Abstract

A visible light spectral domain optical coherence microscopy system was developed. A high axial resolution of 0.88 μm in tissue was achieved using a broad visible light spectrum (425 – 685 nm). Healthy human brain tissue was imaged to quantify the difference between white (WM) and grey matter (GM) in intensity and attenuation. The high axial resolution enables the investigation of amyloid-beta plaques of various sizes in human brain tissue and animal models of Alzheimer’s disease (AD). By performing a spectroscopic analysis of the OCM data, differences in the characteristics for WM, GM, and neuritic amyloid-beta plaques were found. To gain additional contrast, Congo red stained AD brain tissue was investigated. A first effort was made to investigate optically cleared mouse brain tissue to increase the penetration depth and visualize hyperscattering structures in deeper cortical regions.

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2017 (9)

B. Baumann, A. Woehrer, G. Ricken, M. Augustin, C. Mitter, M. Pircher, G. G. Kovacs, and C. K. Hitzenberger, “Visualization of neuritic plaques in Alzheimer’s disease by polarization-sensitive optical coherence microscopy,” Sci. Rep. 7, 43477 (2017).
[Crossref]

L. van Manen, P. L. Stegehuis, A. Fariña-Sarasqueta, L. M. de Haan, J. Eggermont, B. A. Bonsing, H. Morreau, B. P. Lelieveldt, C. J. van de Velde, D. J. Vahrmeijer, L Alexander, and J. S. Mieog, “Validation of full-field optical coherence tomography in distinguishing malignant and benign tissue in resected pancreatic cancer specimens,” PLoS ONE 12, e0175862 (2017).
[Crossref] [PubMed]

S. P. Chong, M. Bernucci, H. Radhakrishnan, and V. J. Srinivasan, “Structural and functional human retinal imaging with a fiber-based visible light OCT ophthalmoscope,” Biomed. Opt. Express 8, 323–337 (2017).
[Crossref] [PubMed]

A. Lichtenegger, D. J. Harper, M. Augustin, P. Eugui, S. Fialová, A. Woehrer, C. K. Hitzenberger, and B. Baumann, “Visible light spectral domain optical coherence microscopy system for ex vivo imaging,” Proc. SPIE 10051, 1005103 (2017).
[Crossref]

M. Maria, I. Gonzalo, M. Bondu, R. Engelsholm, T. Feuchter, P. Moselund, L. Leick, O. Bang, and A. Podoleanu, “A comparative study of noise in supercontinuum light sources for ultra-high resolution optical coherence tomography,” Proc. SPIE 10056, 100560O (2017).

L. Duan, M. D. McRaven, W. Liu, X. Shu, J. Hu, C. Sun, R. S. Veazey, T. J. Hope, and H. F. Zhang, “Colposcopic imaging using visible-light optical coherence tomography,” J. Biomed. Opt. 22, 056003 (2017).
[Crossref]

J. Lefebvre, A. Castonguay, P. Pouliot, M. Descoteaux, and F. Lesage, “Whole mouse brain imaging using optical coherence tomography: reconstruction, normalization, segmentation, and comparison with diffusion MRI,” Neurophotonics 4, 041501 (2017).
[Crossref] [PubMed]

J. Lefebvre, A. Castonguay, and F. Lesage, “White matter segmentation by estimating tissue optical attenuation from volumetric OCT massive histology of whole rodent brains,” Proc. SPIE 10070, 1007012 (2017).
[Crossref]

P. J. Marchand, A. Bouwens, D. Szlag, D. Nguyen, A. Descloux, M. Sison, S. Coquoz, J. Extermann, and T. Lasser, “Visible spectrum extended-focus optical coherence microscopy for label-free sub-cellular tomography,” Biomed. Opt. Express 8, 3343–3359 (2017).
[Crossref] [PubMed]

2016 (10)

T. Liebmann, N. Renier, K. Bettayeb, P. Greengard, M. Tessier-Lavigne, and M. Flajolet, “Three-dimensional study of Alzheimer’s disease hallmarks using the iDISCO clearing method,” Cell Rep. 16, 1138–1152 (2016).
[Crossref] [PubMed]

A. Azaripour, T. Lagerweij, C. Scharfbillig, A. E. Jadczak, B. Willershausen, and C. J. Van Noorden, “A survey of clearing techniques for 3D imaging of tissues with special reference to connective tissue,” Prog. Histochem. Cytochem. 51, 9–23 (2016).
[Crossref] [PubMed]

