Abstract

Optical coherence tomography (OCT) is a powerful technology for rapid volumetric imaging in biomedicine. The bright field imaging approach of conventional OCT systems is based on the detection of directly backscattered light, thereby waiving the wealth of information contained in the angular scattering distribution. Here we demonstrate that the unique features of few-mode fibers (FMF) enable simultaneous bright and dark field (BRAD) imaging for OCT. As backscattered light is picked up by the different modes of a FMF depending upon the angular scattering pattern, we obtain access to the directional scattering signatures of different tissues by decoupling illumination and detection paths. We exploit the distinct modal propagation properties of the FMF in concert with the long coherence lengths provided by modern wavelength-swept lasers to achieve multiplexing of the different modal responses into a combined OCT tomogram. We demonstrate BRAD sensing for distinguishing differently sized microparticles and showcase the performance of BRAD-OCT imaging with enhanced contrast for ex vivo tumorous tissue in glioblastoma and neuritic plaques in Alzheimer’s disease.

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2017 (6)

2016 (5)

O. Liba, E. D. SoRelle, D. Sen, and A. de la Zerda, “Contrast-enhanced optical coherence tomography with picomolar sensitivity for functional in vivo imaging,” Sci. Reports 6, 23337 (2016).
[Crossref]

M. Lee, E. Lee, J. Jung, H. Yu, K. Kim, J. Yoon, S. Lee, Y. Jeong, and Y. Park, “Label-free optical quantification of structural alterations in Alzheimer’s disease,” Sci. Reports 6, 31034 (2016).
[Crossref]

Q. T. Ostrom, H. Gittleman, J. Xu, C. Kromer, Y. Wolinsky, C. Kruchko, and J. S. Barnholtz-Sloan, “CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2009–2013,” Neuro Oncol.  18, v1–v75 (2016).
[Crossref]

A. Badon, D. Li, G. Lerosey, A. C. Boccara, M. Fink, and A. Aubry, “Smart optical coherence tomography for ultra-deep imaging through highly scattering media,” Sci. Adv. 2, e1600370 (2016).
[Crossref] [PubMed]

G. Plascencia-Villa, A. Ponce, J. F. Collingwood, M. J. Arellano-Jiménez, X. Zhu, J. T. Rogers, I. Betancourt, M. José-Yacamán, and G. Perry, “High-resolution analytical imaging and electron holography of magnetite particles in amyloid cores of Alzheimer’s disease,” Sci. Reports 6, 24873 (2016).
[Crossref]

2015 (6)

C. Kut, K. L. Chaichana, J. Xi, S. M. Raza, X. Ye, E. R. McVeigh, F. J. Rodriguez, A. Quiñones-Hinojosa, and X. Li, “Detection of human brain cancer infiltration ex vivo and in vivo using quantitative optical coherence tomography,” Sci. Transl. Medicine 7, 292ra100 (2015).
[Crossref]

A. Alex, A. Li, R. E. Tanzi, and C. Zhou, “Optogenetic pacing in Drosophila melanogaster,” Sci. Adv. 1, e1500639 (2015).
[Crossref] [PubMed]

D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
[Crossref] [PubMed]

Y. Weng, E. Ip, Z. Pan, and T. Wang, “Single-end simultaneous temperature and strain sensing techniques based on Brillouin optical time domain reflectometry in few-mode fibers,” Opt. Express 23, 9024–9039 (2015).
[Crossref] [PubMed]

G. Liu, O. Tan, S. S. Gao, A. D. Pechauer, B. Lee, C. D. Lu, J. G. Fujimoto, and D. Huang, “Postprocessing algorithms to minimize fixed-pattern artifact and reduce trigger jitter in swept source optical coherence tomography,” Opt. Express 23, 9824–9834 (2015).
[Crossref] [PubMed]

E. Auksorius and A. Claude Boccara, “Dark-field full-field optical coherence tomography,” Opt. Lett. 40, 3272–3275 (2015).
[Crossref] [PubMed]

