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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 4, Iss. 12 — Nov. 10, 2009
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Quantitative myelin imaging with coherent anti-Stokes Raman scattering microscopy: alleviating the excitation polarization dependence with circularly polarized laser beams

E. Bélanger, S. Bégin, S. Laffray, Y. De Koninck, R. Vallée, and D. Côté  »View Author Affiliations


Optics Express, Vol. 17, Issue 21, pp. 18419-18432 (2009)
http://dx.doi.org/10.1364/OE.17.018419


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Abstract

The use of coherent anti-Stokes Raman scattering microscopy tuned to the lipid vibration for quantitative myelin imaging suffers from the excitation polarization dependence of this third-order nonlinear optical effect. The contrast obtained depends on the orientation of the myelin membrane, which in turn affects the morphometric parameters that can be extracted with image analysis. We show how circularly polarized laser beams can be used to avoid this complication, leading to images free of excitation polarization dependence. The technique promises to be optimal for in vivo imaging and the resulting images can be used for coherent anti-Stokes Raman scattering optical histology on native state tissue.

© 2009 Optical Society of America

1. Introduction

Optical imaging is an essential tool in biology because of its ability to spatially resolve sub-cellular details with high molecular contrast. With the advent of commercial solutions for laser scanned confocal and multiphoton microscopy, high-resolution optical imaging has evolved from a specialized technique for optical scientists to a tool commonly used by biologists for everyday experiments[1

1. J. B. Pawley, ed., Handbook of biological confocal microscopy, 3rd ed. (Springer, 1995).

]. This widespread acceptance combined with advances in chemistry and genetics has generated great interest in the development of new contrast agents[2

2. N. C. Shaner, R. E. Campbell, P. A. Steinbach, B. N. G. Giepmans, A. E. Palmer, and R. Y. Tsien, “Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein,” Nat. Biotechnol. 22, 1567–1572 (2004). [CrossRef] [PubMed]

] and new methods for imaging in general[3

3. F. Helmchen and W. Denk, “Deep tissue two-photon microscopy,” Nat. Methods 2, 932–940 (2005). [CrossRef] [PubMed]

]. There is now a growing set of contrast agents that spans a wide collection of targets, from proteins to cell populations[4

4. N. C. Shaner, P. A. Steinbach, and R. Y. Tsien, “A guide to choosing fluorescent proteins,” Nat. Methods 2, 905–909 (2005). [CrossRef] [PubMed]

]. For instance, the use of antibody-targeted exogenous fluorescent agents or chimeric fluorescent proteins[2

2. N. C. Shaner, R. E. Campbell, P. A. Steinbach, B. N. G. Giepmans, A. E. Palmer, and R. Y. Tsien, “Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein,” Nat. Biotechnol. 22, 1567–1572 (2004). [CrossRef] [PubMed]

] in transgenic animals enable to follow very specific populations of cells and proteins in their native environment[5

5. B. N. G. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien, “The fluorescent toolbox for assessing protein location and function,” Science 312, 217–224 (2006). [CrossRef] [PubMed]

]. However, two aspects may lead to deleterious artifacts. First, the use of exogenous labels or of chimeric proteins can ultimately affect the function of the tagged proteins themselves. Moreover, one can not exclude that the over-expression of chimeric proteins to obtain sufficient fluorescent signals may have adverse effects on the cellular physiology. These techniques have nevertheless become very powerful and are unavoidable tools for understanding cell signaling pathways, cellular physiology and physiophatology[6

6. I. Veilleux, J. A. Spencer, D. P. Biss, D. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum. Electron. 14, 10–18 (2008). [CrossRef]

]. However, some structures can be difficult to label. For instance, cell membranes can be impermeable to dyes and can make dye penetration difficult. For these reasons, endogenous contrasts have also been investigated as a mean to overcome some of the limitations of exogenous labelling. Several such contrast methods are already used for biological applications: fluorescence of endogenous molecules[7

7. W. R. Zipfel, R. M. Williams, R. Christie, A. Y. Nikitin, B. T. Hyman, and W. W. Webb, “Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation.” Proc. Natl. Acad. Sci. U.S.A. 100, 7075–7080 (2003). [CrossRef] [PubMed]

], second-harmonic generation (SHG) of noncentrosymmetric structures[8

8. P. J. Campagnola and L. M. Loew, “Second-harmonic imaging microscopy for visualizing biomolecular arrays in cells, tissues and organisms,” Nat. Biotechnol. 21, 1356–1360 (2003). [CrossRef] [PubMed]

], and spontaneous Raman scattering from endogenous vibrations[9

9. E. B. Hanlon, R. Manoharan, T. W. Koo, K. E. Shafer, J. T. Motz, M. Fitzmaurice, J. R. Kramer, I. Itzkan, R. R. Dasari, and M. S. Feld, “Prospects for in vivo Raman spectroscopy,” Phys. Med. Biol. 45, R1–R59 (2000). [CrossRef] [PubMed]

]. In the last decade, coherent anti-Stokes Raman scattering (CARS) microscopy has gained significant attention in biological imaging because of its biochemical specificity and its higher sensitivity at high molecular concentration compared to spontaneous Raman microscopy[10

10. J.-X. Cheng and X. Xie, “Coherent Anti-Stokes Raman Scattering Microscopy: Instrumentation, Theory, and Applications,” J. Phys. Chem. B 108, 827–840 (2004). [CrossRef]

, 11

11. C. Evans and X. S. Xie, “Coherent Anti-Stokes Raman Scattering Microscopy: Chemical Imaging for Biology and Medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008). [CrossRef]

]. By combining two laser beams of different optical frequencies, it becomes possible to resonantly drive the vibration of a molecule to produce an anti-Stokes photon that carries the chemically-specific information. This signal can be orders of magnitude larger than that obtained with spontaneous Raman microscopy, at high molecular concentration, and can be almost comparable to fluorescence. This sensitivity makes it possible to combine this technique with video-rate microscopy and benefit from a high-frame rate for live animal imaging for example[12

12. C. L. Evans, E. O. Potma, M. Puoris’haag, D. Côté, C. P. Lin, and X. S. Xie, “Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy,” Proc. Natl. Acad. Sci. U.S.A. 102, 16807–16812 (2005). [CrossRef] [PubMed]

]. The application of CARS microscopy to lipid imaging has provided a very successful technique to image lipid-rich structures such as sebaceous glands[12

12. C. L. Evans, E. O. Potma, M. Puoris’haag, D. Côté, C. P. Lin, and X. S. Xie, “Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy,” Proc. Natl. Acad. Sci. U.S.A. 102, 16807–16812 (2005). [CrossRef] [PubMed]

], adipocytes[12

12. C. L. Evans, E. O. Potma, M. Puoris’haag, D. Côté, C. P. Lin, and X. S. Xie, “Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy,” Proc. Natl. Acad. Sci. U.S.A. 102, 16807–16812 (2005). [CrossRef] [PubMed]

] and myelin sheaths[13

13. F. P. Henry, D. Côté, M. A. Randolph, E. A. Z. Rust, R. W. Redmond, I. E. Kochevar, C. P. Lin, and J. M. Winograd, “Real-time in vivo assessment of the nerve microenvironment with coherent anti-Stokes Raman scattering microscopy,” Plast. Reconstr. Surg. 123(2S), 123S–130S (2009). [CrossRef]

