Keratoconus Diagnosis and Treatment: Recent Advances and Future Directions

Studying the effect of keratoconus severity on the accuracy of intraocular lens power calculation using newer keratoconus-specific formulas

PURPOSE

to study the effect of keratoconus severity on the accuracy of intraocular lens power calculation using newer keratoconus (KC) specific formulas.

METHODS

This was a retrospective case series that included 99 eyes from 99 patients. The included patients were further subdivided into 3 groups according to keratoconus severity. The results of various IOL power calculation formulas were analyzed in this study. Two KC specific formulas were employed: Barrett True K KC and Kane KC. Additionally, the following formulas were utilized: Barrett Universal II (BUII), EVO 2.0, Hoffer QST, Kane, and PEARL-DGS.

RESULTS

The Kane KC was the only formula to show a myopic mean prediction error (- 0.76 ± 1.06 D). BUII and Barrett True K KC formulas showed the least mean and median absolute errors. The median absolute error (MedAE) for BUII and Barrett True K KC was 0.34 and 0.35 D respectively. BUII and Barrett True K KC formulas had the highest cases within ± 0.25 D of the intended refraction (42.42% and 39.39%, respectively). In severe KC eyes, the MedAE for Barrett True K KC and BUII formulas was 0.56 and 0.46 D respectively. In severe KC eyes, Barrett True K KC and BUII formulas showed the highest cases within ± 0.25 D of the intended refraction (27.27% and 27.27%, respectively).

CONCLUSION

most non KC specific IOL power calculation formulas perform in an acceptable way in mild KC eyes. In moderate and severe KC eyes, the KC specific formulas perform better than the standard formulas. Barrett True K KC formula performed better than Kane KC in moderate and severe KC eyes. BUII formula was the best performing non KC specific formula in moderate and severe KC eyes.

Application of stem cell-derived exosomes in anterior segment eye diseases: A comprehensive update review

Mesenchymal stem cell (MSC) therapy has emerged as a promising approach for addressing various eye-related conditions. Yet, its clinical application faces challenges due to issues such as limited biocompatibility and difficulties in effectively delivering treatment to specific ocular tissues. Recent studies have shifted attention towards MSC-derived exosomes, which share similar regenerative, reparative, and immunomodulatory capabilities with their origin cells. This review delves into the latest research on the use of MSC-derived exosomes for treating anterior segment diseases of the eye. It explores the exosomes' composition, biological functions, and the methods used for their isolation, as well as their roles in disease progression, diagnosis, and therapy. The review critically assesses the therapeutic advantages and mechanisms of action of MSC-derived exosomes in treating conditions like dry eye disease, Sjogren's syndrome, keratoconus, corneal lesions, and corneal allograft rejection. Additionally, it discusses the obstacles and future prospects of employing MSC-derived exosomes as innovative therapies for anterior segment eye diseases. This comprehensive overview underscores the significant potential of MSC-derived exosomes in transforming the treatment paradigm for anterior segment eye disorders, while also highlighting the necessity for further research to enhance their clinical application.

Advances in machine learning for keratoconus diagnosis

PURPOSE

To review studies reporting the role of Machine Learning (ML) techniques in the diagnosis of keratoconus (KC) over the past decade, shedding light on recent developments while also highlighting the existing gaps between academic research and practical implementation in clinical settings.

METHODS

The review process begins with a systematic search of primary digital libraries using relevant keywords. A rigorous set of inclusion and exclusion criteria is then applied, resulting in the identification of 62 articles for analysis. Key research questions are formulated to address advancements in ML for KC diagnosis, corneal imaging modalities, types of datasets utilised, and the spectrum of KC conditions investigated over the past decade. A significant gap between academic research and practical implementation in clinical settings is identified, forming the basis for actionable recommendations tailored for both ML developers and ophthalmologists. Additionally, a proposed roadmap model is presented to facilitate the integration of ML models into clinical practice, enhancing diagnostic accuracy and patient care.

RESULTS

The analysis revealed that the diagnosis of KC predominantly relies on supervised classifiers (97%), with Random Forest being the most used algorithm (27%), followed by Deep Learning including Convolution Neural Networks (16%), Feedforward and Feedback Neural Networks (12%), and Support Vector Machines (12%). Pentacam is identified as the leading corneal imaging modality (56%), and a substantial majority of studies (91%) utilize local datasets, primarily consisting of numerical corneal parameters (77%). The most studied KC conditions were non-KC (NKC) vs. clinical KC (CKC) (29%), NKC vs. Subclinical KC (SCKC) (24%), NKC vs. SCKC vs. CKC (20%), SCKC vs. CKC (7%). However, only 20% of studies focused on addressing KC severity stages, emphasizing the need for more research in this area. These findings highlight the current landscape of ML in KC diagnosis and uncover existing challenges, and suggest potential avenues for further research and development, with particular emphasis on the dominance of certain algorithms and imaging modalities.

CONCLUSION

Key obstacles include the lack of consensus on an objective diagnostic standard for early KC detection and severity staging, limited multidisciplinary collaboration, and restricted access to public datasets. Further research is crucial to overcome these challenges and apply findings in clinical practice.

