Comparison of manual and artificial intelligence-automated choroidal thickness segmentation of optical coherence tomography imaging in myopic adults.

BACKGROUND: Myopia affects 1.4 billion individuals worldwide. Notably, there is increasing evidence that choroidal thickness plays an important role in myopia and risk of developing myopia-related conditions. With the advancements in artificial intelligence (AI), choroidal thickness segmentation can now be automated, offering inherent advantages such as better repeatability, reduced grader variability, and less reliance for manpower. Hence, we aimed to evaluate the agreement between AI-automated and manual segmented measurements of subfoveal choroidal thickness (SFCT) using two swept-source optical coherence tomography (OCT) systems. METHODS: Subjects aged ≥ 16 years, with myopia of ≥ 0.50 diopters in both eyes, were recruited from the Prospective Myopia Cohort Study in Singapore (PROMYSE). OCT scans were acquired using Triton DRI-OCT and PLEX Elite 9000. OCT images were segmented both automatically with an established SA-Net architecture and manually using a standard technique with adjudication by two independent graders. SFCT was subsequently determined based on the segmentation. The Bland-Altman plot and intraclass correlation coefficient (ICC) were used to evaluate the agreement. RESULTS: A total of 229 subjects (456 eyes) with mean [± standard deviation (SD)] age of 34.1 (10.4) years were included. The overall SFCT (mean ± SD) based on manual segmentation was 216.9 ± 82.7 µm with Triton DRI-OCT and 239.3 ± 84.3 µm with PLEX Elite 9000. ICC values demonstrated excellent agreement between AI-automated and manual segmented SFCT measurements (PLEX Elite 9000: ICC = 0.937, 95% CI: 0.922 to 0.949, P < 0.001; Triton DRI-OCT: ICC = 0.887, 95% CI: 0.608 to 0.950, P < 0.001). For PLEX Elite 9000, manual segmented measurements were generally thicker when compared to AI-automated segmented measurements, with a fixed bias of 6.3 µm (95% CI: 3.8 to 8.9, P < 0.001) and proportional bias of 0.120 (P < 0.001). On the other hand, manual segmented measurements were comparatively thinner than AI-automated segmented measurements for Triton DRI-OCT, with a fixed bias of - 26.7 µm (95% CI: - 29.7 to - 23.7, P < 0.001) and proportional bias of - 0.090 (P < 0.001). CONCLUSION: We observed an excellent agreement in choroidal segmentation measurements when comparing manual with AI-automated techniques, using images from two SS-OCT systems. Given its edge over manual segmentation, automated segmentation may potentially emerge as the primary method of choroidal thickness measurement in the future.

Biomechanical evaluation of porcine lens capsule with and without nucleus after capsulotomy - Finite element analysis.

Previous studies have shown that the nucleus could offer structural support to the lens capsule. This study investigated the biomechanical performance of porcine lens with and without nucleus for 4 mm, 4.5 mm, 5 mm, 5.5 mm and 6 mm capsulotomy and its potential impact on the stretch ratio of capsular bag when the anterior capsulotomy edge was stretched. Our simulation results showed higher strain for the capsular bag with nucleus, which is crucial for the porcine lens to tolerate more stretch without failure. This simulation could support future study on the optimization of capsulotomy based on patient specific condition, that is, the geometry of lens.

Femtosecond laser-assisted in situ keratomileusis versus small-incision lenticule extraction: current approach based on evidence.