G. G. Kovacs, “Can Creutzfeldt-Jakob disease unravel the mysteries of Alzheimer?” Prion 10, 369–376 (2016).
[Crossref] [PubMed]

S. Fuchs, C. Rödel, A. Blinne, U. Zastrau, M. Wünsche, V. Hilbert, L. Glaser, J. Viefhaus, E. Frumker, P. Corkum, E. Foerster, and G. G. Paulus, “Nanometer resolution optical coherence tomography using broad bandwidth XUV and soft x-ray radiation,” Sci. Rep 6, 20658 (2016).
[Crossref] [PubMed]

J. Barrick, A. Doblas, M. R. Gardner, P. R. Sears, L. E. Ostrowski, and A. L. Oldenburg, “High-speed and high-sensitivity parallel spectral-domain optical coherence tomography using a supercontinuum light source,” Opt. Lett. 41, 5620–5623 (2016).
[Crossref] [PubMed]

Z. Nafar, M. Jiang, R. Wen, and S. Jiao, “Visible-light optical coherence tomography-based multimodal retinal imaging for improvement of fluorescent intensity quantification,” Biomed. Opt. Express 7, 3220–3229 (2016).
[Crossref] [PubMed]

R. S. Shah, B. T. Soetikno, J. Yi, W. Liu, D. Skondra, H. F. Zhang, and A. A. Fawzi, “Visible-light optical coherence tomography angiography for monitoring laser-induced choroidal neovascularization in mice,” Invest. Ophthalmol. Vis. Sci. 57, OCT86–OCT95 (2016).
[Crossref] [PubMed]

R. P. McNabb, T. Blanco, H. M. Bomze, H. C. Tseng, D. R. Saban, J. A. Izatt, and A. N. Kuo, “Method for single illumination source combined optical coherence tomography and fluorescence imaging of fluorescently labeled ocular structures in transgenic mice,” Exp. Eye Res. 151, 68–74 (2016).
[Crossref] [PubMed]

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
[Crossref] [PubMed]

H. Wang, T. Akkin, C. Magnain, R. Wang, J. Dubb, W. J. Kostis, M. A. Yaseen, A. Cramer, S. Sakadžić, and D. Boas, “Polarization sensitive optical coherence microscopy for brain imaging,” Opt. Lett. 41, 2213–2216 (2016).
[Crossref] [PubMed]

2015 (10)

Alzheimer’s Association, “2015 Alzheimer’s disease facts and figures,” Alzheimers Dement. 11, 332 (2015).
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S. P. Chong, C. W. Merkle, D. F. Cooke, T. Zhang, H. Radhakrishnan, L. Krubitzer, and V. J. Srinivasan, “Noninvasive, in vivo imaging of subcortical mouse brain regions with 1.7 μ m optical coherence tomography,” Opt. Lett. 40, 4911–4914 (2015).
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C. Kut, K. L. Chaichana, J. Xi, S. M. Raza, X. Ye, E. R. McVeigh, F. J. Rodriguez, A. Quiñones-Hinojosa, and X. Li, “Detection of human brain cancer infiltration ex vivo and in vivo using quantitative optical coherence tomography,” Sci. Transl. Med. 7, 292ra100 (2015).
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D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
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E. Murray, J. H. Cho, D. Goodwin, T. Ku, J. Swaney, S.-Y. Kim, H. Choi, Y.-G. Park, J.-Y. Park, A. Hubbert, M. McCue, S. Vassallo, N. Bakh, M. P. Frosch, V. J. Wedeen, S. Seung, and K. Chung, “Simple, scalable proteomic imaging for high-dimensional profiling of intact systems,” Cell 163, 1500–1514 (2015).
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J. Yi, S. Chen, X. Shu, A. A. Fawzi, and H. F. Zhang, “Human retinal imaging using visible-light optical coherence tomography guided by scanning laser ophthalmoscopy,” Biomed. Opt. Express 6, 3701–3713 (2015).
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A. Pitzschke, B. Lovisa, O. Seydoux, M. Haenggi, M. F. Oertel, M. Zellweger, Y. Tardy, and G. Wagnières, “Optical properties of rabbit brain in the red and near-infrared: changes observed under in vivo, postmortem, frozen, and formalin-fixated conditions,” J. Biomed. Opt. 20, 025006 (2015).
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N. Jährling, K. Becker, B. M. Wegenast-Braun, S. A. Grathwohl, M. Jucker, and H.-U. Dodt, “Cerebral β-amyloidosis in mice investigated by ultramicroscopy,” PLoS ONE 10, e0125418 (2015).
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J. Gallwas, A. Stanchi, N. Ditsch, T. Schwarz, C. Dannecker, S. Mueller, H. Stepp, and U. Mortensen, “Effect of optical clearing agents on optical coherence tomography images of cervical epithelium,” Lasers Med Sci. 30, 517–525 (2015).
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A. d’Esposito, D. Nikitichev, A. Desjardins, S. Walker-Samuel, and M. F. Lythgoe, “Quantification of light attenuation in optically cleared mouse brains,” J. Biomed. Opt. 20, 080503 (2015).
[Crossref]