, 14

14. H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent anti-stokes Raman scattering imaging of axonal myelin in live spinal tissues,” Biophys. J. 89, 581–591 (2005). [CrossRef] [PubMed]

] without the use of any exogenous labels. However, the nonlinear enhancement arising from CARS microscopy comes at the cost of complexity: two lasers are needed, the nonlinear interaction with the molecules depends on the polarization of the incident beams and the generated signal is quadratic with the molecular concentration[10

10. J.-X. Cheng and X. Xie, “Coherent Anti-Stokes Raman Scattering Microscopy: Instrumentation, Theory, and Applications,” J. Phys. Chem. B 108, 827–840 (2004). [CrossRef]

]. This is particularly limiting for quantitative imaging since the structure orientation with respect to the lasers polarization affects the signal strength[14

14. H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent anti-stokes Raman scattering imaging of axonal myelin in live spinal tissues,” Biophys. J. 89, 581–591 (2005). [CrossRef] [PubMed]

] which in turn affects the morphometric parameters that can be extracted with image analysis. In the case of myelin imaging, this means the amount of signal depends on the membranes orientation since the long lipid chains are always aligned perpendicular to the latter[15

15. E. O. Potma and X. S. Xie, “Detection of single lipid bilayers with coherent anti-Stokes Raman scattering (CARS) microscopy,” J. Raman Spectrosc. 34, 642–650 (2003). [CrossRef]

].

In this paper, we will demonstrate quantitative morphometry of myelin in rat white matter spinal cord tissue with a robust optical technique that alleviates the polarization dependence of the CARS signal intensity. Our procedure uses a combination of circularly polarized laser beams to produce CARS images with minimal polarization dependence. This method avoids the acquisition of multiple images with post-processing for recovering a polarization-independent myelin signal. Moreover, it allows the correlation of the pixel value with the square of the density of myelin and makes images suitable for morphometric interpretation using standard semi-automatic computer-assisted data analysis tools. This technical approach based on the endogenous signal of myelin promises to be optimal for real-time in vivo structural imaging of healthy or pathological tissue.

2. Materials and methods

2.1. Laser light source for CARS imaging

The laser system (Fig. 1(a)) consists of an Optical Parametric Oscillator (OPO) (Levante Emerald, APE-Berlin) pumped by a frequency-doubled Nd:Vanadate mode-locked laser (High-Q Laser, Austria). The pump laser generates a 7 ps, 80 MHz pulse train of 532 nm and 1064 nm laser light. The OPO utilizes a temperature-tuned LBO nonlinear crystal for parametric oscillation and is pumped with 5.5 W of 532 nm laser light. In order to probe the CH2 symmetric stretch vibrations of lipids (2845 cm-1), we use the signal from the OPO (tuned to 816.8 nm) as the CARS Pump beam with a fraction of the 1064 nm laser as the Stokes beam. To control the states of polarization (SOP) of the excitation beams at the sample, a device for compensating ellipticity introduced by dichroics is required for both laser beams (Fig. 1(a)). The SOP of both laser beams is controlled using a combination of a half-wave plate (Tower Optical Corporation, AO15Z 1/2 817 and AO15Z 1/2 1064) and a quarter-wave plate (Tower Optical Corporation, AO15Z 1/4 817 and AO15Z 1/4 1064) (see section 3.2). The beam sizes are individually adjusted using a telescope so that they overfill the objective back aperture. The Pump beam (OPO, 816.8 nm) and the Stokes beam (1064 nm) are then overlapped in space using a dichroic long-pass filter (Semrock, LP02-1064RU-25) and in time using a delay line before they are sent collinearly to the laser scanning microscope. In order to avoid photodamage of the spinal cord tissue, the average power of the Pump and Stokes beam at the sample is limited to 40 mW and 25 mW, respectively.

Fig. 1. (a) Laser system for CARS imaging. HWPp: half-wave plate at the Pump wavelength, HWPs: half-wave plate at the Stokes wavelength, QWPp: quarter-wave plate at the Pump wavelength, QWPs: quarter-wave plate at the Stokes wavelength, Tp: telescope for the Pump beam, Ts: telescope for the Stokes beam, DL: delay line, DF1: recombining dichroic filter, DF2: detection dichroic filter, MO: microscope objective, SPF: short-pass filter, BPF: band-pass filter, L: lens and PMT: photomultiplier tube. (b) Cross section view of a myelin sheath (only one wrapping is shown). Ep: Pump electric field amplitude, Es: Stokes electric field amplitude and θ is the angle between the laboratory x-axis and the direction of the linear polarization of the excitation beams. (c) Diagram of transverse and longitudinal imaging planes. (d) Evolution of the state of polarization of the excitation beams (either pump or Stokes) at the various positions labeled in (a). Dotted lines are the fast and slow axes of the HWP and QWP respectively. DF combines the effects of both dichroic filters DF1 and DF2.

2.2. Epi-detection scheme

The CARS images are acquired using a modified commercial beam-scanning microscope (Olympus, IX71/FV300) with a long working distance 60X (NA 0.9) water immersed objective (LUMPlanFI/IR, Olympus). The backscattered anti-Stokes signal (662.8 nm) is collected in the epi-direction[12

12. C. L. Evans, E. O. Potma, M. Puoris’haag, D. Côté, C. P. Lin, and X. S. Xie, “Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy,” Proc. Natl. Acad. Sci. U.S.A. 102, 16807–16812 (2005). [CrossRef] [PubMed]

]. It is separated from the Pump and Stokes beams by a dichroic long-pass filter (Semrock, FF735-Di01-25x36) and spectrally filtered of unwanted residual light using a combination of two laser block filters (Semrock, FF01-750/SP-25) and a band-pass filter (Semrock, FF01-655/40-25). A red-sensitive photomultiplier tube (Hamamatsu, R3896) is used as a non-descanned epi-detector (Fig. 1(a)) in the external detector position, 12 cm apart from objective.

2.3. Preparation of fixed spinal cord tissue and slices

All experimental procedures have been performed in accordance with guidelines from the Canadian Council on Animal Care. Male Sprague Dawley rats of 280–350 g body weight (Charles River Laboratories, Wilmington, MA) were killed by intracardiac perfusion with 4% paraformaldehyde (PFA, Fischer Scientific, Pittsburgh) in 0.1 M phosphate buffer (PB), pH 7.4, under deep anesthesia. The spinal cord was extruded, and post-fixed overnight in 4% PFA. The lumbar enlargement was isolated, rinsed several times with 0.1 M PB. 1 mm thick transversal slices were made with a vibratome (Leica, VT 1000).

2.4. Preparation of live spinal cord tissue and slices

In cases where live tissues were required, animals were deeply anesthetized by 4% isoflurane and immediately decapitated. The spinal cord was rapidly removed by hydraulic extrusion and immersed in a cold oxygenated (95% O2, 5% CO2) artificial cerebrospinal fluid (ACSF) solution containing the following (in mM): 126 NaCl, 2.5 KCl, 2 MgCl-, 2 CaCl2, 1.25 NaHPO4, 26 NaHCO3, and 10 glucose. The lumbar spinal enlargement was isolated, and maintained in continuously oxygenated ACSF solution for at least 20 min prior to CARS imaging experiment.