Autorefraction versus subjective refraction in high astigmatism

AIM

To compare the subjective refraction data with auto-refraction findings in high astigmatisms.

METHODS

In a cross-sectional study, sampling was done from in different geographic regions in Iran using a multistage random cluster sampling method. All study participants underwent cycloplegic auto-refraction and subjective refraction using the red-green test.

RESULTS

In this study, 277 eyes of 158 students aged 8 to 15y were analyzed. According to the results, the mean difference between subjective refraction and autorefraction in measuring sphere, cylinder, spherical equivalent, J0, and J45 was -0.18±0.76, -0.36±0.40, -0.36±0.79, 0.15±0.20, and 0.05±0.21 respectively. The correlation of these two refraction methods in measuring the aforementioned indices was 0.963, 0.898, 0.960, 0.931, and 0.948 respectively. The 95% limits of agreement of the two methods in measuring the above indices were -1.66 to 1.31, -1.14 to 0.42, -1.91 to 1.19, -0.24 to 0.54, and -0.36 to 0.47 respectively. The agreement between the two methods decreased with increasing cylinder power, and the best agreement was found in myopic individuals.

CONCLUSION

The measurements obtained by autorefractometer have a significantly higher cylinder average compared to subjective refraction. However, in the cylinder range of 4-5 diopters, the values of J0 and J45 do not have a high correlation.

Evaluation of Responses to Questions About Keratoconus Using ChatGPT-4.0, Google Gemini and Microsoft Copilot: A Comparative Study of Large Language Models on Keratoconus

OBJECTIVES

Large language models (LLMs) are increasingly being used today and are becoming increasingly important for providing accurate clinical information to patients and physicians. This study aimed to evaluate the effectiveness of generative pre-trained transforme-4.0 (ChatGPT-4.0), Google Gemini, and Microsoft Copilot LLMs in responding to patient questions regarding keratoconus.

METHODS

The LLMs' responses to the 25 most common questions about keratoconus asked by real-life patients were blindly rated by two ophthalmologists using a 5-point Likert scale. In addition, the DISCERN scale was used to evaluate the responses of the language models in terms of reliability, and the Flesch reading ease and Flesch-Kincaid grade level indices were used to determine readability.

RESULTS

ChatGPT-4.0 provided more detailed and accurate answers to patients' questions about keratoconus than Google Gemini and Microsoft Copilot, with 92% of the answers belonging to the "agree" or "strongly agree" categories. Significant differences were observed between all three LLMs on the Likert scale ( P <0.001).

CONCLUSIONS

Although the answers of ChatGPT-4.0 to questions about keratoconus were more complex for patients than those of other language programs, the information provided was reliable and accurate.

Developing and validating a comprehensive polygenic risk score to enhance keratoconus risk prediction

PURPOSE

This study aimed to develop and validate a comprehensive polygenic risk score (PRS) for keratoconus, enhancing the predictive accuracy for identifying individuals at increased risk, which is crucial for preventing keratoconus-associated visual impairment such as post-Laser-assisted in situ keratomileusis (LASIK) ectasia.

METHODS

We applied a multi-trait analysis approach (MTAG) to genome-wide association study data on keratoconus and quantitative keratoconus-related traits and used this to construct PRS models for keratoconus risk using several PRS methodologies. We evaluated the predictive performance of the PRSs in two biobanks: Estonian Biobank (EstBB; 375 keratoconus cases and 17 902 controls) and UK Biobank (UKB: 34 keratoconus cases and 1000 controls). Scores were compared using the area under the curve (AUC) and odds ratios (ORs) for various PRS models.

RESULTS

The PRS models demonstrated significant predictive capabilities in EstBB, with the SBayesRC model achieving the highest OR of 2.28 per standard deviation increase in PRS, with a model containing age, sex and PRS showing good predictive accuracy (AUC = 0.72). In UKB, we found that adding the best-performing PRS to a model containing corneal measurements increased the AUC from 0.84 to 0.88 (P = 0.012 for difference), with an OR of 4.26 per standard deviation increase in the PRS. These models showed improved predictive capability compared to previous keratoconus PRS.

CONCLUSION

The PRS models enhanced prediction of keratoconus risk, even with corneal measurements, showing potential for clinical use to identify individuals at high risk of keratoconus, and potentially help reduce the risk of post-LASIK ectasia.

Comparison of biomechanical indices measured by ocular response analyzer between children and elderly: a systematic review

Biomechanical study of the visual system by ocular response analyzer investigates the inter-structural biological relationships, mechanics, and function of the visual system. This review aimed to investigate the changes in corneal biomechanical parameters with age and sex. The articles published in PubMed between 2000 and 2021 were investigated and critiqued, and valid scientific evidence was collected, reviewed and concluded according to the inclusion and exclusion criteria. Most studies showed that corneal biomechanical changes occur infrequently in children up to the age of 20y, and with increasing age and wider age range, there was a significant decrease in corneal biomechanical indices, especially corneal hysteresis. In children and adults, most studies have shown that these biomechanical indicators, especially corneal resistance factor, were higher in females. Although hormonal changes may contribute to this finding, the role of axial length and other biometric indicators should not be ignored. The axial length, the intraocular pressure, and the corneal thickness are other factors associated with biomechanical parameters that should be taken into account in clinical diagnosis and management especially for patients undergoing refractive surgery as well as keratoconus patients.

