Abstract

OCT has been demonstrated as an efficient imaging modality in various biomedical and clinical applications. However, there is a missing link with respect to the source of contrast between OCT and other modern imaging modalities, no quantitative comparison has been demonstrated between them, yet. We evaluated, to our knowledge, for the first time in vivo OCT measurement of rat brain with our previously proposed forward imaging method by both qualitatively and quantitatively correlating OCT with the corresponding T1-weighted and T2-weighted magnetic resonance images, fiber density map (FDM), and two types of histology staining (cresyl violet and acetylcholinesterase AchE), respectively. Brain anatomical structures were identified and compared across OCT, MRI and histology imaging modalities. Noticeable resemblances corresponding to certain anatomical structures were found between OCT and other image profiles. Correlation was quantitatively assessed by estimating correlation coefficient (R) and mutual information (MI). Results show that the 1-D OCT measurements in regards to the intensity profile and estimated attenuation factor, do not have profound linear correlation with the other image modalities suggested from correlation coefficient estimation. However, findings in mutual information analysis demonstrate that there are markedly high MI values in OCT-MRI signals.

© 2017 Optical Society of America

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2016 (1)

R. Sparks, G. Zombori, R. Rodionov, M. Nowell, S. B. Vos, M. A. Zuluaga, B. Diehl, T. Wehner, A. Miserocchi, A. W. McEvoy, J. S. Duncan, and S. Ourselin, “Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment,” Int. J. Comput. Assist. Radiol. Surg. 161–14 (2016).

2015 (2)

I. Gudmundsdottir, P. Adamson, C. Gray, J. C. Spratt, M. W. Behan, P. Henriksen, D. E. Newby, N. Mills, N. G. Uren, and N. L. Cruden, “Optical coherence tomography versus intravascular ultrasound to evaluate stent implantation in patients with calcific coronary artery disease,” Open Heart 2(1) 225 (2015).
[Crossref]

Z. Eaton-Rosen, A. Melbourne, E. Orasanu, M. J. Cardoso, M. Modat, A. Bainbridge, G. S. Kendall, N. J. Robertson, N. Marlow, and S. Ourselin, “Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI,” NeuroImage 111, 580–589 (2015).
[Crossref] [PubMed]

2014 (2)

M. Krzywinski and N. Altman, “Points of significance: Visualizing samples with box plots,” Nat. Meth. 11(2), 119–120 (2014).
[Crossref]

Y. Xie, N. Martini, C. Hassler, R. Kirch, A. Seifert, T. Stieglitz, and U. G. Hofmann, “In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography,” Front Neuroeng 734 (2014).
[Crossref] [PubMed]

2013 (5)

Y. Xie, T. Bonin, S. Löffler, G. Hüttmann, V. Tronnier, and U. G. Hofmann, “Coronal in vivo forward-imaging of rat brain morphology with an ultra-small optical coherence tomography fiber probe,” Phys. Med. Biol. 58(3), 555–568 (2013).
[Crossref] [PubMed]

J. D. Johansson and K. Wårdell, “Intracerebral quantitative chromophore estimation from reflectance spectra captured during deep brain stimulation implantation,” J. Biophotonics 6(5), 435–445 (2013).
[Crossref]

L.-A. Harsan, C. Dávidb, M. Reiserta, S. Schnella, J. Henniga, D. von Elverfeldta, and J. F. Staigerd, “Mapping remodeling of thalamocortical projections in the living reeler mouse brain by diffusion tractography,” Proceedings of the National Academy of Sciences 110(19), E1797–E1806 (2013).
[Crossref]

R. John, S. G. Adie, E. J. Chaney, M. Marjanovic, K. V. Tangella, and S. A. Boppart, “Three-dimensional optical coherence tomography for optical biopsy of lymph nodes and assessment of metastatic disease,” Ann Surg Oncol 20(11), 3685–3693 (2013).
[Crossref]

