Abstract

Abstract: Measurement of bioluminescent or fluorescent optical reporters with an implanted fiber-optic probe is a promising approach to allow real-time monitoring of molecular and cellular processes in conscious behaving animals. Technically, this approach relies on sensitive light detection due to the relatively limited light signal and inherent light attenuation in scattering tissue. In this paper, we show that specific geometries of lensed fiber probes improve photon collection in turbid tissue such as brain. By employing Monte Carlo simulation and experimental measurement, we demonstrate that hemispherical- and axicon-shaped lensed fibers increase collection efficiency by up to 2-fold when compared with conventional bare fiber. Additionally we provide theoretical evidence that axicon lenses with specific angles improve photon collection over a wider axial range while conserving lateral collection when compared to hemispherical lensed fiber. These findings could guide the development of a minimally-invasive highly sensitive fiber optic-based light signal monitoring technique and may have broad implications such as fiber-based detection used in diffuse optical spectroscopy.

© 2014 Optical Society of America

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References

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2014 (1)

2013 (2)

G. Oh, E. Chung, and S. H. Yun, “Optical fibers for high-resolution in vivo microendoscopic fluorescence imaging,” Opt. Fiber Technol. 19(6), 760–771 (2013).
[Crossref]

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

2012 (1)

C. Grienberger and A. Konnerth, “Imaging calcium in neurons,” Neuron 73(5), 862–885 (2012).
[Crossref] [PubMed]

2011 (1)

B. Wang, S. Fan, L. Li, and C. Wang, “Study of probe-sample distance for biomedical spectra measurement,” Biomed. Eng. Online 10(1), 95 (2011).
[Crossref] [PubMed]

2010 (3)

2009 (1)

2008 (2)

O. Brzobohatý, T. Cizmár, and P. Zemánek, “High quality quasi-Bessel beam generated by round-tip axicon,” Opt. Express 16(17), 12688–12700 (2008).
[Crossref] [PubMed]

F. Jaillon, W. Zheng, and Z. Huang, “Beveled fiber-optic probe couples a ball lens for improving depth-resolved fluorescence measurements of layered tissue: Monte Carlo simulations,” Phys. Med. Biol. 53(4), 937–951 (2008).
[Crossref] [PubMed]

2007 (1)

2005 (1)

2004 (1)

2003 (1)

2002 (3)

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

T. J. Pfefer, K. T. Schomacker, M. N. Ediger, and N. S. Nishioka, “Multiple-fiber probe design for fluorescence spectroscopy in tissue,” Appl. Opt. 41(22), 4712–4721 (2002).
[Crossref] [PubMed]

E. Beaurepaire and J. Mertz, “Epifluorescence collection in two-photon microscopy,” Appl. Opt. 41(25), 5376–5382 (2002).
[Crossref] [PubMed]

1998 (1)

1995 (1)

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio. 47(2), 131–146 (1995).
[Crossref]

1954 (1)

1941 (1)

L. G. Henyey and J. L. Greenstein, “Diffuse radiation in the galaxy,” Astrophys. J. 93, 70–83 (1941).
[Crossref]

Aoki, T.

Arifler, D.

Bargo, P. R.

Beaurepaire, E.

Brightwell, A.

Brzobohatý, O.

Burke, G.

Carnohan, M.

Chang, S. K.

Chonan, S.

Chung, E.

G. Oh, E. Chung, and S. H. Yun, “Optical fibers for high-resolution in vivo microendoscopic fluorescence imaging,” Opt. Fiber Technol. 19(6), 760–771 (2013).
[Crossref]

Cizmár, T.

Costa, R. M.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Cottone, G.

Cui, G.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Ediger, M. N.

Engelbrecht, C. J.

Fan, S.

B. Wang, S. Fan, L. Li, and C. Wang, “Study of probe-sample distance for biomedical spectra measurement,” Biomed. Eng. Online 10(1), 95 (2011).
[Crossref] [PubMed]

Fang, Q.

French, P. J.

Gillenwater, A. M.

Göbel, W.

Greenstein, J. L.

L. G. Henyey and J. L. Greenstein, “Diffuse radiation in the galaxy,” Astrophys. J. 93, 70–83 (1941).
[Crossref]

Grienberger, C.