2014 (1)

M. Kreysing, D. Ott, M. J. Schmidberger, O. Otto, M. Schürmann, E. Martín-Badosa, G. Whyte, and J. Guck, “Dynamic operation of optical fibres beyond the single-mode regime facilitates the orientation of biological cells,” Nat. Commun. 5, 5481 (2014).
[Crossref] [PubMed]

2013 (2)

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, 11 (2013).
[Crossref]

D. J. Richardson, J. M. Fini, and L. E. Nelson, “Space-division multiplexing in optical fibres,” Nat. Photonics 7, 354–362 (2013).
[Crossref]

2012 (6)

P. J. Keller and H.-U. Dodt, “Light sheet microscopy of living or cleared specimens,” Curr. Opin. Neurobiol. 22, 138–143 (2012).
[Crossref]

T. Čižmár and K. Dholakia, “Exploiting multimode waveguides for pure fibre-based imaging,” Nat. Commun. 3, 1027 (2012).
[Crossref] [PubMed]

J. Schindelin, I. Arganda-Carreras, E. Frise, V. Kaynig, M. Longair, T. Pietzsch, S. Preibisch, C. Rueden, S. Saalfeld, B. Schmid, J.-Y. Tinevez, D. J. White, V. Hartenstein, K. Eliceiri, P. Tomancak, and A. Cardona, “Fiji - an Open Source platform for biological image analysis,” Nat. Methods 9, 676–682 (2012).
[Crossref] [PubMed]

Y. Yang, T. Wang, M. Brewer, and Q. Zhu, “Quantitative analysis of angle-resolved scattering properties of ovarian tissue using optical coherence tomography,” J. Biomed. Opt. 17, 90503 (2012).
[Crossref] [PubMed]

M. Kalashnikov, W. Choi, M. Hunter, C.-C. Yu, R. R. Dasari, and M. S. Feld, “Assessing the contribution of cell body and intracellular organelles to the backward light scattering,” Opt. Express 20, 816–826 (2012).
[Crossref] [PubMed]

W. Choi, B. Baumann, E. A. Swanson, and J. G. Fujimoto, “Extracting and compensating dispersion mismatch in ultrahigh-resolution Fourier domain OCT imaging of the retina,” Opt. Express 20, 25357–25368 (2012).
[Crossref] [PubMed]

2011 (4)

2010 (2)

2009 (1)

H. Jans, X. Liu, L. Austin, G. Maes, and Q. Huo, “Dynamic Light Scattering as a Powerful Tool for Gold Nanoparticle Bioconjugation and Biomolecular Binding Studies,” Anal. Chem. 81, 9425–9432 (2009).
[Crossref] [PubMed]

2008 (2)

S. Jiao and M. Ruggeri, “Polarization effect on the depth resolution of optical coherence tomography,” J. Biomed. Opt. 13, 60503 (2008).
[Crossref]

K. J. Chalut, S. Chen, J. D. Finan, M. G. Giacomelli, F. Guilak, K. W. Leong, and A. Wax, “Label-Free, High-Throughput Measurements of Dynamic Changes in Cell Nuclei Using Angle-Resolved Low Coherence Interferometry,” Biophys. J. 94, 4948–4956 (2008).
[Crossref] [PubMed]

2007 (3)

E. M. C. Hillman, “Optical brain imaging in vivo: techniques and applications from animal to man,” J. Biomed. Opt. 12, 51402 (2007).
[Crossref]

D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, “Three-dimensional endomicroscopy using optical coherence tomography,” Nat. Photonics 1, 709–716 (2007).
[Crossref]

A. E. Desjardins, B. J. Vakoc, G. J. Tearney, and B. E. Bouma, “Backscattering spectroscopic contrast with angle-resolved optical coherence tomography,” Opt. Lett. 32, 3158–3160 (2007).
[Crossref] [PubMed]

