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This article reviews literature on the use of artificial intelligence (AI) methods for the diagnosis and treatment of primary angle-closure disease (PACD). The review describes how AI techniques enhance the efficiency of population screening for anterior chamber angle closure, presents technologies utilizing deep learning, including neural networks, for the analysis of large datasets obtained through anterior segment imaging methods, such as anterior segment optical coherence tomography (AS-OCT), digital gonioscopy, and ultrasound biomicroscopy, and discusses methods for treating PACD with the help of AI. Integration of deep learning and imaging techniques represents a crucial step in optimizing the diagnosis and treatment of PACD, reducing the burden on the healthcare system.

This article reviews literature on the use of artificial intelligence (AI) for screening, diagnosis, monitoring and treatment of glaucoma. The first part of the review provides information how AI methods improve the effectiveness of glaucoma screening, presents the technologies using deep learning, including neural networks, for the analysis of big data obtained by methods of ocular imaging (fundus imaging, optical coherence tomography of the anterior and posterior eye segments, digital gonioscopy, ultrasound biomicroscopy, etc.), including a multimodal approach. The results found in the reviewed literature are contradictory, indicating that improvement of the AI models requires further research and a standardized approach. The use of neural networks for timely detection of glaucoma based on multimodal imaging will reduce the risk of blindness associated with glaucoma.

The second part of the literature review on the application of artificial intelligence (AI) methods for screening, diagnosing, monitoring, and treating glaucoma provides information on how AI methods enhance the effectiveness of glaucoma monitoring and treatment, presents technologies that use machine learning, including neural networks, to predict disease progression and determine the need for anti-glaucoma surgery. The article also discusses the methods of personalized treatment based on projection machine learning methods and outlines the problems and prospects of using AI in solving tasks related to screening, diagnosing, and treating glaucoma.

Purpose: This study compares and evaluates the parameters of iridotrabecular contact (ITC) in patients with primary angle closure disease (PACD) with natural lenses and pseudophakia based on anterior segment imaging data from swept-source optical coherence tomography (SS-OCT)., Material and Methods: This retrospective study analyzed data from 92 patients aged 32 to 89 years, and included 56 patients with PACD (43 with natural lenses and 13 with pseudophakia) and 36 in the control group (21 with natural lenses and 15 with pseudophakia). All participants underwent SS-OCT (CASIA2; Tomey Corporation, Japan), which included an assessment of the ITC Index and ITC Area., Results: The ITC parameters in PACD, both with and without pseudophakia, were significantly higher than in the corresponding control groups. In pseudophakic PACD patients, the ITC Index was 8.7±7.2%, and the ITC Area was 0.82±0.54 mm², compared to 0.00±0.00% and 0.00±0.00 mm² in the pseudophakic control group (all p =0.01). For the PACD group with natural lenses, the ITC Index was 45.4±21.8%, and the ITC Area was 5.81±3.9 mm², compared to 0.05±0.11% and 0.56±1.17 mm² in the corresponding control group (all p =0.00). Significantly higher ITC values were found in the PACD group with natural lenses compared to those with pseudophakia (ITC Index 45.4±21.8% vs. 8.7±7.2%, respectively, p =0.00; ITC Area 5.81±3.9 mm² vs. 0.82±0.54 mm², respectively, p =0.00)., Conclusion: Significantly higher ITC values were demonstrated in PACD patients with natural lenses compared to those with pseudophakia. However, the persistence of residual angle closure in primary angle-closure glaucoma after lens extraction suggests the feasibility of proactive surgical intervention at earlier stages of the disease.

Background: Primary angle closure glaucoma (PACG) is still one of the leading causes of irreversible blindness, with a trend towards an increase in the number of patients to 32.04 million by 2040, an increase of 58.4% compared with 2013. Health risk assessment based on multi-level diagnostics and machine learning-couched treatment algorithms tailored to individualized profile of patients with primary anterior chamber angle closure are considered essential tools to reverse the trend and protect vulnerable subpopulations against health-to-disease progression., Aim: To develop a methodology for personalized choice of an effective method of primary angle closure (PAC) treatment based on comparing the prognosis of intraocular pressure (IOP) changes due to laser peripheral iridotomy (LPI) or lens extraction (LE)., Methods: The multi-parametric data analysis was used to develop models predicting individual outcomes of the primary angle closure (PAC) treatment with LPI and LE. For doing this, we suggested a positive dynamics in the intraocular pressure (IOP) after treatment, as the objective measure of a successful treatment. Thirty-seven anatomical parameters have been considered by applying artificial intelligence to the prospective study on 30 (LE) + 30 (LPI) patients with PAC., Results and Data Interpretation in the Framework of 3p Medicine: Based on the anatomical and topographic features of the patients with PAC, mathematical models have been developed that provide a personalized choice of LE or LPI in the treatment. Multi-level diagnostics is the key tool in the overall advanced approach. To this end, for the future application of AI in the area, it is strongly recommended to consider the following:Clinically relevant phenotyping applicable to advanced population screeningSystemic effects causing suboptimal health conditions considered in order to cost-effectively protect affected individuals against health-to-disease transitionClinically relevant health risk assessment utilizing health/disease-specific molecular patterns detectable in body fluids with high predictive power such as a comprehensive tear fluid analysis., Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00337-1., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s) 2023.)