Strategies for Early Keratoconus Diagnosis: A Narrative Review of Evaluating Affordable and Effective Detection Techniques

Keratoconus is a progressive corneal disorder that can lead to irreversible visual impairment if not detected early. Despite its high prevalence, early diagnosis is often delayed, especially in low-to-middle-income countries due to limited awareness and restricted access to advanced diagnostic tools such as corneal topography, tomography, optical coherence tomography, and corneal biomechanical assessments. These technologies are essential for identifying early-stage keratoconus, yet their high cost limits accessibility in resource-limited settings. While cost and portability are important for accessibility, the sensitivity and specificity of diagnostic tools must be considered as primary metrics to ensure accurate and effective detection of early keratoconus. This review examines both traditional and advanced diagnostic techniques, including the use of machine learning and artificial intelligence, to enhance early diagnosis. Artificial intelligence-based approaches show significant potential for transforming keratoconus diagnosis by improving the accuracy and sensitivity of early diagnosis, especially when combined with imaging devices. Notable innovations include tools such as SmartKC, a smartphone-based machine-learning application, mobile corneal topography through the null-screen test, and the Smartphone-based Keratograph, providing affordable and portable solutions. Additionally, contrast sensitivity testing demonstrates potential for keratoconus detection, although a precise platform for routine clinical use has yet to be established. The review emphasizes the need for increased awareness among clinicians, particularly in underserved regions, and advocates for the development of accessible, low-cost diagnostic tools. Further research is needed to validate the effectiveness of these emerging technologies in detecting early keratoconus.

Whole-genome sequencing identifies novel loci for keratoconus and facilitates risk stratification in a Han Chinese population

BACKGROUND

Keratoconus (KC) is a prevalent corneal condition with a modest genetic basis. Recent studies have reported significant genetic associations in multi-ethnic cohorts. However, the situation in the Chinese population remains unknown. This study was conducted to identify novel genetic variants linked to KC and to evaluate the potential applicability of a polygenic risk model in the Han Chinese population.

METHODS

A total of 830 individuals diagnosed with KC and 779 controls from a Chinese cohort were enrolled and genotyped by whole-genome sequencing (WGS). Common and rare variants were respectively subjected to single variant association analysis and gene-based burden analysis. Polygenic risk score (PRS) models were developed using top single-nucleotide polymorphisms (SNPs) identified from a multi-ethnic meta-analysis and then evaluated in the Chinese cohort.

RESULTS

The characterization of germline variants entailed correction for population stratification and validation of the East Asian ancestry of the included samples via principal component analysis. For rare protein-truncating variants (PTVs) with minor allele frequency (MAF) < 5%, ZC3H11B emerged as the top prioritized gene, albeit failing to reach the significance threshold. We detected three common variants reaching genome-wide significance (P ≤ 5 × 10-8), all of which are novel to KC. Our study validated three well known predisposition loci, COL5A1, EIF3A and FNDC3B. Additionally, a significant correlation of allelic effects was observed for suggestive SNPs between the largest multi-ethnic meta-genome-wide association study (GWAS) and our study. The PRS model, generated using top SNPs from the meta-GWAS, stratified individuals in the upper quartile, revealing up to a 2.16-fold increased risk for KC.

CONCLUSIONS

Our comprehensive WGS-based GWAS in a large Chinese cohort enhances the efficiency of array-based genetic studies, revealing novel genetic associations for KC and highlighting the potential for refining clinical decision-making and early prevention strategies.

Advances in Corneal Diagnostics Using Machine Learning

This paper provides comprehensive insights into the cornea and its diseases, with a particular focus on keratoconus. This paper explores the cornea's function in maintaining ocular health, detailing its anatomy, pathological conditions, and the latest developments in diagnostic techniques. Keratoconus is discussed extensively, covering its subtypes, etiology, clinical manifestations, and the application of the Q-value for quantification. Several diagnostic techniques, such as corneal topography, are crucial points of discussion. This paper also examines the use of machine learning models, specifically Decision Tree and Nearest Neighbor Analysis, which enhance the accuracy of diagnosing based on topographical corneal parameters from corneal topography. These models provide valuable insights into disease progression and aid in clinical decision making. Integrating these technologies in medical research opens promising avenues for enhanced disease detection. Our findings demonstrate the effectiveness of Decision Tree and Nearest Neighbor Analysis in classifying and predicting conditions based on corneal parameters. The Decision Tree achieved classification accuracy of 62% for training and 65.7% for testing, while Nearest Neighbor Analysis yielded 65.4% for training and 62.6% for holdout samples. These models offer valuable insights into the progression and severity of keratoconus, aiding clinicians in treatment and management decisions.

Exploring New Links Among Keratoconus, Hormonal Factors, and Medications: Insights From a Case-Control Study Utilizing the All of Us Database

Purpose

We aimed to identify clinical factors associated with keratoconus (KC) risk in the All of Us database.

