The possibilities of using adaptive optics in modern ophthalmology

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Abstract

Until recently, the assessment of individual retinal cells was possible only with the help of histological examination, since such retinal imaging methods as scanning laser ophthalmoscopy and optical coherence tomography had low resolution to obtain images of structures at the cellular level, which was mainly due to aberrations caused by the optics of the eye. Adaptive optics technology has improved the performance of optical systems by correcting optical wavefront aberrations. Adaptive optics allows noninvasively visualizing the retina at the microscopic level in vivo, providing the opportunity to analyze individual structures such as photoreceptors, blood vessels, nerve fibers, ganglion cells and a lattice plate. Adaptive optics imaging in patients with diabetic retinopathy makes it possible to accurately determine the spatial distribution of cones, a decrease in which is associated with the presence of diabetic retinopathy and an increase in the severity of the disease. The detection of differences in cone distribution density between the control group and patients with diabetes mellitus without clinical signs of diabetic retinopathy may contribute to its early diagnosis, as well as a deeper understanding of the consequences of changes in the photoreceptor apparatus. Adaptive optics imaging methods are able to identify disorders of photoreceptor cells and assess the degree of progression of age-related macular degeneration, which definitely expands diagnostic capabilities at the early stages of its detection. Assessment of the condition of nerve fiber bundles through the use of Adaptive optics helps to identify changes associated with glaucoma, and also provides the ability to visualize details that cannot be evaluated using optical coherence tomography. Adaptive optics imaging allows you to directly measure the wall of retinal vessels and the diameter of their lumen. The ratio of wall thickness to vessel lumen and the cross-sectional area of the vessel wall directly reflect the remodeling process and can be used for the purpose of early diagnosis and monitoring of hypertension.

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About the authors

Anna A. Pavlova

Rostov State Medical University

Author for correspondence.
Email: anna.pawlowapavlova@yandex.ru
ORCID iD: 0009-0002-3039-8200
Russian Federation, Rostov-on-Don

Stella S. Nastenko

Rostov State Medical University

Email: stellanastenko@gmail.com
ORCID iD: 0009-0009-1629-6313
Russian Federation, Rostov-on-Don

Aziza A. Bolatkhanova

Stavropol State Medical University

Email: bolatkhanovaaziza2001@mail.ru
ORCID iD: 0009-0001-9317-440X
Russian Federation, Stavropol

Valeriya Yu. Marchenko

Rostov State Medical University

Email: valeriya.dunaeva@mail.ru
ORCID iD: 0009-0005-4180-8481
Russian Federation, Rostov-on-Don

Darya V. Lukyanova

Rostov State Medical University

Email: dariagu033@gmail.com
ORCID iD: 0009-0008-7200-084X
Russian Federation, Rostov-on-Don

Maria D. Burnasheva

Rostov State Medical University

Email: Bmd2001@bk.ru
ORCID iD: 0009-0001-3110-7551
Russian Federation, Rostov-on-Don

Zagid Z. Zarbaliev

Rostov State Medical University

Email: zzarbaliev@mail.ru
ORCID iD: 0009-0007-1508-2124
Russian Federation, Rostov-on-Don

Ilya A. Bespalov

Stavropol State Medical University

Email: ilya_bespalov_2000@mail.ru
ORCID iD: 0009-0009-0686-4129
Russian Federation, Stavropol

Pavel N. Kalyuzhnyi

Stavropol State Medical University

Email: pasha-sunny5@yandex.ru
ORCID iD: 0009-0007-2042-2242
Russian Federation, Stavropol

Diana R. Kanina

Rostov State Medical University

Email: Vviana@inbox.ru
ORCID iD: 0009-0002-3250-3123
Russian Federation, Rostov-on-Don

Andrey E. Shlychkov

Rostov State Medical University

Email: Shlychkov_a00@bk.ru
ORCID iD: 0009-0000-8762-6388
Russian Federation, Rostov-on-Don

Sonya G. Tarasova

Rostov State Medical University

Email: tarasovatarasova2001@yandex.ru
ORCID iD: 0009-0001-1574-5158
Russian Federation, Rostov-on-Don

