Research progress and clinical application of adaptive optics in retinal imaging_Chinese Journal of Ocular Fundus Diseases

Authors：

Fang Qi ^1,2 , Zhang Lei ² ,  Wang Haiyan ² , Wang Ru ²

1. Xi'an Medical University, Xi'an 710021, China;
2. Xi'an People's Hospital (Xi'an Fourth Hospital), Shaanxi Eye Hospital, Xi'an Key Laboratory of Digital Medical Technology of Ophthalmologic Imaging, Xi'an 710004, China;

Corresponding author：

Wang Haiyan, Email: haiyanwang@med.nwu.edu.cn

Keywords：

Adaptive optics; Imaging; Retinal disease; Review

DOI：

10.3760/cma.j.cn511434-20240407-00141

Video：

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As a newly developing technology of adaptive optics (AO), the combination of AO technology with traditional fundus imaging devices, such as fundus camera, scanning laser ophthalmoscope as well as optical coherence tomography, can image photoreceptor cells, retinal pigment epithelial cells, retinal ganglion cells, and retinal vascular system. Currently, AO technology is applied in the diagnosis, monitor and management of retinal diseases, enabling the observation of early changes of photoreceptor cells and analyzing vascular parameters in inherited retinal diseases, age-related macular degeneration, retinal vascular diseases such as diabetic retinopathy and retinal vein occlusion, inflammatory retinal diseases and central serous chorioretinopathy. Major breakthrough brought by AO technology along with rapid progress driven by ophthalmic imaging devices can help clarify the pathogenesis of eye diseases. and offer a comprehensive understanding of the new perspectives provided by AO technology for fundus imaging. Of course, limitation of popularizing application of AO device exists due to small scan range and optic media opacity. Thus, a comprehensive understanding of AO technology provides a new horizon for retina imaging. A comprehensive understanding of AO technology provides updated vision for fundus imaging, and is expected to promote the clinical application of AO technology in ophthalmology, and to enable cellular-resolution imaging of the living human retina.

Citation： Fang Qi, Zhang Lei, Wang Haiyan, Wang Ru. Research progress and clinical application of adaptive optics in retinal imaging. Chinese Journal of Ocular Fundus Diseases, 2024, 40(8): 645-650. doi: 10.3760/cma.j.cn511434-20240407-00141 Copy