PURPOSE OF REVIEW: Laser keratorefractive surgery achieves excellent visual outcomes for refractive error correction. With femtosecond laser, small incision lenticule extraction (SMILE) is an increasingly viable alternative to laser-assisted in situ keratomileusis (LASIK). Comparative studies demonstrate similar efficacy and predictability between SMILE and LASIK, making it difficult for clinicians to choose which to use. This review thus compares femtosecond-LASIK (FS-LASK) and SMILE in various scenarios, to assist clinicians in deciding which refractive surgery procedure to recommend. RECENT FINDINGS: SMILE may be superior for highly myopic eyes due to a smaller decrease in functional optical zone. SMILE further induces less spherical aberration and less overall higher order aberrations in mesopic conditions. SMIILE also has less postoperative dry eye, making it suitable those with preexisting dry eye. For low to moderate myopic astigmatism correction, FS-LASIK has less undercorrection compared to SMILE. Lastly, SMILE has not yet received Food and Drug Administration or Conformité Européenne approval for hyperopic correction, rendering FS-LASIK the choice of procedure for hyperopic correction. SUMMARY: Both FS-LASIK and SMILE demonstrate good efficacy and predictability. Understanding specific clinical scenarios where one may be superior to the other will aid clinicians in choosing the most suitable procedure for personalized care.

Myopia Control: Are We Ready for an Evidence Based Approach?

INTRODUCTION: Myopia and its vision-threatening complications present a significant public health problem. This review aims to provide an updated overview of the multitude of known and emerging interventions to control myopia, including their potential effect, safety, and costs. METHODS: A systematic literature search of three databases was conducted. Interventions were grouped into four categories: environmental/behavioral (outdoor time, near work), pharmacological (e.g., atropine), optical interventions (spectacles and contact lenses), and novel approaches such as red-light (RLRL) therapies. Review articles and original articles on randomized controlled trials (RCT) were selected. RESULTS: From the initial 3224 retrieved records, 18 reviews and 41 original articles reporting results from RCTs were included. While there is more evidence supporting the efficacy of low-dose atropine and certain myopia-controlling contact lenses in slowing myopia progression, the evidence about the efficacy of the newer interventions, such as spectacle lenses (e.g., defocus incorporated multiple segments and highly aspheric lenslets) is more limited. Behavioral interventions, i.e., increased outdoor time, seem effective for preventing the onset of myopia if implemented successfully in schools and homes. While environmental interventions and spectacles are regarded as generally safe, pharmacological interventions, contact lenses, and RLRL may be associated with adverse effects. All interventions, except for behavioral change, are tied to moderate to high expenditures. CONCLUSION: Our review suggests that myopia control interventions are recommended and prescribed on the basis of accessibility and clinical practice patterns, which vary widely around the world. Clinical trials indicate short- to medium-term efficacy in reducing myopia progression for various interventions, but none have demonstrated long-term effectiveness in preventing high myopia and potential complications in adulthood. There is an unmet need for a unified consensus for strategies that balance risk and effectiveness for these methods for personalized myopia management.

Comparative Study of Primary SMILE, SMILE Enhancement, and Femtosecond Laser-Assisted LASIK on Higher Order Aberrations and Corneal Densitometry.

PURPOSE: To compare differences in corneal densitometry (CD) and higher order aberrations (HOAs) in eyes that underwent small incision lenticule extraction (SMILE) and femtosecond laser-assisted laser in situ keratomileusis (FS-LASIK) for the treatment of myopia and myopic astigmatism at postoperative months 3, 6, and 12, and to evaluate their changes in a separate cohort of eyes after SMILE enhancement. METHODS: In this prospective, randomized, paired-eye clinical trial, consecutive eligible participants were randomized to undergo SMILE or FS-LASIK in either eye. Main outcome measures were CD and HOAs preoperatively and at 3, 6, and 12 months postoperatively. A separate cohort of consecutive patients who had SMILE and underwent enhancement were also included for comparison. RESULTS: For CD, no significant differences were found between SMILE and FS-LASIK up to month 12. For HOA measured by wavefront aberrometry, both SMILE and FS-LASIK had an increase in total root mean square (RMS) HOAs, spherical aberration (SA), and vertical coma up to month 12. SMILE had an additional increase in vertical quatrefoil, and FS-LASIK had an increase in horizontal coma at month 12. FS-LASIK had higher SA than SMILE, whereas SMILE had higher vertical quatrefoil than FS-LASIK at month 12. Central and posterior zone CD had significantly decreased after SMILE enhancement compared to after primary SMILE up to 2 years after enhancement. RMS HOAs, lower order aberrations, and SA were all increased after SMILE enhancement compared to after primary SMILE. CONCLUSIONS: SMILE induced lower SA but higher vertical quatrefoil than FS-LASIK at 1 year. Both SMILE and FS-LASIK had similar increases in RMS HOAs and vertical coma up to 1 year. There were no differences in CD between both groups. SMILE enhancement additionally had decreased central and posterior CD but greater RMS HOAs and SA compared to primary SMILE. [J Refract Surg. 2024;40(5):e291-e303.].