References

  1. Neroev VV, Aliev AA, Nurudinov MM. Comparative analysis of optical aberrations, anatomical and optical parameters of the cornea in glaucoma surgery. Russian Ophthalmological Journal. 2018;11(4):24–28. (In Russ.) EDN: YPHUST doi: 10.21516/2072-0076-2018-11-4-24-28
  2. Pevko DV. Aberrations in the optical system of the eye: a review of the problem. The EYE. 2017;19(4(116)):9–17. (In Russ.) EDN: XUNFXT
  3. Liang J, Williams DR, Miller DT. Supernormal vision and high-resolution retinal imaging through adaptive optics. J Opt Soc Am a Opt Image Sci Vis. 1997;14(11):2884–2892. doi: 10.1364/josaa.14.002884
  4. Lombardo M, Serrao S, Devaney N, et al. Adaptive optics technology for high-resolution retinal imaging. Sensors (Basel). 2012;13(1):334–366. doi: 10.3390/s130100334
  5. Liang J, Grimm B, Goelz S, Bille JF. Objective measurement of wave aberrations of the human eye with the use of a Hartmann–Shack wave-front sensor. J Opt Soc Am a Opt Image Sci Vis. 1994;11(7):1949–1957. doi: 10.1364/josaa.11.001949
  6. Ulińska M, Zaleska-Żmijewska A, Szaflik J. The new possibilities of the in vivo retinal imaging with the use of adaptive optics. Klinika Oczna / Acta Ophthalmologica Polonica. 2017;119(1):63–66. doi: 10.5114/ko.2017.71771 (In Polish.)
  7. Zhang B, Li N, Kang J, et al. Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update. Int J Ophthalmol. 2017;10(11):1751–1758. doi: 10.18240/ijo.2017.11.18
  8. Mohankumar A, Gurnani B. Scanning laser ophthalmoscope. In: StatPearls. Treasure Island (FL): StatPearls Publishing; 2023.
  9. Zhang P, Wahl DJ, Mocci J, et al. Adaptive optics scanning laser ophthalmoscopy and optical coherence tomography (AO-SLO-OCT) system for in vivo mouse retina imaging. Biomed Opt Express. 2022;14(1):299–314. doi: 10.1364/BOE.473447
  10. Litts KM, Cooper RF, Duncan JL, Carroll J. Photoreceptor-based biomarkers in aoslo retinal imaging. Invest Ophthalmol Vis Sci. 2017;58(6):BIO255–BIO267. doi: 10.1167/iovs.17-21868
  11. Bakker E, Dikland FA, van Bakel R, et al. Adaptive optics ophthalmoscopy: a systematic review of vascular biomarkers. Surv Ophthalmol. 2022;67(2):369–387. doi: 10.1016/j.survophthal.2021.05.012
  12. Tan NY, Koh V, Girard MJ, Cheng CY. Imaging of the lamina cribrosa and its role in glaucoma: a review. Clin Exp Ophthalmol. 2018;46(2):177–188. doi: 10.1111/ceo.13126
  13. Nadler Z, Wang B, Schuman JS, et al. In vivo three-dimensional characterization of the healthy human lamina cribrosa with adaptive optics spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2014;55(10):6459–6466. doi: 10.1167/iovs.14-15177
  14. Kuznetsov KO, Safina ER, Gaimakova DV, et al. Metformin and malignant neoplasms: a possible mechanism of antitumor action and prospects for use in practice. Problems of Endocrinology. 2022;68(5):45–55. (In Russ.) EDN: AGJWVI doi: 10.14341/probl13097
  15. Demidova TY, Kozhevnikov AA. Diabetic retinopathy: history, modern approaches to management, prospective views of prevention and treatment. Diabetes Mellitus. 2020;23(1):95–105. EDN: ECFMZS doi: 10.14341/DM10273
  16. Lombardo M, Parravano M, Lombardo G, et al. Adaptive optics imaging of parafoveal cones in type 1 diabetes. Retina. 2014;34(3):546–557. doi: 10.1097/IAE.0b013e3182a10850
  17. Lammer J, Prager SG, Cheney MC, et al. Cone photoreceptor irregularity on adaptive optics scanning laser ophthalmoscopy correlates with severity of diabetic retinopathy and macular edema. Invest Ophthalmol Vis Sci. 2016;57(15):6624–6632. doi: 10.1167/iovs.16-19537
