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Medicina
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Advances in Diagnosis and Therapies of Ocular Diseases
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Advances in Diagnosis and Therapies of Ocular Diseases

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Ophthalmology".

Deadline for manuscript submissions: 10 January 2026 | Viewed by 3633

Special Issue Editor

Dr. Ana Maria Dascalu

E-Mail Website
Guest Editor
Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy Bucharest, 020021 Bucharest, Romania
Interests: diabetic retinopathy; glaucoma; age related macular degeneration; optic neuropathies; inflammatory biomarkers
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Despite continuous improvements in diagnosis and therapy, blindness and visual impairment are still significant challenges in healthcare systems, in the context of increasing population and aging globally. Cataract, glaucoma, age-related macular degeneration, and uncorrected refraction errors are listed among the top causes of visual impairment worldwide. In recent years, there have been significant achievements regarding ophthalmic imaging and development of surgical techniques and devices. In the era of artificial intelligence and telemedicine, new techniques were designed to improve screening and monitoring of chronic ophthalmic diseases.

In this Special Issue, we would like to invite you to submit papers (original research and reviews) thematically connected to the scope of this Special Issue. We are particularly, but not exclusively, interested in papers focused on the recent development in diagnosis and therapy of ophthalmic diseases, management of postoperative complications, new biomarkers of diagnosis and monitoring, the impact of COVID-19 pandemic on the ocular diseases, and the use of artificial intelligence-based models in ophthalmology.

Dr. Ana Maria Dascalu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Medicina is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • early biomarkers
  • retinal and optic nerve imaging
  • ocular surgery
  • glaucoma drainage devices
  • neuroprotection
  • refraction errors
  • artificial intelligence

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Published Papers (4 papers)

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Research

Jump to: Review, Other

12 pages, 557 KiB  
Article
Advancing Diagnostics with Semi-Automatic Tear Meniscus Central Area Measurement for Aqueous Deficient Dry Eye Discrimination
by Hugo Pena-Verdeal, Jacobo Garcia-Queiruga, Belen Sabucedo-Villamarin, Carlos Garcia-Resua, Maria J. Giraldez and Eva Yebra-Pimentel
Medicina 2025, 61(8), 1322; https://doi.org/10.3390/medicina61081322 - 22 Jul 2025
Viewed by 225
Abstract
Background and Objectives: To clinically validate a semi-automatic measurement of Tear Meniscus Central Area (TMCA) to differentiate between Non-Aqueous Deficient Dry Eye (Non-ADDE) and Aqueous Deficient Dry Eye (ADDE) patients. Materials and Methods: 120 volunteer participants were included in the study. Following [...] Read more.
Background and Objectives: To clinically validate a semi-automatic measurement of Tear Meniscus Central Area (TMCA) to differentiate between Non-Aqueous Deficient Dry Eye (Non-ADDE) and Aqueous Deficient Dry Eye (ADDE) patients. Materials and Methods: 120 volunteer participants were included in the study. Following TFOS DEWS II diagnostic criteria, a battery of tests was conducted for dry eye diagnosis: Ocular Surface Disease Index questionnaire, tear film osmolarity, tear film break-up time, and corneal staining. Additionally, lower tear meniscus videos were captured with Tearscope illumination and, separately, with fluorescein using slit-lamp blue light and a yellow filter. Tear meniscus height was measured from Tearscope videos to differentiate Non-ADDE from ADDE participants, while TMCA was obtained from fluorescein videos. Both parameters were analyzed using the open-source software NIH ImageJ. Results: Receiver Operating Characteristics analysis showed that semi-automatic TMCA evaluation had significant diagnostic capability to differentiate between Non-ADDE and ADDE participants, with an optimal cut-off value to differentiate between the two groups of 54.62 mm2 (Area Under the Curve = 0.714 ± 0.051, p < 0.001; specificity: 71.7%; sensitivity: 68.9%). Conclusions: The semi-automatic TMCA evaluation showed preliminary valuable results as a diagnostic tool for distinguishing between ADDE and Non-ADDE individuals. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Therapies of Ocular Diseases)
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14 pages, 2091 KiB  
Article
PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data
by Mousa Moradi, Saber Kazeminasab Hashemabad, Daniel M. Vu, Allison R. Soneru, Asahi Fujita, Mengyu Wang, Tobias Elze, Mohammad Eslami and Nazlee Zebardast
Medicina 2025, 61(3), 541; https://doi.org/10.3390/medicina61030541 - 20 Mar 2025
Viewed by 737
Abstract
Background and Objectives: Glaucoma (GL) classification is crucial for early diagnosis and treatment, yet relying solely on stand-alone models or International Classification of Diseases (ICD) codes is insufficient due to limited predictive power and inconsistencies in clinical labeling. This study aims to [...] Read more.
Background and Objectives: Glaucoma (GL) classification is crucial for early diagnosis and treatment, yet relying solely on stand-alone models or International Classification of Diseases (ICD) codes is insufficient due to limited predictive power and inconsistencies in clinical labeling. This study aims to improve GL classification using stacked weight-based machine learning models. Materials and Methods: We analyzed a subset of 33,636 participants (58% female) with 340,444 visual fields (VFs) from the Mass Eye and Ear (MEE) dataset. Five clinically relevant GL detection models (LoGTS, UKGTS, Kang, HAP2_part1, and Foster) were selected to serve as base models. Two multi-layer perceptron (MLP) models were trained using 52 total deviation (TD) and pattern deviation (PD) values from Humphrey field analyzer (HFA) 24-2 VF tests, along with four clinical variables (age, gender, follow-up time, and race) to extract model weights. These weights were then utilized to train three meta-learners, including logistic regression (LR), extreme gradient boosting (XGB), and MLP, to classify cases as GL or non-GL. Results: The MLP meta-learner achieved the highest performance, with an accuracy of 96.43%, an F-score of 96.01%, and an AUC of 97.96%, while also demonstrating the lowest prediction uncertainty (0.08 ± 0.13). XGB followed with 92.86% accuracy, a 92.31% F-score, and a 96.10% AUC. LR had the lowest performance, with 89.29% accuracy, an 86.96% F-score, and a 94.81% AUC, as well as the highest uncertainty (0.58 ± 0.07). Permutation importance analysis revealed that the superior temporal sector was the most influential VF feature, with importance scores of 0.08 in Kang’s and 0.04 in HAP2_part1 models. Among clinical variables, age was the strongest contributor (score = 0.3). Conclusions: The meta-learner outperformed stand-alone models in GL classification, achieving an accuracy improvement of 8.92% over the best-performing stand-alone model (LoGTS with 87.51%), offering a valuable tool for automated glaucoma detection. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Therapies of Ocular Diseases)
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Review