Potential applications of artificial intelligence in image analysis in cornea diseases: a review.

Artificial intelligence (AI) is an emerging field which could make an intelligent healthcare model a reality and has been garnering traction in the field of medicine, with promising results. There have been recent developments in machine learning and/or deep learning algorithms for applications in ophthalmology-primarily for diabetic retinopathy, and age-related macular degeneration. However, AI research in the field of cornea diseases is relatively new. Algorithms have been described to assist clinicians in diagnosis or detection of cornea conditions such as keratoconus, infectious keratitis and dry eye disease. AI may also be used for segmentation and analysis of cornea imaging or tomography as an adjunctive tool. Despite the potential advantages that these new technologies offer, there are challenges that need to be addressed before they can be integrated into clinical practice. In this review, we aim to summarize current literature and provide an update regarding recent advances in AI technologies pertaining to corneal diseases, and its potential future application, in particular pertaining to image analysis.

Deep learning for detection of Fuchs endothelial dystrophy from widefield specular microscopy imaging: a pilot study.

BACKGROUND: To describe the diagnostic performance of a deep learning (DL) algorithm in detecting Fuchs endothelial corneal dystrophy (FECD) based on specular microscopy (SM) and to reliably detect widefield peripheral SM images with an endothelial cell density (ECD) > 1000 cells/mm2. METHODS: Five hundred and forty-seven subjects had SM imaging performed for the central cornea endothelium. One hundred and seventy-three images had FECD, while 602 images had other diagnoses. Using fivefold cross-validation on the dataset containing 775 central SM images combined with ECD, coefficient of variation (CV) and hexagonal endothelial cell ratio (HEX), the first DL model was trained to discriminate FECD from other images and was further tested on an external set of 180 images. In eyes with FECD, a separate DL model was trained with 753 central/paracentral SM images to detect SM with ECD > 1000 cells/mm2 and tested on 557 peripheral SM images. Area under curve (AUC), sensitivity and specificity were evaluated. RESULTS: The first model achieved an AUC of 0.96 with 0.91 sensitivity and 0.91 specificity in detecting FECD from other images. With an external validation set, the model achieved an AUC of 0.77, with a sensitivity of 0.69 and specificity of 0.68 in differentiating FECD from other diagnoses. The second model achieved an AUC of 0.88 with 0.79 sensitivity and 0.78 specificity in detecting peripheral SM images with ECD > 1000 cells/mm2. CONCLUSIONS: Our pilot study developed a DL model that could reliably detect FECD from other SM images and identify widefield SM images with ECD > 1000 cells/mm2 in eyes with FECD. This could be the foundation for future DL models to track progression of eyes with FECD and identify candidates suitable for therapies such as Descemet stripping only.

Neuropathic Corneal Pain: Tear Proteomic and Neuromediator Profiles, Imaging Features, and Clinical Manifestations.