Methods

This retrospective matched case-control study utilized patient data from the All of Us Research Program. All patients with a KC diagnosis (n = 572) were enrolled in the study and matched with three controls (n = 1716) based on age ± 1 year, race, ethnicity, and sex. The patients' medical histories, including diabetes, sleep apnea, obesity, smoking, ocular surface disease (encompassing dry eye, eczema, and allergic or atopic conjunctivitis), allergic rhinitis, pregnancy, estrogen-containing medications, tetracyclines, and vitamin C supplementation, were collected using electronic health records. Multivariable odds ratios (ORs) between KC and health history were calculated using the R programming language.

Results

The study included 2288 participants with an average age of 58.7 years. All included variables showed a significant positive correlation with KC except smoking history, which showed a negative correlation. The most significant correlations were ocular surface disease (OR = 6.04) and obesity (OR = 1.82). Significant positive associations were also identified for tetracyclines and estrogen-containing medications with KC. Smoking was negatively correlated.

Conclusions

In addition to previously known risk factors, patients with a history of increased estrogen exposure and tetracycline usage were more likely to have a KC diagnosis whereas those with a smoking history were less likely.

Translational Relevance

Understanding the risk factors for KC, including estrogen exposure and tetracycline medications, enhances our ability to identify at-risk patients and implement earlier screening, diagnosis, and interventions.

Transcriptomic analysis of keratoconus in Han Chinese patients: Insights into differential gene expression and ethnic-specific patterns

Keratoconus (KC) is a progressive corneal ectatic disorder with a high prevalence among Asians. This study aimed to explore the differential gene expression patterns in Han Chinese patients with KC, focusing on mRNAs and long noncoding RNAs (lncRNAs), to provide insights into the pathogenesis of the disease. Corneal tissues from KC patients and healthy controls were collected, and RNA sequencing was performed to profile mRNA and lncRNA expression. A total of 1973 differentially expressed mRNAs (DEGs) and 386 differentially expressed lncRNAs (DELs) were identified in KC-affected corneas. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed significant enrichment in pathways related to ECM modulation, PI3K-Akt pathway and calcium signaling pathway. Furthermore, protein-protein interaction (PPI) network highlighted hub genes involved in ECM remodeling and inflammatory responses. Co-expression analysis of lncRNAs and mRNAs further prioritized 13 DELs linked to these hub genes. RT-qPCR validation confirmed the differential expression of select candidates. A meta-analysis integrating seven datasets from diverse ethnic backgrounds was performed and it suggested ethnic-specific differences in gene expression patterns. This study sheds new light on the molecular mechanisms underlying KC in the Han Chinese population, pinpointing potential therapeutic targets. It also emphasizes the critical role of ethnic-specific gene expression patterns in KC research, highlighting a need for tailored approaches in disease management and treatment.

Blepharoptosis Associated With the Wearing of Hard Contact Lenses in Keratoconic Eyes

Keratoconus is a condition that causes progressive thinning and anterior protrusion of the cornea. Because of its irregular astigmatism, mild to moderate keratoconus is corrected with hard contact lenses (HCLs), but blepharoptosis due to the long-term wearing of HCLs is often a problem. In this study, we investigated blepharoptosis in HCL wearers with keratoconus. Thirty-seven keratoconic eyes were enrolled and divided into several groups according to their wearing history or age. Eyelid margin distance (EMD), margin light reflex distance-1 (MRD-1), and levator function (LF) were measured using a distantometer or anterior segment optical coherence tomography (AS-OCT). The EMD decreased with years of wear but showed no correlation with age; the MRD-1 decreased with years of wear and with older age; the LF showed no relationship with either years of wear or age. In the classification of ptosis, there was no severe ptosis in the present sample. The long-term wearing of HCLs is likely to cause blepharoptosis even in keratoconic eyes.

Customized Corneal Cross-Linking with Microneedle-Mediated Riboflavin Delivery for Keratoconus Treatment

In this study, a novel customized corneal cross-linking (CXL) treatment is explored that utilizes microneedles (MNs) for targeted riboflavin (RF) administration prior to the CXL procedure. Unlike the conventional "one-size-fits-all" approach, this protocol offers an option for more precise and efficacious treatment. To simulate a customized corneal crosslinking technique, four distinct microneedle (MN) molds designs, including circular, semi-circular, annular and butterfly shaped, are crafted for loading an optimized RF-hyaluronic acid solution and for the subsequent fabrication of MN arrays with varying morphologies. These MNs can gently puncture the corneal epithelium while preserving the integrity of the underlying stromal layer. Following the application of these microneedles, RF solution is replenished to enhance the RF content within the stroma through the punctures created by the MNs, resulting in exceptional customized corneal cross-linking effects that are comparable to the conventional epi-off CXL protocol. Additionally, it flattened the corneal curvature within the treated zone and facilitated rapid postoperative recovery of corneal tissue. These findings suggest that the integration of customized microneedle RF delivery with corneal crosslinking technology represents a potential novel treatment modality, holding promise for the tailored treatment of corneal pathologies, and offering a more precise and efficient alternative to traditional methods.