When spinal cord slices were required for the imaging experiment, rats were briefly perfused transcardially before decapitation, with a ice-cold oxygenated ACSF containing (in mM): 252 sucrose, 2.5 KCl, 6 MgCl-, 1.5 CaCl2, 1.25 NaHPO4, 26 NaHCO3, 10 glucose, and 5 kynurenate. 1 mm thick slices were cut from the isolated lumbar spinal enlargement in the transversal plane using a vibratome, and were allowed to recover for 15–30 min in an immersion chamber. Slices were then transferred to an oxygenated ACSF solution described above. After 1 h of recovery, individual slices were transferred to a IX71 compatible recording chamber (RC-26G, Harvard Apparatus) and continuously superfused (1–2 ml/min) with this oxygenated ACSF.

2.5. Semi-automatic computer-assisted morphometric analysis of myelinated axons

In-house software, implemented in MATLAB, has been developed for computing morphometric parameters. The state-of-the-art method for computing morphometric information from myelinated axons, developed for histology on ultra-thin slices of fixed tissue, consists in thresh-olding an image and seek for boundaries using a recognition algorithm[16

16. R. L. Friede, “Computer editing of morphometric data on nerve fibers. An improved computer program,” Acta Neuropathol. 72, 74–81 (1986). [CrossRef] [PubMed]

]. The boundaries are identified using a sliding threshold set by the user manually. Those boundaries are then used to make various measurements such as the fiber and axon area, the fiber and axon diameter, the g-ratio (ratio of the axon diameter to the fiber diameter), the myelin thickness and the myelin area are computed[17

17. W. Beuche and R. L. Friede, “A quantitative assessment of myelin sheaths in the peripheral nerves of dystrophic, quaking, and trembler mutants.” Acta Neuropathol. 66, 29–36 (1985). [CrossRef] [PubMed]

, 18

18. R. L. Friede and W. Beuche, “A new approach toward analyzing peripheral nerve fiber populations. I. Variance in sheath thickness corresponds to different geometric proportions of the internodes.” J. Neuropathol. Exp. Neurol. 44, 60–72 (1985). [CrossRef] [PubMed]

].

3. Physical description

3.1. Theoretical analysis of CARS signal generation in myelin

Myelin, the electrically-insulating sheaths surrounding the axons in the peripheral nervous system and mainly in the white matter of the central nervous system, is a wrapping of phospholipid bilayers essentially composed of about 75% lipids and 25% proteins. In a rat, each bilayer has a typical thickness of approximately 10 nm. A standard sheath is constituted of approximately 80 wrappings of individual bilayer providing a total thickness of myelin of around 1 µm[19

19. C. Hildebrand and R. Hahn, “Relation between myelin sheath thickness and axon size in spinal cord white matter of some vertebrate species,” J. Neurol. Sci. 38, 421–434 (1978). [CrossRef] [PubMed]

]. Lipids are essentially made of long chains (z-axis) of CH2 that are perpendicular to the membrane (x-axis). All phospholipids are angularly distributed about the carbon chains (z-axis) without any preferential direction[20

20. T. L. Mazely and W. M. H. III, “Third-order susceptibility tensors of partially ordered systems,” J. Chem. Phys. 87, 1962–1966 (1987). [CrossRef]

]. This means that in the CH2 plane (x-y plane) all the molecules are uniformly oriented, granting the myelin sheaths a macroscopic rotation symmetry axis (z-axis) that is perpendicular to the myelin membrane (Fig. 1(b)), only the first wrapping is shown). Each microscopic molecule of CH2 forms an orthorhombic unit cell, which has an mm 2 point group symmetry characterized by a two-fold rotation axis plus two mirror planes that contain the axis of rotation. The macroscopic third-order susceptibility associated with this symmetry has 21 independent nonzero elements; 3 elements with indices all equal (χ 3 xxxx, χ 3 yyyy, χ 3 zzzz) and 18 coefficients with indices equal in pairs[21

21. C. C. Shang and H. Hsu, “The spatial symmetrical forms of third-order nonlinear susceptibility,” IEEE J. Quant. Electron. 23, 177–179 (1987). [CrossRef]

]. Since the CARS process is far from an absorptive electronic resonance, further simplification is possible by applying explicitly Kleinman’s symmetry arguments[22

22. D. A. Kleinman, “Nonlinear dielectric polarization in optical media,” Phys. Rev. 126, 1977–1979 (1962). [CrossRef]

] and using the contracted notation for third-order nonlinear effects[23

23. D. Chemla, R. F. Begley, and R. Byer, “Experimental and theoretical studies of third-harmonic generation in the chalcopyrite CdGeAs2,” IEEE J. Quant. Electron. 10, 71–81 (1974). [CrossRef]

], leading to macroscopic third-order susceptibility with only 4 independent nonzero elements: c11, c33, c16 and c18, respectively corresponding to indices xxxx, zzzz, xxzz and xxyy. There are two planes possible for imaging as shown on Fig. 1(c): transverse (used with sliced tissue) and longitudinal (used for whole spinal cord). Assuming that the propagation axis is perpendicular to the transverse plane of the myelin sheath cylindrical geometry (Fig. 1(b)) and that both lasers pulses are linearly polarized in that plane, the CARS signal intensity can be calculated. The excitation polarization dependence of the CARS signal intensity of myelin is:

Iωaslinear(θ)Ep4Es2[sin2θ[c33+cos2θ[3c16c33]]2+
cos2θ[3c16+cos2θ[c113c16]]2],
(1)

where Ep and Es represent the Pump and Stokes electric field amplitudes respectively and θ is the angle between the laboratory x-axis and the direction of the linear polarization of the excitation beams. Eq. (1) clearly shows that the CARS signal intensity possesses an angular modulation generating excitation polarization dependence. Since the direction of the linear polarization of the excitation beams is fixed, variations in the signal intensity occur when the orientation of the lipid membranes varies. In particular, excitation polarization dependence appears while imaging myelin cross sections or tortuous longitudinal myelin sheaths.

A similar mathematical development can be performed assuming that both lasers are circularly polarized in the transverse plane. In this case, the CARS signal intensity can be expressed as:

Iωascircular18Ep4Es2[[c11+3c16]2+[c333c16]2].
(2)

It is clear from Eq. (2) that the angular modulation of CARS signal intensity has been removed. Because of the point group symmetry (mm2) of the myelin sheaths and the direction of propagation, no additional terms are probed with circular polarizations. This method yields CARS images intrinsically free of excitation polarization dependence since a circular polarization is an average projection on every tensor elements and the tensor elements do not vary in intensity throughout the image (only their orientations change). Note that the polarization of the emitted light does not affect the detected intensity since no element in the detection path is polarization sensitive (detectors or dichroic). With the procedure explained below, images of myelin cross sections can be made more uniform such that they can be used for quantitative analysis. For images in the longitudinal plane (Fig. 1(c)), the polarization dependence cannot vanish completely with circular polarization because the orientation of the lipid chains changes with imaging depth which alters the combination of accessible tensor elements. Nevertheless, the use of circular polarization in this case also reduces the polarization dependence to allow a more accurate quantitative analysis.

