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Transscleral optical phase imaging of the human retina

Abstract

In vivo observation of the human retina at the cellular level is crucial to detect the first signs of retinal diseases and properly treat them. Despite the phenomenal advances in adaptive optics systems, clinical imaging of many retinal cells is still elusive due to the low signal-to-noise ratio induced by transpupillary illumination. We present a transscleral optical phase imaging method, which relies on high-angle oblique illumination of the retina, combined with adaptive optics, to enhance cell contrast. Examination of 11 healthy volunteer eyes, without pupil dilation, shows the ability of this method to produce in vivo images of retinal cells, from the retinal pigment epithelium to the nerve fibre layer. This method also allows the generation of high-resolution label-free ex vivo phase images of flat-mounted retinas. The in vivo images with 4.4° × 4.4° field of view are recorded in less than 10 s, opening new avenues in the exploration of healthy and diseased retinas.

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Fig. 1: Illumination of the retinal layers provided as transscleral illumination.
Fig. 2: Optical diagram of the in vivo TOPI system.
Fig. 3: In vivo full-field (4.4° × 4.4°) image of the RPE of a healthy volunteer.
Fig. 4: Microcapillaries and NFL TOPI images of subject S10, taken at different eccentricities.
Fig. 5: Comparison between in vivo images from a transpupil flood illumination commercial system and a transscleral illumination TOPI image on the same area.
Fig. 6: Image correlation analysis between oblique illumination OPI microscopy and fluorescence confocal microscopy of retinal vessels and their surrounding cells.

Data availability

All data needed to evaluate the conclusions in this paper are present in the paper and/or the Supplementary Information. The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request.

Code availability

The code for performing the reconstruction process is available on request from the authors.

References

  1. Wong, W. et al. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. Lancet Glob. Health 2, 106–116 (2014).

    Google Scholar 

  2. Pallikaris, A., Williams, D. R. & Hofer, H. The reflectance of single cones in the living human eye. Invest. Ophthalmol. Vis. Sci. 44, 4580–4592 (2003).

    Google Scholar 

  3. Gao, W., Cense, B., Zhang, Y., Jonnal, R. S. & Miller, D. T. Measuring retinal contributions to the optical Stiles–Crawford effect with optical coherence tomography. Opt. Express 16, 6486–6501 (2008).

    ADS  Google Scholar 

  4. Artal, P. & Navarro, R. High-resolution imaging of the living human fovea: measurement of the intercenter cone distance by speckle interferometry. Opt. Lett. 14, 1098–1100 (1989).

    ADS  Google Scholar 

  5. Fernández, E. J., Iglesias, I. & Artal, P. Closed-loop adaptive optics in the human eye. Opt. Lett. 26, 746–748 (2001).

    ADS  Google Scholar 

  6. Viard, C. et al. Imaging microscopic structures in pathological retinas using a flood illumination adaptive optics retinal camera. Proc. SPIE 7885, 788509 (2011).

    Google Scholar 

  7. Gofas-Salas, E. High loop rate adaptive optics flood illumination ophthalmoscope with structured illumination capability. Appl. Opt. 57, 5635–5642 (2018).

    ADS  Google Scholar 

  8. Gofas-Salas, E. Near infrared adaptive optics flood illumination retinal angiography. Biomed. Opt. Express 10, 2730–2743 (2019).

    Google Scholar 

  9. Liu, Z., Kurokawa, K., Zhang, F., Lee, J. J. & Miller, D. T. Imaging and quantifying ganglion cells and other transparent neurons in the living human retina. Proc. Natl Acad. Sci. USA 114, 12803–12808 (2017).

    ADS  Google Scholar 

  10. Miller, D. T., Kocaoglu, O. P., Wang, Q. & Lee, S. Adaptive optics and the eye (super resolution OCT). Eye 25, 321–330 (2011).

    Google Scholar 

  11. Rossi, E. A. et al. Imaging individual neurons in the retinal ganglion cell layer of the living eye. Proc. Natl Acad. Sci. USA 114, 586–591 (2017).

    ADS  Google Scholar 

  12. Guevara-Torres, A., Williams, D. R. & Schallek, J. Imaging translucent cell bodies in the living mouse retina without contrast agents. Biomed. Opt. Express 6, 2106–2119 (2015).