  18. Cristescu IE, Baltă F, Zăgrean L. Cone photoreceptor density in type I diabetic patients measured with an adaptive optics retinal camera. Rom J Ophthalmol. 2019;63(2):153–160.
  19. Tan W, Wright T, Rajendran D, et al. Cone-photoreceptor density in adolescents with type 1 diabetes. Invest Ophthalmol Vis Sci. 2015;56(11):6339–6343. doi: 10.1167/iovs.15-16817
  20. Zaleska-Żmijewska A, Wawrzyniak ZM, et al. Adaptive optics (rtx1) high-resolution imaging of photoreceptors and retinal arteries in patients with diabetic retinopathy. J Diabetes Res. 2019;2019:9548324. doi: 10.1155/2019/9548324
  21. Datlinger F, Wassermann L, Reumueller A, et al. Assessment of detailed photoreceptor structure and retinal sensitivity in diabetic macular ischemia using adaptive optics-OCT and microperimetry. Invest Ophthalmol Vis Sci. 2021;62(13):1. doi: 10.1167/iovs.62.13.1
  22. Lombardo M, Parravano M, Serrao S, et al. Analysis of retinal capillaries in patients with type 1 diabetes and nonproliferative diabetic retinopathy using adaptive optics imaging. Retina. 2013;33(8):1630–1639. doi: 10.1097/IAE.0b013e3182899326
  23. Ueno Y, Iwase T, Goto K, et al. Association of changes of retinal vessels diameter with ocular blood flow in eyes with diabetic retinopathy. Sci Rep. 2021;11(1):4653. doi: 10.1038/s41598-021-84067-2
  24. Cristescu IE, Zagrean L, Balta F, Branisteanu DC. Retinal microcirculation investigation in type I and II diabetic patients without retinopathy using an adaptive optics retinal camera. Acta Endocrinol (Buchar). 2019;15(4):417–422. doi: 10.4183/aeb.2019.417
  25. Palochak CMA, Lee HE, Song JA, et al. Retinal blood velocity and flow in early diabetes and diabetic retinopathy using adaptive optics scanning laser ophthalmoscopy. J Clin Med. 2019;8(8):1165. doi: 10.3390/jcm8081165
  26. Tam J, Dhamdhere KP, Tiruveedhula P, et al. Disruption of the retinal parafoveal capillary network in type 2 diabetes before the onset of diabetic retinopathy. Invest Ophthalmol Vis Sci. 2011;52(12):9257–9266. doi: 10.1167/iovs.11-8481
  27. Gilmanshin TR. Epidemiology of age-related macular degeneration in the republic of bashkortostan (clinical and statistical analisys of the “ural eye and medical study”). Ophthalmology in Russia. 2019;16(1S):137–141. (In Russ.) EDN: KSSSTZ doi: 10.18008/1816-5095-2019-1S-137-141
  28. Fedotova TS, Hokkanen VM, Trofimova SV. Pathogenetic aspects of age-related macular degeneration of the retina. Bulletin of OSU. 2014;(12):173. (In Russ.) EDN: TUOAXN
  29. Rossi EA, Norberg N, Eandi C, et al. A new method for visualizing drusen and their progression in flood-illumination adaptive optics ophthalmoscopy. Transl Vis Sci Technol. 2021;10(14):19. doi: 10.1167/tvst.10.14.19
  30. Godara P, Siebe C, Rha J, Michaelides M, Carroll J. Assessing the photoreceptor mosaic over drusen using adaptive optics and SD-OCT. Ophthalmic Surg Lasers Imaging. 2010;41:104–108. doi: 10.3928/15428877-20101031-07
  31. Boretsky A, Khan F, Burnett G, et al. In vivo imaging of photoreceptor disruption associated with age-related macular degeneration: A pilot study. Lasers Surg Med. 2012;44(8):603–610. doi: 10.1002/lsm.22070
  32. Gocho K, Sarda V, Falah S, et al. Adaptive optics imaging of geographic atrophy. Invest Ophthalmol Vis Sci. 2013;54(5):3673–3680. doi: 10.1167/iovs.12-10672
  33. Querques G, Kamami-Levy C, Georges A, et al. Adaptive optics imaging of foveal sparing in geographic atrophy secondary to age-related macular degeneration. Retina. 2016;36(2):247–254. doi: 10.1097/IAE.0000000000000692
  34. Takagi S, Mandai M, Gocho K, et al. Evaluation of transplanted autologous induced pluripotent stem cell-derived retinal pigment epithelium in exudative age-related macular degeneration. Ophthalmol Retina. 2019;3(10):850–859. doi: 10.1016/j.oret.2019.04.021