3.2. Polarization ellipticity compensation

Precise control over the polarization of the excitation beams at the sample is challenging due to the presence of dichroic filters downstream from those adjustments. The differences in amplitude of reflection and transmission coefficients between the s and p polarization axis (|Rs|≠|Rp| and |Ts|≠|Tp|) of the filters as well as the introduction of a phase shift (δ) between these two polarization components can alter the SOP, introducing ellipticity to the excitation beams. The usual solution, proposed by Chu et al.[24

24. S.-W. Chu, S.-Y. Chen, G.-W. Chern, T.-H. Tsai, Y.-C. Chen, B.-L. Lin, and C.-K. Sun, “Studies of chi(2)/chi(3) tensors in submicron-scaled bio-tissues by polarization harmonics optical microscopy,” Biophys. J. 86, 3914–3922 (2004). [CrossRef] [PubMed]

], uses linear polarization and is not feasible in vivo since it requires rotating the samples. The need for specimen rotation has been removed in a recently proposed solution generating linear polarizations with high-extinction ratio[25

25. C.-K. Chou, W.-L. Chen, P. T. Fwu, S.-J. Lin, H.-S. Lee, and C.-Y. Dong, “Polarization ellipticity compensation in polarization second-harmonic generation microscopy without specimen rotation,” J. Biomed. Opt. 13, 014005 (2008). [CrossRef] [PubMed]

], for SHG microscopy in rat tail tendon fibrils.

tan(2ϕ)=sin(2β)tan(δ),
(3)

where δ represents the phase shift for light polarized along the p-polarized with respect to light polarized along s-polarized axis, β is the angle of the quarter-wave plate’s slow axis relative to the s-polarized axis, ϕ(ϕ=α-β) is the angle between the excitation polarization after the half-wave plate and the slow axis of the quarter-wave plate and α is the angle between the excitation polarization after the half-wave plate and the s-polarized axis. The circularity of the CARS Pump and Stokes beams, at the sample, has been verified before every imaging session with a rotating polarizer (Thorlabs, LPVIS100). Both SOP were circular within a deviation of less than ±5 % (power ratio of the semi-minor to the semi-major axis of the polarization ellipse).

3.3. Other approaches to minimize the excitation polarization dependence of the CARS signal

Very recently, a solution has been proposed by Fu et al.[26

26. Y. Fu, T. B. Huff, H.-W. Wang, H. Wang, and J.-X. Cheng, “Ex vivo and in vivo imaging of myelin fibers in mouse brain by coherent anti-Stokes Raman scattering microscopy,” Opt. Express 16, 19396–19409 (2008). [CrossRef] [PubMed]

], to cancel the excitation polarization dependence of the CARS signal in myelin. This approach involves the offline mathematical recombination of two images acquired with orthogonal linear polarizations. However, the description of sections 3.1 and 4.1 shows that three tensor elements (c11, c16 and c33) contribute to the CARS signal generation, which implies that the solution proposed by Fu et al.[26

26. Y. Fu, T. B. Huff, H.-W. Wang, H. Wang, and J.-X. Cheng, “Ex vivo and in vivo imaging of myelin fibers in mouse brain by coherent anti-Stokes Raman scattering microscopy,” Opt. Express 16, 19396–19409 (2008). [CrossRef] [PubMed]

] is an approximation since it only considers one term of the full tensor expression (c11). A better but tedious method using linearly polarized excitation beams consists in rotating the polarization in the x-z plane by small increments while recording an image for each value of θ. Thereafter a pixel-by-pixel maximum intensity projection is performed (offline) to get the signal coming from the angle at which the lasers polarization and the membranes are collinear. This approach effectively cancels the excitation polarization dependence of the CARS signal, but it is not suitable for in vivo applications because it requires taking many images at the same location with different linear polarizations. On the other hand, our approach based on circularly polarized laser beams produces CARS images with minimal polarization dependence without any post-processing. Alternatively, it could be possible to rapidly modulate the linear polarization angle of the excitation beams and use phase-locked detection to measure the maximum signal together with its associated phase shift. This would provide quantity and orientation of the lipid chains in a single measurement, in a way similar to what was reported in SHG microscopy for collagen fibers[27

27. P. Stoller, K. M. Reiser, P. M. Celliers, and A. M. Rubenchik, “Polarization-modulated second harmonic generation in collagen,” Biophys. J. 82, 3330–3342 (2002). [CrossRef] [PubMed]

]. However, this is technically very challenging for a dual beam system such as a CARS microscope and was not implemented since the lipid chain orientation is not needed for morphometry.

4. Results

4.1. Quantification of the excitation polarization dependence of myelin CARS signal

Figure 2(a) and Fig. 2(b) show transverse sections of myelinated axons from the white matter of fixed spinal cord tissue recorded with linearly and circularly polarized laser beams. The angle between the macroscopic x-axis of the myelin sheaths and the direction of the linear polarizations of the beams varies around the axons, inducing a systematic excitation polarization dependence of the CARS signal (see inset of Fig. 2(a)). On the other hand, the use of circular polarizations for excitation removes most polarization dependence (see inset of Fig. 2(b)), since it probes all available tensor elements and essentially averages out the polarization dependence. In images of parallel-running axons from the white matter of live spinal cord tissue (Fig. 2(c)), the polarization dependence of the CARS signal is much less important but still present. The large scale alignment of the fibers gives an approximately constant value of θ in Eq. (1) and automatically minimizes polarization effects. However, regions where fibers are not exactly parallel to each other show this polarization dependence (see the encircled zones on Fig. 2(c) and Fig. 2(d)). This is particularly important when studying pathological cases such as multiple sclerosis and nerve injuries[13

13. F. P. Henry, D. Côté, M. A. Randolph, E. A. Z. Rust, R. W. Redmond, I. E. Kochevar, C. P. Lin, and J. M. Winograd, “Real-time in vivo assessment of the nerve microenvironment with coherent anti-Stokes Raman scattering microscopy,” Plast. Reconstr. Surg. 123(2S), 123S–130S (2009). [CrossRef]

] where large scale alignment of the myelin sheaths is not expected to be preserved.

The excitation polarization dependence of the myelin CARS signal intensity can be quantified with high-resolution images of a single cross section of myelin from the white matter of live spinal cord tissue acquired with the excitation beams linearly polarized along two orthogonal axes (Fig. 3(a) and 3(b)). Regions around the axon where the CARS signal is larger correspond to recorded pixels where the polarization of both beams is parallel to the myelin membrane. A plot of line profiles centered on the axon and taken at 1° increments shows absolute maxima occurring at 180° apart, when the excitation beams are linearly polarized perpendicular to the long and oriented molecular chains of CH2. Conversely, non-zero minima are seen when the excitation beams are linearly polarized perpendicular to the myelin membrane. This observation is consistent with the work of Potma et al.[15

15. E. O. Potma and X. S. Xie, “Detection of single lipid bilayers with coherent anti-Stokes Raman scattering (CARS) microscopy,” J. Raman Spectrosc. 34, 642–650 (2003). [CrossRef]

] on single lipid bilayer, but differs from the model proposed by Fu et al.[26

26. Y. Fu, T. B. Huff, H.-W. Wang, H. Wang, and J.-X. Cheng, “Ex vivo and in vivo imaging of myelin fibers in mouse brain by coherent anti-Stokes Raman scattering microscopy,” Opt. Express 16, 19396–19409 (2008). [CrossRef] [PubMed]

] which predicts a vanishing CARS signal for myelin membrane oriented perpendicularly to the polarization of the excitation beams.

