Artificial intelligence in ophthalmology.

One of the fields of medicine in which artificial intelligence techniques have made progress is ophthalmology. Artificial intelligence (A.I.) applications for preventing vision loss in eye illnesses have developed quickly. Artificial intelligence uses computer programs to execute various activities while mimicking human thought. Machine learning techniques are frequently utilized in the field of ophthalmology. Ophthalmology holds great promise for advancing artificial intelligence, thanks to various digital methods like optical coherence tomography (OCT) and visual field testing. Artificial intelligence has been used in ophthalmology to treat eye conditions impairing vision, including macular holes (M.H.), age-related macular degeneration (AMD), diabetic retinopathy, glaucoma, and cataracts. The more common occurrence of these diseases has led to artificial intelligence development. It is important to get annual screenings to detect eye diseases such as glaucoma, diabetic retinopathy, and age-related macular degeneration. These conditions can cause decreased visual acuity, and it is necessary to identify any changes or progression in the disease to receive appropriate treatment. Numerous studies have been conducted based on artificial intelligence using different algorithms to improve and simplify current medical practice and for early detection of eye diseases to prevent vision loss. Abbreviations: AI = artificial intelligence, AMD = age-related macular degeneration, ANN = artificial neural networks, AAO = American Academy of Ophthalmology, CNN = convolutional neural network, DL = deep learning, DVP = deep vascular plexus, FDA = Food and Drug Administration, GCL = ganglion cell layer, IDP = Iowa Detection Program, ML = Machine learning techniques, MH = macular holes, MTANN = massive training of the artificial neural network, NLP = natural language processing methods, OCT = optical coherence tomography, RBS = Radial Basis Function, RNFL = nerve fiber layer, ROP = Retinopathy of Prematurity, SAP = standard automated perimetry, SVP = Superficial vascular plexus, U.S. = United States, VEGF = vascular endothelial growth factor.

Aflibercept Versus Bevacizumab as First-Line Therapy in Age-Related Macular Degeneration.

BACKGROUND: AMD (age-related macular degeneration) is the main cause of central vision loss in the population over 60 years old. AMD does not affect peripheral vision and complete blindness does not occur, instead, central vision is affected both for distance and for near. The purpose of this study is to evaluate the neovascular form of AMD treatment and compare ocular and systemic effects after intravitreal injection of aflibercept, respectively after bevacizumab when administered in comparable dosages and regimens. We conducted a retrospective, single-center study from June 2021 to December 2022 and enrolled 20 patients with neovascular AMD who had not received any prior treatment for this condition. We randomly assigned them to two groups of 10: group one received aflibercept and group two received bevacizumab as intravitreal injections under aseptic conditions. We excluded 2 patients who did not meet the criteria and ended up with two groups of 9 patients who received monocular treatment. We gave the patients 3 monthly injections of anti-VEGF agent and followed them up at 1 month, 3 months, and 9 months after the treatment. We assessed their visual acuity, intraocular pressure and OCT appearance at each follow-up visit. The primary outcome was visual acuity. All 18 patients included in the study reported an improvement in visual acuity after the intervention. When comparing the two anti-VEGF agents, data revealed the effect of aflibercept was prompter and more long-lasting. Areas of retinal ischemia appeared in both cases. However, they were observed faster in the case of patients treated with aflibercept. Thus, neovascular AMD is a disease that occurs with age, it can be early detected by OCT and slowed the progression to central blindness with intravitreal treatment.