PURPOSE: To investigate the tear proteomic and neuromediator profiles, in vivo confocal microscopy (IVCM) imaging features, and clinical manifestations in neuropathic corneal pain (NCP) patients. DESIGN: Cross-sectional study. METHODS: A total of 20 NCP patients and 20 age-matched controls were recruited. All subjects were evaluated by corneal sensitivity, Schirmer test, tear break-up time, and corneal and ocular surface staining, Ocular Surface Disease Index and Ocular Pain Assessment Survey questionnaires were administered, as well as IVCM examinations for corneal nerves, microneruomas, and epithelial and dendritic cells. Tears were collected for neuromediator and proteomic analysis using enzyme-linked immunosorbent assay and data-independent acquisition mass spectrometry. RESULTS: Burning and sensitivity to light were the 2 most common symptoms in NCP. A total of 188 significantly dysregulated proteins, such as elevated metallothionein-2, creatine kinases B-type, vesicle-associated membrane protein 2, neurofilament light polypeptide, and myelin basic protein, were identified in the NCP patients. The top 10 dysregulated biological pathways in NCP include neurotoxicity, axonal signaling, wound healing, neutrophil degradation, apoptosis, thrombin signaling mitochondrial dysfunction, and RHOGDI and P70S6K signaling pathways. Compared to controls, the NCP cohort presented with significantly decreased corneal sensitivity (P < .001), decreased corneal nerve fiber length (P = .003), corneal nerve fiber density (P = .006), and nerve fiber fractal dimension (P = .033), as well as increased corneal nerve fiber width (P = .002), increased length, total area and perimeter of microneuromas (P < .001, P < .001, P = .019), smaller corneal epithelial size (P = .017), and higher nerve growth factor level in tears (P = .006). CONCLUSIONS: These clinical manifestations, imaging features, and molecular characterizations would contribute to the diagnostics and potential therapeutic targets for NCP.

Pathologic myopia in highly myopic patients with high axial anisomyopia.

PURPOSE: To determine prevalence of anisomyopia (axial length (AL) difference ≥2.5 mm) among high myopes ((HMs), defined by spherical equivalent of ≤6.0 diopters or AL ≥ 26.5 mm). To characterise the shorter anisomyopic eye (SAE) and evaluate if pathologic myopia (PM) in the longer anisomyopic eye (LAE) was associated with increased risk of PM in the SAE. METHODS: 1168 HMs were recruited from Singapore National Eye Centre clinic for this cross-sectional study. Biometry, fundus photography and swept-source optical coherence tomography were performed. Patients with high axial anisomyopia were identified. Structural characteristics and presence of PM were described. Stepwise multivariate regression explored associations between PM in the LAE and pathology in the SAE, controlling for confounding variables. RESULTS: Prevalence of anisomyopia was 15.8% (184 of 1168 patients). Anisomyopic patients (age 65.8±13.5 years) had mean AL of 30.6±2.0 mm and 26.2±2.3 mm in the LAE and SAE, respectively. 52.7% of SAEs had AL < 26.5 mm. Prevalence of myopic macular degeneration, macula-involving posterior staphyloma (PS), myopic traction maculopathy (MTM) and myopic choroidal neovascularisation (mCNV) in the SAE was 52.2%, 36.5%, 13.0% and 8.2%, respectively. Macular hole in the LAE was associated with increased risk of MTM in the SAE (OR=4.88, p=0.01). mCNV in the LAE was associated with mCNV in the SAE (OR=3.57, p=0.02). PS in the LAE was associated with PS in the SAE (OR=4.03, p<0.001). CONCLUSIONS: Even when controlled for AL, PM complications in the LAE predict similar PM complications in the SAE. Patients with high axial anisometropia with PM in the LAE should be monitored carefully for complications in the SAE.

Cataract surgery after corneal refractive surgery: preoperative considerations and management.