Herpes Simplex Keratitis Following Corneal Crosslinking for Keratoconus: A One-Year Case Series Follow-Up

Corneal crosslinking (CXL) is a medical procedure used to treat keratoconus. CXL works by strengthening the collagen fibers of the cornea through the application of riboflavin (vitamin B2) and ultraviolet (UV) light, which helps to stabilize the cornea and prevent further deterioration. There is a recognized risk that CXL can trigger the reactivation of dormant herpes simplex virus (HSV), leading to herpetic keratitis even in patients with no history of herpetic disease. We examined the medical history of 52 patients who underwent CXL procedures due to previously diagnosed keratoconus. We reviewed the patient's medical histories to assess whether there was a herpes labialis infection and/or herpetic keratitis. Altogether, 52 eyes (from 52 patients) were analyzed. Of those, four (7.69%) patients were diagnosed with epithelial herpetic keratitis on the 5-8th day after surgery. All four patients had a history of herpes labialis and no prior HSV keratitis infection. Two patients developed herpetic keratitis despite prophylactic therapy with acyclovir 5 days before surgery. A positive history of HSV lip infection before CXL was present in 18/52 (34.62%). During a one-year follow-up period, no patient experienced a recurrence. Close follow-up is crucial for diagnosing herpetic keratitis after corneal crosslinking. The use of prophylactic antiviral therapy in patients who are asymptomatic and have a history of recurrent herpes labialis does not guarantee the prevention of infection.

Topography-guided photorefractive keratectomy combined with accelerated corneal collagen cross-linking versus cross-linking alone for progressive keratoconus: a long-term prospective cohort study

Purpose

To comprehensively compare the long-term outcome of the combined topography guided photorefractive keratectomy (TG-PRK) with accelerated corneal cross-linking (ACXL) and ACXL alone in eyes with progressive keratoconus. The analysis focused on the changes in the detailed corneal aberrometric values.

Methods

This single-center, prospective cohort study included 28 patients (30 eyes) of the TG-PRK plus ACXL group and 14 patients (15 eyes) of the ACXL alone group. The mean duration of the follow-up was 44 ± 10.18 months (ranged from 31 to 65 months). The preoperative data and the postoperative measurement data at the last follow-up visit, including demographic data, uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), manifest refraction, corneal topography, pachymetry, aberrometry and densitometry were analyzed.

Results

The CDVA significantly improved in the TG-PRK plus ACXL group at the last follow-up visit (p = 0.006), while no significant improvement was found in the ACXL alone group (p = 0.432). The maximal keratometry of the anterior corneal surface (Kmax) of both groups significantly decreased at the last follow-up visit (p < 0.05). Compared with the ACXL alone group, the Kmax of the TG-PRK plus ACXL group showed a greater decline (p = 0.008). The total corneal aberrations, the corneal lower-order aberrations (LOAs), the corneal higher order aberrations (HOAs), the vertical coma and the spherical aberration (SA) at the 4.0 mm and 6.0 mm zone of the TG-PRK plus ACXL group significantly decreased at the last follow-up visit (all p < 0.05). The declines of the total corneal aberrations, the corneal LOAs, the corneal HOAs and the vertical coma at the 4.0 mm and 6.0 mm zone of the TG-PRK plus ACXL group were significantly higher than those in the ACXL alone group (p < 0.001).

Conclusion

Compared with ACXL alone, combined TG-PRK with ACXL procedure had a significantly higher reduction in the corneal HOAs and better CDVA, while providing a similar long-term stability and safety. For progressive keratoconus patients with adequate corneal thickness, the combined procedure might be a recommended treatment option.

Smart decision support system for keratoconus severity staging using corneal curvature and thinnest pachymetry indices

BACKGROUND

This study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements.

METHODS

A clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience.

RESULTS

The performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality.

CONCLUSION

The developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting.

Keratectasia severity staging and progression assessment based on the biomechanical E-staging

Until recently, corneal topography has been the gold standard in detecting keratectasia and monitoring its progression. The recently introduced ABCD tomographic keratoconus staging system focuses on anterior ("A") and posterior ("B") radius of curvature, thinnest corneal thickness ("C"), best-corrected visual acuity with spectacles ("D") and is supplemented with the introduction of the biomechanical E-staging (BEST, "E"). The need for biomechanical staging arose from the fact of altered biomechanical characteristics of keratectasia in comparison to healthy corneas. Ectatic corneas usually exhibit a biomechanical weakening and greater deformation than healthy corneas when exposed to a biomechanical stressor such as a standardized air puff indentation as provided by the Corvis ST® (CST, Oculus, Wetzlar, Germany). The BEST is based on the linear term of the Corvis Biomechanical Index (CBI) and provides a biomechanical keratoconus severity staging and progression assessment within the CST software. This review traces the development of the BEST as an addition to the tomographic ABCD staging system and highlights its strengths and limitations when applied in daily practice for the detection, monitoring and progression assessment in keratectasia.

Keratoconus: imaging modalities and management

Background

Keratoconus (KCN) is characterized by gradual thinning and steepening of the cornea, which can lead to significant vision problems owing to high astigmatism, corneal scarring, or even corneal perforation. The detection of KCN in its early stages is crucial for effective treatment. In this review, we describe current advances in the diagnosis and treatment of KCN.

