Abstract

We developed a new algorithm that fits optical coherence tomography (OCT) signals as a function of depth to a general theoretical OCT model which takes into account multiple scattering effects. With use of this algorithm, it was possible to extract both the scattering coefficient and anisotropy factor from a particular region of interest in an OCT image. The extraction algorithm was evaluated against measurements from an integrating sphere on a set of tissue phantoms and yielded valid results. Finally, a preliminary ex vivo OCT investigation on human aortic specimen indicated that the algorithm may contribute importantly to differentiation between normal and atherosclerotic arteries. We conclude that this algorithm may facilitate tissue characterization by OCT.

© 2004 Optical Society of America

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References

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Appl. Opt.

Circ. Res.

Z. Fayad and V. Fuster, "Clinical imaging of the high-risk or vulnerable atherosclerotic plaque," Circ. Res. 89, 305-316 (2001).
[CrossRef] [PubMed]

Circulation

H. Yabushita, B. E. Bouma, S. L. Houser, H. T. Aretz, I. K. Jang, K. H. Schlendorf, C. R. Kauffman, M. Shishkov, D. H. Kang, E. F. Halpern, and G. J. Tearney, "Characterization of human atherosclerosis by optical coherence tomography," Circulation 106, 1640-1645 (2002).
[CrossRef] [PubMed]

G. J. Tearney, H. Yabushita, S. L. Houser, H. T. Aretz, I. K. Jang, K. H. Schlendorf, C. R. Kauffman, M. Shishkov, E. F. Halpern, and B. E. Bouma, "Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography," Circulation 107, 113-119 (2003).
[CrossRef] [PubMed]

European Conference in Biomedical Optics

D. Levitz, C. B. Andersen, M. H. Frosz, L. Thrane, P. R. Hansen, T. M. Jørgensen, and P. E. Andersen "Assessing blood vessel abnormality via extracting scattering properties from OCT images" in European Conference in Biomedical Optics (ECBO), W. Drexler, ed. Proc. SPIE 5140, 12-19 (2003).

Heart

B. E. Bouma, G. J. Tearney, H. Yabushita, M. Shishkov, C. R. Kauffman, D. DeJoseph Gauthier, B. D. MacNeill, S. L. Houser, H. T. Aretz, E. F. Halpern, and I. K. Jang, "Evaluation of intracoronary stenting by intravascular optical coherence tomography," Heart 89, 317-321 (2003).
[CrossRef] [PubMed]

J Am Coll Cardiol

I. K. Jang, B. E. Bouma, D. H. Kang, S. J. Park, S. W. Park, K. B. Seung, K. B. Choi, M. Shishkov, K. H. Schlendorf, E. Pomerantsev, S. L. Houser, H. T. Aretz, and G. J. Tearney, "Visualization of coronary atherosclerotic plaques in patients using optical coherence tomography: comparison with intravascular ultrasound," J Am Coll Cardiol 39, 604-609 (2002).
[CrossRef] [PubMed]

J. Biomed. Opt.

D. D. Royston, R. S. Poston, and S. A. Prahl, "Optical properties of scattering and absorbing materials used in the development of optical phantoms at 1064 nm," J. Biomed. Opt. 1, 110-116 (1997).
[CrossRef]

J. Opt. Soc. Am. A

J. Photochem. Photobiol. B

J. C. Kennedy, R. H. Pottier, and D. C. Pross, "Photodynamic therapy with endogenous protoporphyrin IX: Basic principles and present clinical experience," J. Photochem. Photobiol. B 6, 143-148 (1990).
[CrossRef] [PubMed]

Laser Physics

N. M. Shakhova, V. M. Gelikonov, V. A. Kamensky, R. V. Kuranov, and E. V. Turchin, "Clinical aspects of the endoscopic optical coherence tomography: a methods for improving the diagnostics efficiency," Laser Physics 12, 23-32 (2002).

Opt. Lett.

Opt. Lett. 27

B. Povazay, K. Bizheva, A. Unterhuber, B. Hermann, H. Sattmann, A. F. Fercher, W. Drexler, A. Apolonski, W. J. Wadsworth, J. C. Knight, P. S. J. Russel, M. Vetterlein, and E. Scherzer, "Submicrometer axial resolution optical coherence tomography," Opt. Lett. 27, 1800-1802 (2002).
[CrossRef]

Phys. Med. Biol.

