “The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation,” Biophys. J. 87(6), 4259–4270 (2004).
[Crossref] [PubMed]

C. R. Phys. (1)

P. M. Vlahovska, D. Barthes-Biesel, and C. Misbah, “Flow dynamics of red blood cells and their biomimetic counterparts,” C. R. Phys. 14(6), 451–458 (2013).
[Crossref]

Clin. Hemorheol. Microcirc. (2)

H. J. Mutsaerts, M. Out, P. T. Goedhart, C. Ince, M. R. Hardeman, J. A. Romijn, T. J. Rabelink, J. H. Reiber, and F. M. Box, “Improved viscosity modeling in patients with type 2 diabetes mellitus by accounting for enhanced red blood cell aggregation tendency,” Clin. Hemorheol. Microcirc. 44(4), 303–313 (2010).
[PubMed]

A. Luquita, L. Urli, M. J. Svetaz, A. M. Gennaro, R. Volpintesta, S. Palatnik, and M. Rasia, “Erythrocyte aggregation in rheumatoid arthritis: Cell and plasma factor’s role,” Clin. Hemorheol. Microcirc. 41(1), 49–56 (2009).
[PubMed]

IEEE Trans. Biomed. Eng. (1)

J. G. Dobbe, G. J. Streekstra, J. Strackee, M. C. Rutten, J. M. Stijnen, and C. A. Grimbergen, “Syllectometry: the effect of aggregometer geometry in the assessment of red blood cell shape recovery and aggregation,” IEEE Trans. Biomed. Eng. 50(1), 97–106 (2003).
[Crossref] [PubMed]

IEEE Trans. Ultrason. Ferroelectr. Freq. Control (3)

F. L. Lizzi, M. Ostromogilsky, E. J. Feleppa, M. C. Rorke, and M. M. Yaremko, “Relationship of ultrasonic spectral parameters to features of tissue microstructure,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 34(3), 319–329 (1987).
[Crossref] [PubMed]

R. K. Saha, “A simulation study on the quantitative assessment of tissue microstructure with photoacoustics,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(5), 881–895 (2015).
[Crossref] [PubMed]

S. Wang, C. Tao, Y. Yang, X. Wang, and X. Liu, “Theoretical and experimental study of spectral characteristics of the photoacoustic signal from stochastically distributed particles,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 62(7), 1245–1255 (2015).
[Crossref] [PubMed]

Int. Angiol. (1)

C. Le Devehat, M. Vimeux, G. Bondoux, and T. Khodabandehlou, “Red blood cell aggregation in diabetes mellitus,” Int. Angiol. 9(1), 11–15 (1990).
[PubMed]

J. Acoust. Soc. Am. (4)

F. T. Yu and G. Cloutier, “Experimental ultrasound characterization of red blood cell aggregation using the structure factor size estimator,” J. Acoust. Soc. Am. 122(1), 645–656 (2007).
[Crossref] [PubMed]

M. F. Insana, R. F. Wagner, D. G. Brown, and T. J. Hall, “Describing small-scale structure in random media using pulse-echo ultrasound,” J. Acoust. Soc. Am. 87(1), 179–192 (1990).
[Crossref] [PubMed]

F. L. Lizzi, M. Greenebaum, E. J. Feleppa, M. Elbaum, and D. J. Coleman, “Theoretical framework for spectrum analysis in ultrasonic tissue characterization,” J. Acoust. Soc. Am. 73(4), 1366–1373 (1983).
[Crossref] [PubMed]

R. K. Saha, “Computational modeling of photoacoustic signals from mixtures of melanoma and red blood cells,” J. Acoust. Soc. Am. 136(4), 2039–2049 (2014).
[Crossref] [PubMed]

J. Biomed. Opt. (1)

E. Hysi, R. K. Saha, and M. C. Kolios, “Photoacoustic ultrasound spectroscopy for assessing red blood cell aggregation and oxygenation,” J. Biomed. Opt. 17(12), 125006 (2012).
[Crossref] [PubMed]

Med. Phys. (1)

