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Modern trends in diagnostics and prediction of results of anti-vascular endothelial growth factor therapy of pigment epithelial detachment in neovascular agerelated macular degeneration using deep machine learning method (literature review)

https://doi.org/10.29413/ABS.2021-6.6-1.22

Abstract

Detachment of the pigment epithelium is the separation of the basement membrane of the retinal pigment epithelium from the inner collagen layer of Bruch’s membrane, which occurs in 80 % of cases in patients with neovascular age-related macular degeneration. The outcome of anti-VEGF therapy for pigment epithelial detachment may be adherence of the pigment epithelium, the formation of pigment epithelium tear, or preservation of the detachment. The pigment epithelium tear of 3–4th degrees can lead to a sharp decrease in visual acuity.
Most retrospective studies confi rm the absence of a proven correlation between anatomical and functional outcomes in the treatment of pigment epithelial detachment in cases of maintaining the integrity of the pigment epithelium monolayer, and therefore the main attention of researchers is focused on studying the morphological features of pigment epithelial detachment during therapy with angiogenesis inhibitors. Modern technologies of spectral optical coherence tomography make it possible to evaluate detailed quantitative parameters of pigment epithelium detachment, such as height, width, maximum linear diameter, area, volume and refl ectivity within the detachment.
Groups of Russian and foreign authors identify various biomarkers recorded on optical coherence tomography images. Dynamic registration of such biomarkers expands the ability of clinicians to predict morphological changes in pigment epithelial detachment during anti-VEGF therapy, as well as to optimize treatment regimens to prevent complications in the form of pigment epithelium tear leading to a decrease in visual acuity.
Modern methods of deep machine learning and the use of neural networks allow achieving higher accuracy in diff erentiating the types of retinal fluids and automating the quantitative determination of fl uid under the pigment epithelium. These technologies allow achieving a high level of compliance with manual expert assessment and increasing the accuracy and speed of predicting morphological results of treatment of pigment epithelium detachments.

About the Authors

E. V. Kozina
Krasnodar Branch of the S. Fyodorov Eye Microsurgery Federal State Institution 
Russian Federation

 Ophthalmologist

Krasnykh Partizan str. 6, Krasnodar 350012, Russian Federation 



S. N. Sakhnov
Krasnodar Branch of the S. Fyodorov Eye Microsurgery Federal State Institution; Kuban State Medical University 
Russian Federation

 Cand. Sc. (Med.), Cand. Sc. (Econ.), Director; Head of the Department of Eye Diseases

Krasnykh Partizan str. 6, Krasnodar 350012, Russian Federation 

Mitrofana Sedina str. 4, Krasnodar 350063, Russian Federation 



V. V. Myasnikova
Krasnodar Branch of the S. Fyodorov Eye Microsurgery Federal State Institution; Kuban State Medical University 
Russian Federation

 Dr. Sc. (Med.), Docent, Deputy Director for Science; Associate Professor
at the Department of Anesthesiology, Rheanimatology and Transfusiology of the Advanced Training and Professional Retraining Faculty

Krasnykh Partizan str. 6, Krasnodar 350012, Russian Federation 

Mitrofana Sedina str. 4, Krasnodar 350063, Russian Federation 



E. V. Bykova
Krasnodar Branch of the S. Fyodorov Eye Microsurgery Federal State Institution
Russian Federation

 Cand. Sc. (Med.), Head of the Department of Diagnostics, Ophthalmologist

Krasnykh Partizan str. 6, Krasnodar 350012, Russian Federation 



L. E. Aksenova
Krasnodar Branch of the S. Fyodorov Eye Microsurgery Federal State Institution 
Russian Federation

 Engineer for Scientifi c and Technical Information

 Krasnykh Partizan str. 6, Krasnodar 350012, Russian Federation 



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For citations:


Kozina E.V., Sakhnov S.N., Myasnikova V.V., Bykova E.V., Aksenova L.E. Modern trends in diagnostics and prediction of results of anti-vascular endothelial growth factor therapy of pigment epithelial detachment in neovascular agerelated macular degeneration using deep machine learning method (literature review). Acta Biomedica Scientifica. 2021;6(6-1):190-203. (In Russ.) https://doi.org/10.29413/ABS.2021-6.6-1.22

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