T.-H. Tsai, B. Potsaid, Y. K. Tao, V. Jayaraman, J. Jiang, P. J. S. Heim, M. F. Kraus, C. Zhou, J. Hornegger, H. Mashimo, A. E. Cable, and J. G. Fujimoto, “Ultrahigh speed endoscopic optical coherence tomography using micromotor imaging catheter and vcsel technology,” Biomed. Opt. Express 4(7), 1119–1132 (2013).
[Crossref] [PubMed]

2012 (3)

2011 (3)

M. Reisert, I. Mader, C. Anastasopoulos, M. Weigel, S. Schnell, and V. Kiselev, “Global fiber reconstruction becomes practical,” NeuroImage 54(2), 955–962 (2011).
[Crossref]

Y.-S. Jeong, M. K. Jeong, and O. A. Omitaomu, “Weighted dynamic time warping for time series classification,” Pattern. Recogn. 44(9), 2231–2240 (2011).
[Crossref]

M. Khalil, C. Langkammer, S. Ropele, K. Petrovic, M. Wallner-Blazek, M. Loitfelder, M. Jehna, G. Bachmaier, R. Schmidt, C. Enzinger, S. Fuchs, and F. Fazekas, “Determinants of brain iron in multiple sclerosis: A quantitative 3T MRI study,” Neurology 77(18), 1691–1697 (2011).
[Crossref] [PubMed]

2010 (4)

C. A. Paul, B. Beltz, and J. Berger-Sweeney, “Staining for acetylcholinesterase in brain sections,” Cold Spring Harbor Protocols 2010, 8 (2010).

L.-A. Harsan, D. Paul, S. Schnell, B. W. Kreher, J. Hennig, J. F. Staiger, and D. von Elverfeldt, “In vivo diffusion tensor magnetic resonance imaging and fiber tracking of the mouse brain,” NMR Biomed 23(7), 884–896 (2010).
[Crossref] [PubMed]

G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
[Crossref] [PubMed]

S. Hemm and K. Wårdell, “Stereotactic implantation of deep brain stimulation electrodes: a review of technical systems, methods and emerging tools,” Med. Biol. Eng. Comput. 48(7), 611–624 (2010).
[Crossref] [PubMed]

2009 (1)

D. Paul, M. Zaitsev, L. Harsan, A. Kurutsch, D. N. Splitthoff, F. Hennel, M. Choli, and D. von Elverfeldt, “Implementation and application of PSF-based EPI distortion correction to high field animal imaging,” Int. J. Biomed. Imaging 2009, 946271 (2009).
[Crossref]

2008 (1)

2007 (2)

R. Kuranov, V. Sapozhnikova, D. Prough, I. Cicenaite, and R. Esenaliev, “Correlation between optical coherence tomography images and histology of pigskin,” Appl. Opt. 46(10), 1782–1786 (2007).
[Crossref] [PubMed]

W. D. Rooney, G. Johnson, X. Li, E. R. Cohen, S.-G. Kim, K. Ugurbil, and C. S. Springer, “Magnetic field and tissue dependencies of human brain longitudinal 1H2O relaxation in vivo,” Magn. Reson. Med. 57(2), 308–318 (2007).
[Crossref] [PubMed]

2006 (2)

L. T. Holly, J. D. Schwender, D. P. Rouben, and K. T. Foley, “Minimally invasive transforaminal lumbar interbody fusion: indications, technique, and complications,” Neurosurg. Focus 20(3), 1–5 (2006).
[Crossref]

S. W. Jeon, M. A. Shure, K. B. Baker, D. Huang, A. M. Rollins, A. Chahlavi, and A. R. Rezai, “A feasibility study of optical coherence tomography for guiding deep brain probes,” J. Neurosci. Methods 154(1–2), 96–101 (2006).
[Crossref] [PubMed]

2005 (1)

E. Keogh and C. A. Ratanamahatana, “Exact indexing of dynamic time warping,” Knowl. Inf. Syst. 7(3), 358–386 (2005).
[Crossref]

2004 (1)