2014 (7)

W. J. Brown, S. Kim, and A. Wax, “Noise characterization of supercontinuum sources for low-coherence interferometry applications,” J. Opt. Soc. Am. A 31, 2703–2710 (2014).
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K. Vermeer, et al. J. Mo, J. J. A. Weda, H. G. Lemij, and J. F. de Boer, “Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography,” Biomed. Opt. Express 5, 322–337 (2014).
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F. Li, Y. Song, A. Dryer, W. Cogguillo, Y. Berdichevsky, and C. Zhou, “Nondestructive evaluation of progressive neuronal changes in organotypic rat hippocampal slice cultures using ultrahigh-resolution optical coherence microscopy,” Neurophotonics 1, 025002 (2014).
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J. Yi, S. Chen, V. Backman, and H. F. Zhang, “In vivo functional microangiography by visible-light optical coherence tomography,” Biomed. Opt. Express 5, 3603–3612 (2014).
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H. Wang, J. Zhu, and T. Akkin, “Serial optical coherence scanner for large-scale brain imaging at microscopic resolution,” Neuroimage 84, 1007–1017 (2014).
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L. Rizzi, I. Rosset, and M. Roriz-Cruz, “Global epidemiology of dementia: Alzheimer’s and vascular types,” Biomed. Res. Int. 2014, 908915 (2014).
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C. Magnain, J. C. Augustinack, M. Reuter, C. Wachinger, M. P. Frosch, T. Ragan, T. Akkin, V. J. Wedeen, D. A. Boas, and B. Fischl, “Blockface histology with optical coherence tomography: a comparison with Nissl staining,” Neuroimage 84, 524–533 (2014).
[Crossref]

2012 (9)

V. J. Srinivasan, H. Radhakrishnan, J. Y. Jiang, S. Barry, and A. E. Cable, “Optical coherence microscopy for deep tissue imaging of the cerebral cortex with intrinsic contrast,” Opt. Express 20, 2220–2239 (2012).
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T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

A. G. Vlassenko, T. L. Benzinger, and J. C. Morris, “PET amyloid-beta imaging in preclinical Alzheimer’s disease,” Biochim. Biophys. Acta, Mol. Basis Dis. 1822, 370–379 (2012).
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X. Wen, S. L. Jacques, V. V. Tuchin, and D. Zhu, “Enhanced optical clearing of skin in vivo and optical coherence tomography in-depth imaging,” J. Biomed. Opt. 17, 066022 (2012).
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C. J. Goergen, H. Radhakrishnan, S. Sakadžić, E. T. Mandeville, E. H. Lo, D. E. Sosnovik, and V. J. Srinivasan, “Optical coherence tractography using intrinsic contrast,” Opt. Lett. 37, 3882–3884 (2012).
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Y. Z. Wadghiri, D. M. Hoang, T. Wisniewski, and E. M. Sigurdsson, “In vivo magnetic resonance imaging of amyloid-β plaques in mice,” Amyloid Proteins: Methods and Protocols 492, 435–451 (2012).
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K. A. Johnson, N. C. Fox, R. A. Sperling, and W. E. Klunk, “Brain imaging in Alzheimer disease,” Cold Spring Harb. Perspect. Med. 2, a006213 (2012).
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W. Choi, B. Baumann, E. A. Swanson, and J. G. Fujimoto, “Extracting and compensating dispersion mismatch in ultrahigh-resolution Fourier domain OCT imaging of the retina,” Opt. Express 20, 25357–25368 (2012).
[Crossref] [PubMed]