  35. Takayama K, Ooto S, Hangai M, et al. High-resolution imaging of retinal nerve fiber bundles in glaucoma using adaptive optics scanning laser ophthalmoscopy. Am J Ophthalmol. 2013;155(5):870–881. doi: 10.1016/j.ajo.2012.11.016
  36. Hasegawa T, Ooto S, Akagi T, et al. Expansion of retinal nerve fiber bundle narrowing in glaucoma: An adaptive optics scanning laser ophthalmoscopy study. Am J Ophthalmol Case Rep. 2020;19:100732. doi: 10.1016/j.ajoc.2020.100732
  37. Chen MF, Chui TY, Alhadeff P, et al. Adaptive optics imaging of healthy and abnormal regions of retinal nerve fiber bundles of patients with glaucoma. Invest Ophthalmol Vis Sci. 2015;56(1):674–681. doi: 10.1167/iovs.14-15936
  38. Choi SS, Zawadzki RJ, Lim MC, et al. Evidence of outer retinal changes in glaucoma patients as revealed by ultrahigh-resolution in vivo retinal imaging. Br J Ophthalmol. 2011;95(1):131–141. doi: 10.1136/bjo.2010.183756
  39. Choi SS, Zawadzki RJ, Keltner JL, Werner JS. Changes in cellular structures revealed by ultra-high resolution retinal imaging in optic neuropathies. Invest Ophthalmol Vis Sci. 2008;49(5): 2103–2119. doi: 10.1167/iovs.07-0980
  40. Hasegawa T, Ooto S, Takayama K, et al. Cone integrity in glaucoma: an adaptive-optics scanning laser ophthalmoscopy study. Am J Ophthalmol. 2016;171:53–66. doi: 10.1016/j.ajo.2016.08.021
  41. Vilupuru AS, Rangaswamy NV, Frishman LJ, et al. Adaptive optics scanning laser ophthalmoscopy for in vivo imaging of lamina cribrosa. J Opt Soc Am a Opt Image Sci Vis. 2007;24(5):1417–1425. doi: 10.1364/josaa.24.001417
  42. Akagi T, Hangai M, Takayama K, et al. In vivo imaging of lamina cribrosa pores by adaptive optics scanning laser ophthalmoscopy. Invest Ophthalmol Vis Sci. 2012;53(7):4111–4119. doi: 10.1167/iovs.11-7536
  43. Zwillinger S, Paques M, Safran B, Baudouin C. In vivo characterization of lamina cribrosa pore morphology in primary open-angle glaucoma. J Fr Ophtalmol. 2016;39(3):265–271. doi: 10.1016/j.jfo.2015.11.006
  44. King BJ, Burns SA, Sapoznik KA, et al. High-resolution, adaptive optics imaging of the human trabecular meshwork in vivo. Transl Vis Sci Technol. 2019;8(5):5. doi: 10.1167/tvst.8.5.5
  45. Hugo J, Chavane F, Beylerian M, et al. Morphologic analysis of peripapillary retinal arteriole using adaptive optics in primary open-angle glaucoma. J Glaucoma. 2020;29(4):271–275. doi: 10.1097/IJG.0000000000001452
  46. Moshetova LK, Vorobyeva IV, Dgebuadze A. Modern aspects of hypertensive angioretinopathy. Ophthalmology in Russia. 2018;15(4):470–475. (In Russ.) EDN: VPUTVS doi: 10.18008/1816-5095-2018-4-470-475
  47. Mehta RA, Akkali MC, Jayadev C, et al. Morphometric analysis of retinal arterioles in control and hypertensive population using adaptive optics imaging. Indian J Ophthalmol. 2019;67(10): 1673–1677. doi: 10.4103/ijo.IJO_253_19
  48. Rosenbaum D, Mattina A, Koch E, et al. Effects of age, blood pressure and antihypertensive treatments on retinal arterioles remodeling assessed by adaptive optics. J Hypertens. 2016;34(6): 1115–1122. doi: 10.1097/HJH.0000000000000894
  49. Sapoznik KA, Gast TJ, Carmichael-Martins A, et al. Retinal arteriolar wall remodeling in diabetes captured with AOSLO. Transl Vis Sci Technol. 2023;12(11):16. doi: 10.1167/tvst.12.11.16
  50. Arichika S, Uji A, Yoshimura N. Adaptive optics assisted visualization of thickened retinal arterial wall in a patient with controlled malignant hypertension. Clin Ophthalmol. 2014;8:2041–2043. doi: 10.2147/OPTH.S71964
