Abstract

Enhanced tissue contrast in developmental biology specimens is demonstrated in vivo using a new type of spectroscopic optical coherence tomography analysis that is insensitive to spectroscopic noise sources. The technique is based on a statistical analysis of spectral modulation at each image pixel, and provides contrast based on both the intensity of the backscattered light and the distribution of scattering particle sizes. Since the technique does not analyze optical power at absolute wavelengths, it is insensitive to all spectroscopic noise that appears as local Doppler shifts. No exogenous contrast agents or dyes are required, and no additional components are needed to correct for reference arm motion.

© 2004 Optical Society of America

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References

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Cytometry

P. Sloot, A. Hoekstra, and C. Figdor, "Osmotic response of lymphocytes measured by means of forward light scattering: theoretical considerations," Cytometry 9, 636-641 (1988)
[CrossRef] [PubMed]

Gastroenterology

M. Wallace, L. T. Perelman, V. Backman, J. M. Crawford, M. Fitzmaurice, M. Seiler, K. Badizadegan, S. Shields, I. Itzkan, R. R. Dasari, J. Van Dam, and M. S. Feld, "Endoscopic detection of dysplasia in patients with Barrett's esophagus using light-scattering spectroscopy," Gastroenterology 119, 677 (2000)
[CrossRef] [PubMed]

IEEE J. Sel. Top. Quantum Electron

V. Backman, V. Gopal, M. Kalashnikov, K. Badizadegan, R. Gurjar, A. Wax, I. Georgakoudi, M. Mueller, C. W. Boone, R. R. Dasari, and M. S. Feld, "Measuring cellular structure at submicrometer scale with light scattering spectroscopy," IEEE J. Sel. Top. Quantum Electron. 7, 887-893 (2001)
[CrossRef]

IEEE J. Sel. Top. Quantum Electron.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Dasari, L. T. Perelman, and M. S. Feld, "Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ," IEEE J. Sel. Top. Quantum Electron. 5, 1019-1026 (1999)
[CrossRef]

J. Biomed. Opt.

J. M. Schmitt, S. H. Xiang, and K. M. Yung, "Speckle in optical coherence tomography," J. Biomed. Opt. 4, 95- 105 (1999)
[CrossRef] [PubMed]

J. Opt. Soc. Am A

A. Wax, C. Yang, V. Backman, M. Kalashnikov, R. R. Dasari, and M. S. Feld, "Determination of particle size by using the angular distribution of backscattered light as measured with low-coherence interferometry," J. Opt. Soc. Am A 19, 737-744 (2002)
[CrossRef]

Nature

V. Backman, M. Wallace, L. T. Perelman, J. Arendt, R. Gurjar, M. Muller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, and M. S. Feld, "Detection of preinvasive cancer cells," Nature 406, 35-36 (2000)
[CrossRef] [PubMed]

Nature Medicine

R. Gurjar, V. Backman, K. Badizadegan, R. R. Dasari, I. Itzkan, L. T. Perelman, and M. S. Feld, "Imaging human epithelial properties with polarized light scattering spectroscopy," Nature Medicine 7, 1245-1248 (2001)
[CrossRef] [PubMed]

Opt. Lett.

Phys. Med. Biol.

J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Muller, "The spatial variation of the refractive index in biological cells," Phys. Med. Biol. 41, 369-382 (1996)
[CrossRef] [PubMed]

Phys. Rev. Lett.

L. T. Perelman, V. Backman, M. Wallace, G. Zonios, R. Manoharan, A. Nusrat, S. Shields, M. Seiler, C. Lima, T. Hamano, I. Itzkan, J. Van Dam, J. M. Crawford, and M. S. Feld, "Observation of periodic fine structure in reflectance from biological tissue: a new technique for measuring nuclear size distribution," Phys. Rev. Lett. 80, 627-630 (1998)
[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

H. van de Hulst, Light Scattering by Small Particles (Dover Publications, New York, New York, 1981)

A.V. Oppenheim, R.W. Schafer, and J.R. Buck, �??The chirp transform algorithm,�?? in Discrete-Time Signal Processing, M. Horton, ed. (Prentice Hall, Upper Saddle River, New Jersey, 1999), pp. 656-661

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Figures (9)

Fig. 1.
Fig. 1.

Schematic of spectroscopic OCT system. Dual balanced detection is used to reject amplitude noise in the Ti:sapphire laser. The reference mirror is scanned using a linear galvanometer. The detected signal is bandpass filtered, and the intereference fringes are acquired using a 16-bit A/D card.

Fig. 2.
Fig. 2.

STFT segment from Xenopus Laevis tadpole, calculated using the CZT and FFT algorithms, each with 512 points. Data point density in the area of interest using the CZT is ~30 times higher than using the FFT. The FFT data set extends from -fs/2 to +fs/2, while the CZT data set extends only from 7.2 kHz–12 kHz.

Fig. 3.
Fig. 3.

Spectroscopic OCT image showing the center wavelength of the reflected spectrum from a mirror. Red colors indicate a comparatively long center wavelength, while green colors indicate a comparatively short center wavelength. The chirp of the incident pulse appears as a chirp in the detected spectrum, as shown by the depth-varying center wavelength. As the reference path dispersion is changed along the transverse coordinate, the chirp varies from short-long to long-short wavelength.

Fig. 4.
Fig. 4.

Detected spectra from a glass coverslip and regions containing 20 µm, 5 µm, 800 nm, and 200 nm microspheres. 20 µm and 5 µm microspheres induce spectral modulation consistent with isolated particle Mie scattering. 800 nm and 200 nm microspheres induce modulation consistent with scattering from multiple particles.

Fig. 5.
Fig. 5.

Autocorrelation of the optical spectra for a glass coverslip and regions containing 20 µm, 5 µm, 800 nm, and 200 nm microspheres. Characteristic differences are observed in the bandwidth, shape, and number of peaks in the autocorrelation functions. These properties are related to the degree of spectral modulation caused by the target. Insert: The bandwidth at 90% of the peak can be used as one measure which differentiates particle sizes.

Fig. 7.
Fig. 7.

Intensity-based OCT image of an in vivo developing zebrafish embryo.

Fig. 8.
Fig. 8.

In vivo spectroscopic OCT image of a developing zebrafish embryo using the center wavelength as the spectroscopic metric. No contrast enhancement between the embryo, membrane, and nutrients is observed. Spectroscopic noise from galvanometer motion and chirp of the incident pulses is present.

Fig. 9.
Fig. 9.

In vivo spectroscopic OCT image of a developing zebrafish embryo using the autocorrelation bandwidth of the optical spectra as the spectroscopic metric. Improved contrast between the embryo, membrane, and nutrients is obtained. Spectroscopic noise from nonuniform reference arm galvanometer motion and chirp of the incident pulses is not present.

Fig. 10.
Fig. 10.

In vivo OCT images of a developing Xenopus Laevis (African frog) tadpole, using standard intensity-based imaging (A), spectropscopic imaging using center wavelength as the metric (B), and spectroscopic imaging using the autocorrelation function of the optical spectra as the metric (C). Galvanometer noise and red-shifting are present in (B), and no significant contrast enhancement is obtained. No spectroscopic noise is present in (C), and enhanced contrast between the different tissue types of the specimen is achieved.

Equations (4)

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λ opt = 2 v g f RF
X czt [ k ] = n = 0 L 1 x [ n ] z n e j r k n , 0 k < L 1
X czt [ k ] = n = 0 L 1 x [ n ] e j ( ω 0 + ( ω 1 ω 0 ) k L ) n , 0 k < L 1
r XX [ m ] = k X n [ k ] X n [ k m ]

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