J. Yi and V. Backman, “Imaging a full set of optical scattering properties of biological tissue by inverse spectroscopic optical coherence tomography,” Opt. Lett. 37, 4443–4445 (2012).
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2011 (4)

C. Humpel, “Identifying and validating biomarkers for Alzheimer’s disease,” Trends Biotechnol. 29, 26–32 (2011).
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H. Wang, A. J. Black, J. Zhu, T. W. Stigen, M. K. Al-Qaisi, T. I. Netoff, A. Abosch, and T. Akkin, “Reconstructing micrometer-scale fiber pathways in the brain: multi-contrast optical coherence tomography based tractography,” Neuroimage 58, 984–992 (2011).
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J. Binding, J. B. Arous, J.-F. Léger, S. Gigan, C. Boccara, and L. Bourdieu, “Brain refractive index measured in vivo with high-NA defocus-corrected full-field OCT and consequences for two-photon microscopy,” Opt. Express 19, 4833–4847 (2011).
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F. E. Robles, C. Wilson, G. Grant, and A. Wax, “Molecular imaging true-colour spectroscopic optical coherence tomography,” Nature Photonics 5, 744–747 (2011).
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2010 (2)

J. Dong, R. Revilla-Sanchez, S. Moss, and P. G. Haydon, “Multiphoton in vivo imaging of amyloid in animal models of Alzheimer’s disease,” Neuropharmacology 59, 268–275 (2010).
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J. D. Johansson, “Spectroscopic method for determination of the absorption coefficient in brain tissue,” J. Biomed. Opt. 15, 057005 (2010).
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2009 (2)

A. J. Howie and D. B. Brewer, “Optical properties of amyloid stained by Congo red: history and mechanisms,” Micron 40, 285–301 (2009).
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B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med. 15, 1219–1223 (2009).
[Crossref]

2007 (1)

E. M. Hillman, “Optical brain imaging in vivo: techniques and applications from animal to man,” J. Biomed. Opt. 12, 051402 (2007).
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2006 (1)

S. Gebhart, W. Lin, and A. Mahadevan-Jansen, “In vitro determination of normal and neoplastic human brain tissue optical properties using inverse adding-doubling,” Phys. Med. Biol. 51, 2011 (2006).
[Crossref] [PubMed]

2005 (2)

P. Babu, D. Chopra, T. G. Row, and U. Maitra, “Micellar aggregates and hydrogels from phosphonobile salts,” Org. Biomol. Chem 3, 3695–3700 (2005).
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K. Bizheva, A. Unterhuber, B. Hermann, B. Považay, H. Sattmann, A. F. Fercher, W. Drexler, M. Preusser, H. Budka, A. Stingl, and T. Le, “Imaging ex vivo healthy and pathological human brain tissue with ultra-high-resolution optical coherence tomography,” J. Biomed. Opt. 10, 011006 (2005).
[Crossref]

2004 (1)

2002 (1)

2000 (3)

1999 (1)

1995 (1)

B. Hyman, H. West, G. Rebeck, S. Buldyrev, R. Mantegna, M. Ukleja, S. Havlin, and H. Stanley, “Quantitative analysis of senile plaques in Alzheimer disease: observation of log-normal size distribution and molecular epidemiology of differences associated with apolipoprotein E genotype and trisomy 21 (Down syndrome),” Proc. Natl. Acad. Sci. U.S.A. 92, 3586–3590 (1995).
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Abosch, A.

H. Wang, A. J. Black, J. Zhu, T. W. Stigen, M. K. Al-Qaisi, T. I. Netoff, A. Abosch, and T. Akkin, “Reconstructing micrometer-scale fiber pathways in the brain: multi-contrast optical coherence tomography based tractography,” Neuroimage 58, 984–992 (2011).
[Crossref] [PubMed]

Aisen, P.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
[Crossref] [PubMed]

Akkin, T.