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1. Akyol E, Hagag AM, Sivaprasad S, et al. Adaptive optics: principles and applications in ophthalmology[J]. Eye (Lond), 2021, 35(1): 244-264. DOI: 10.1038/s41433-020-01286-z.
2. Wongwai J, Buranasiri P, Pasupa K, et al. Analysis of volumetric 3D reconstruction of lamina cribrosa images from swept-source optical coherence tomography in glaucomatous and healthy subjects[J]. Biomed Opt Express, 2023, 14(9): 4627-4643. DOI: 10.1364/BOE.497242.
3. 张影, 张荟颖, 姚进. 基于自适应光学的视网膜成像技术应用进展[J]. 国际眼科杂志, 2023, 23(12): 1978-1982. DOI: 10.3980/j.issn.1672-5123.2023.12.08.Zhang Y, Zhang HY, Yao J. Advancements in the application of adaptive optics-based retinal imaging technology[J]. Int Rev Ophthalmol, 2023, 23(12): 1978-1982. DOI: 10.3980/j.issn.1672-5123.2023.12.08.
4. Liang J, Williams DR, Miller DT. Supernormal vision and high-resolution retinal imaging through adaptive optics[J]. J Opt Soc Am A Opt Image Sci Vis, 1997, 14(11): 2884-2892. DOI: 10.1364/josaa.14.002884.
5. Roorda A, Williams DR. The arrangement of the three cone classes in the living human eye[J]. Nature, 1999, 397(6719): 520-522. DOI: 10.1038/17383.
6. Warner RL, Gast TJ, Sapoznik KA, et al. Measuring temporal and spatial variability of red blood cell velocity in human retinal vessels[J]. Invest Ophthalmol Vis Sci, 2021, 62(14): 29-37. DOI: 10.1167/iovs.62.14.29.
7. Cooper RF, Wilk MA, Tarima S, et al. Evaluating descriptive metrics of the human cone mosaic[J]. Invest Ophthalmol Vis Sci, 2016, 57(7): 2992-3001. DOI: 10.1167/iovs.16-19072.
8. Zhang B, Li N, Kang J, et al. Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update[J]. Int J Ophthalmol, 2017, 10(11): 1751-1758. DOI: 10.18240/ijo.2017.11.18.
9. Jonas JB, Wang YX, Zhang Q, et al. Macular bruch's membrane length and axial length. The Beijing Eye Study[J/OL]. PLoS One, 2015, 10(8): e0136833[2015-08-28]. https://pubmed.ncbi.nlm.nih.gov/26317992/. DOI: 10.1371/journal.pone.0136833.
10. Chui TY, Song H, Clark CA, et al. Cone photoreceptor packing density and the outer nuclear layer thickness in healthy subjects[J]. Invest Ophthalmol Vis Sci, 2012, 53(7): 3545-3553. DOI: 10.1167/iovs.11-8694.
11. Jonas JB, Schneider U, Naumann GO. Count and density of human retinal photoreceptors[J]. Graefe's Arch Clin Exp Ophthalmol, 1992, 230(6): 505-510. DOI: 10.1007/BF00181769.
12. Dubra A, Sulai Y, Norris JL, et al. Noninvasive imaging of the human rod photoreceptor mosaic using a confocal adaptive optics scanning ophthalmoscope[J]. Biomed Opt Express, 2011, 2(7): 1864-1876. DOI: 10.1364/BOE.2.001864.
13. Merino D, Duncan JL, Tiruveedhula P, et al. Observation of cone and rod photoreceptors in normal subjects and patients using a new generation adaptive optics scanning laser ophthalmoscope[J]. Biomed Opt Express, 2011, 2(8): 2189-2201. DOI: 10.1364/BOE.2.002189.
14. Roorda A, Zhang Y, Duncan JL. High-resolution in vivo imaging of the RPE mosaic in eyes with retinal disease[J]. Invest Ophthalmol Vis Sci, 2007, 48(5): 2297-2303. DOI: 10.1167/iovs.06-1450.
15. Williams DR, Burns SA, Miller DT, et al. Evolution of adaptive optics retinal imaging[J]. Biomed Opt Express, 2023, 14(3): 1307-1338. DOI: 10.1364/BOE.485371.
16. Neriyanuri S, Bedggood P, Symons RCA, et al. Flow heterogeneity and factors contributing to the variability in retinal capillary blood flow[J]. Invest Ophthalmol Vis Sci, 2023, 64(10): 15-28. DOI: 10.1167/iovs.64.10.15.
17. Gu BY, Wang XL, Twa MD, et al. Noninvasive in vivo characterization of erythrocyte motion in human retinal capillaries using high-speed adaptive optics near-confocal imaging[J]. Biomed Opt Express, 2018, 9(8): 3653-3677. DOI: 10.1364/BOE.9.003653.
18. Martin JA, Roorda A. Direct and noninvasive assessment of parafoveal capillary leukocyte velocity[J]. Ophthalmology, 2005, 112(12): 2219-2224. DOI: 10.1016/j.ophtha.2005.06.033.
19. Joseph A, Chu CJ, Feng GP, et al. Label-free imaging of immune cell dynamics in the living retina using adaptive optics[J/OL]. Elife, 2020, 9(1): e60547[2020-10-14]. https://pubmed.ncbi.nlm.nih.gov/33052099/. DOI: 10.7554/eLife.60547.
20. Mo S, Krawitz B, Efstathiadis E, et al. Imaging foveal microvasculature: optical coherence tomography angiography versus adaptive optics scanning light ophthalmoscope fluorescein angiography[J]. Invest Ophthalmol Vis Sci, 2016, 57(9): 130-140. DOI: 10.1167/iovs.15-18932.
21. Pircher M, Zawadzki RJ. Review of adaptive optics OCT (AO-OCT): principles and applications for retinal imaging[J]. Biomed Opt Express, 2017, 8(5): 2536-2562. DOI: 10.1364/BOE.8.002536.
22. Corless JM. Lamellar structure of bleached and unbleached rod photoreceptor membranes[J]. Nature, 1972, 237(5352): 229-231. DOI: 10.1038/237229a0.
23. Reumueller A, Wassermann L, Salas M, et al. Three-dimensional assessment of para- and perifoveal photoreceptor densities and the impact of meridians and age in healthy eyes with adaptive-optics optical coherence tomography (AO-OCT)[J]. Opt Express, 2020, 28(24): 36723-36739. DOI: 10.1364/OE.409076.
24. Pandiyan VP, Schleufer S, Slezak E, et al. Characterizing cone spectral classification by optoretinography[J]. Biomed Opt Express, 2022, 13(12): 6574-6594. DOI: 10.1364/BOE.473608.
25. Lassoued A, Zhang FR, Kurokawa K, et al. Cone photoreceptor dysfunction in retinitis pigmentosa revealed by optoretinography[J/OL]. Proc Natl Acad Sci USA, 2021, 118(47): e2107444118[2021-11-23]. https://pubmed.ncbi.nlm.nih.gov/34795055/. DOI: 10.1073/pnas.2107444118.
26. Song HX, Rossi EA, Yang Q, et al. High-resolution adaptive optics in vivo autofluorescence imaging in stargardt disease[J]. JAMA Ophthalmol, 2019, 137(6): 603-609. DOI: 10.1001/jamaophthalmol.2019.0299.
27. Palejwala NV, Gale MJ, Clark RF, et al. Insights into autosomal dominant stargardt-like macular dystrophy through multimodality diagnostics imaging[J]. Retina, 2016, 36(1): 119-130. DOI: 10.1097/IAE.0000000000000659.
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