C. Grienberger and A. Konnerth, “Imaging calcium in neurons,” Neuron 73(5), 862–885 (2012).
[Crossref] [PubMed]

Helmchen, F.

Henyey, L. G.

L. G. Henyey and J. L. Greenstein, “Diffuse radiation in the galaxy,” Astrophys. J. 93, 70–83 (1941).
[Crossref]

Huang, Z.

F. Jaillon, W. Zheng, and Z. Huang, “Beveled fiber-optic probe couples a ball lens for improving depth-resolved fluorescence measurements of layered tissue: Monte Carlo simulations,” Phys. Med. Biol. 53(4), 937–951 (2008).
[Crossref] [PubMed]

Hussain, I. A.

Jacques, S. L.

P. R. Bargo, S. A. Prahl, and S. L. Jacques, “Collection efficiency of a single optical fiber in turbid media,” Appl. Opt. 42(16), 3187–3197 (2003).
[Crossref] [PubMed]

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio. 47(2), 131–146 (1995).
[Crossref]

Jaillon, F.

F. Jaillon, W. Zheng, and Z. Huang, “Beveled fiber-optic probe couples a ball lens for improving depth-resolved fluorescence measurements of layered tissue: Monte Carlo simulations,” Phys. Med. Biol. 53(4), 937–951 (2008).
[Crossref] [PubMed]

Jin, X.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Jones, L. R.

Jun, S. B.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Kato, S.

Knight, B.

Konnerth, A.

C. Grienberger and A. Konnerth, “Imaging calcium in neurons,” Neuron 73(5), 862–885 (2012).
[Crossref] [PubMed]

Li, J.

Li, L.

B. Wang, S. Fan, L. Li, and C. Wang, “Study of probe-sample distance for biomedical spectra measurement,” Biomed. Eng. Online 10(1), 95 (2011).
[Crossref] [PubMed]

Liang, J.

Lovinger, D. M.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Lu, B.

Mack, V.

Marcu, L.

Margallo-Balbás, E.

Mätzler, C.

C. Mätzler, “MATLAB functions for Mie scattering and absorption, version 2,” IAP Res. Rep8, (2002).

McLeod, J. H.

Mertz, J.

Nishioka, N. S.

Oh, G.

G. Oh, E. Chung, and S. H. Yun, “Optical fibers for high-resolution in vivo microendoscopic fluorescence imaging,” Opt. Fiber Technol. 19(6), 760–771 (2013).
[Crossref]

Papaioannou, T.

Pavlova, I.

Pfefer, T. J.

Pham, M. D.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Pogue, B. W.

Prahl, S. A.

Preyer, N. W.

Qu, X.

Ren, N.

Richards-Kortum, R.

Ross, R.

Schober, R.

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Schomacker, K. T.

Schulze, P. C.

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Schwarz, R. A.

Schwarzmaier, H. J.

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Shen, H.

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[Crossref] [PubMed]

Tian, J.

Ulrich, F.

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Vogel, S. S.

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Wang, B.

B. Wang, S. Fan, L. Li, and C. Wang, “Study of probe-sample distance for biomedical spectra measurement,” Biomed. Eng. Online 10(1), 95 (2011).
[Crossref] [PubMed]

Wang, C.

B. Wang, S. Fan, L. Li, and C. Wang, “Study of probe-sample distance for biomedical spectra measurement,” Biomed. Eng. Online 10(1), 95 (2011).
[Crossref] [PubMed]

Wang, G.

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[Crossref] [PubMed]

Wang, L.

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio. 47(2), 131–146 (1995).
[Crossref]

Yaroslavsky, A. N.

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Yaroslavsky, I. V.

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Yun, S. H.

G. Oh, E. Chung, and S. H. Yun, “Optical fibers for high-resolution in vivo microendoscopic fluorescence imaging,” Opt. Fiber Technol. 19(6), 760–771 (2013).
[Crossref]

Zemánek, P.

Zheng, L.

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio. 47(2), 131–146 (1995).
[Crossref]

Zheng, W.