H. Wang, T. Akkin, C. Magnain, R. Wang, J. Dubb, W. J. Kostis, M. A. Yaseen, A. Cramer, S. Sakadžić, and D. Boas, “Polarization sensitive optical coherence microscopy for brain imaging,” Opt. Lett. 41, 2213–2216 (2016).
[Crossref] [PubMed]

H. Wang, J. Zhu, and T. Akkin, “Serial optical coherence scanner for large-scale brain imaging at microscopic resolution,” Neuroimage 84, 1007–1017 (2014).
[Crossref]

C. Magnain, J. C. Augustinack, M. Reuter, C. Wachinger, M. P. Frosch, T. Ragan, T. Akkin, V. J. Wedeen, D. A. Boas, and B. Fischl, “Blockface histology with optical coherence tomography: a comparison with Nissl staining,” Neuroimage 84, 524–533 (2014).
[Crossref]

H. Wang, A. J. Black, J. Zhu, T. W. Stigen, M. K. Al-Qaisi, T. I. Netoff, A. Abosch, and T. Akkin, “Reconstructing micrometer-scale fiber pathways in the brain: multi-contrast optical coherence tomography based tractography,” Neuroimage 58, 984–992 (2011).
[Crossref] [PubMed]

Alexander, L

L. van Manen, P. L. Stegehuis, A. Fariña-Sarasqueta, L. M. de Haan, J. Eggermont, B. A. Bonsing, H. Morreau, B. P. Lelieveldt, C. J. van de Velde, D. J. Vahrmeijer, L Alexander, and J. S. Mieog, “Validation of full-field optical coherence tomography in distinguishing malignant and benign tissue in resected pancreatic cancer specimens,” PLoS ONE 12, e0175862 (2017).
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Al-Qaisi, M. K.

H. Wang, A. J. Black, J. Zhu, T. W. Stigen, M. K. Al-Qaisi, T. I. Netoff, A. Abosch, and T. Akkin, “Reconstructing micrometer-scale fiber pathways in the brain: multi-contrast optical coherence tomography based tractography,” Neuroimage 58, 984–992 (2011).
[Crossref] [PubMed]

Andrieu, S.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
[Crossref] [PubMed]

Apolonski, A.

Arous, J. B.

Augustin, M.

B. Baumann, A. Woehrer, G. Ricken, M. Augustin, C. Mitter, M. Pircher, G. G. Kovacs, and C. K. Hitzenberger, “Visualization of neuritic plaques in Alzheimer’s disease by polarization-sensitive optical coherence microscopy,” Sci. Rep. 7, 43477 (2017).
[Crossref]

A. Lichtenegger, D. J. Harper, M. Augustin, P. Eugui, S. Fialová, A. Woehrer, C. K. Hitzenberger, and B. Baumann, “Visible light spectral domain optical coherence microscopy system for ex vivo imaging,” Proc. SPIE 10051, 1005103 (2017).
[Crossref]

Augustinack, J. C.

C. Magnain, J. C. Augustinack, M. Reuter, C. Wachinger, M. P. Frosch, T. Ragan, T. Akkin, V. J. Wedeen, D. A. Boas, and B. Fischl, “Blockface histology with optical coherence tomography: a comparison with Nissl staining,” Neuroimage 84, 524–533 (2014).
[Crossref]

Azaripour, A.

A. Azaripour, T. Lagerweij, C. Scharfbillig, A. E. Jadczak, B. Willershausen, and C. J. Van Noorden, “A survey of clearing techniques for 3D imaging of tissues with special reference to connective tissue,” Prog. Histochem. Cytochem. 51, 9–23 (2016).
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Babu, P.

P. Babu, D. Chopra, T. G. Row, and U. Maitra, “Micellar aggregates and hydrogels from phosphonobile salts,” Org. Biomol. Chem 3, 3695–3700 (2005).
[Crossref] [PubMed]

Backman, V.

Bakardjian, H.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
[Crossref] [PubMed]

Bakh, N.

E. Murray, J. H. Cho, D. Goodwin, T. Ku, J. Swaney, S.-Y. Kim, H. Choi, Y.-G. Park, J.-Y. Park, A. Hubbert, M. McCue, S. Vassallo, N. Bakh, M. P. Frosch, V. J. Wedeen, S. Seung, and K. Chung, “Simple, scalable proteomic imaging for high-dimensional profiling of intact systems,” Cell 163, 1500–1514 (2015).
[Crossref] [PubMed]

Bang, O.

M. Maria, I. Gonzalo, M. Bondu, R. Engelsholm, T. Feuchter, P. Moselund, L. Leick, O. Bang, and A. Podoleanu, “A comparative study of noise in supercontinuum light sources for ultra-high resolution optical coherence tomography,” Proc. SPIE 10056, 100560O (2017).