Fig. 2. Example of the excitation polarization dependence of the CARS signal of myelin. (a) and (b) Myelin images from transverse sections of fixed spinal cord, acquired with the excitation beams linearly polarized and circularly polarized respectively. (c) and (d) Myelin images from longitudinal sections of live spinal cord tissue at the equatorial plane, acquired with the excitation beams linearly polarized and circularly polarized respectively.

On the other hand, when using circularly polarized laser beams, the intensity of all pixels is not modulated by any excitation polarization effects (Fig. 4(a) and Fig. 4(c)), as would be expected from Eq. (2). The plot of line profiles for live and fixed myelin sheaths recorded with circularly polarized excitation beams is shown on Fig. 4(b) and Fig. 4(d) respectively. Those images are free from excitation polarization dependance and the pixel values are directly proportional to the square of the density of myelin within the focal point and therefore more suitable for morphometric data analysis.

4.2. Morphometric information of myelinated axons using circularly polarized laser beams

In the literature, it is common to assess the structural characteristics of myelinated axons with four plots of parameters measured on transversal cuts of spinal cord tissue[16

16. R. L. Friede, “Computer editing of morphometric data on nerve fibers. An improved computer program,” Acta Neuropathol. 72, 74–81 (1986). [CrossRef] [PubMed]

, 17

17. W. Beuche and R. L. Friede, “A quantitative assessment of myelin sheaths in the peripheral nerves of dystrophic, quaking, and trembler mutants.” Acta Neuropathol. 66, 29–36 (1985). [CrossRef] [PubMed]

, 18

18. R. L. Friede and W. Beuche, “A new approach toward analyzing peripheral nerve fiber populations. I. Variance in sheath thickness corresponds to different geometric proportions of the internodes.” J. Neuropathol. Exp. Neurol. 44, 60–72 (1985). [CrossRef] [PubMed]

] (described in section 2.5). First, the caliber histogram (Fig. 5(b)) provides accurate information on the size distribution of axons. Second, the scatter plot of the g-ratio as a function of the axon diameter (Fig. 5(c)) is of paramount importance since it reflects either the type of nerves studied or the presence of a pathological state[17

17. W. Beuche and R. L. Friede, “A quantitative assessment of myelin sheaths in the peripheral nerves of dystrophic, quaking, and trembler mutants.” Acta Neuropathol. 66, 29–36 (1985). [CrossRef] [PubMed]

]. For example, the presence of thinly myelinated axons (high g-ratio) is common to many pathological states and regenerating fibers. Linear regression on the scatter plot of the axon diameter versus the fiber diameter (Fig. 5(d)) permits computation of the g-ratio. Finally, the scatter plot of the myelin area as a function of the fiber diameter (Fig. 5(e)) is also of prime significance in the examination of remyelinating axons[28

28. W. Beuche and R. L. Friede, “A new approach toward analyzing peripheral nerve fiber populations. II. Foreshortening of regenerated internodes corresponds to reduced sheath thickness.” J. Neuropathol. Exp. Neurol. 44, 73–84 (1985). [CrossRef] [PubMed]

].

Although transverse cuts of spinal cord provide a large number of axons with which to perform morphometric analysis with good statistics, it is often preferable to obtain morphometric data from live uncut tissue to avoid preparation and cutting artifacts. This can be performed on intact (contact-free) spinal cord with the acquisition of a z-stack followed by three-dimensional reconstruction, thanks to the optical sectioning provided by CARS imaging. Figure 5 shows such a reconstruction from 29 images (240 µm×240 µm, total depth=14 µm) of live spinal segment acquired with the excitation beams circularly polarized. From this three-dimensional reconstruction, 39 orthogonal views perpendicular to the parallel-running axons (5 µm apart) have been generated with the freely accessible Volume Viewer plugin. A typical example is shown on Fig. 5(a) and a short animation displaying the full set is available as supplemental multimedia content (Multimedia 1). From these orthogonal views, 180 morphometric measurements (on 20 different parallel-running axons) have been performed in order to characterize the axons from a specific region of the spinal cord in its native state. Figure 5(b)–(e) summarizes our results using the collection of graphics described earlier. First, from the histogram of caliber classes for the 180 morphometric measurements (Fig. 5(b)), it is found that all axon diameters range between 3.5 µm and 9.5 µm with a mean axon diameter of 6.78±1.19 µm. Then, the scatter diagram of the g-ratio versus the axon caliber (Fig. 5(c)) reveals variations in g-ratios between 0.5 and 0.65 and a minor trend to increase with the axon caliber. The third plot (Fig. 5(d)) allows the direct computation of the mean g-ratio which was found to be 0.57±0.04 (R=0.90). Finally, Fig. 5(e) relates the myelin area to the fiber diameter and shows that the probed nerve population is in a non-pathological state since no splitting or y-shaped distribution is observed[28

28. W. Beuche and R. L. Friede, “A new approach toward analyzing peripheral nerve fiber populations. II. Foreshortening of regenerated internodes corresponds to reduced sheath thickness.” J. Neuropathol. Exp. Neurol. 44, 73–84 (1985). [CrossRef] [PubMed]

].

Fig. 3. Quantification of the excitation polarization dependence of the CARS signal of a single cross section of myelinated axon from live spinal cord tissue. The images (a) and (b) have been acquired with the excitation beams linearly polarized along two perpendicular directions. (c) The expression for the theoretical excitation polarization dependence of the CARS signal intensity has been superimposed (black continuous line) to the experimentally measured polarization dependence (red dots).
Fig. 4. A single cross section of myelin from a transverse slice of live (a) and fixed (c) spinal cord tissue are shown. (b) and (d) Illustrate the angular distribution of the normalized CARS signal for the myelin cross section shown in (a) and (c) respectively.

5. Discussion

5.1. Validation of the theoretical model of the excitation polarization dependence

The experimentally measured linear polarization dependence was fitted with the three non-vanishing elements of the macroscopic third-order susceptibility of Eq. (1) as free parameters. As can be seen from Fig. 3(c), the theoretical model follows accurately the experimentally measured polarization dependence, yielding non-zero values for the three elements (c11=1.00, c16=0.19 and c33=0.48) that contribute to the CARS signal generation in myelin. This confirms that none of these coefficients can be excluded while seeking a method that removes the excitation polarization dependence of the CARS signal.

5.2. Chemical specificity of the CARS signal

Fig. 5. This set of curves displays structural informations from live spinal cord tissue with circularly polarized laser beams. (a) Typical contact-free CARS optical slice. (Media 1)(b) Histogram of caliber classes reveals that the mean axon diameter is 6.78±1.19 µm. (c) Scatter diagram of the g-ratio versus the axon caliber. The g-ratios varie between 0.5 and 0.65. (d) Plot of the axon diameter versus the fiber diameter. A linear regression reveals a mean g-ratio of 0.57±0.04. (e) Scatter diagram of myelin area to the fiber diameter. This single population curve shows that the probed nerve is in a non-pathological state.

