Through-skull fluorescence imaging of the brain in a new near-infrared window

Journal name:
Nature Photonics
Volume:
8,
Pages:
723–730
Year published:
DOI:
doi:10.1038/nphoton.2014.166
Received
Accepted
Published online

Abstract

To date, brain imaging has largely relied on X-ray computed tomography and magnetic resonance angiography, with their limited spatial resolution and long scanning times. Fluorescence-based brain imaging in the visible and traditional near-infrared regions (400–900 nm) is an alternative, but at present it requires craniotomy, cranial windows and skull-thinning techniques, and the penetration depth is limited to 1–2 mm due to light scattering. Here, we report through-scalp and through-skull fluorescence imaging of mouse cerebral vasculature without craniotomy, utilizing the intrinsic photoluminescence of single-walled carbon nanotubes in the 1.3–1.4 μm near-infrared window (NIR-IIa window). Reduced photon scattering in this spectral region allows fluorescence imaging to a depth of >2 mm in mouse brain with sub-10-μm resolution. An imaging rate of ∼5.3 frames per second allows for dynamic recording of blood perfusion in the cerebral vessels with sufficient temporal resolution, providing real-time assessment of a blood flow anomaly in a mouse middle cerebral artery occlusion stroke model.

At a glance

Figures

  1. Imaging in various NIR subregions.
    Figure 1: Imaging in various NIR subregions.

    a, A fluorescence emission spectrum of SWNT–IRDye800 conjugate in the range of 850–1,650 nm under excitation from an 808 nm laser. The emission spectra of IRDye800 and SWNTs are plotted with different y-axis scales to accommodate both into the same graph, due to the much higher fluorescence intensity of IRDye800 than SWNTs. b, NIR fluorescence images of a capillary tube filled with SWNT–IRDye800 solution immersed at depths of 1 mm (top) and 10 mm (bottom) in 1% Intralipid, recorded in NIR-I, NIR-II and NIR-IIa regions, respectively. c, Extinction spectrum (black curve) and scattering spectrum (red curve, measured by subtracting water and Intralipid absorptions from the extinction spectrum, Supplementary Fig. 2) of 1% Intralipid in water with a path length of 1 mm measured with a UV–Vis–NIR spectrometer, as well as a reduced scattering coefficient profile (blue, converted to the unit of OD with base-10 common log) of 1% Intralipid derived from the literature33.

  2. In vivo mouse brain imaging with SWNT–IRDye800 in different NIR subregions.
    Figure 2: In vivo mouse brain imaging with SWNT–IRDye800 in different NIR subregions.

    a, A C57Bl/6 mouse head with hair removed. bd, Fluorescence images of the same mouse head in the NIR-I, NIR-II and NIR-IIa regions. In d, the inferior cerebral vein, superior sagittal sinus and transverse sinus are labelled 1, 2 and 3, respectively. e, Extinction spectra of scalp (red) and skull (blue) as well as the water absorption spectrum (black). f, Reduced scattering coefficients μ of scalp skin (red), cranial bone (blue) and brain tissue (black) plotted against wavelength, based on the previously reported scattering properties for these tissues8, 35, 36.

  3. Non-invasive, high-resolution NIR-IIa fluorescence imaging of mouse brain vasculature.
    Figure 3: Non-invasive, high-resolution NIR-IIa fluorescence imaging of mouse brain vasculature.

    a, Photograph showing the stereotactic microscopic imaging set-up. A red laser is used for alignment and shows the beam location. b, Schematic showing the penetration of NIR-IIa fluorescence through brain tissue, skull and scalp. c, Photoluminescence versus excitation spectrum of LS nanotubes in aqueous solution. The 1.3–1.4 µm NIR-IIa region is in red. d, Low-magnification cerebral vascular image taken with a field of view of 25 mm × 20 mm. e, Cerebral vascular image of the same mouse head zoomed into the left cerebral hemisphere, with a field of view of 8 mm × 6.4 mm. f, Cerebral vascular image of the same mouse head taken using a microscope objective, with a field of view of 1.7 mm × 1.4 mm. The depth of these in-focus vascular features was determined to be 2.6 mm. g, Zoomed-in image of a sub-region in f taken by a higher-magnification objective, with a field of view of 0.80 mm × 0.64 mm. Inset: cross-sectional intensity profile (black) and Gaussian fit (red) along the yellow-dashed bar. hk, Two other high-resolution cerebral vascular images with a field of view of 0.80 mm × 0.64 mm taken on another mouse (h,j) and their cross-sectional fluorescence intensity profiles (black) and Gaussian fit (red) along the yellow-dashed bars (i,k).

  4. Dynamic NIR-IIa fluorescence imaging of mouse cerebral vasculature.
    Figure 4: Dynamic NIR-IIa fluorescence imaging of mouse cerebral vasculature.

    ac, Time-course NIR-IIa images of a control healthy mouse (Mouse C1). df, PCA overlaid images showing arterial (red) and venous (blue) vessels of Mouse C1. gi, Time-course NIR-IIa images of a mouse with MCAO (Mouse M1). jl, PCA overlaid images showing arterial (red) and venous (blue) vessels of Mouse M1. m,n, Normalized NIR-IIa signal in the left (red) and right (black) cerebral hemispheres of Mouse C1 (m) and Mouse M1 (n) versus time. o, Average blood perfusion of the left cerebral hemisphere of the control group (n = 3), MCAO group (n = 4) and cerebral hypoperfusion group (n = 4), measured by the NIR-II method (red) and laser Doppler blood spectroscopy (blue). Errors bars indicate the standard deviation of each group.