Barrick, J.

Barry, S.

Bartlett, L. A.

B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med. 15, 1219–1223 (2009).
[Crossref]

Baumann, B.

B. Baumann, A. Woehrer, G. Ricken, M. Augustin, C. Mitter, M. Pircher, G. G. Kovacs, and C. K. Hitzenberger, “Visualization of neuritic plaques in Alzheimer’s disease by polarization-sensitive optical coherence microscopy,” Sci. Rep. 7, 43477 (2017).
[Crossref]

A. Lichtenegger, D. J. Harper, M. Augustin, P. Eugui, S. Fialová, A. Woehrer, C. K. Hitzenberger, and B. Baumann, “Visible light spectral domain optical coherence microscopy system for ex vivo imaging,” Proc. SPIE 10051, 1005103 (2017).
[Crossref]

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

Becker, K.

N. Jährling, K. Becker, B. M. Wegenast-Braun, S. A. Grathwohl, M. Jucker, and H.-U. Dodt, “Cerebral β-amyloidosis in mice investigated by ultramicroscopy,” PLoS ONE 10, e0125418 (2015).
[Crossref]

Benali, H.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
[Crossref] [PubMed]

Benzinger, T. L.

A. G. Vlassenko, T. L. Benzinger, and J. C. Morris, “PET amyloid-beta imaging in preclinical Alzheimer’s disease,” Biochim. Biophys. Acta, Mol. Basis Dis. 1822, 370–379 (2012).
[Crossref]

Berclaz, C.

T. Bolmont, A. Bouwens, C. Pache, M. Dimitrov, C. Berclaz, M. Villiger, B. M. Wegenast-Braun, T. Lasser, and P. C. Fraering, “Label-free imaging of cerebral β-amyloidosis with extended-focus optical coherence microscopy,” J. Neurosci. 32, 14548–14556 (2012).
[Crossref] [PubMed]

Berdichevsky, Y.

F. Li, Y. Song, A. Dryer, W. Cogguillo, Y. Berdichevsky, and C. Zhou, “Nondestructive evaluation of progressive neuronal changes in organotypic rat hippocampal slice cultures using ultrahigh-resolution optical coherence microscopy,” Neurophotonics 1, 025002 (2014).
[Crossref]

Bernucci, M.

Bertram, L.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
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Bettayeb, K.

T. Liebmann, N. Renier, K. Bettayeb, P. Greengard, M. Tessier-Lavigne, and M. Flajolet, “Three-dimensional study of Alzheimer’s disease hallmarks using the iDISCO clearing method,” Cell Rep. 16, 1138–1152 (2016).
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Bevilacqua, F.

Binding, J.

Bizheva, K.

K. Bizheva, A. Unterhuber, B. Hermann, B. Považay, H. Sattmann, A. F. Fercher, W. Drexler, M. Preusser, H. Budka, A. Stingl, and T. Le, “Imaging ex vivo healthy and pathological human brain tissue with ultra-high-resolution optical coherence tomography,” J. Biomed. Opt. 10, 011006 (2005).
[Crossref]

B. Povazay, K. Bizheva, A. Unterhuber, B. Hermann, H. Sattmann, A. Fercher, W. Drexler, A. Apolonski, W. Wadsworth, J. Knight, P. S. J. Russell, M. Vetterlein, and E. Scherzer, “Submicrometer axial resolution optical coherence tomography,” Opt. Lett. 27, 1800–1802 (2002).
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Black, A. J.

H. Wang, A. J. Black, J. Zhu, T. W. Stigen, M. K. Al-Qaisi, T. I. Netoff, A. Abosch, and T. Akkin, “Reconstructing micrometer-scale fiber pathways in the brain: multi-contrast optical coherence tomography based tractography,” Neuroimage 58, 984–992 (2011).
[Crossref] [PubMed]

Blanco, T.