2003 (4)

M. Gloesmann, B. Hermann, C. Schubert, H. Sattmann, P. K. Ahnelt, and W. Drexler, “Histologic correlation of pig retina radial stratification with ultrahigh-resolution optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 44(4), 1696–1703 (2003).
[Crossref] [PubMed]

J. G. Fujimoto, “Optical coherence tomography for ultrahigh resolution in vivo imaging,” Nat Biotech 21(11), 1361–1367 (2003).
[Crossref]

A. I. Kholodnykh, I. Y. Petrova, M. Motamedi, and R. O. Esenaliev, “Accurate measurement of total attenuation coefficient of thin tissue with optical coherence tomography,” IEEE J. Sel. Top. Quantum Electron. 9(2), 210–221 (2003).
[Crossref]

T. G. van Leeuwen, D. J. Faber, and M. C. Aalders, “Measurement of the axial point spread function in scattering media using single-mode fiber-based optical coherence tomography,” IEEE J. Sel. Top. Quantum Electron. 9(2), 227–233 (2003).
[Crossref]

1999 (1)

M. A. Jacobs, J. P. Windham, H. Soltanian-Zadeh, D. J. Peck, and R. A. Knight, “Registration and warping of magnetic resonance images to histological sections,” Med. Phys. 26(8), 1568–1578 (1999).
[Crossref] [PubMed]

1997 (2)

F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens, “Multimodality image registration by maximization of mutual information,” IEEE Trans. Med. Imaging 16(2), 187–198 (1997).
[Crossref] [PubMed]

G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, “In vivo endoscopic optical biopsy with optical coherence tomography,” Science 276(5321), 2037–2039 (1997).
[Crossref] [PubMed]

1996 (1)

J. V. Rosenfeld, “Minimally invasive neurosurgery,” Aust N Z J Surg 66(8), 553–559 (1996).
[Crossref] [PubMed]

1991 (2)

C. K. Hitzenberger, “Optical measurement of the axial eye length by laser doppler interferometry,” Invest Ophthalmol Vis Sci 32, 616–624 (1991).
[PubMed]

D. Huang, E. Swanson, C. Lin, J. Schuman, W. Stinson, W. Chang, M. Hee, T. Flotte, K. Gregory, C. Puliafito, and et al., “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

1981 (1)

C. S. Myers and L. R. Rabiner, “A comparative study of several dynamic time-warping algorithms for connected-word recognition,” Bell System Technical Journal 60(7), 1389–1409 (1981).
[Crossref]

Aalders, M. C.

T. G. van Leeuwen, D. J. Faber, and M. C. Aalders, “Measurement of the axial point spread function in scattering media using single-mode fiber-based optical coherence tomography,” IEEE J. Sel. Top. Quantum Electron. 9(2), 227–233 (2003).
[Crossref]

Adamson, P.

I. Gudmundsdottir, P. Adamson, C. Gray, J. C. Spratt, M. W. Behan, P. Henriksen, D. E. Newby, N. Mills, N. G. Uren, and N. L. Cruden, “Optical coherence tomography versus intravascular ultrasound to evaluate stent implantation in patients with calcific coronary artery disease,” Open Heart 2(1) 225 (2015).
[Crossref]

Adie, S. G.

R. John, S. G. Adie, E. J. Chaney, M. Marjanovic, K. V. Tangella, and S. A. Boppart, “Three-dimensional optical coherence tomography for optical biopsy of lymph nodes and assessment of metastatic disease,” Ann Surg Oncol 20(11), 3685–3693 (2013).
[Crossref]

Aguirre, A.

W. Drexler, Y. Chen, A. Aguirre, B. Považay, A. Unterhuber, and J. G. Fujimoto, Optical coherence tomography: Technology and applications for neuroimaging (Springer, 2008), chap. 8: Ultrahigh resolution optical coherence tomography, pp. 239–279.
[Crossref]

Ahnelt, P. K.