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13 pages, 1806 KiB  
Review
Refractive Alterations in Marfan Syndrome: A Narrative Review
by Dionysios G. Vakalopoulos, Stamatios Lampsas, Marina S. Chatzea, Konstantina A. Togka, Vasileios Tsagkogiannis, Dimitra Mitsopoulou, Lida Lalou, Aikaterini Lampsa, Marios Katsimpras, Petros Petrou and George D. Kymionis
Medicina 2025, 61(2), 250; https://doi.org/10.3390/medicina61020250 - 1 Feb 2025
Cited by 1 | Viewed by 1919
Abstract
Marfan syndrome (MFS) is a genetic disorder that affects the connective tissue in several systems, with ocular, cardiovascular, and skeletal system manifestations. Its ocular manifestations include ectopia lentis (EL), myopia, astigmatism, and corneal abnormalities. This review examines refractive alterations related to MFS such [...] Read more.
Marfan syndrome (MFS) is a genetic disorder that affects the connective tissue in several systems, with ocular, cardiovascular, and skeletal system manifestations. Its ocular manifestations include ectopia lentis (EL), myopia, astigmatism, and corneal abnormalities. This review examines refractive alterations related to MFS such as EL, microspherophakia, lens coloboma, altered corneal biomechanics (flattening, thinning, and astigmatism), and myopia and their impact on visual acuity. The pathogenesis of these manifestations stems from mutations in the FBN1 gene (encoding fibrillin-1). Moreover, the current medical and surgical management strategies for MFS-related refractive errors, including optical correction (eyeglasses, contact lenses, etc.), and surgical interventions like lensectomy, intraocular lens (IOL) implantation (anterior chamber, posterior chamber, scleral-fixated, iris-fixated), and the use of capsular tension rings/segments are further discussed. Considering the likelihood of underdiagnosing and underestimating ocular involvement in MFS, this updated review highlights the critical need to identify and address these refractive issues to enhance the visual outcomes for those affected. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Therapies of Ocular Diseases)
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Other

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19 pages, 2934 KiB  
Systematic Review
A Systematic Review and Meta-Analysis of the Success Rate of the Primary Probing in Pediatric Patients with Congenital Nasolacrimal Duct Obstruction in Different Age Groups
by Zhansaya Sultanbayeva, Auyeskhan Dzhumabekov, Neilya Aldasheva, Botagoz Issergepova, Yerzhan Kuanyshbekov, Maiya Taushanova and Indira Karibayeva
Medicina 2025, 61(8), 1432; https://doi.org/10.3390/medicina61081432 - 8 Aug 2025
Viewed by 275
Abstract
Background: Primary probing of the nasolacrimal duct remains the first-line surgical intervention for congenital nasolacrimal duct obstruction (CNLDO) in infants and young children. However, age-dependent success rates have been less thoroughly investigated. This systematic review and meta-analysis aims to evaluate the age-related success [...] Read more.
Background: Primary probing of the nasolacrimal duct remains the first-line surgical intervention for congenital nasolacrimal duct obstruction (CNLDO) in infants and young children. However, age-dependent success rates have been less thoroughly investigated. This systematic review and meta-analysis aims to evaluate the age-related success rates of primary probing in children with CNLDO. Methods: Systematic literature searches were performed in PubMed, Web of Science, Scopus, ScienceDirect, and Google Scholar in May 2025. A random-effects model was applied to estimate the overall success rate, while sensitivity analyses and publication bias assessments were performed to explore sources of variability. All statistical analyses were carried out using the “meta” and “metafor” packages in RStudio. Results: This meta-analysis reveals age-stratified success rates of primary probing for CNLDO: the highest pooled success rate occurred in infants aged 0–6 months (90.67%, I2 = 81%, p < 0.01), with procedures under general anesthesia achieving 95.42% (I2 = 50%; p = 0.11) efficacy. Success rates remained favorable in the 6–12 month group (85.18%, I2 = 86%, p < 0.01 overall; 89.60% with general anesthesia) but declined progressively thereafter (82.34%, I2 = 78%, p < 0.01 at 12–24 months). While a modest rebound occurred in the 24–48 month group (85.33%, I2 = 69%, p < 0.01), the oldest cohort (48+ months) demonstrated markedly reduced efficacy (63.47%, I2 = 66%, p = 0.05), despite exclusive use of general anesthesia. Conclusion: Primary probing yields the most favorable outcomes when conducted before 12 months of age, particularly under general anesthesia. Nonetheless, the overall certainty of evidence is low—mainly due to variability across studies—which should be taken into account in clinical decision-making. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Therapies of Ocular Diseases)
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