R. P. McNabb, T. Blanco, H. M. Bomze, H. C. Tseng, D. R. Saban, J. A. Izatt, and A. N. Kuo, “Method for single illumination source combined optical coherence tomography and fluorescence imaging of fluorescently labeled ocular structures in transgenic mice,” Exp. Eye Res. 151, 68–74 (2016).
[Crossref] [PubMed]

Blennow, K.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen, S. Andrieu, H. Bakardjian, H. Benali, L. Bertram, K. Blennow, K. Broich, E. Cavedo, S. Crutch, C. Dartigues, Jean-Fracois, Duyckaerts, S. Epdelbaum, G. B. Frisoni, S. Gauthier, R. Genthon, A. A. Gouw, M.-O. Habert, D. M. Holtzman, M. Kivipelto, S. Lista, J.-L. Molinuevo, S. E. O’Bryant, G. D. Rabinovivi, C. Rowe, S. Salloway, L. S. Schneider, R. Sperling, M. Teichmann, M. C. Carrillo, J. Cummings, and C. R. Jack, “Preclinical Alzheimer’s disease: definition, natural history, and diagnostic criteria,” Alzheimers Dement 12, 292–323 (2016).
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Blinne, A.

S. Fuchs, C. Rödel, A. Blinne, U. Zastrau, M. Wünsche, V. Hilbert, L. Glaser, J. Viefhaus, E. Frumker, P. Corkum, E. Foerster, and G. G. Paulus, “Nanometer resolution optical coherence tomography using broad bandwidth XUV and soft x-ray radiation,” Sci. Rep 6, 20658 (2016).
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B. Ghafaryasl, K. A. Vermeer, J. F. de Boer, M. E. van Velthoven, and L. J. van Vliet, “Noise-adaptive attenuation coefficient estimation in spectral domain optical coherence tomography data,” Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium, pp. 706–709 (2016)

S. Boppart, W. Drexler, U. Morgner, F. Kirtner, and J. Fujimoto, “Ultrahigh resolution and spectroscopic oct imaging of cellular morphology and function,” in “Proceedings of Inter-Institute Workshop on In Vivo Optical Imaging at the National Institutes of Health,” (1999).

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Figures (10)

Fig. 1
Fig. 1

The spectral domain visible light OCM system. (a) Sketch of the system with BF (Bandpass Filter), BS (Beam Splitter), C (Collimator), DC (Dispersion Compensation), DG (Diffraction Grating), F (Filter), FG (Frame Grabber), L (Lens), LSC (Line Scan Camera), M (Mirror), MEMS (Microelectromechanical Mirror), MEMS C (MEMS Control), NDF (Neutral Density Filter), O (Objective), P (Polarizer), PC (Computer), RM (Reference Mirror), SLS (Supercontinuum Light Source). (b) Image of the sample arm. (c) Image of the spectrometer.

Fig. 2
Fig. 2

Specifications of the visible light OCM system, (a) The spectrum as measured by the spectrometer with central wavelength λc = 555 nm and full-width at half maximum Δλt = 156 nm and the quantum efficiency (dotted line) of the line scan camera (data were taken from the Basler sprint user’s manual 2015 [34]). (b) Axial resolution (Δz = 1.2 μm) measurement in the first 500 μm. (c) The axial resolution over the whole depth range. (d) Transversal resolution (Δx = 2 μm) measurement with the US Air Force 1951 resolution test target. (e) Roll-off measurement at six depth positions.

Fig. 3
Fig. 3

Workflow for imaging mouse brains using OCM and the post processing pipeline. (a) The first step was to extract the mouse brain, which was then fixed and clearing was performed. Imaging of the optically cleared brains was conducted and the results were analyzed. (b) Processing pipeline for attenuation en-face maps and spectroscopic OCT images. Both attenuation coefficients were calculated for 3D OCM intensity data and en-face maps were computed. For each A-scan of one B-scan the original spectrum was filtered by the chosen number of Gaussian windows to create the spectroscopic B-scans which could be combined to a spectroscopic B-scan.

Fig. 4
Fig. 4

OCM imaging of healthy human brain. (a) Healthy brain tissue, where a black square indicates the scanning area and the corresponding histological image including a region of white matter (WM) and grey matter (GM). (b) Scatter plot with intensity values vs. global attenuation coefficients for GM and WM region. (c) Average projection en-face image generated over the first 100 μm below the surface. (d) Rendering of 3D OCM intensity image (inverted grey scale) and a B-scan showing a tissue region including GM and WM. (e) Local attenuation map generated over the first 100 μm below the surface.