M. Gloesmann, B. Hermann, C. Schubert, H. Sattmann, P. K. Ahnelt, and W. Drexler, “Histologic correlation of pig retina radial stratification with ultrahigh-resolution optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 44(4), 1696–1703 (2003).
[Crossref] [PubMed]

Altman, N.

M. Krzywinski and N. Altman, “Points of significance: Visualizing samples with box plots,” Nat. Meth. 11(2), 119–120 (2014).
[Crossref]

Anastasopoulos, C.

M. Reisert, I. Mader, C. Anastasopoulos, M. Weigel, S. Schnell, and V. Kiselev, “Global fiber reconstruction becomes practical,” NeuroImage 54(2), 955–962 (2011).
[Crossref]

Bachmaier, G.

M. Khalil, C. Langkammer, S. Ropele, K. Petrovic, M. Wallner-Blazek, M. Loitfelder, M. Jehna, G. Bachmaier, R. Schmidt, C. Enzinger, S. Fuchs, and F. Fazekas, “Determinants of brain iron in multiple sclerosis: A quantitative 3T MRI study,” Neurology 77(18), 1691–1697 (2011).
[Crossref] [PubMed]

Bainbridge, A.

Z. Eaton-Rosen, A. Melbourne, E. Orasanu, M. J. Cardoso, M. Modat, A. Bainbridge, G. S. Kendall, N. J. Robertson, N. Marlow, and S. Ourselin, “Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI,” NeuroImage 111, 580–589 (2015).
[Crossref] [PubMed]

Baker, K. B.

S. W. Jeon, M. A. Shure, K. B. Baker, D. Huang, A. M. Rollins, A. Chahlavi, and A. R. Rezai, “A feasibility study of optical coherence tomography for guiding deep brain probes,” J. Neurosci. Methods 154(1–2), 96–101 (2006).
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F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens, “Multimodality image registration by maximization of mutual information,” IEEE Trans. Med. Imaging 16(2), 187–198 (1997).
[Crossref] [PubMed]

Swanson, E.

D. Huang, E. Swanson, C. Lin, J. Schuman, W. Stinson, W. Chang, M. Hee, T. Flotte, K. Gregory, C. Puliafito, and et al., “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Tangella, K. V.

R. John, S. G. Adie, E. J. Chaney, M. Marjanovic, K. V. Tangella, and S. A. Boppart, “Three-dimensional optical coherence tomography for optical biopsy of lymph nodes and assessment of metastatic disease,” Ann Surg Oncol 20(11), 3685–3693 (2013).
[Crossref]

Tao, Y. K.

Tearney, G. J.

C. I. Unglert, W. C. Warger, J. Hostens, E. Namati, R. Birngruber, B. E. Bouma, and G. J. Tearney, “Validation of two-dimensional and three-dimensional measurements of subpleural alveolar size parameters by optical coherence tomography,” J. Biomed. Opt. 17(12), 126015 (2012).
[Crossref] [PubMed]

G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
[Crossref] [PubMed]

G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, “In vivo endoscopic optical biopsy with optical coherence tomography,” Science 276(5321), 2037–2039 (1997).
[Crossref] [PubMed]

Thomas, J. A.

T. M. Cover and J. A. Thomas, Elements of information theoryJohn Wiley & Sons, 2012.

Tronnier, V.

Y. Xie, T. Bonin, S. Löffler, G. Hüttmann, V. Tronnier, and U. G. Hofmann, “Coronal in vivo forward-imaging of rat brain morphology with an ultra-small optical coherence tomography fiber probe,” Phys. Med. Biol. 58(3), 555–568 (2013).
[Crossref] [PubMed]

Tsai, T.-H.

Ugurbil, K.

W. D. Rooney, G. Johnson, X. Li, E. R. Cohen, S.-G. Kim, K. Ugurbil, and C. S. Springer, “Magnetic field and tissue dependencies of human brain longitudinal 1H2O relaxation in vivo,” Magn. Reson. Med. 57(2), 308–318 (2007).
[Crossref] [PubMed]

Unglert, C. I.