PURPOSE OF REVIEW: Corneal refractive surgery (CRS) is one of the most popular eye procedures, with more than 40 million cases performed globally. As CRS-treated patients age and develop cataract, the number of cases that require additional preoperative considerations and management will increase around the world. Thus, we provide an up-to-date, concise overview of the considerations and outcomes of cataract surgery in eyes with previous CRS, including surface ablation, laser in-situ keratomileusis (LASIK), and small-incision lenticule extraction (SMILE). RECENT FINDINGS: Challenges associated with accurate biometry in eyes with CRS have been mitigated recently through total keratometry, ray tracing, intraoperative aberrometry, and machine learning assisted intraocular lens (IOL) power calculation formulas to improve prediction. Emerging studies have highlighted the superior performance of ray tracing and/or total keratometry-based formulas for IOL power calculation in eyes with previous SMILE. Dry eye remains a common side effect after cataract surgery, especially in eyes with CRS, though the risk appears to be lower after SMILE than LASIK (in the short-term). Recent presbyopia-correcting IOL designs such as extended depth of focus (EDOF) IOLs may be suitable in carefully selected eyes with previous CRS. SUMMARY: Ophthalmologists will increasingly face challenges associated with the surgical management of cataract in patients with prior CRS. Careful preoperative assessment of the ocular surface, appropriate use of IOL power calculation formulas, and strategies for presbyopia correction are key to achieve good clinical and refractive outcomes and patient satisfaction. Recent advances in CRS techniques, such as SMILE, may pose new challenges for such eyes in the future.

Topical Atropine for Childhood Myopia Control: The Atropine Treatment Long-Term Assessment Study.

Importance: Clinical trial results of topical atropine eye drops for childhood myopia control have shown inconsistent outcomes across short-term studies, with little long-term safety or other outcomes reported. Objective: To report the long-term safety and outcomes of topical atropine for childhood myopia control. Design, Setting, and Participants: This prospective, double-masked observational study of the Atropine for the Treatment of Myopia (ATOM) 1 and ATOM2 randomized clinical trials took place at 2 single centers and included adults reviewed in 2021 through 2022 from the ATOM1 study (atropine 1% vs placebo; 1999 through 2003) and the ATOM2 study (atropine 0.01% vs 0.1% vs 0.5%; 2006 through 2012). Main Outcome Measures: Change in cycloplegic spherical equivalent (SE) with axial length (AL); incidence of ocular complications. Results: Among the original 400 participants in each original cohort, the study team evaluated 71 of 400 ATOM1 adult participants (17.8% of original cohort; study age, mean [SD] 30.5 [1.2] years; 40.6% female) and 158 of 400 ATOM2 adult participants (39.5% of original cohort; study age, mean [SD], 24.5 [1.5] years; 42.9% female) whose baseline characteristics (SE and AL) were representative of the original cohort. In this study, evaluating ATOM1 participants, the mean (SD) SE and AL were -5.20 (2.46) diopters (D), 25.87 (1.23) mm and -6.00 (1.63) D, 25.90 (1.21) mm in the 1% atropine-treated and placebo groups, respectively (difference of SE, 0.80 D; 95% CI, -0.25 to 1.85 D; P = .13; difference of AL, -0.03 mm; 95% CI, -0.65 to 0.58 mm; P = .92). In ATOM2 participants, the mean (SD) SE and AL was -6.40 (2.21) D; 26.25 (1.34) mm; -6.81 (1.92) D, 26.28 (0.99) mm; and -7.19 (2.87) D, 26.31 (1.31) mm in the 0.01%, 0.1%, and 0.5% atropine groups, respectively. There was no difference in the 20-year incidence of cataract/lens opacities, myopic macular degeneration, or parapapillary atrophy (ß/γ zone) comparing the 1% atropine-treated group vs the placebo group. Conclusions and Relevance: Among approximately one-quarter of the original participants, use of short-term topical atropine eye drops ranging from 0.01% to 1.0% for a duration of 2 to 4 years during childhood was not associated with differences in final refractive errors 10 to 20 years after treatment. There was no increased incidence of treatment or myopia-related ocular complications in the 1% atropine-treated group vs the placebo group. These findings may affect the design of future clinical trials, as further studies are required to investigate the duration and concentration of atropine for childhood myopia control.

Artificial intelligence and digital health in global eye health: opportunities and challenges.