J. M. Schmitt, A. Knüttel, M. Yadlowsky, and M. A. Eckhaus, "Optical-coherence tomography of a dense tissue: statistics of attenuation and backscattering," Phys. Med. Biol. 39, 1705-1720 (1994).
[CrossRef] [PubMed]

Phys. Rev. A

C. C. Cheng and M. G. Raymer, "Propagation of transverse optical coherence in random multiple-scattering media," Phys. Rev. A 62, 1-12 (2000).
[CrossRef]

Science

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, "Optical coherence tomography," Science 254, 1178-1181 (1991).
[CrossRef] [PubMed]

Other

C. F. Bohren and D. R. Huffman, Absorption and scattering of light by small particles (John Wiley & Sons, Inc., New York, NY 1983).

A. E. Siegman, Lasers (University Science Books, Mill Valley, CA 1986).

S. A. Prahl, Inverse Adding-Doubling Software. 1999. <a href="http://omlc.ogi.edu/software/iad/index.html">http://omlc.ogi.edu/software/iad/index.html</a>.

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Figures (6)

Fig. 1.
Fig. 1.

The OCT system. The optical circulator and a second detector (dashed line) were only used in the first part of the study. PLD: programmable logic device.

Fig. 2.
Fig. 2.

A schematic representation of the principles of the extraction algorithm. The sample arm geometry and input parameter values from our OCT setup are shown in (A). These parameters were used to generate an image (B) and were also employed during curve fitting (C-D). A transverse ROI was selected in (B, inset), averaged, smoothed, and plotted in (C). The axial pixels of the ROI were chosen in (C, inset), and shown as points in (D). zROI represents the probing depth within the region of interest in (D). The fit was performed on the resulting data-points using µs and θrms initial value guesses as additional input. The algorithm returned µs, θrms, the fit’s error estimates, and a plot comparing the fit to the data points (D).

Fig. 3.
Fig. 3.

A comparison of µs values (means ± standard deviation) obtained from measurements on tissue phantoms with OCT extractions (green) and the integrating sphere (IS, in red). Note a step wise increase on two separate sets of 3 phantoms purposely prepared to exhibit such an increase. Details about phantom nomenclature can be found in Ref. [19].

Fig. 4.
Fig. 4.

A comparison of geff value (means ± standard deviations) from OCT extractions (points) and the Mie calculation (line). Overlap in results is seen for every phantom. Details regarding phantom nomenclature can be found in Ref. [19].

Fig. 5.
Fig. 5.

Correlation of raw OCT images (A, C, E, and G) and histopathology (B, D, F, and H). Normal intima labeled ‘I’ in (A-B). Lipid-rich lesion (C-D), with a lipid pool marked ‘LP’. Fibrous plaque (E-F), with fibrous area marked ‘F’. Fibrocalcific lesion (G-H), with the calcifications denoted ‘C’. Rupture artifacts caused by the decalcifying process are clearly seen in (H). The arrows represent the intima in (A-F) and the fitting region in (G-H), respectively. Bars=500 µm.

Fig. 6.
Fig. 6.

Distributions of µs (A) and geff (B) for normal arteries and lipid-rich, fibrous, and fibrocalcific atherosclerotic plaques, respectively. In (A), µs for normal samples (striped) were centered between 15 and 40 mm-1, but were centered at lower values for lipid-rich (green) and fibrocalcific (blue) plaques, and were randomly distributed for fibrous plaques (red). In (B), geff values were generally higher in normal intimas than in atherosclerotic lesions.

Equations (4)

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w H 2 = w 0 2 ( A B f ) 2 + ( B k w 0 ) 2 ,
Ψ ( z ) = exp ( 2 μ s z ) + 4 exp ( μ s z ) [ 1 exp ( μ s z ) ] 1 + w S 2 w H 2 + [ 1 exp ( μ s z ) ] 2 w H 2 w S 2 .
w S 2 = w 0 2 ( A B f ) 2 + ( B k w 0 ) 2 + ( 2 B k ρ 0 ( z ) ) 2 ,
ρ 0 ( z ) = 3 μ s z λ π θ rms ( nB z ) ,

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