C. I. Unglert, W. C. Warger, J. Hostens, E. Namati, R. Birngruber, B. E. Bouma, and G. J. Tearney, “Validation of two-dimensional and three-dimensional measurements of subpleural alveolar size parameters by optical coherence tomography,” J. Biomed. Opt. 17(12), 126015 (2012).
[Crossref] [PubMed]

Unterhuber, A.

W. Drexler, Y. Chen, A. Aguirre, B. Považay, A. Unterhuber, and J. G. Fujimoto, Optical coherence tomography: Technology and applications for neuroimaging (Springer, 2008), chap. 8: Ultrahigh resolution optical coherence tomography, pp. 239–279.
[Crossref]

Uren, N. G.

I. Gudmundsdottir, P. Adamson, C. Gray, J. C. Spratt, M. W. Behan, P. Henriksen, D. E. Newby, N. Mills, N. G. Uren, and N. L. Cruden, “Optical coherence tomography versus intravascular ultrasound to evaluate stent implantation in patients with calcific coronary artery disease,” Open Heart 2(1) 225 (2015).
[Crossref]

van der Steen, A. F. W.

G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
[Crossref] [PubMed]

van Leenders, G. L. J. H.

G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
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T. G. van Leeuwen, D. J. Faber, and M. C. Aalders, “Measurement of the axial point spread function in scattering media using single-mode fiber-based optical coherence tomography,” IEEE J. Sel. Top. Quantum Electron. 9(2), 227–233 (2003).
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G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
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G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
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F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens, “Multimodality image registration by maximization of mutual information,” IEEE Trans. Med. Imaging 16(2), 187–198 (1997).
[Crossref] [PubMed]

von Elverfeldt, D.

L.-A. Harsan, D. Paul, S. Schnell, B. W. Kreher, J. Hennig, J. F. Staiger, and D. von Elverfeldt, “In vivo diffusion tensor magnetic resonance imaging and fiber tracking of the mouse brain,” NMR Biomed 23(7), 884–896 (2010).
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D. Paul, M. Zaitsev, L. Harsan, A. Kurutsch, D. N. Splitthoff, F. Hennel, M. Choli, and D. von Elverfeldt, “Implementation and application of PSF-based EPI distortion correction to high field animal imaging,” Int. J. Biomed. Imaging 2009, 946271 (2009).
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L.-A. Harsan, C. Dávidb, M. Reiserta, S. Schnella, J. Henniga, D. von Elverfeldta, and J. F. Staigerd, “Mapping remodeling of thalamocortical projections in the living reeler mouse brain by diffusion tractography,” Proceedings of the National Academy of Sciences 110(19), E1797–E1806 (2013).
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R. Sparks, G. Zombori, R. Rodionov, M. Nowell, S. B. Vos, M. A. Zuluaga, B. Diehl, T. Wehner, A. Miserocchi, A. W. McEvoy, J. S. Duncan, and S. Ourselin, “Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment,” Int. J. Comput. Assist. Radiol. Surg. 161–14 (2016).

Wallner-Blazek, M.

M. Khalil, C. Langkammer, S. Ropele, K. Petrovic, M. Wallner-Blazek, M. Loitfelder, M. Jehna, G. Bachmaier, R. Schmidt, C. Enzinger, S. Fuchs, and F. Fazekas, “Determinants of brain iron in multiple sclerosis: A quantitative 3T MRI study,” Neurology 77(18), 1691–1697 (2011).
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J. D. Johansson and K. Wårdell, “Intracerebral quantitative chromophore estimation from reflectance spectra captured during deep brain stimulation implantation,” J. Biophotonics 6(5), 435–445 (2013).
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S. Hemm and K. Wårdell, “Stereotactic implantation of deep brain stimulation electrodes: a review of technical systems, methods and emerging tools,” Med. Biol. Eng. Comput. 48(7), 611–624 (2010).
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C. I. Unglert, W. C. Warger, J. Hostens, E. Namati, R. Birngruber, B. E. Bouma, and G. J. Tearney, “Validation of two-dimensional and three-dimensional measurements of subpleural alveolar size parameters by optical coherence tomography,” J. Biomed. Opt. 17(12), 126015 (2012).
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R. Sparks, G. Zombori, R. Rodionov, M. Nowell, S. B. Vos, M. A. Zuluaga, B. Diehl, T. Wehner, A. Miserocchi, A. W. McEvoy, J. S. Duncan, and S. Ourselin, “Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment,” Int. J. Comput. Assist. Radiol. Surg. 161–14 (2016).