F. Jaillon, W. Zheng, and Z. Huang, “Beveled fiber-optic probe couples a ball lens for improving depth-resolved fluorescence measurements of layered tissue: Monte Carlo simulations,” Phys. Med. Biol. 53(4), 937–951 (2008).
[Crossref] [PubMed]

Appl. Opt. (5)

Astrophys. J. (1)

L. G. Henyey and J. L. Greenstein, “Diffuse radiation in the galaxy,” Astrophys. J. 93, 70–83 (1941).
[Crossref]

Biomed. Eng. Online (1)

B. Wang, S. Fan, L. Li, and C. Wang, “Study of probe-sample distance for biomedical spectra measurement,” Biomed. Eng. Online 10(1), 95 (2011).
[Crossref] [PubMed]

Biomed. Opt. Express (1)

Comput. Meth. Prog. Bio. (1)

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio. 47(2), 131–146 (1995).
[Crossref]

J. Opt. Soc. Am. (1)

Nature (1)

G. Cui, S. B. Jun, X. Jin, M. D. Pham, S. S. Vogel, D. M. Lovinger, and R. M. Costa, “Concurrent activation of striatal direct and indirect pathways during action initiation,” Nature 494(7436), 238–242 (2013).
[Crossref] [PubMed]

Neuron (1)

C. Grienberger and A. Konnerth, “Imaging calcium in neurons,” Neuron 73(5), 862–885 (2012).
[Crossref] [PubMed]

Opt. Express (4)

Opt. Fiber Technol. (1)

G. Oh, E. Chung, and S. H. Yun, “Optical fibers for high-resolution in vivo microendoscopic fluorescence imaging,” Opt. Fiber Technol. 19(6), 760–771 (2013).
[Crossref]

Opt. Lett. (2)

Phys. Med. Biol. (3)

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol. 55(4), 947–962 (2010).
[Crossref] [PubMed]

F. Jaillon, W. Zheng, and Z. Huang, “Beveled fiber-optic probe couples a ball lens for improving depth-resolved fluorescence measurements of layered tissue: Monte Carlo simulations,” Phys. Med. Biol. 53(4), 937–951 (2008).
[Crossref] [PubMed]

A. N. Yaroslavsky, P. C. Schulze, I. V. Yaroslavsky, R. Schober, F. Ulrich, and H. J. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Biol. 47(12), 2059–2073 (2002).
[Crossref] [PubMed]

Other (2)

J. D. Foley, Computer Graphics: Principles and Practice (Addison-Wesley Professional, 1996).

C. Mätzler, “MATLAB functions for Mie scattering and absorption, version 2,” IAP Res. Rep8, (2002).

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Figures (16)