Global eye health is defined as the degree to which vision, ocular health, and function are maximised worldwide, thereby optimising overall wellbeing and quality of life. Improving eye health is a global priority as a key to unlocking human potential by reducing the morbidity burden of disease, increasing productivity, and supporting access to education. Although extraordinary progress fuelled by global eye health initiatives has been made over the last decade, there remain substantial challenges impeding further progress. The accelerated development of digital health and artificial intelligence (AI) applications provides an opportunity to transform eye health, from facilitating and increasing access to eye care to supporting clinical decision making with an objective, data-driven approach. Here, we explore the opportunities and challenges presented by digital health and AI in global eye health and describe how these technologies could be leveraged to improve global eye health. AI, telehealth, and emerging technologies have great potential, but require specific work to overcome barriers to implementation. We suggest that a global digital eye health task force could facilitate coordination of funding, infrastructural development, and democratisation of AI and digital health to drive progress forwards in this domain.

Artificial intelligence and digital solutions for myopia.

Myopia as an uncorrected visual impairment is recognized as a global public health issue with an increasing burden on health-care systems. Moreover, high myopia increases one's risk of developing pathologic myopia, which can lead to irreversible visual impairment. Thus, increased resources are needed for the early identification of complications, timely intervention to prevent myopia progression, and treatment of complications. Emerging artificial intelligence (AI) and digital technologies may have the potential to tackle these unmet needs through automated detection for screening and risk stratification, individualized prediction, and prognostication of myopia progression. AI applications in myopia for children and adults have been developed for the detection, diagnosis, and prediction of progression. Novel AI technologies, including multimodal AI, explainable AI, federated learning, automated machine learning, and blockchain, may further improve prediction performance, safety, accessibility, and also circumvent concerns of explainability. Digital technology advancements include digital therapeutics, self-monitoring devices, virtual reality or augmented reality technology, and wearable devices - which provide possible avenues for monitoring myopia progression and control. However, there are challenges in the implementation of these technologies, which include requirements for specific infrastructure and resources, demonstrating clinically acceptable performance and safety of data management. Nonetheless, this remains an evolving field with the potential to address the growing global burden of myopia.

Management of keratoconus: an updated review.

Keratoconus is the most common corneal ectatic disorder. It is characterized by progressive corneal thinning with resultant irregular astigmatism and myopia. Its prevalence has been estimated at 1:375 to 1:2,000 people globally, with a considerably higher rate in the younger populations. Over the past two decades, there was a paradigm shift in the management of keratoconus. The treatment has expanded significantly from conservative management (e.g., spectacles and contact lenses wear) and penetrating keratoplasty to many other therapeutic and refractive modalities, including corneal cross-linking (with various protocols/techniques), combined CXL-keratorefractive surgeries, intracorneal ring segments, anterior lamellar keratoplasty, and more recently, Bowman's layer transplantation, stromal keratophakia, and stromal regeneration. Several recent large genome-wide association studies (GWAS) have identified important genetic mutations relevant to keratoconus, facilitating the development of potential gene therapy targeting keratoconus and halting the disease progression. In addition, attempts have been made to leverage the power of artificial intelligence-assisted algorithms in enabling earlier detection and progression prediction in keratoconus. In this review, we provide a comprehensive overview of the current and emerging treatment of keratoconus and propose a treatment algorithm for systematically guiding the management of this common clinical entity.

Posterior scleral birefringence measured by triple-input polarization-sensitive imaging as a biomarker of myopia progression.

In myopic eyes, pathological remodelling of collagen in the posterior sclera has mostly been observed ex vivo. Here we report the development of triple-input polarization-sensitive optical coherence tomography (OCT) for measuring posterior scleral birefringence. In guinea pigs and humans, the technique offers superior imaging sensitivities and accuracies than dual-input polarization-sensitive OCT. In 8-week-long studies with young guinea pigs, scleral birefringence was positively correlated with spherical equivalent refractive errors and predicted the onset of myopia. In a cross-sectional study involving adult individuals, scleral birefringence was associated with myopia status and negatively correlated with refractive errors. Triple-input polarization-sensitive OCT may help establish posterior scleral birefringence as a non-invasive biomarker for assessing the progression of myopia.