Y. Sun, E. S. Sobel, and H. Jiang, “First assessment of three-dimensional quantitative photoacoustic tomography for in vivo detection of osteoarthritis in the finger joints,” Med. Phys. 38(7), 4009–4017 (2011).
[Crossref] [PubMed]

Nat. Biotechnol. (1)

X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Nat. Photonics (1)

L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3(9), 503–509 (2009).
[Crossref] [PubMed]

Opt. Express (2)

Pediatr. Res. (1)

O. Linderkamp, P. Ozanne, P. Y. K. Wu, and H. J. Meiselman, “Red blood cell aggregation in preterm and term neonates and adults,” Pediatr. Res. 18(12), 1356–1360 (1984).
[Crossref] [PubMed]

Radiology (1)

G. Xu, Z. X. Meng, J. D. Lin, J. Yuan, P. L. Carson, B. Joshi, and X. Wang, “The functional pitch of an organ: quantification of tissue texture with photoacoustic spectrum analysis,” Radiology 271(1), 248–254 (2014).
[Crossref] [PubMed]

Rev. Sci. Instrum. (1)

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[Crossref]

Ultrasound Med. Biol. (1)

R. E. Kumon, C. X. Deng, and X. Wang, “Frequency-domain analysis of photoacoustic imaging data from prostate adenocarcinoma tumors in a murine model,” Ultrasound Med. Biol. 37(5), 834–839 (2011).
[Crossref] [PubMed]

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Figures (4)

Fig. 1
Fig. 1 Theoretical analysis of PA spectrum of the random granular mixture. R is the average distance between the ROI and the observation point r′. r i is the central position of the ith particle and its distance to the observation point r′ is Ri.
Fig. 2
Fig. 2 Experimental setup and phantoms. (a) Schematic diagram of the experimental system. (b) A partial photograph of the phantom for mb/M = 0.75.
Fig. 3
Fig. 3 The results of the phantom experiments. (a) The detected PA signals. The insets are the enlarged parts within the gray band. (b) The solid lines are spectra of five different mass ratios. The dashed line is the calibration spectrum of phantom injected with the uniform particles of 49 μm. Here, the curves are plotted with an offset increment of about −7 dB to show their shape clearly. (c) The solid lines are calibrated spectra. The dashed line is the linear regression of the spectrum for mb/M = 1.00. (d) Extracting the equivalent diameter according to the experimental slopes and the theoretically predicted slopes [red line].
Fig. 4
Fig. 4 Quantitative detection of the equivalent characteristic size for different ratios. (a) The equivalent diameter vs. the mass ratio of abnormal particles. (b) The equivalent diameter vs. the number ratio of abnormal particles.

Equations (9)

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1 c 2 2 t 2 p ( r , t ) 2 p ( r , t ) = β C P A ( r ) h l ( t ) t
S ( f ) S 0 ( f ) | V A ( r ) e j k r d x d y d z | 2
A ( r ) = i A i ( r r i )
S ( f ) = S 0 ( f ) | i m i ϕ ( f , a i ) e j k R i | 2
ϕ ( f , a i ) = 1 m i V i A i ( r r i ) e j k ( x x i ) d r
S ( f ) S 0 ( f ) | i m i [ ϕ ( f , a 0 ) + ϕ a ' ( f , a 0 ) ( a i a 0 ) ] e j k R i | 2
S ( f ) S 0 ( f ) | i m i [ ϕ ( f , a 0 ) + ϕ a ' ( f , a 0 ) ( a ^ a 0 ) ] i e j k R i | 2 S 0 ( f ) | i m i ϕ ( f , a ^ ) i e j k R i | 2 = S 0 ( f ) M 2 | φ ( f , a ^ ) | 2
φ ( f , a ^ ) = ϕ ( f , a ^ ) i e j k R i     and     a ^ = i ( m i / M ) a i     with     M = i m i
| φ ( f , a ^ ) | 2 = r ' R A ( r ' ; f , a ^ ) d r ' with R A ( r ' ) = { 1 / 6 π a ^ 3 ( 1 | 3 r ' | / 2 a ^ + | r ' | 3 / 2 a ^ 3 ) | r ' | a ^ 0 | r ' | > a ^

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