  51. Bykova EV, Labyntseva YaA, Kozina EV, Bronskaya AN. Modern aspects of diagnostics and treatment of central serous chorioretinopathy. Modern Problems of Science and Education. 2022;(2):146. EDN: DEAICH doi: 10.17513/spno.31588
  52. Ochinciuc R, Ochinciuc U, Stanca HT, et al. Photoreceptor assessment in focal laser-treated central serous chorioretinopathy using adaptive optics and fundus autofluorescence. Medicine (Baltimore). 2020;99(15):e19536. doi: 10.1097/MD.0000000000019536
  53. Ooto S, Hangai M, Sakamoto A, et al. High-resolution imaging of resolved central serous chorioretinopathy using adaptive optics scanning laser ophthalmoscopy. Ophthalmology. 2010;117(9): 1800–1809.E2. doi: 10.1016/j.ophtha.2010.01.042
  54. Meirelles ALB, Rodrigues MW, Guirado AF, Jorge R. Photoreceptor assessment using adaptive optics in resolved central serous chorioretinopathy. Arq Bras Oftalmol. 2017;80(3):192–195. doi: 10.5935/0004-2749.20170047
  55. Gerardy M, Yesilirmak N, Legras R, et al. Central serous chorioretinopathy: high-resolution imaging of asymptomatic fellow eyes using adaptive optics scanning laser ophthalmoscopy. Retina. 2022;42(2):375–380. doi: 10.1097/IAE.0000000000003311
  56. Vienola KV, Lejoyeux R, Gofas-Salas E, et al. Autofluorescent hyperreflective foci on infrared autofluorescence adaptive optics ophthalmoscopy in central serous chorioretinopathy. Am J Ophthalmol Case Rep. 2022;28:101741. doi: 10.1016/j.ajoc.2022.101741
  57. Mahendradas P, Vala R, Kawali A, et al. Adaptive optics imaging in retinal vasculitis. Ocul Immunol Inflamm. 2018;26(5): 760–766. doi: 10.1080/09273948.2016.1263341
  58. Errera MH, Laguarrigue M, Rossant F, et al. High-resolution imaging of retinal vasculitis by flood illumination adaptive optics ophthalmoscopy: a follow-up study. Ocul Immunol Inflamm. 2020;28(8):1171–1180. doi: 10.1080/09273948.2019.1646773
  59. Biggee K, Gale MJ, Smith TB, et al. Parafoveal cone abnormalities and recovery on adaptive optics in posterior uveitis. Am J Ophthalmol Case Rep. 2016;1:16–22. doi: 10.1016/j.ajoc.2016.03.001
  60. Giansanti F, Mercuri S, Vannozzi L, et al. Adaptive optics imaging to analyze the photoreceptor layer reconstitution in acute syphilitic posterior placoid chorioretinopathy. Life (Basel). 2022;12(9):1361. doi: 10.3390/life12091361
  61. Kadomoto S, Uji A, Arichika S, et al. Macular cone abnormalities in Behçet’s disease detected by adaptive optics scanning light ophthalmoscope. Ophthalmic Surg Lasers Imaging Retina. 2021;52(4):218–225. doi: 10.3928/23258160-20210330-06
  62. Milash SV, Zolnikova IV, Kadyshev VV. Multimodal imaging of hereditary retinal dystrophies (a series of clinical cases). Russian Ophthalmological Journal. 2020;13(4):75–82. EDN: IMQTHJ doi: 10.21516/2072-0076-2020-13-4-75-82

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2. Fig. 1. Image of the retinal artery of a patient (WLR 0.250) from the control group (a) and from the diabetic retinopathy group with diabetes and hypertension (WLR 0.360) (b), obtained using the retinal camera with adaptive optics Rtx1, obtained automatically, with visualization of the wall and lumen using AOdetectArtery. Adapted from [20]

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3. Fig. 2. Images obtained using AO-SLO: a — retinal nerve fiber bundles visualized throughout the entire region; b — area without nerve fiber bundles and with ring structures; с — retinal nerve fiber bundles (gray rectangle) located between areas without bundles (red arrows). Scale bar: 100 µm (a, c); 25 µm (b). Adapted from [37]

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