Fig. 5
Fig. 5

OCM imaging in the brain of a human AD patient. (a) Photograph of the AD brain tissue with the scanned area marked with a black square. (b) Rendering of 3D OCM intensity image (inverted grey scale) with amyloid-beta plaques marked with red arrows. (c) Histological example image of a neuritic plaque stained with Congo red. (d) Zoom in a plaque-rich region. (e) Mean intensity projection en-face image of AD tissue over a depth of 200 μm (inverted grey scale). (f) Spectroscopic B-scan of AD brain tissue using three Gaussian windows. (g) Box plots of signal intensity and local attenuation coefficients for GM, WM and plaques (P). Significant differences (p < 0.001) are indicated by asterisks.

Fig. 6
Fig. 6

Spectroscopic evaluation of AD brain tissue. (a) The seven Gaussian windows used for the spectroscopic analysis. (b) Intensity against wavelength for WM, GM and plaques with the wavelength dependent standard deviations of the data represented by shaded bands. (c) Local attenuation coefficients against wavelength for WM, GM and plaques with the wavelength dependent standard deviations of the data represented by shaded bands. (d)-(g) B-scans of the same region as seen by different wavelength regions, (d) λ4 = 560 nm, (e) λ5 = 580 nm, (f) λ6 = 600 nm, (g) λ7 = 620 nm. Red arrows indicate the plaques and the green arrows mark the plaques where the values were extracted from.

Fig. 7
Fig. 7

Evaluation of measurements of Congo red stained AD brain tissue. (a) Image of the Congo red stained brain tissue, where the scanning area is indicated by a white square. The insert shows a micrograph of the corresponding histology. (b) 3D OCM image including plaque regions indicated by red arrows. (c) Plots showing the intensity and the local attenuation against the three wavelength regions with the wavelength dependent standard deviations represented by shaded bands. (d) Combined spectroscopic OCM image with three Gaussian windows. Plaques are indicated by black arrows. (e) Spectroscopic OCM image computed using two Gaussian windows. (f) Intensity against attenuation plot for the three wavelength regions with the respective wavelength dependent standard deviations.

Fig. 8
Fig. 8

Investigating the cleared mouse brain. (a) Mouse brain before optical clearing. (b) Mouse brain after 1 day in thermal clearing solution. (c) Mouse brain after 2 days in thermal clearing solution. The black square indicates the area scanned by OCM. (d) Mean OCM amplitude extracted from a region of 100 μm × 100 μm beneath the surface versus clearing steps with the standard deviations of the data represented by shaded bands. (e) OCM B-scan structural image before clearing with an A-scan and the fitted global attenuation line. (f) OCM image after one day in Thermal Clearing Solution and zoom into a structural detail (potentially a vessel) in a deeper tissue area. (g) Mean global attenuation in a region of 100 μm × 100 μm beneath the surface versus clearing steps with the standard deviations of the data represented by shaded bands. After imaging the values were normalized with respect to the measurement before performing the optical clearing.

Fig. 9
Fig. 9

Boxplots showing the OCM signal amplitude values at various time points during the optical tissue clearing process. The trend line was computed from the mean values at each time point. The background amplitude is shown as a dashed black line for reference.

Fig. 10
Fig. 10

Investigating a cleared AD mouse brain. (a) Mouse brain before optical clearing, where the scanning area is indicated by a black square. (b) Mouse brain after 60 minutes of clearing. (c) Cleared and Congo red stained AD mouse brain. (d) Spectroscopic image (three Gaussian windows) of Congo red stained AD mouse brain tissue. (e) OCM B-scan of mouse brain tissue before optical clearing. (f) OCM B-scan of mouse brain tissue after performing optical clearing. (g) OCM B-scan image of Congo red stained AD mouse brain. (h) Red channel from the two Gaussian windows. (i) Green channel from the two Gaussian windows.

Tables (1)

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Table 1 Parameters for spectroscopic imaging approaches.

Equations (5)

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Δ z = 2 ln ( 2 ) π λ i 2 Δ λ i .
Δ λ 1 = Δ λ t 1 + 1 λ 1 2 ( i = 2 N λ i 2 )
Δ λ i + 1 = λ i + 1 2 λ i 2 Δ λ i , i = 1 N 1
I ( z ) = I 0 exp ( μ t z )
μ t [ i ] = 1 2 Δ log ( 1 + I [ i ] i + 1 N I [ i ] ) .

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