Methods

This narrative review focuses on recent advancements in the diagnosis and treatment of KCN, especially evolving approaches and strategies. To ensure the inclusion of the most recent literature, relevant publications discussing advanced imaging techniques and treatment options for KCN were extensively gathered from the PubMed/MEDLINE and Google Scholar databases. The following index terms and keywords were used for the online search: keratoconus, diagnosis of keratoconus, advances in the diagnosis of keratoconus, topography or tomography, anterior segment optical coherence tomography, treatment of keratoconus, advances in the treatment of keratoconus, collagen crosslinking, intrastromal ring, keratoplasty, and new techniques in keratoconus.

Results

Various screening methods such as corneal topography, tomography, anterior segment optical coherence tomography, and assessment of corneal biomechanics have been developed to identify KCN in its early stages. After diagnosis, KCN management focuses on preventing disease progression. Corneal collagen crosslinking is a minimally invasive treatment that can slow or stop the progression of the condition. Recent research has also explored the use of copper sulfate eye drops (IVMED-80) as a noninvasive treatment to prevent the progression of KCN. Current treatment options for visual improvement include scleral lenses, intracorneal ring segments, corneal allogeneic intrastromal ring segments, and deep anterior lamellar keratoplasty. Recently, novel alternative procedures, such as isolated Bowman layer transplantation, either as a corneal stromal inlay or onlay, have demonstrated encouraging outcomes. Artificial intelligence has gained acceptance for providing best practices for the diagnosis and management of KCN, and the science of its application is contentiously debated; however, it may not have been sufficiently developed.

Conclusions

Early detection and advancements in screening methods using current imaging modalities have improved diagnosis of KCN. Improvement in the accuracy of current screening or diagnostic tests and comparison of their validities are achievable by well-designed, large-scale, prospective studies. The safety and effectiveness of emerging treatments for KCN are currently being investigated. There is an ongoing need for studies to track progress and evaluate clinicians' knowledge and practices in treating patients with KCN. Artificial intelligence capabilities in management approach considering the currently available imaging modalities and treatment options would best benefit the patient.

The Association of a Single Nucleotide Variant in COL5A1 to Early Onset Keratoconus and Pectus Excavatum-Convergence of Extracellular Matrix Pathologies

Keratoconus is a bilateral ocular condition characterized by irregularities and the thinning of the cornea. Decreased central corneal thickness is a hallmark of the condition, and numerous genes have played a role in altering corneal thickness and the subsequent development of keratoconus. Variants in the structural and regulatory genes of the extracellular matrix have been highly associated with keratoconus, as well as with pectus excavatum, a chest wall deformity commonly seen in connective tissue disorders. This report describes a patient with a c.1720-11T>A intronic variant in the collagen-encoding gene, COL5A1, who was diagnosed with early-onset keratoconus and demonstrated a significant pectus excavatum. This report associates a COL5A1 variant with these seemingly unrelated phenotypic associations, further advancing the literature on the topic.

Utility of artificial intelligence in the diagnosis and management of keratoconus: a systematic review

Introduction

The application of artificial intelligence (AI) systems in ophthalmology is rapidly expanding. Early detection and management of keratoconus is important for preventing disease progression and the need for corneal transplant. We review studies regarding the utility of AI in the diagnosis and management of keratoconus and other corneal ectasias.

Methods

We conducted a systematic search for relevant original, English-language research studies in the PubMed, Web of Science, Embase, and Cochrane databases from inception to October 31, 2023, using a combination of the following keywords: artificial intelligence, deep learning, machine learning, keratoconus, and corneal ectasia. Case reports, literature reviews, conference proceedings, and editorials were excluded. We extracted the following data from each eligible study: type of AI, input used for training, output, ground truth or reference, dataset size, availability of algorithm/model, availability of dataset, and major study findings.

Results

Ninety-three original research studies were included in this review, with the date of publication ranging from 1994 to 2023. The majority of studies were regarding the use of AI in detecting keratoconus or subclinical keratoconus (n=61). Among studies regarding keratoconus diagnosis, the most common inputs were corneal topography, Scheimpflug-based corneal tomography, and anterior segment-optical coherence tomography. This review also summarized 16 original research studies regarding AI-based assessment of severity and clinical features, 7 studies regarding the prediction of disease progression, and 6 studies regarding the characterization of treatment response. There were only three studies regarding the use of AI in identifying susceptibility genes involved in the etiology and pathogenesis of keratoconus.

Discussion

Algorithms trained on Scheimpflug-based tomography seem promising tools for the early diagnosis of keratoconus that can be particularly applied in low-resource communities. Future studies could investigate the application of AI models trained on multimodal patient information for staging keratoconus severity and tracking disease progression.

Multi-modal imaging for the detection of early keratoconus: a narrative review

Keratoconus is a common progressive corneal disorder that can be associated with significant ocular morbidity. Various corneal imaging techniques have been used for the diagnosis of established cases. However, in the early stages of the disease, which include subclinical keratoconus and forme fruste keratoconus, detection of such cases can be challenging. The importance of detecting such cases is very important because early intervention can halt disease progression, improve visual outcomes and prevent postrefractive surgery ectasia associated with performing corneal refractive procedures in such patients. This narrative review aimed to examine several established and evolving imaging techniques for the detection of early cases of keratoconus. The utilization of combinations of these techniques may further increase their diagnostic ability.