    Google Scholar 

  13. Chui, T. Y., Gast, T. J. & Burns, S. A. Imaging of vascular wall fine structure in human retina using adaptive optics scanning laser ophthalmoscopy. Invest. Ophthalmol. Vis. Sci. 54, 7115–7124 (2013).

    Google Scholar 

  14. Chui, T. Y. P., Van Nasdale, D. A. & Burns, S. A. The use of forward scatter to improve retinal vascular imaging with an adaptive optics scanning laser ophthalmoscope. Biomed. Opt. Express 3, 2537–2549 (2012).

    Google Scholar 

  15. Cunefare, D. et al. Automated detection of cone photoreceptors in split detector adaptive optics scanning light ophthalmoscope images. Invest. Ophthalmol. Vis. Sci. 57, 61 (2016).

    Google Scholar 

  16. Sulai, Y. N., Scoles, D., Harvey, Z. & Dubra, A. Visualization of retinal vascular structure and perfusion with a nonconfocal adaptive optics scanning light ophthalmoscope. J. Opt. Soc. Am. A 31, 569–579 (2014).

    ADS  Google Scholar 

  17. Scoles, D., Sulai, Y. N. & Dubra, A. In vivo dark-field imaging of the retinal pigment epithelium cell mosaic. Biomed. Opt. Express 4, 1710–1723 (2013).

    Google Scholar 

  18. Granger, C. E. et al. Human retinal pigment epithelium: in vivo cell morphometry, multispectral autofluorescence and relationship to cone mosaic. Invest. Ophthalmol. Vis. Sci. 59, 5705–5716 (2018).

    Google Scholar 

  19. Liu, Z., Kocaoglu, O. P. & Miller, D. T. 3D imaging of retinal pigment epithelial cells in the living human retina. Invest. Ophthalmol. Vis. Sci. 57, 533–543 (2016).

    Google Scholar 

  20. Vogel, A., Dlugos, C., Nuffer, R. & Birngruber, R. Optical properties of human sclera, and their consequences for transscleral laser applications. Lasers Surg. Med. 11, 331–340 (1991).

    Google Scholar 

  21. Geeraets, W. et al. The relative absorption of thermal energy in retina and choroid. Invest. Ophthalmol. Vis. Sci. 3, 340–347 (1962).

    Google Scholar 

  22. Delori, F. C. & Pflibsen, K. P. Spectral reflectance of the human ocular fundus. Appl. Opt. 28, 1061–1077 (1989).

    ADS  Google Scholar 

  23. JGiese, J. D., Ford, T. N. & Mertz, J. Fast volumetric phase-gradient imaging in thick samples. Opt. Express 22, 1152–1162 (2014).

    ADS  Google Scholar 

  24. Carpentras, D., Laforest, T., Künzi, M. & Moser, C. Effect of backscattering in phase contrast imaging of the retina. Opt. Express 26, 6785–6795 (2018).

    ADS  Google Scholar 

  25. Liang, J., Williams, D. R. & Miller, D. T. Supernormal vision and high-resolution retinal imaging through adaptive optics. J. Opt. Soc. Am. A 14, 2884–2892 (1997).

    ADS  Google Scholar 

  26. Fitzpatrick, T. B. The validity and practicality of sun-reactive skin types I through VI. Arch. Dermatol. 6, 869–871 (1988).

    Google Scholar 

  27. Morgan, J. I. W., Dubra, A., Wolfe, R., Merigan, W. H. & Williams, D. R. In vivo autofluorescence imaging of the human and macaque retinal pigment epithelial cell mosaic. Invest. Ophthalmol. Vis. Sci. 50, 1350–1359 (2009).

    Google Scholar 

  28. Bhatia, S. K. et al. Analysis of RPE morphometry in human eyes. Mol. Vis. 22, 898–916 (2016).

    Google Scholar 

  29. Zhao, M. et al. A new CRB1 rat mutation links Müller glial cells to retinal telangiectasia. J. Neurosci. 35, 6093–6106 (2015).

    Google Scholar 

  30. Bhutto, I. & Lutty, G. Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex. Mol. Aspects Med. 33, 295–317 (2018).

    Google Scholar 

  31. Humayun, M. Morphometric analysis of the extramacular retina from postmortem eyes with retinitis pigmentosa. Invest. Ophthalmol. Vis. Sci. 40, 143–148 (1999).