2004 (1)

2003 (2)

L.-W. Jin, K. A. Claborn, M. Kurimoto, M. A. Geday, I. Maezawa, F. Sohraby, M. Estrada, W. Kaminksy, and B. Kahr, “Imaging linear birefringence and dichroism in cerebral amyloid pathologies,” Proc. Natl. Acad. Sci. 100, 15294–15298 (2003).
[Crossref] [PubMed]

A. Fercher, W. Drexler, C. Hitzenberger, and T. Lasser, “Optical coherence tomography - principles and applications,” Rep. Prog. Phys. 66, 239–303 (2003).
[Crossref]

2002 (1)

2001 (1)

A. C. Ruifrok and D. A. Johnston, “Quantification of histochemical staining by color deconvolution,” Anal. Quant. Cytol. Histol. 23, 291–299 (2001).
[PubMed]

2000 (1)

I. Turek, I. Martincek, and R. Stransky, “Interference of modes in optical fibers,” Opt. Eng. 39, 1304–1310 (2000).
[Crossref]

1999 (1)

J. M. Schmitt, “Optical coherence tomography (OCT): a review,” IEEE J. Sel. Top. Quantum Electron. 5, 1205–1215 (1999).
[Crossref]

1996 (1)

1995 (1)

A. F. Fercher, C. K. Hitzenberger, G. Kamp, and S. Y. El-Zaiat, “Measurement of intraocular distances by backscattering spectral interferometry,” Opt. Commun. 117, 43–48 (1995).
[Crossref]

1991 (1)

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. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
[Crossref] [PubMed]

1986 (1)

M. Spajer, B. Carquille, and H. Maillotte, “Application of intermodal interference to fibre sensors,” Opt. Commun. 60, 261–264 (1986).
[Crossref]

Adler, D. C.

D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, “Three-dimensional endomicroscopy using optical coherence tomography,” Nat. Photonics 1, 709–716 (2007).
[Crossref]

Albanese, A.

N. Lippok, M. Villiger, A. Albanese, E. F. J. Meijer, K. Chung, T. P. Padera, S. N. Bhatia, and B. E. Bouma, “Depolarization signatures map gold nanorods within biological tissue,” Nat. Photonics 11, 583–588 (2017).
[Crossref]

Alex, A.

A. Alex, A. Li, R. E. Tanzi, and C. Zhou, “Optogenetic pacing in Drosophila melanogaster,” Sci. Adv. 1, e1500639 (2015).
[Crossref] [PubMed]

Arellano-Jiménez, M. J.

G. Plascencia-Villa, A. Ponce, J. F. Collingwood, M. J. Arellano-Jiménez, X. Zhu, J. T. Rogers, I. Betancourt, M. José-Yacamán, and G. Perry, “High-resolution analytical imaging and electron holography of magnetite particles in amyloid cores of Alzheimer’s disease,” Sci. Reports 6, 24873 (2016).
[Crossref]

Arganda-Carreras, I.

J. Schindelin, I. Arganda-Carreras, E. Frise, V. Kaynig, M. Longair, T. Pietzsch, S. Preibisch, C. Rueden, S. Saalfeld, B. Schmid, J.-Y. Tinevez, D. J. White, V. Hartenstein, K. Eliceiri, P. Tomancak, and A. Cardona, “Fiji - an Open Source platform for biological image analysis,” Nat. Methods 9, 676–682 (2012).
[Crossref] [PubMed]

Arous, J. B.

Aubry, A.

A. Badon, D. Li, G. Lerosey, A. C. Boccara, M. Fink, and A. Aubry, “Smart optical coherence tomography for ultra-deep imaging through highly scattering media,” Sci. Adv. 2, e1600370 (2016).
[Crossref] [PubMed]

Augustin, M.