AvaGen Genetic Testing versus Ocular Screening Assessments Including the Keratoconus Severity Score (KSS) and Randleman Ectasia Risk Score System (ERSS) in Refractive Surgery Candidates

Purpose

To determine whether the AvaGen (AG) Genetic Eye Test provided additional information for screening for the presence of keratoconus (KC) and assessing KC risk in refractive surgery candidates, as compared to the Keratoconus Severity Score (KSS) and Randleman Ectasia Risk Score System (ERSS).

Methods

This retrospective study analyzed patients seeking refractive surgery at an eye clinic in the United States between January 2022 and July 2023. The inclusion criteria encompassed those with a family history of KC, positive KC indices, or both. Corneal evaluations and demographic information were recorded and analyzed. KSS and ERSS criteria were utilized to evaluate postoperative KC and ectasia risk, respectively. Patients were categorized on how the AG genetic test compared to KSS and ERSS criteria. Clinicians assessed topographic indices, criteria scoring, and AG testing to deliver a definitive surgical recommendation.

Results

Among the 19 patients evaluated for ectasia risk, AG testing showed lower KC risk than ocular screening in three patients (15.8%), equal risk in three patients (15.8%), and higher risk in 13 patients (68.4%). The mean AG scores were 45.7 ± 7.0, 49.0 ± 3.46, and 61 ± 13.0 for these respective categories. The most frequently identified KC risk genes were ADAMTS18, COL2A1, and COL4A1. The AG test modified the physician's recommendation for refractive surgery in nine cases (47.4%).

Conclusion

Despite the promising application of AG testing for assessing KC risk, further research and development are needed to enhance its applicability for screening refractive surgery candidates, in addition to standard ocular screening approaches.

The candidate proteins associated with keratoconus: A meta-analysis and bioinformatic analysis

PURPOSE

Keratoconus (KC) is a multifactorial disorder. This study aimed to conduct a systematic meta-analysis to exclusively explore the candidate proteins associated with KC pathogenesis.

METHODS

Relevant literature published in the last ten years in Pubmed, Web of Science, Cochrane, and Embase databases were searched. Protein expression data were presented as the standard mean difference (SMD) and 95% confidence intervals (CI). The meta-analysis is registered on PROSPERO, registration number CRD42022332442 and was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA). GO and KEGG enrichment analysis were performed, as well as the miRNAs and chemicals targeting the candidate proteins were predicted. PPI was analyzed to screen the hub proteins, and their expression was verified by RT-qPCR.

RESULTS

A total of 21 studies were included in the meta-analysis, involving 346 normal eyes and 493 KC eyes. 18 deregulated proteins with significant SMD values were subjected to further analysis. In which, 7 proteins were up-regulated in KC compared with normal controls, including IL6 (SMD 1.54, 95%CI [0.85, 2.24]), IL1B (SMD 2.07, 95%CI [0.98, 3.16]), TNF (SMD 2.1, 95%CI [0.24, 3.96]), and MMP9 (SMD 1.96, 95%CI [0.68, 3.24]). While 11 proteins were down-regulated in KC including LOX (SMD 2.54, 95%CI [-4.51, -0.57]). GO and KEGG analysis showed that the deregulated proteins were involved in inflammation, extracellular matrix (ECM) remodeling, and apoptosis. MMP9, IL6, LOX, TNF, and IL1B were regarded as hub proteins according to the PPI analysis, and their transcription changes in stromal fibroblasts of KC were consistent with the results of the meta-analysis. Moreover, 10 miRNAs and two natural polyphenols interacting with hub proteins were identified.

CONCLUSION

This study obtained 18 candidate proteins and demonstrated altered cytokine profiles, ECM remodeling, and apoptosis in KC patients through meta-analysis and bioinformatic analysis. It will provide biomarkers for further understanding of KC pathogenesis, and potential therapeutic targets for the drug treatment of KC.

Transepithelial Accelerated Crosslinking for Progressive Keratoconus: A Critical Analysis of Medium-Term Treatment Outcomes

Purpose

To report the 4-year outcomes of transepithelial accelerated corneal collagen crosslinking (TE-ACXL) in the treatment of eyes with progressive keratoconus (KC).

Methods

Eyes of patients who underwent TE-ACXL (6mW/cm2 for 15 minutes) for progressive KC and presented 48 months of follow-up were included. Corrected distance visual acuity (CDVA), keratometry measurements (Kmax, maximum keratometry, Kmean, mean keratometry and Astg, corneal astigmatism), thinnest corneal thickness (PachyMin), and topographic, and tomographic indices (specifically the posterior radius of curvature from the 3.0 mm centered on the thinnest point of the cornea (PRC), and the D-index) were analysed preoperatively and every 12 months after TE-ACXL, up to 48 months. Progression after TE-ACXL was considered when eyes presented ≥1 criteria: (1) increase of ≥1D in Kmax or increase of ≥0.75D in Kmean or increase of ≥1D in Astg; (2) reduction of ≥0.085 mm in PRC; (3) decrease ≥5% in PachyMin.