5.3. Use of circular polarization and its impact on CARS signal generation

The use of circularly polarized excitation beams alleviates the excitation polarization dependence on either live or fixed tissues. However, because the CARS signal scales as I 2 p Is, special care must be exercised when circularizing the excitation beams. As shown on Fig. 4(b) and Fig. 4(d), small systematic variations remain which may be due to small deviations (less than ~5%) from perfectly circularly polarized laser beams at the sample. This has been confirmed by verifying the circularity of the CARS Pump and Stokes beams at the sample which was then compared to the normalized CARS intensity. In addition, the generated CARS signal using circularly polarized excitation beams is ~3.25 times smaller than the maximum intensity generated with linearly polarized beams (θ=0° in Eq. (1)) and ~1.33 times larger than the minimum intensity generated with linearly polarized beams (θ=90° in Eq. (1)). The images can be properly used for morphometric analysis as this modulation is minimal and their contrast is sufficient.

5.4. Native state morphometry

Myelin sheath cross sections and longitudinal myelin profiles common to many diseases can be analyzed when the image intensity is adequately representing the amount of myelin, such as what is provided with circularly polarized light. For example, on Fig. 3(a) where linear polarization is used, analysis would erroneously suggest that the myelin membrane is thinner on the left and right sides than on top and bottom sides. The inaccuracy of the g-ratio measurement would seriously limit its physiological relevance as a key parameter in the assessment of the myelin health. On the other hand, CARS images recorded with circularly polarized laser beams can be readily analyzed using boundary recognition algorithms and morphometric information can be accurately calculated (Fig. 5). The measured range between 0.5 and 0.65 can be compared with the work of Hildebrand et al.[19

19. C. Hildebrand and R. Hahn, “Relation between myelin sheath thickness and axon size in spinal cord white matter of some vertebrate species,” J. Neurol. Sci. 38, 421–434 (1978). [CrossRef] [PubMed]

], where they reported g-ratios for fixed spinal cord tissue ranging between 0.65 and 0.82. However, morphometric information extracted from fixed tissue is almost certainly altered by the preparation itself (fixation and cutting artifacts). In an effort to estimate these changes, they hypothesize that the g-ratio for live spinal cord tissue should vary between 0.55 and 0.72, which is considered optimal for the conduction velocity of impulses in myelinated fibers[29

29. R. S. Smith and Z. J. Koles, “Myelinated nerve fibers: computed effect of myelin thickness on conduction velocity,” Am. J. Physiol. 219, 1256–1258 (1970). [PubMed]

]. The data on intact spinal cord tissue with our method supports this hypothesis, as shown on Fig. 5(c).

5.5. Other considerations for the circular polarization method

5.6. Outlook

Typically, assessment of myelin health using morphometric parameters is obtained from histopathology on ultra-thin slices of fixed tissues with brightfield imaging or electron microscopy[19

19. C. Hildebrand and R. Hahn, “Relation between myelin sheath thickness and axon size in spinal cord white matter of some vertebrate species,” J. Neurol. Sci. 38, 421–434 (1978). [CrossRef] [PubMed]

]. Performing longitudinal studies to follow the progression of a disease with this method is tedious at best due to the complexity of sample preparation and processing combined with the poor tissue sampling. Methods for the exogenous labelling of myelin in vivo have been developed[30

30. I. Micu, A. Ridsdale, L. Zhang, J. Woulfe, J. McClintock, C. A. Brantner, S. B. Andrews, and P. K. Stys, “Realtime measurement of free Ca2+ changes in CNS myelin by two-photon microscopy,” Nat. Med. 13, 874–879 (2007). [CrossRef] [PubMed]

] but it is well known that the use of dyes could perturb the biological system under investigation and dye penetration into the myelin is an issue. In this respect, label-free imaging techniques have many major advantages over other imaging modalities. CARS microscopy is particularly interesting for the study of demyelinating diseases such as multiple sclerosis, an autoimmune disease where the immune system attacks the central nervous system, leading to the destruction of the electrically-insulating myelin sheaths surrounding the axons. The exact details leading to the disease are still an active area of research and many animal models are used to study its progression. CARS microscopy provides the required framework that will open the way to large scale longitudinal studies and ultimately to a better understanding of the disease.

6. Conclusion

In conclusion, a robust optical technique that alleviates the excitation polarization dependence of the CARS signal intensity has been successfully implemented in our laboratory and extensively tested on fixed and live rat spinal cord tissue. With this strategy, the CARS intensity within the focal volume is more homogenous throughout images, leading to more accurate measurements of the morphometric characteristics of the myelin under investigation. This has been used on live spinal cord tissue to compute morphometric analysis of healthy myelinated axons in their native state. Our approach provides quantifiable endogenous signal which can be used to assess myelin health using standard morphometric techniques and has the potential to become a powerful tool in the quest to understand demyelinating diseases.

Acknowledgments

We want to thank H. Dufour for his technical assistance on custom image analysis software and electronics and M. Lessard-Viger for his help with figures. This work was supported by the National Science and Engineering Research Council of Canada (NSERC-CHRP), Canadian Foundation for Innovation (CFI), Canadian Institutes of Health Research (CIHR-CHRP), Canadian Institute for Photonics Innovation (CIPI). D. Côté is the holder of a Canadian Reasearch Chair in Biophotonics. E. Bélanger is a recipient of a NSERC Ph.D. scholarship. S. Bégin is the holder of a FQRNT Ph.D. scholarship.

References and links

1.

J. B. Pawley, ed., Handbook of biological confocal microscopy, 3rd ed. (Springer, 1995).

2.

N. C. Shaner, R. E. Campbell, P. A. Steinbach, B. N. G. Giepmans, A. E. Palmer, and R. Y. Tsien, “Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein,” Nat. Biotechnol. 22, 1567–1572 (2004). [CrossRef] [PubMed]

3.

F. Helmchen and W. Denk, “Deep tissue two-photon microscopy,” Nat. Methods 2, 932–940 (2005). [CrossRef] [PubMed]

4.

N. C. Shaner, P. A. Steinbach, and R. Y. Tsien, “A guide to choosing fluorescent proteins,” Nat. Methods 2, 905–909 (2005). [CrossRef] [PubMed]

5.

B. N. G. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien, “The fluorescent toolbox for assessing protein location and function,” Science 312, 217–224 (2006). [CrossRef] [PubMed]

6.

I. Veilleux, J. A. Spencer, D. P. Biss, D. Côté, and C. P. Lin, “In vivo cell tracking with video rate multimodality laser scanning microscopy,” IEEE J. Sel. Top. Quantum. Electron. 14, 10–18 (2008). [CrossRef]

7.

W. R. Zipfel, R. M. Williams, R. Christie, A. Y. Nikitin, B. T. Hyman, and W. W. Webb, “Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation.” Proc. Natl. Acad. Sci. U.S.A. 100, 7075–7080 (2003). [CrossRef] [PubMed]

8.