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Figures (7)

Fig. 1
Fig. 1 FMF detection concept. (a) Simplified scheme of the BRAD-OCT experimental set-up with FMF detection. The FMF implemented in the prototype collects the backscattered light and encodes it into the different transversal modes. As light portions coupled into the modes travel different path lengths along the FMF as shown in (b), they will sequentially arrive at the distal end of the fiber, reconstructing the modal images at different depth positions. This concept is demonstrated in (c) where the modal images are mapped into different depths of a cross-sectional OCT image of brain tissue.
Fig. 2
Fig. 2 Interference of fiber modes. (a) Intensity distributions of modes LP01, LP11 and LP21 supported by the FMF. (b) Interference beam profiles simulated for a perfect alignment (upper row) and for an asymmetric interference pattern where the spots have been displaced by 0.58w (bottom row). (c) Modal intensities with respect to the relative shift Δρ/w between sample and reference beam. (d) Relative signal-to-noise ratio for the different FMF modes measured with a scattering paper in the sample position. The red star indicates a higher-order mode that appears close to the noise level in our interference signal. This mode was disregarded in the imaging experiments due to its weak intensity and strong dispersion.
Fig. 3
Fig. 3 Detailed layout of the BRAD-OCT system. RR: retroreflector, PC: polarization control paddles, SMF: single-mode fiber, FMF: few-mode fiber, FC: fiber collimator, PBS: polarizing beam splitter, BS: beam splitter, QWP: quarter wave plate, L: lens, BD: balanced detector, S: sample, MEMS: microelectromechanical scanning mirror, DAQ: data acquisition board, AOC: analog output card.
Fig. 4
Fig. 4 Neuritic plaque scattering model. (a) Description of the radial distribution of the fibrils composing the neuritic plaques. (b) Scattering shape of a unique fibril oriented at different angles θ respect to the incident beam. (c) Rotation of the cone around the y-axis. (d) Rotation around the z-axis. (e) Total scattering profile (logarithmic scale). (f) Simulated scattering profile (logarithmic scale).
Fig. 5
Fig. 5 Angular response of fiber modes and BRAD ratios for different particle sizes. (a) Angular FMF response to different angle orientations in a field of view of ±4° of a mirror in the sample position. The fiber angular transfer function shows good agreement with the modal intensity profiles simulated in Fig. 2. (b) Electron microscopy scans of the different particle sizes. (c) Angular scattering profiles were simulated for different microparticle sizes using Mie theory. The light scattered from the polymer microparticles excites the FMF modes according to the angular response measured for the FMF as shown in (d) and (e) for LP01 and LP11. (f) Results of the BRAD ratio between LP01/LP11 and LP01/LP21 for the different microparticle sizes measured with BRAD-OCT and the corresponding theoretical results displayed in red.
Fig. 6
Fig. 6 BRAD-OCT in cancer imaging. (a) Macroscopic image of a temporal lobe resection partly infiltrated by glioblastoma (note petechial bleedings in the white matter). The scanned area is indicated by a square. (b) En face map displaying the BRAD ratio of LP21 and LP01 revealed different scattering characteristics for the cancerous area as compared to the adjacent brain parenchyma. (c) The corresponding histological scan of the brain sample after OCT imaging revealed adjacent brain parenchyma of low cellularity (blue box). In contrast, tumorous tissue (orange box) is associated with increased cell density and wide variations in the nuclear size and shape. (d) Representative OCT volume of the scanned area with overlaid BRAD map indicating the tumor area and infiltration zone. (e) Nuclear density map by digital histology. (f) Nuclear size map. (g) Comparison of BRAD ratio with nuclear density in an area of tumorous and adjacent tissue, respectively. (h) Comparison of BRAD ratio with nuclear size.
Fig. 7
Fig. 7 BRAD-OCT of neuritic plaques in Alzheimer’s disease. (a) OCT depth-multiplexed B-scan images of a brain from a late-stage Alzheimer’s patient for the LP01, LP11 and LP21 modes. Neuritic plaques can be observed as hyper-scattering structures particularly showing up in the B-scans obtained by the higher-order modes. (b–d) En-face intensity projection images for LP01, LP11, and LP21. The bright field scattering collected by the fundamental mode LP01 (b) does not enable clear differentiation of neuritic plaques while the higher modes (c – d) enhance the contrast between plaques (arrows in (a)) and the surrounding tissue. The combination of the modal en face projections in the channels of an RGB image provides an easy discrimination between (e) Alzheimer affected and (f) non-affected tissue, highlighting the neuritic plaques in the green channel. (g) Volume rendering encoding all modal information in an RGB channel. (h) Histologic section of a neuritic plaque highlighted with Congo red stain scanned after applying BRAD-OCT.