Results

41 eyes from 30 patients were included, with a mean age at crosslinking of 20.90±4.69 years. There was a significant increase in Kmean (+0.64±1.04 D, p<0.001; +0.98 ± 1.49 D, p<0.001; +1.27±2.01 D, p<0.001; +1.13±2.00 D, p=0.006) and a significant decrease in PRC throughout follow-up (-0.12±0.22, p=0.002; -0.15±0.24, p<0.001; -0.17±0.43, p=0.021; -0.16±0.43, p=0.027). PachyMin decreased significantly at 36 and 48 months (-8.50±15.93 μm, p=0.004; -7.82±18.37, p=0.033). According to our progression criteria, there was a major progression rate throughout follow-up (57.1%, 61.1%, 58.8%, and 67.9%, respectively). Surgery and follow-up were uneventful in all subjects. Eleven eyes (26.8%) required further procedures, ≥36 months after the initial TE-ACXL, due to persistent progressive disease.

Conclusion

TE-ACXL proved to be a safe therapeutic option for progressive KC. However, its efficacy is deemed unsatisfactory, as a notable proportion of affected eyes may continue to advance within a 4-year timeframe, necessitating additional procedures to halt the disease's course.

Longitudinal Changes of Cornea Volume Measured by Means of Anterior Segment-Optical Coherence Tomography in Patients with Stable and Progressive Keratoconus

Keratoconus is a corneal disease which results in progressive thinning and protrusion of the cornea leading to irregular astigmatism. The purpose of this study was to evaluate longitudinal changes in corneal volume (CV) occurring over time in keratoconus eyes. Consecutive patients affected by keratoconus were evaluated by means of anterior segment-optical coherence tomography (AS-OCT) at two different time points: baseline (T0) and after 1 year (T1). Anterior and posterior refractive value; corneal thickness at the thinnest point (TP) and corneal volume (CV) calculated within discs of 3, 5 and 8 mm of diameter; anterior chamber depth (ACD); and anterior chamber volume (ACV) were obtained. Enrolled patients were divided into 3 groups (groups 1, 2, 3) according to the increasing disease severity and into 2 groups (groups A, B) according to the progression or stability of the disease. Overall, 116 eyes of 116 patients (76 males and 40 females, mean age 34.76 ± 13.99 years) were included. For the entire group of keratoconus patients, in comparison with T0, mean TP decreased at T1 from 458.7 ± 52.2 µm to 454.6 ± 51.6 µm (p = 0.0004); in parallel, mean value of CV calculated at 5 mm and 8 mm decreased significantly (from 10.78 ± 0.8 at T0 to 10.75 ± 0.79 at T1 (p = 0.02), and from 32.03 ± 2.01 mm3 at T0 to 31.95 ± 1.98 at T1 (p = 0.02), respectively). Conversely, there were no statistically significant differences in CV at 3 mm from T0 to T1 (p = 0.08), as well as for ACD and ACV. Regarding the course of the disease, patients belonging to group A showed statistically significant differences from T0 to T1 for TP, and for CV at 3 mm, 5 mm and 8 mm (p < 0.0001, p < 0.0001, p < 0.001 and p = 0.0058 respectively). There were no statistically significant differences for ACD (p = 0.6916) and ACV calculated at 3, 5 and 8 mm (p = 0.7709, p = 0.3765, p = 0.2475, respectively) in group A. At the same time, no statistically significant differences for ACD (p = 0.2897) and ACV calculated at 3, 5 and 8 mm (p = 0.9849, p = 0.6420, p = 0.8338, respectively) were found in group B. There were statistically significant positive correlations between changes of TP and CV at 3 mm (r = 0.6324, p < 0.0001), 5 mm (r = 0.7622, p < 0.0001) and 8 mm (r = 0.5987 p < 0.0001). In conclusion, given the strong correlation with TP, CV might be considered an additional AS-OCT parameter to be used in association with conventional parameters when detecting longitudinal changes in keratoconic eyes.

Oxidative stress in the eye and its role in the pathophysiology of ocular diseases

Oxidative stress occurs through an imbalance between the generation of reactive oxygen species (ROS) and the antioxidant defense mechanisms of cells. The eye is particularly exposed to oxidative stress because of its permanent exposure to light and due to several structures having high metabolic activities. The anterior part of the eye is highly exposed to ultraviolet (UV) radiation and possesses a complex antioxidant defense system to protect the retina from UV radiation. The posterior part of the eye exhibits high metabolic rates and oxygen consumption leading subsequently to a high production rate of ROS. Furthermore, inflammation, aging, genetic factors, and environmental pollution, are all elements promoting ROS generation and impairing antioxidant defense mechanisms and thereby representing risk factors leading to oxidative stress. An abnormal redox status was shown to be involved in the pathophysiology of various ocular diseases in the anterior and posterior segment of the eye. In this review, we aim to summarize the mechanisms of oxidative stress in ocular diseases to provide an updated understanding on the pathogenesis of common diseases affecting the ocular surface, the lens, the retina, and the optic nerve. Moreover, we discuss potential therapeutic approaches aimed at reducing oxidative stress in this context.