P. J. Campagnola and L. M. Loew, “Second-harmonic imaging microscopy for visualizing biomolecular arrays in cells, tissues and organisms,” Nat. Biotechnol. 21, 1356–1360 (2003). [CrossRef] [PubMed]

9.

E. B. Hanlon, R. Manoharan, T. W. Koo, K. E. Shafer, J. T. Motz, M. Fitzmaurice, J. R. Kramer, I. Itzkan, R. R. Dasari, and M. S. Feld, “Prospects for in vivo Raman spectroscopy,” Phys. Med. Biol. 45, R1–R59 (2000). [CrossRef] [PubMed]

10.

J.-X. Cheng and X. Xie, “Coherent Anti-Stokes Raman Scattering Microscopy: Instrumentation, Theory, and Applications,” J. Phys. Chem. B 108, 827–840 (2004). [CrossRef]

11.

C. Evans and X. S. Xie, “Coherent Anti-Stokes Raman Scattering Microscopy: Chemical Imaging for Biology and Medicine,” Annu. Rev. Anal. Chem. 1, 883–909 (2008). [CrossRef]

12.

C. L. Evans, E. O. Potma, M. Puoris’haag, D. Côté, C. P. Lin, and X. S. Xie, “Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy,” Proc. Natl. Acad. Sci. U.S.A. 102, 16807–16812 (2005). [CrossRef] [PubMed]

13.

F. P. Henry, D. Côté, M. A. Randolph, E. A. Z. Rust, R. W. Redmond, I. E. Kochevar, C. P. Lin, and J. M. Winograd, “Real-time in vivo assessment of the nerve microenvironment with coherent anti-Stokes Raman scattering microscopy,” Plast. Reconstr. Surg. 123(2S), 123S–130S (2009). [CrossRef]

14.

H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, “Coherent anti-stokes Raman scattering imaging of axonal myelin in live spinal tissues,” Biophys. J. 89, 581–591 (2005). [CrossRef] [PubMed]

15.

E. O. Potma and X. S. Xie, “Detection of single lipid bilayers with coherent anti-Stokes Raman scattering (CARS) microscopy,” J. Raman Spectrosc. 34, 642–650 (2003). [CrossRef]

16.

R. L. Friede, “Computer editing of morphometric data on nerve fibers. An improved computer program,” Acta Neuropathol. 72, 74–81 (1986). [CrossRef] [PubMed]

17.

W. Beuche and R. L. Friede, “A quantitative assessment of myelin sheaths in the peripheral nerves of dystrophic, quaking, and trembler mutants.” Acta Neuropathol. 66, 29–36 (1985). [CrossRef] [PubMed]

18.

R. L. Friede and W. Beuche, “A new approach toward analyzing peripheral nerve fiber populations. I. Variance in sheath thickness corresponds to different geometric proportions of the internodes.” J. Neuropathol. Exp. Neurol. 44, 60–72 (1985). [CrossRef] [PubMed]

19.

C. Hildebrand and R. Hahn, “Relation between myelin sheath thickness and axon size in spinal cord white matter of some vertebrate species,” J. Neurol. Sci. 38, 421–434 (1978). [CrossRef] [PubMed]

20.

T. L. Mazely and W. M. H. III, “Third-order susceptibility tensors of partially ordered systems,” J. Chem. Phys. 87, 1962–1966 (1987). [CrossRef]

21.

C. C. Shang and H. Hsu, “The spatial symmetrical forms of third-order nonlinear susceptibility,” IEEE J. Quant. Electron. 23, 177–179 (1987). [CrossRef]

22.

D. A. Kleinman, “Nonlinear dielectric polarization in optical media,” Phys. Rev. 126, 1977–1979 (1962). [CrossRef]

23.

D. Chemla, R. F. Begley, and R. Byer, “Experimental and theoretical studies of third-harmonic generation in the chalcopyrite CdGeAs2,” IEEE J. Quant. Electron. 10, 71–81 (1974). [CrossRef]

24.

S.-W. Chu, S.-Y. Chen, G.-W. Chern, T.-H. Tsai, Y.-C. Chen, B.-L. Lin, and C.-K. Sun, “Studies of chi(2)/chi(3) tensors in submicron-scaled bio-tissues by polarization harmonics optical microscopy,” Biophys. J. 86, 3914–3922 (2004). [CrossRef] [PubMed]

25.

C.-K. Chou, W.-L. Chen, P. T. Fwu, S.-J. Lin, H.-S. Lee, and C.-Y. Dong, “Polarization ellipticity compensation in polarization second-harmonic generation microscopy without specimen rotation,” J. Biomed. Opt. 13, 014005 (2008). [CrossRef] [PubMed]

26.

Y. Fu, T. B. Huff, H.-W. Wang, H. Wang, and J.-X. Cheng, “Ex vivo and in vivo imaging of myelin fibers in mouse brain by coherent anti-Stokes Raman scattering microscopy,” Opt. Express 16, 19396–19409 (2008). [CrossRef] [PubMed]

27.

P. Stoller, K. M. Reiser, P. M. Celliers, and A. M. Rubenchik, “Polarization-modulated second harmonic generation in collagen,” Biophys. J. 82, 3330–3342 (2002). [CrossRef] [PubMed]

28.

W. Beuche and R. L. Friede, “A new approach toward analyzing peripheral nerve fiber populations. II. Foreshortening of regenerated internodes corresponds to reduced sheath thickness.” J. Neuropathol. Exp. Neurol. 44, 73–84 (1985). [CrossRef] [PubMed]

29.

R. S. Smith and Z. J. Koles, “Myelinated nerve fibers: computed effect of myelin thickness on conduction velocity,” Am. J. Physiol. 219, 1256–1258 (1970). [PubMed]

30.

I. Micu, A. Ridsdale, L. Zhang, J. Woulfe, J. McClintock, C. A. Brantner, S. B. Andrews, and P. K. Stys, “Realtime measurement of free Ca2+ changes in CNS myelin by two-photon microscopy,” Nat. Med. 13, 874–879 (2007). [CrossRef] [PubMed]

OCIS Codes
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(180.6900) Microscopy : Three-dimensional microscopy
(300.6230) Spectroscopy : Spectroscopy, coherent anti-Stokes Raman scattering
(180.4315) Microscopy : Nonlinear microscopy

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: July 8, 2009
Revised Manuscript: September 1, 2009
Manuscript Accepted: September 12, 2009
Published: September 28, 2009

Virtual Issues
Vol. 4, Iss. 12 Virtual Journal for Biomedical Optics

Citation
E. Bélanger, S. Bégin, S. Laffray, Y. De Koninck, R. Vallée, and D. Côté, "Quantitative myelin imaging with coherent anti-Stokes Raman scattering microscopy: alleviating the excitation polarization dependence with circularly polarized laser beams," Opt. Express 17, 18419-18432 (2009)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-17-21-18419