Weigel, M.

M. Reisert, I. Mader, C. Anastasopoulos, M. Weigel, S. Schnell, and V. Kiselev, “Global fiber reconstruction becomes practical,” NeuroImage 54(2), 955–962 (2011).
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Y. Xie, T. Bonin, S. Löffler, G. Hüttmann, V. Tronnier, and U. G. Hofmann, “Coronal in vivo forward-imaging of rat brain morphology with an ultra-small optical coherence tomography fiber probe,” Phys. Med. Biol. 58(3), 555–568 (2013).
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Yoshida, K.

W. Jensen, U. G. Hofmann, and K. Yoshida, “Assessment of subdural insertion force of single-tine microelectrodes in rat cerebral cortex,” in Proceedings of the 25th Annual International Conference of the IEEE, vol. 3 (2003), pp. 2168–2171.

Zaitsev, M.

D. Paul, M. Zaitsev, L. Harsan, A. Kurutsch, D. N. Splitthoff, F. Hennel, M. Choli, and D. von Elverfeldt, “Implementation and application of PSF-based EPI distortion correction to high field animal imaging,” Int. J. Biomed. Imaging 2009, 946271 (2009).
[Crossref]

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R. Sparks, G. Zombori, R. Rodionov, M. Nowell, S. B. Vos, M. A. Zuluaga, B. Diehl, T. Wehner, A. Miserocchi, A. W. McEvoy, J. S. Duncan, and S. Ourselin, “Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment,” Int. J. Comput. Assist. Radiol. Surg. 161–14 (2016).

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R. Sparks, G. Zombori, R. Rodionov, M. Nowell, S. B. Vos, M. A. Zuluaga, B. Diehl, T. Wehner, A. Miserocchi, A. W. McEvoy, J. S. Duncan, and S. Ourselin, “Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment,” Int. J. Comput. Assist. Radiol. Surg. 161–14 (2016).

Ann Surg Oncol (1)

R. John, S. G. Adie, E. J. Chaney, M. Marjanovic, K. V. Tangella, and S. A. Boppart, “Three-dimensional optical coherence tomography for optical biopsy of lymph nodes and assessment of metastatic disease,” Ann Surg Oncol 20(11), 3685–3693 (2013).
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Front Neuroeng (1)

Y. Xie, N. Martini, C. Hassler, R. Kirch, A. Seifert, T. Stieglitz, and U. G. Hofmann, “In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography,” Front Neuroeng 734 (2014).
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IEEE J. Sel. Top. Quantum Electron. (2)

A. I. Kholodnykh, I. Y. Petrova, M. Motamedi, and R. O. Esenaliev, “Accurate measurement of total attenuation coefficient of thin tissue with optical coherence tomography,” IEEE J. Sel. Top. Quantum Electron. 9(2), 210–221 (2003).
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T. G. van Leeuwen, D. J. Faber, and M. C. Aalders, “Measurement of the axial point spread function in scattering media using single-mode fiber-based optical coherence tomography,” IEEE J. Sel. Top. Quantum Electron. 9(2), 227–233 (2003).
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IEEE Trans. Med. Imaging (1)

F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens, “Multimodality image registration by maximization of mutual information,” IEEE Trans. Med. Imaging 16(2), 187–198 (1997).
[Crossref] [PubMed]