Prcis: Treatment strategy of primary angle closure (PAC) is not clear due to the large number of clinical and anatomic-topographic parameters in PAC, influencing the treatment algorithm. Using the machine learning method DD-SIMCA, we justify the expediency of early lens extraction (LE) in PAC., Purpose: To compare the anatomic and functional efficacy of LE and laser peripheral iridotomy (LPI) in patients with PAC using Machine Learning., Materials and Methods: This prospective study included 120 patients aged 41-80 years: 60 eyes with PAC, 30 with PAC suspects, and 30 with healthy eyes (control). Thirty PAC eyes with intraocular pressure (IOP) up to 30 mm Hg were treated using LE with intraocular lens implantation and 30 eyes with LPI. All subjects underwent Swept Source optical coherence tomography. We analyzed 35 parameters of each eye including the lens vault, the choroidal thickness, the anterior chamber angle, and iris specifications such as iris curvature. Considering the correlations between them, the machine learning method DD-SIMCA 1-class classification was applied: the proximity of each sample to the target class (control) was characterized by the total distance to it., Results: After LE, IOP was significantly lower than after LPI ( P =0). Every third eye with PAC after LE reached the target class: specificity according to DD-SIMCA equals 0.67. This was not observed for the eyes after LPI: specificity equals 1.0. After LE, all parameters of the anterior chamber angle did not differ from the control (all P >0.05). After LPI, there was an increase in anterior chamber depth ( P =0) and a decrease in lens vault ( P =0), but results comparable to the control were achieved only for iris curvature ( P =1.000)., Conclusion: The efficacy of LE in PAC is higher than LPI due to the better postoperative anterior chamber topography and lower IOP. This study lends further clinical and anatomic support to the emerging notion of LE as an effective treatment for PAC., Competing Interests: Disclosure: The authors declare no conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

The article reviews literature data on the search for predictors of the success of laser peripheral iridotomy (LPI) and lensectomy in the early stages of primary angle closure disease (PACD) and presents a trend analysis of the studies conducted on individuals identified as primary angle closure suspects (PACs) and those with primary angle closure (PAC). The concept of the review was determined by the ambiguous choice of treatment for patients at the stage of PAC onset. Determining the success predictors of LPI or lensectomy plays a key role in optimizing the treatment of PACD. The results of literature analysis are contradictory, which indicates the need for further research taking into account modern methods of visualization of the eye structures such as optical coherence tomography (OCT), Swept Source OCT (SS-OCT), and the use of uniform criteria for evaluating the effectiveness of treatment.

Objective: To review the literature devoted to the problem of primary anterior chamber angle closure (PAC) and the development of this pathology from glaucoma suspect to primary angle closure glaucoma. The paper includes a trend analysis of the studies concerning primary angle closure suspects (PACS). The concept of this review is conditioned by the conflicting strategies for treating patients with initial PAC without glaucomatous optic neuropathy. Solving the problem of angle closure plays a key role in preventing the development of PAC glaucoma, which is the world's leading cause of irreversible blindness. This part of the review provides information on the frequency and rate of disease progression in PACS. The analyzed literature data is contradictory and indicates the need for further search that would consider a standardized approach to defining the concept of PAC disease, demographic factors and unified examination methods for generalizing and systematizing data in order to draw out unified treatment recommendations.

Purpose: To compare microcirculatory changes in patients with early stages of primary angle closure disease (PACD) and primary open-angle glaucoma (POAG)., Material and Methods: The study retrospectively analyzed the clinical data of 60 eyes with PACD, 30 with initial POAG, and 30 eyes without any ophthalmic pathologies. Vessel density (VD) in the optic nerve head and peripapillary retina (wiVD Disc), as well as in the inner layers of fovea and parafovea (wiVD Macula) and their different sectors were determined in all patients by optical coherence tomography angiography (OCTA). The correlation of VD with axial length (AL), anterior chamber depth (ACD), lens thickness (TL), and corneal-compensated intraocular pressure (IOPcc) was assessed., Results: The wiVD Disc in PACD (42.47±4.23%) was lower than in POAG eyes (47.46±2.10%), p <0.001, but the difference for wiVD Macula was not significant: 41.71±4.55% and 39.29±2.46%, respectively ( p =0.47). In both PACD and POAG, all OCTA parameters were lower than in normal eyes: p =0.000 for both wiVD Disc and wiVD Macula. WiVD Disc correlated with ACD both in PACD ( r =0.724, p =0.012) and in POAG ( r = 0.685, p =0.012), but a correlation with IOPcc was found only in PACD ( r = -0.670, p =0.033). The largest number of inverse correlations was found between TL and VD both for wiVD Disc ( r = -0.714, p =0.006) and the parameters of macular area (in para- and perifovea)., Conclusion: OCTA parameters differ significantly from the norm even in the early stages of both PACD and POAG. In PACD, there was a significant decrease in microcirculation in the peripapillary retina compared to POAG, which had an inverse correlation with IOPcc; there was also an inverse correlation of OCTA parameters in the optic nerve head and macula with lens thickness.

Objective: To review the literature devoted to the search of predictors of primary angle closure (PAC) progression as an important link in the pathogenesis of primary angle-closure glaucoma. This part presents a cluster analysis, describes the mechanisms of PAC development, and considers the studies aimed at discovering the risk factors for the progression of primary angle closure suspect into true angle closure. The results of the analyzed literature are ambiguous, indicating the need for further research that would involve strict inclusion criteria, and a standard approach to defining the primary angle closure disease and expanding the diagnostic parameters, in which a key role belongs to anterior segment optical coherence tomography (AS-OCT).