References

  1. Go, A. S. et al. Heart disease and stroke statistics—2013 update—a report from the American Heart Association. Circulation 127, E6E245 (2013).
  2. Schramm, P. et al. Comparison of CT and CT angiography source images with diffusion-weighted imaging in patients with acute stroke within 6 hours after onset. Stroke 33, 24262432 (2002).
  3. Wright, S. N. et al. Digital reconstruction and morphometric analysis of human brain arterial vasculature from magnetic resonance angiography. Neuroimage 82, 170181 (2013).
  4. Huang, C.-H. et al. High-resolution structural and functional assessments of cerebral microvasculature using 3D gas ΔR2*-mMRA. PloS ONE 8, e78186 (2013).
  5. Flohr, T. G. et al. First performance evaluation of a dual-source CT (DSCT) system. Eur. Radiol. 16, 256268 (2006).
  6. Jacoby, C. et al. Dynamic changes in murine vessel geometry assessed by high-resolution magnetic resonance angiography: a 9.4 T study. J. Magn. Reson. Imaging 28, 637645 (2008).
  7. Paulus, M. J., Gleason, S. S., Kennel, S. J., Hunsicker, P. R. & Johnson, D. K. High resolution X-ray computed tomography: an emerging tool for small animal cancer research. Neoplasia 2, 6270 (2000).
  8. Horton, N. G. <i>et al</i>. In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nature Photon. 7, 205209 (2013).
  9. Svoboda, K., Denk, W., Kleinfeld, D. & Tank, D. W. In vivo dendritic calcium dynamics in neocortical pyramidal neurons. Nature 385, 161165 (1997).
  10. Drew, P. J. et al. Chronic optical access through a polished and reinforced thinned skull. Nature Methods 7, 981984 (2010).
  11. Yang, G., Pan, F., Parkhurst, C. N., Grutzendler, J. & Gan, W.-B. Thinned-skull cranial window technique for long-term imaging of the cortex in live mice. Nature Protoc. 5, 201208 (2010).
  12. Martirosyan, N. L. et al. Use of in vivo near-infrared laser confocal endomicroscopy with indocyanine green to detect the boundary of infiltrative tumor. Laboratory investigation. J. Neurosurg. 115, 11311138 (2011).
  13. Theer, P., Hasan, M. T. & Denk, W. Two-photon imaging to a depth of 1000 µm in living brains by use of a Ti:Al2O3 regenerative amplifier. Opt. Lett. 28, 10221024 (2003).
  14. Kobat, D., Horton, N. G. & Xu, C. In vivo two-photon microscopy to 1.6-mm depth in mouse cortex. J. Biomed. Opt. 16, 106014 (2011).
  15. Splinter, R. & Hooper, B. A. An Introduction to Biomedical Optics (Taylor & Francis, 2007).
  16. Frangioni, J. V. In vivo near-infrared fluorescence imaging. Curr. Opin. Chem. Biol. 7, 626634 (2003).
  17. Smith, A. M., Mancini, M. C. & Nie, S. Bioimaging: second window for in vivo imaging. Nature Nanotech. 4, 710711 (2009).
  18. Yi, H. et al. M13 phage-functionalized single-walled carbon nanotubes as nanoprobes for second near-infrared window fluorescence imaging of targeted tumors. Nano Lett. 12, 11761183 (2012).
  19. Welsher, K. et al. A route to brightly fluorescent carbon nanotubes for near-infrared imaging in mice. Nature Nanotech. 4, 773780 (2009).
  20. Welsher, K., Sherlock, S. P. & Dai, H. Deep-tissue anatomical imaging of mice using carbon nanotube fluorophores in the second near-infrared window. Proc. Natl Acad. Sci. USA 108, 89438948 (2011).
  21. Hong, G. et al. Three-dimensional imaging of single nanotube molecule endocytosis on plasmonic substrates. Nature Commun. 3, 700 (2012).
  22. Hong, G. et al. Multifunctional in vivo vascular imaging using near-infrared II fluorescence. Nature Med. 18, 18411846 (2012).
  23. Won, N. et al. Imaging depths of near-infrared quantum dots in first and second optical windows. Mol. Imaging 11, 338352 (2012).
  24. Hong, G. et al. In vivo fluorescence imaging with Ag2S quantum dots in the second near-infrared region. Angew. Chem. Int. Ed. 51, 98189821 (2012).
  25. Naczynski, D. J. et al. Rare-earth-doped biological composites as in vivo shortwave infrared reporters. Nature Commun. 4, 2199 (2013).
  26. Tao, Z. et al. Biological imaging using nanoparticles of small organic molecules with fluorescence emission at wavelengths longer than 1000 nm. Angew. Chem. Int. Ed. 52, 1300213006 (2013).
  27. Dong, B. et al. Facile synthesis of highly photoluminescent Ag2Se quantum dots as a new fluorescent probe in the second near-infrared window for in vivo imaging. Chem. Mater. 25, 25032509 (2013).
  28. Hong, G. et al. Near-infrared II fluorescence for imaging hindlimb vessel regeneration with dynamic tissue perfusion measurement. Circ. Cardiovasc. Imaging 7, 517525 (2014).
  29. Hong, G. et al. Ultrafast fluorescence imaging in vivo with conjugated polymer fluorophores in the second near-infrared window. Nature Commun. 5, 4206 (2014).
  30. Chiang, I. W. et al. Purification and characterization of single-wall carbon nanotubes (SWNTs) obtained from the gas-phase decomposition of CO (HiPco process). J. Phys. Chem. B 105, 82978301 (2001).
  31. O'Connell, M. J. et al. Band gap fluorescence from individual single-walled carbon nanotubes. Science 297, 593596 (2002).
  32. Bachilo, S. M. et al. Structure-assigned optical spectra of single-walled carbon nanotubes. Science 298, 23612366 (2002).
  33. Van Staveren, H. J., Moes, C. J. M., van Marie, J., Prahl, S. A. & van Gemert, M. J. C. Light scattering in Intralipid-10% in the wavelength range of 400–1100 nm. Appl. Opt. 30, 45074514 (1991).
  34. Curcio, J. A. & Petty, C. C. The near infrared absorption spectrum of liquid water. J. Opt. Soc. Am. 41, 302304 (1951).
  35. Bashkatov, A. N., Genina, E. A., Kochubey, V. I. & Tuchin, V. V. Optical properties of human cranial bone in the spectral range from 800 to 2000 nm. Saratov Fall Meeting 2005: Optical Technologies in Biophysics and Medicine VII 6163, 616310 (2006).
  36. Bashkatov, A. N., Genina, E. A., Kochubey, V. I. & Tuchin, V. V. Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm. J. Phys. D 38, 25432555 (2005).
  37. White, J. G., Amos, W. B. & Fordham, M. An evaluation of confocal versus conventional imaging of biological structures by fluorescence light-microscopy. J. Cell Biol. 105, 4148 (1987).
  38. Kleinfeld, D., Mitra, P. P., Helmchen, F. & Denk, W. Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex. Proc. Natl Acad. Sci. USA 95, 1574115746 (1998).
  39. Shih, A. Y. et al. Two-photon microscopy as a tool to study blood flow and neurovascular coupling in the rodent brain. J. Cerebr. Blood Flow Metab. 32, 12771309 (2012).
  40. Helmchen, F. & Kleinfeld, D. In vivo measurements of blood flow and glial cell function with two-photon laser-scanning microscopy. Methods Enzymol. 444, 231254 (2008).
  41. Helmchen, F. & Denk, W. Deep tissue two-photon microscopy. Nature Methods 2, 932940 (2005).
  42. Dunn, A. K. Laser speckle contrast imaging of cerebral blood flow. Ann. Biomed. Eng. 40, 367377 (2012).
  43. Boas, D. A. & Dunn, A. K. Laser speckle contrast imaging in biomedical optics. J. Biomed. Opt. 15, 011109 (2010).
  44. Vakoc, B. J. et al. Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging. Nature Med. 15, 12191223 (2009).
  45. Senarathna, J., Rege, A., Li, N. & Thakor, N. V. Laser speckle contrast imaging: theory, instrumentation and applications. IEEE Rev. Biomed. Eng. 6, 99110 (2013).
  46. Hillman, E. M. C. & Moore, A. All-optical anatomical co-registration for molecular imaging of small animals using dynamic contrast. Nature Photon. 1, 526530 (2007).