    Google Scholar 

  32. Rothschild, P. ROCK-1 mediates diabetes-induced retinal pigment epithelial and endothelial cell blebbing: contribution to diabetic retinopathy. Sci. Rep. 7, 8834 (2017).

    ADS  Google Scholar 

  33. Fisher, C. R. & Ferrington, D. A. Perspective on AMD pathobiology: a bioenergetic crisis in the RPE. Invest. Ophthalmol. Vis. Sci. 59, 41–47 (2018).

    Google Scholar 

  34. Zhang, Q. et al. Comparison of histologic findings in age-related macular degeneration with RPE flatmount images. Mol. Vis. 25, 70–78 (2019).

    Google Scholar 

  35. London, A., Benhar, I. & Schwartz, M. The retina as a window to the brain-from eye research to CNS disorders. Nat. Rev. Neurol. 9, 44–53 (2013).

    Google Scholar 

  36. Morgia, C. L., Ross-Cisneros, F. N., Sadun, A. A. & Carelli, V. Retinal ganglion cells and circadian rhythms in Alzheimer’s disease, Parkinson’s disease and beyond. Front. Neurol. 8, 162 (2017).

    Google Scholar 

  37. Geffen, N. et al. Transscleral selective laser trabeculoplasty without a gonioscopy lens. J. Glaucoma 26, 201–207 (2017).

    Google Scholar 

  38. Thévenaz, P., Ruttimann, U. E. & Unser, M. A pyramid approach to subpixel registration based on intensity. IEEE Trans. Image Process. 7, 27–41 (1998).

    ADS  Google Scholar 

  39. Strouthidis, N. et al. Factors affecting the test-retest variability of Heidelberg retina tomograph and Heidelberg retina tomograph II measurements. Br. J. Ophthalmol. 89, 1427–1432 (2005).

    Google Scholar 

  40. Monemhaghdoust, Z., Montfort, F., Emery, Y., Depeursinge, C. & Moser, C. Off-axis digital holographic camera for quantitative phase microscopy. Biomed. Opt. Express 5, 1721–1730 (2014).

    Google Scholar 

  41. Tian, L. & Waller, L. Quantitative differential phase contrast imaging in an LED array microscope. Opt. Express 23, 11394–11403 (2015).

    ADS  Google Scholar 

  42. Mehta, S. B. & Sheppard, C. J. R. Quantitative phase-gradient imaging at high resolution with asymmetric illumination-based differential phase contrast. Opt. Lett. 34, 1924–1926 (2009).

    ADS  Google Scholar 

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Acknowledgements

We thank M. Nicolas from the eye bank of the Jules-Gonin Eye Hospital for providing a post-mortem human eye, I. Mantel and the team of the centre for clinical investigation for their time spent in performing the ophthalmologic checks for our study on healthy participants, and S. Roy, A. Matet and D. Sage for discussions. In addition to the research partners, this study was supported by the following programmes: the Enable programme of the Technology Transfer Office at EPFL (610263), EPFL Innogrant (INNO 17-15), Bridge Proof of Concept (InnoSuisse and SNSF, 20B1-1_178253), the Gebert Rüf Stiftung Foundation (GRS-052/17) and EIT Health Innovation by Idea (19323-ASSESS).

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Authors and Affiliations

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Contributions

T.L. designed and built the ex vivo microscope, obtained the ex vivo results, built the in vivo device, wrote the code for ex vivo and in vivo processing and wrote the paper. M.K. designed and built the in vivo device, wrote the code for in vivo processing and wrote the paper. D.C. developed the theoretical model and wrote the paper. L.K. provided and prepared the ex vivo samples, participated in the interpretation of the phase images and wrote the paper. F.B.-C. supervised the project and wrote the paper. C.M. designed the experiment, supervised the project and wrote the paper.

Corresponding author

Correspondence to Christophe Moser.

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Competing interests

T.L., M.K., F.B.-C. and C.M. are involved in a company (EarlySight SA, Switzerland) aiming to commercialize the technology. A patent application, no. WO2017195163A1, has been submitted.

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Supplementary Information

Supplementary Figs. 1–10, Table 1 and Notes 1–3.

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Laforest, T., Künzi, M., Kowalczuk, L. et al. Transscleral optical phase imaging of the human retina. Nat. Photonics 14, 439–445 (2020). https://doi.org/10.1038/s41566-020-0608-y

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