Fig. 1
Fig. 1 Schematic diagram of the photon collection geometry and analytically obtained axial collection efficiency profiles. (A) Schematics of the axial photon collection geometry and parameters under non-scattering condition. (B) Diagram of general possible photon collection paths under scattering conditions. (C) Axial collection efficiency η (blue line; maximum at ΩNA/4π ratio) and fraction of photons entering the core aperture (red dashed line; ΩcoreNA ratio) under non-scattering conditions. (D) Zoomed plot for the axial collection efficiency η under non-scattering conditions.
Fig. 2
Fig. 2 Schematic diagram of the fiber optic-based photon collection measurement system. (A) Experimental layout of the overall measurement system. (B) Schematic drawing of the photon collection path through the scattering samples.
Fig. 3
Fig. 3 Custom-made flat polished and micro-lensed fibers. (A) Flat polished bare fiber. (B) Axicon lensed fiber with silica tip. (C) Hemispherical lensed fiber with silica tip. (D) Hemispherical lensed fiber with polymer tip.
Fig. 4
Fig. 4 Schematic representation of the Monte Carlo simulation method to calculate photon collection with lensed fiber geometry. (A) Geometry of the collection path and useful parameters. (B) Flow chart of the simulation program for the lensed fibers. (C) Various distal shapes of the lensed fibers used in the simulation.
Fig. 5
Fig. 5 Axial profiles of the collection efficiency η (on-axis) for non-scattering and scattering samples. (A) Collection efficiency of the bare fiber for the non-scattering sample (blue line) and for the tissue-like scattering sample (red line). Solid lines (blue and red) represent simulated collection efficiencies. Black round and square marks represents measured collection efficiencies. Profiles for the fraction of photons entering the core aperture are plotted with gray color (left-axis). (B) Semi-logarithmic representation of the efficiency and the fraction of photons entering the core aperture for the bare fiber. Note the change of the exponential decaying slope below and above zNA for scattering collection case. Analytical non-scattering collection normalized to experimental solid angle Ωobj is given for easy comparison (Green dashed line).
Fig. 6
Fig. 6 Simulated axial profiles of the collection efficiency for hemispherical and axicon-lensed fibers in a scattering sample. (A) The collection efficiency profiles for hemispherical-lensed fibers as a function of different refractive indexes (n = 1.49-1.79). (B) The collection efficiency profiles for axicon-lensed fibers depending on the different base angle (2.5-15 degree) and lens materials (solid lines: n = 1.79, dashed lines: n = 1.49). The bare-fiber collection profile is also represented in the two figures with a black line as a reference.
Fig. 7
Fig. 7 Two-dimensional spatial distribution of the collection efficiency for different shapes of distal lenses in scattering medium: (A) bare, (B) axicon, and (C) hemispherical lensed fibers. The radial coordinate r gives the lateral dependency of the collection efficiency and axial z coordinate provides depth-dependent collection efficiency.
Fig. 8
Fig. 8 Relative signal gain among the different fiber geometries. Spatial distribution of the collection gain for (A) axicon-lensed and (B) hemispherical fibers as compared to the bare fiber. White contours represents the collection gain of 1; improved photon collection over the bare fiber shown by the warmer color region. (C) Relative signal gain between axicon and hemispherical fibers. The figure clearly demonstrates that the axicon lensed fiber provides enhanced photon collection over a much wider range than the hemispherical counterpart, except very near the region of the fiber tip.
Fig. 9
Fig. 9 Experimental signal gain of the lensed fibers. (A) Experimental setup. (B) Measured on-axis collection profiles with a scattering phantom. (C) Measured on-axis collection profiles for brain cortical slices. Simulated data are also presented with dotted line (light color) to aid the comparison.
Fig. 10
Fig. 10 Axial collection efficiency profiles with the point-like and disk-like optical sources. Simulation conditions are as follows: (A) Point-like source and non-scattering medium. (B) Point-like source and scattering medium. (C) Disk-like source and non-scattering medium. (D) Disk-like source and scattering medium. The gray lines represent total number of photons striking the fiber end face.
Fig. 11
Fig. 11 Two-dimensional spatial distribution of the collection efficiency with an ideal point-like source for (A) bare fiber, (B) axicon, and (C) hemispherical lensed fibers in scattering medium: The radial coordinate r gives the lateral dependency of the collection efficiency and axial z coordinate provides depth-dependent collection efficiency.
Fig. 12
Fig. 12 Relative signal gain among the different fiber geometries for a point-like source. Spatial distribution of the collection gain for (A) axicon-lensed and (B) hemispherical fibers as compared to the bare fiber. (C) Relative signal gain between axicon and hemispherical fibers.
Fig. 13
Fig. 13 Lateral dependence of the collection efficiency at five different distances (0 - 300 μm with 50 μm incremental steps) for the three type of fibers in scattering sample.
Fig. 14
Fig. 14 Axial collection efficiency profiles and expected signal gain with the volumetric sphere-like source (radius r = 50 μm) in scattering medium. (A) Axial collection efficiency profiles for the volumetric source with the different distal lens shapes. (B) Expected axial signal gain of the axicon- (red line) and hemispherical-(blue line) lensed fibers as compared to the bare fiber, and relative axial collection gain of the axicon-lensed fiber as compared to the hemispherical-lensed fiber (green line; axicon-to-hemispherical gain).
Fig. 15
Fig. 15 Axial collection efficiency profiles for different fiber core diameters under scattering (A, B) and non-scattering (C, D) conditions. Associated fiber diameters and types are presented on the top and right side of each figures.
Fig. 16
Fig. 16 Scattering coefficient dependence of the collection efficiency for different fiber core diameters: (A) 50 μm, (B) 100 μm, (C) 200 μm, and (D) 400 μm fiber.

Tables (1)

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Table 1 Physical properties of the micro-lensed fibers used for the experiments

Equations (2)

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Ω core (z)=2π(1cos θ core )
η(z)= min( Ω core , Ω NA ) 4π

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