Equations (18)

Equations on this page are rendered with MathJax. Learn more.

ψ l , m ( r , φ ) = { A l m J l ( U l m ) J l ( U l m r a ) e ± i l φ , r < a A l m K l ( W l m ) K l ( W l m r a ) e ± i l φ , r < a
Ψ ( r , φ , z , t ) = p a p ψ p ( r , φ ) e i ( ω t β p z 2 k z s )
Ψ ˜ ( ρ , θ , z , t ) = p a p ψ ˜ p ( ρ , θ ) e i ( ω t β p L FMF 2 k z s ) .
Ψ ˜ ref ( ρ , θ , z , t ) = a ref ψ ˜ ref ( ρ , θ ) e i ( ω t β ref L FMF 2 k z ref ) .
Ψ ˜ d e t ( ρ , θ , z , t ) = Ψ ˜ ( ρ , θ , z , t ) + Ψ ˜ ref ( ρ , θ , z , t ) = p a p ψ ˜ ( ρ , θ ) e i ( ω t β p L FMF 2 k z s ) + a ref ψ ˜ ref ( ρ , θ ) e i ( ω t β ref L FMF 2 k z ref ) .
I 1 ( ρ , θ ) ~ a ref 2 | ψ ˜ ref ( ρ , θ ) | 2 ,
I 2 ( ρ , θ ) ~ p a p 2 | ψ ˜ p ( ρ , θ ) | 2 ,
I 3 ( ρ , θ ) ~ p q 2 a p a q | ψ ˜ p ( ρ , θ ) ψ ˜ q ( ρ , θ ) γ p , q ( τ ) | cos [ ( β q β p ) L FMF δ p , q ] ,
I 4 ( ρ , θ , k ) ~ p 2 a p a ref | ψ ˜ p ( ρ , θ ) ψ ˜ ref ( ρ , θ ) γ p , ref ( τ ) | cos [ ( β ref β p ) L FMF + 2 k Δ z δ p , ref ] .
A ψ j ψ k d A = C δ j k
A ψ j ψ k d A = C δ j k
V = 2 π λ a NA = 2 π λ a n c o r e 2 n c l a d d i n g 2
M V 2 2
Δ z = Δ n eff L
( S x S y S z ) = ( z n tan θ cos v z n tan θ sin v z n )
( S x S y S z ) = ( cos θ 0 sin θ 0 1 0 sin θ 0 cos θ ) ( z n tan θ cos v z n tan θ sin v z n ) = ( z n ( 1 + cos v ) sin θ z n tan θ sin v z n ( cos θ cos v sin θ tan θ ) )
( S x S y S z ) = ( cos ω sin ω 0 sin ω cos ω 0 0 0 1 ) ( z n ( 1 + cos v ) sin θ z n tan θ sin v z n ( cos θ cos v sin θ tan θ ) ) = ( z n ( ( 1 + cos v ) sin θ cos ω sin ω sin v tan θ ) z n ( ( 1 + cos v ) sin θ sin ω cos ω sin v tan θ ) z n ( cos θ cos v sin θ tan θ ) ) )
I t o t a l ( θ ) θ π I ( θ ) d θ = π 2 4 θ 2 4 .

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