Background: An increasing amount of people are globally affected by retinal diseases, such as diabetes, vascular occlusions, maculopathy, alterations of systemic circulation, and metabolic syndrome. Aim: This review will discuss novel technologies in and potential approaches to the detection and diagnosis of retinal diseases with the support of cutting-edge machines and artificial intelligence (AI). Methods: The demand for retinal diagnostic imaging exams has increased, but the number of eye physicians or technicians is too little to meet the request. Thus, algorithms based on AI have been used, representing valid support for early detection and helping doctors to give diagnoses and make differential diagnosis. AI helps patients living far from hub centers to have tests and quick initial diagnosis, allowing them not to waste time in movements and waiting time for medical reply. Results: Highly automated systems for screening, early diagnosis, grading and tailored therapy will facilitate the care of people, even in remote lands or countries. Conclusion: A potential massive and extensive use of AI might optimize the automated detection of tiny retinal alterations, allowing eye doctors to perform their best clinical assistance and to set the best options for the treatment of retinal diseases.

BACKGROUND: Corneal transplantation in keratoconus (KC) patients is generally considered to be successful with a high grade of patient satisfaction. Long-term studies suggest a 6% to 11% probability of KC recurrence manifested by keratometric instability and progressive corneal ectasia. METHODS: We propose to review the frequency, risk factors for the development, and the surgical options for the correction of high irregular astigmatism due to late graft ectasia following penetrating keratoplasty (PK). RESULTS: Post-keratoplasty ectasia is characterized by increasing corneal steepening with myopic shift and high irregular astigmatism, developing years or decades after PK, mostly occurring in KC patients. Contact lenses may adequately improve the visual acuity; however, because these patients are often elderly and intolerant to hard contact lenses, ultimately a surgical correction is proposed to the patient. Compressive suture and corneal wedge resection may improve corneal astigmatism, but the outcomes are unpredictable and often temporary. For this reason, a larger PK graft is often proposed for surgical rehabilitation with the consequence of removing more of the recipient’s healthy endothelium and exposing the patient to a renewed immunogenic stimulus and short-term graft failure for endothelial decompensation. More recently, lamellar keratoplasty using various techniques has been proposed as an alternative to PK in order to maximize the visual outcomes and minimize the complications. CONCLUSIONS: Management of advanced corneal ectasia is a significant challenge for corneal surgeons. Many surgical approaches have been developed, so there is a large arsenal of surgical operations to correct post-PK ectasia. Among them, large-diameter anterior lamellar keratoplasty may be a viable, safer, and effective alternative to PK for the correction of post-keratoplasty ectasia.

Background: If left untreated, glaucoma—the second most common cause of blindness worldwide—causes irreversible visual loss due to a gradual neurodegeneration of the retinal ganglion cells. Conventional techniques for identifying glaucoma, like optical coherence tomography (OCT) and visual field exams, are frequently laborious and dependent on subjective interpretation. Through the fast and accurate analysis of massive amounts of imaging data, artificial intelligence (AI), in particular machine learning (ML) and deep learning (DL), has emerged as a promising method to improve the early detection and management of glaucoma. Aims: The purpose of this study is to examine the current uses of AI in the early diagnosis, treatment, and detection of glaucoma while highlighting the advantages and drawbacks of different AI models and algorithms. In addition, it aims to determine how AI technologies might transform glaucoma treatment and suggest future lines of inquiry for this area of study. Methods: A thorough search of databases, including Web of Science, PubMed, and Scopus, was carried out to find pertinent papers released until August 2024. The inclusion criteria were limited to research published in English in peer-reviewed publications that used AI, ML, or DL to diagnose or treat glaucoma in human subjects. Articles were chosen and vetted according to their quality, contribution to the field, and relevancy. Results: Convolutional neural networks (CNNs) and other deep learning algorithms are among the AI models included in this paper that have been shown to have excellent sensitivity and specificity in identifying glaucomatous alterations in fundus photos, OCT scans, and visual field tests. By automating standard screening procedures, these models have demonstrated promise in distinguishing between glaucomatous and healthy eyes, forecasting the course of the disease, and possibly lessening the workload of physicians. Nonetheless, several significant obstacles remain, such as the requirement for various training datasets, outside validation, decision-making transparency, and handling moral and legal issues. Conclusions: Artificial intelligence (AI) holds great promise for improving the diagnosis and treatment of glaucoma by facilitating prompt and precise interpretation of imaging data and assisting in clinical decision making. To guarantee wider accessibility and better patient results, future research should create strong generalizable AI models validated in various populations, address ethical and legal matters, and incorporate AI into clinical practice.