Int. J. Biomed. Imaging (1)

D. Paul, M. Zaitsev, L. Harsan, A. Kurutsch, D. N. Splitthoff, F. Hennel, M. Choli, and D. von Elverfeldt, “Implementation and application of PSF-based EPI distortion correction to high field animal imaging,” Int. J. Biomed. Imaging 2009, 946271 (2009).
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Int. J. Comput. Assist. Radiol. Surg. (1)

R. Sparks, G. Zombori, R. Rodionov, M. Nowell, S. B. Vos, M. A. Zuluaga, B. Diehl, T. Wehner, A. Miserocchi, A. W. McEvoy, J. S. Duncan, and S. Ourselin, “Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment,” Int. J. Comput. Assist. Radiol. Surg. 161–14 (2016).

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J. Biomed. Opt. (2)

G. van Soest, T. Goderie, E. Regar, S. Koljenović, G. L. J. H. van Leenders, N. Gonzalo, S. van Noorden, T. Okamura, B. E. Bouma, G. J. Tearney, J. W. Oosterhuis, P. W. Serruys, and A. F. W. van der Steen, “Atherosclerotic tissue characterization in vivo by optical coherence tomography attenuation imaging,” J. Biomed. Opt. 15(1), 011105 (2010).
[Crossref] [PubMed]

C. I. Unglert, W. C. Warger, J. Hostens, E. Namati, R. Birngruber, B. E. Bouma, and G. J. Tearney, “Validation of two-dimensional and three-dimensional measurements of subpleural alveolar size parameters by optical coherence tomography,” J. Biomed. Opt. 17(12), 126015 (2012).
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J. D. Johansson and K. Wårdell, “Intracerebral quantitative chromophore estimation from reflectance spectra captured during deep brain stimulation implantation,” J. Biophotonics 6(5), 435–445 (2013).
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[Crossref] [PubMed]

Med. Biol. Eng. Comput. (1)

S. Hemm and K. Wårdell, “Stereotactic implantation of deep brain stimulation electrodes: a review of technical systems, methods and emerging tools,” Med. Biol. Eng. Comput. 48(7), 611–624 (2010).
[Crossref] [PubMed]

Med. Phys. (1)

M. A. Jacobs, J. P. Windham, H. Soltanian-Zadeh, D. J. Peck, and R. A. Knight, “Registration and warping of magnetic resonance images to histological sections,” Med. Phys. 26(8), 1568–1578 (1999).
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M. Reisert, I. Mader, C. Anastasopoulos, M. Weigel, S. Schnell, and V. Kiselev, “Global fiber reconstruction becomes practical,” NeuroImage 54(2), 955–962 (2011).
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M. Khalil, C. Langkammer, S. Ropele, K. Petrovic, M. Wallner-Blazek, M. Loitfelder, M. Jehna, G. Bachmaier, R. Schmidt, C. Enzinger, S. Fuchs, and F. Fazekas, “Determinants of brain iron in multiple sclerosis: A quantitative 3T MRI study,” Neurology 77(18), 1691–1697 (2011).
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L.-A. Harsan, D. Paul, S. Schnell, B. W. Kreher, J. Hennig, J. F. Staiger, and D. von Elverfeldt, “In vivo diffusion tensor magnetic resonance imaging and fiber tracking of the mouse brain,” NMR Biomed 23(7), 884–896 (2010).
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I. Gudmundsdottir, P. Adamson, C. Gray, J. C. Spratt, M. W. Behan, P. Henriksen, D. E. Newby, N. Mills, N. G. Uren, and N. L. Cruden, “Optical coherence tomography versus intravascular ultrasound to evaluate stent implantation in patients with calcific coronary artery disease,” Open Heart 2(1) 225 (2015).
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Y. Xie, T. Bonin, S. Löffler, G. Hüttmann, V. Tronnier, and U. G. Hofmann, “Coronal in vivo forward-imaging of rat brain morphology with an ultra-small optical coherence tomography fiber probe,” Phys. Med. Biol. 58(3), 555–568 (2013).
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L.-A. Harsan, C. Dávidb, M. Reiserta, S. Schnella, J. Henniga, D. von Elverfeldta, and J. F. Staigerd, “Mapping remodeling of thalamocortical projections in the living reeler mouse brain by diffusion tractography,” Proceedings of the National Academy of Sciences 110(19), E1797–E1806 (2013).
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D. Huang, E. Swanson, C. Lin, J. Schuman, W. Stinson, W. Chang, M. Hee, T. Flotte, K. Gregory, C. Puliafito, and et al., “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
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G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, “In vivo endoscopic optical biopsy with optical coherence tomography,” Science 276(5321), 2037–2039 (1997).
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Figures (7)