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Author information

  1. These authors contributed equally to this work

    • Guosong Hong,
    • Shuo Diao &
    • Junlei Chang

Affiliations

  1. Department of Chemistry, Stanford University, Stanford, California 94305, USA

    • Guosong Hong,
    • Shuo Diao,
    • Alexander L. Antaris,
    • Changxin Chen,
    • Bo Zhang,
    • Su Zhao &
    • Hongjie Dai
  2. Division of Hematology, School of Medicine, Stanford University, Stanford, California 94305, USA

    • Junlei Chang &
    • Calvin J. Kuo
  3. Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA

    • Dmitriy N. Atochin &
    • Paul L. Huang
  4. Department of Neurology and Neurological Sciences, Stanford University Medical Center, Stanford, California 94305, USA

    • Katrin I. Andreasson

Contributions

H.D., C.J.K., G.H., S.D. and J.C. conceived and designed the experiments. G.H., S.D., J.C., A.L.A., C.C., B.Z., S.Z. and D.N.A. performed the experiments. G.H., S.D., J.C., A.L.A., C.C., B.Z., S.Z., D.N.A., P.L.H., K.I.A., C.J.K. and H.D. analysed the data and wrote the manuscript. All authors discussed the results and commented on the manuscript.

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The authors declare no competing financial interests.

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