Blood-based preparations are used in clinical practice for the treatment of several eye disorders. The aim of this study is to analyze the effect of freeze-drying blood-based preparations on the levels of growth factors and wound healing behaviors in an in vitro model. Platelet-rich plasma (PRP) and serum (S) preparations from the same Cord Blood (CB) sample, prepared in both fresh frozen (FF) and freeze-dried (FD) forms (and then reconstituted), were analyzed for EGF and BDNF content (ELISA Quantikine kit). The human MIO-M1 glial cell line (Moorfield/Institute of Ophthalmology, London, UK) was incubated with FF and FD products and evaluated for cell migration with scratch-induced wounding (IncuCyte S3 Essen BioScience), proliferation with cyclin A2 and D1 gene expression, and activation with vimentin and GFAP gene expression. The FF and FD forms showed similar concentrations of EGF and BDNF in both the S and PRP preparations. The wound healing assay showed no significant difference between the FF and FD forms for both S and PRP. Additionally, cell migration, proliferation, and activation did not appear to change in the FD forms compared to the FF ones. Our study showed that reconstituted FD products maintained the growth factor concentrations and biological properties of FF products and could be used as a functional treatment option.

Objectives: To study the density, spacing, and regularity of retinal cone photoreceptors using an Adaptive Optics (AO) retinal camera (Rtx1^TM, Imagine Eyes, Orsay, France) in patients with Primary Open Angle Glaucoma (POAG) and to compare the outcomes with those of healthy age-matched control subjects. Methods: The study included 43 eyes with POAG and 31 eyes of normal subjects. POAG patients were divided into three groups according to the severity of the visual field defect. The AO Rtx1^TM was used to obtain images of the parafoveal cone mosaic to calculate cone values. Analysis was performed at two and four degrees of eccentricity from the fovea along the four meridians (nasal, temporal, superior, inferior). Results: In POAG eyes, the mean ± standard deviation (SD) cone density at 2° considering all meridians was significantly lower than in normal controls (23,058.6 ± 3532.0 cones/mm², and 25,511.7 ± 3157.5 cones/mm², respectively; p = 0.003). Cone spacing was 7.3 ± 0.5 µm in POAG and 7.0 ± 0.4 µm in normal controls (p = 0.005), and cone regularity was 90.5 ± 4.9% and 93.5 ± 1.9% in POAG and normal controls, respectively (p < 0.001). At 4° similar trends were observed. However, no significant differences were found among patients with different severity of POAG (p > 0.05). Conclusions: Using AO Rtx1^TM, significant differences in retinal photoreceptors mosaic pattern were found between POAG eyes and age-matched controls, indicating a reduction in photoreceptors in POAG. No significant differences in retinal photoreceptor values were found among the three POAG groups.

Introduction: We report a case and discuss the clinical characteristics and treatment of spontaneous Descemet membrane detachment (DMD). Case description: We describe a rare case of spontaneous DMD in a patient with prior anterior uveitis and provide a review of the current literature. A 20-year-old woman with a prior history of anterior uveitis presented with vision loss in the left eye. The slit-lamp examination showed corneal edema secondary to DMD, confirmed by anterior segment optical coherence tomography (AS-OCT). The patient underwent an intracameral injection of 20% sulphur hexafluoride (SF₆) with complete resolution of the DMD. Although rare, several cases of spontaneous DMD have been reported in the literature, mostly occurring after intraocular surgery. We searched the Pubmed database (1949–2021) for peer-reviewed publications relevant to the topic of spontaneous DMD. Discussion: The pathogenesis of spontaneous DMD is complex and depends on several factors. It can occur due to anatomical anomalies, inflammatory disease, trauma, chemical injuries, and surgical or laser procedures. In most cases, early diagnosis and appropriate management led to resolution.