Fig. 1
Fig. 1 An illustration of trajectory profiles extracted from OCT data, displaying intensity and attenuation data. (a) A gray scale image of a sample trajectory reconstructed from 51 vertically aligned A-scan signals taken from 51 measuring steps of along this trajectory. (b) The line profile signal of the OCT image is obtained at the position indicated by a yellow line in (a). The attenuation factor of brain tissue is calculated from the A-scan signal at each depth position in the trajectory, (c1) shows the A-scan plot from position at 0.8 mm (marked by the left green line in (a)). (c2) shows the A-scan plot from position at 9.6 mm (marked by the right green line in (a)). The red lines in these two A-scan plots demonstrate the linear fit by which the attenuation factor is extracted. The overall attenuation profile of the trajectory is shown in (c3).
Fig. 2
Fig. 2 Experimental setup of animal MRI measurement. (a) A MRI-adapted stereotaxic frame for fixation and ventilation tubing for anaesthesia. (b) An illustration of animal placement in the frame. (c) This picture shows the RF coil used in the measurement. The red line indicates the center position of the MR scan.
Fig. 3
Fig. 3 A collage of selected images from MRI measurement and histological staining, and the profile data from trajectories indicated with the red line. All images (T1-weighted (a), T2-weighted (b), DTI fiber density map (c), cresyl violet staining (e), and acetylcholinesterase staining (f)) are with the same anterior-posterior coordinate Bregma −2.00 mm, trajectories are located at medial-lateral −2.50 mm. Panel (d) is the atlas sketch illustrating the anatomic structures lying on the trajectory path.
Fig. 4
Fig. 4 Two representative illustrations of correlation of anatomical structures between OCT signals, T2-weighted MR image, fiber density map and histology image are shown here. The black dotted lines indicate various identified anatomical structures, and show the agreement between image modalities. Both of the OCT intensity profiles and the attenuation present prominent hyperreflective bands corresponding to corpus callosum, superior colliculus, optic tracts, and as well as cerebral peduncle which are brain white matter basically compose of neural fibers. These structures revealed in OCT images and signals are also distinguishable in MRI and histological images. x, and y axis of OCT images in a4 and b4 denote look ahead distance (mm) and trajectory depth (mm), respectively.
Fig. 5
Fig. 5 A collage of OCT data, MRI profiles, and histological profile signals of two sample trajectories. Left panels show the location of trajectories illustrated by the red line in the rat atlas schematics. The coordinate of trajectory A is AP - 2.00 mm, ML - 2.50 mm (a), trajectory B is AP - 5.40 mm, ML - 2.00 mm (b). The plots in right panels are OCT attenuation profile, OCT intensity profile, T1 T2 FDM profile, and histological profile of each trajectory respectively.
Fig. 6
Fig. 6 OCT measurements including intensity profile and attenuation factor of trajectory A and B align with intensity profiles of MR-T1, MR-T2, FDM, AChE staining profile, and cresyl violet staining profile. Resemblances are indicated by arrows.
Fig. 7
Fig. 7 The upper two figures are warping distance distribution depicted with box plot. The middle and lower rows of figures are the distribution of correlation coefficient (R) and mutual information (MI) of the compared signal pairs before warping process, respectively.

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