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References

  1. J. B. Pawley, ed., Handbook of biological confocal microscopy, 3rd ed. (Springer, 1995).
  2. N. C. Shaner, R. E. Campbell, P. A. Steinbach, B. N. G. Giepmans, A. E. Palmer, and R. Y. Tsien, "Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein," Nat. Biotechnol. 22, 1567-1572 (2004). [CrossRef] [PubMed]
  3. F. Helmchen and W. Denk, "Deep tissue two-photon microscopy," Nat. Methods 2, 932-940 (2005). [CrossRef] [PubMed]
  4. N. C. Shaner, P. A. Steinbach, and R. Y. Tsien, "A guide to choosing fluorescent proteins," Nat. Methods 2, 905-909 (2005). [CrossRef] [PubMed]
  5. B. N. G. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien, "The fluorescent toolbox for assessing protein location and function," Science 312, 217-224 (2006). [CrossRef] [PubMed]
  6. I. Veilleux, J. A. Spencer, D. P. Biss, D. Côté, and C. P. Lin, "In vivo cell tracking with video rate multimodality laser scanning microscopy," IEEE J. Sel. Top. Quantum Electron. 14, 10-18 (2008). [CrossRef]
  7. W. R. Zipfel, R. M. Williams, R. Christie, A. Y. Nikitin, B. T. Hyman, and W. W. Webb, "Live tissue intrinsic emission microscopy using multiphoton-excited native fluorescence and second harmonic generation." Proc. Natl. Acad. Sci. U.S.A. 100, 7075-7080 (2003). [CrossRef] [PubMed]
  8. P. J. Campagnola and L. M. Loew, "Second-harmonic imaging microscopy for visualizing biomolecular arrays in cells, tissues and organisms," Nat. Biotechnol. 21, 1356-1360 (2003). [CrossRef] [PubMed]
  9. E. B. Hanlon, R. Manoharan, T. W. Koo, K. E. Shafer, J. T. Motz, M. Fitzmaurice, J. R. Kramer, I. Itzkan, R. R. Dasari, and M. S. Feld, "Prospects for in vivo Raman spectroscopy," Phys. Med. Biol. 45, R1-R59 (2000). [CrossRef] [PubMed]
  10. J.-X. Cheng and X. Xie, "Coherent Anti-Stokes Raman Scattering Microscopy: Instrumentation, Theory, and Applications," J. Phys. Chem. B 108, 827-840 (2004). [CrossRef]
  11. C. Evans and X. S. Xie, "Coherent Anti-Stokes Raman Scattering Microscopy: Chemical Imaging for Biology and Medicine," Annu. Rev. Anal. Chem. 1, 883-909 (2008). [CrossRef]
  12. C. L. Evans, E. O. Potma, M. Puoris’haag, D. Côté, C. P. Lin, and X. S. Xie, "Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy," Proc. Natl. Acad. Sci. U.S.A. 102, 16807-16812 (2005). [CrossRef] [PubMed]
  13. F. P. Henry, D. Côté, M. A. Randolph, E. A. Z. Rust, R. W. Redmond, I. E. Kochevar, C. P. Lin, and J. M. Winograd, "Real-time in vivo assessment of the nerve microenvironment with coherent anti-Stokes Raman scattering microscopy," Plast. Reconstr. Surg. 123(2S), 123S-130S (2009). [CrossRef]
  14. H. Wang, Y. Fu, P. Zickmund, R. Shi, and J.-X. Cheng, "Coherent anti-stokes Raman scattering imaging of axonal myelin in live spinal tissues," Biophys. J. 89, 581-591 (2005). [CrossRef] [PubMed]
  15. E. O. Potma and X. S. Xie, "Detection of single lipid bilayers with coherent anti-Stokes Raman scattering (CARS) microscopy," J. Raman Spectrosc. 34, 642-650 (2003). [CrossRef]
  16. R. L. Friede, "Computer editing of morphometric data on nerve fibers. An improved computer program," Acta Neuropathol. 72, 74-81 (1986). [CrossRef] [PubMed]
  17. W. Beuche and R. L. Friede, "A quantitative assessment of myelin sheaths in the peripheral nerves of dystrophic, quaking, and trembler mutants." Acta Neuropathol. 66, 29-36 (1985). [CrossRef] [PubMed]
  18. R. L. Friede and W. Beuche, "A new approach toward analyzing peripheral nerve fiber populations. I. Variance in sheath thickness corresponds to different geometric proportions of the internodes." J. Neuropathol. Exp. Neurol. 44, 60-72 (1985). [CrossRef] [PubMed]
  19. C. Hildebrand and R. Hahn, "Relation between myelin sheath thickness and axon size in spinal cord white matter of some vertebrate species," J. Neurol. Sci. 38, 421-434 (1978). [CrossRef] [PubMed]
  20. T. L. Mazely and W. M. H.III, "Third-order susceptibility tensors of partially ordered systems," J. Chem. Phys. 87, 1962-1966 (1987). [CrossRef]
  21. C. C. Shang and H. Hsu, "The spatial symmetrical forms of third-order nonlinear susceptibility," IEEE J. Quant. Electron. 23, 177-179 (1987). [CrossRef]
  22. D. A. Kleinman, "Nonlinear dielectric polarization in optical media," Phys. Rev. 126, 1977-1979 (1962). [CrossRef]
  23. D. Chemla, R. F. Begley, and R. Byer, "Experimental and theoretical studies of third-harmonic generation in the chalcopyrite CdGeAs2," IEEE J. Quantum Electron. 10, 71- 81 (1974). [CrossRef]
  24. S.-W. Chu, S.-Y. Chen, G.-W. Chern, T.-H. Tsai, Y.-C. Chen, B.-L. Lin, and C.-K. Sun, "Studies of chi(2)/chi(3) tensors in submicron-scaled bio-tissues by polarization harmonics optical microscopy," Biophys. J. 86, 3914-3922 (2004). [CrossRef] [PubMed]
  25. C.-K. Chou, W.-L. Chen, P. T. Fwu, S.-J. Lin, H.-S. Lee, and C.-Y. Dong, "Polarization ellipticity compensation in polarization second-harmonic generation microscopy without specimen rotation," J. Biomed. Opt. 13, 014005 (2008). [CrossRef] [PubMed]
  26. Y. Fu, T. B. Huff, H.-W. Wang, H. Wang, and J.-X. Cheng, "Ex vivo and in vivo imaging of myelin fibers in mouse brain by coherent anti-Stokes Raman scattering microscopy," Opt. Express 16, 19396-19409 (2008). [CrossRef] [PubMed]
  27. P. Stoller, K. M. Reiser, P. M. Celliers, and A. M. Rubenchik, "Polarization-modulated second harmonic generation in collagen," Biophys. J. 82, 3330-3342 (2002). [CrossRef] [PubMed]
  28. W. Beuche and R. L. Friede, "A new approach toward analyzing peripheral nerve fiber populations. II. Foreshortening of regenerated internodes corresponds to reduced sheath thickness." J. Neuropathol. Exp. Neurol. 44, 73-84 (1985). [CrossRef] [PubMed]
  29. R. S. Smith and Z. J. Koles, "Myelinated nerve fibers: computed effect of myelin thickness on conduction velocity," Am. J. Physiol. 219, 1256-1258 (1970). [PubMed]
  30. I. Micu, A. Ridsdale, L. Zhang, J. Woulfe, J. McClintock, C. A. Brantner, S. B. Andrews, and P. K. Stys, "Realtime measurement of free Ca2+ changes in CNS myelin by two-photon microscopy," Nat. Med. 13, 874-879 (2007). [CrossRef] [PubMed]

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