Identifying Content for an Item Bank to Measure the Quality-of-Life Impact of Myopia Refractive Interventions.

Purpose: To report on the content generation and item refinement phases for a myopia refractive intervention-specific quality-of-life (QoL) item bank that will be operationalized using computerized adaptive testing. Methods: Myopia refractive intervention-specific QoL domains and items were generated from (1) a literature search of existing refractive-intervention QoL questionnaires; (2) semistructured interviews with myopic patients corrected using spectacles, contact lenses and/or refractive surgery (n = 32); (3) and myopia experts (n = 9) recruited from the Singapore National Eye Centre. After a thematic analysis, items were systematically refined and tested using cognitive interviews with 24 additional patients with corrected myopia. Results: Of the 32 participants with myopia interviewed (mean ± standard deviation age, 35.6 ± 9.0 years; 71.9% female; 78.1% Chinese), 12 (37.5%) wore spectacles, 7 (21.9%) used contact lenses, and 20 (62.5%) had undergone laser refractive surgery. Initially, 912 items within 7 independent QoL domains were identified. After refinement, 204 items were retained, including those relating to mobility challenges and work-related difficulties that are not well-represented in current refractive intervention-specific questionnaires. Conclusions: Through a rigorous item generation and selection process, we have developed a 204-item and 7-domain myopia refractive intervention-specific item bank that will now undergo rigorous psychometric testing to generate item calibrations for the validation of a novel computerized adaptive testing instrument designed for use in research and routine clinical practice. Translational Relevance: Once psychometrically validated and operationalized using computerized adaptive testing, this myopia refractive intervention-specific instrument will enable researchers and clinicians to quickly and comprehensively assess the impact of myopic refractive interventions across seven QoL domains.

Bilateral sequential small-incision lenticule extraction and LASIK result in similar short-term quality-of-life outcomes.

PURPOSE: To compare quality of life (QoL) between patients who receive bilateral small-incision lenticule extraction (SMILE) or laser in situ keratomileusis (LASIK) vs bilateral sequential SMILE-LASIK (BSSL) surgery. SETTING: Singapore National Eye Centre, Singapore. DESIGN: Retrospective cohort study. METHODS: 2 patient cohorts were recruited (2010-2012; 2014-2016). The bilateral SMILE (BS) and bilateral LASIK (BL) groups comprised patients (mean ± SD age: 30.3 ± 6.5, 50% male) from a prospective nonrandomized study who chose SMILE and LASIK, respectively. The BSSL group comprised patients (mean ± SD age: 28.6 ± 6.2, 64.3% male) randomized to receive SMILE in 1 eye and LASIK in the other. Rasch-scaled scores of the QoL Impact of Refractive Correction questionnaire between groups postoperatively at 1 and 3 months were compared. RESULTS: At month 1, scores on 3 QoL without emotional well-being items were worse in the BSSL (n = 70) compared with the BL group (n = 25), specficially, "using sunglasses" (ß: -20.6, 95% CI, -34.3 to -6.9), "reliance on refractive correction" (-23.1, 95% CI, -40.9 to -5.4), and "medical complications from optical correction" (ß: -14.8, 95% CI, -27.9 to -1.7). Emotional well-being (overall), and items "feeling able to do things" (ß: 11.0, 95% CI, 1.6-20.4) and "feeling eager to try new things" (ß: 14.1, 95% CI, 3.6-24.6) were better in the BSSL compared with the BS group (n = 25). No substantive differences were observed at month 3. CONCLUSIONS: Refractive correction-related QoL differences at month 1 between BSSL and BS/BL patients attenuated by month 3. Bilateral sequential SMILE-LASIK surgery appeared unlikely to negatively affect QoL beyond 3 months.

Big data in corneal diseases and cataract: Current applications and future directions.

The accelerated growth in electronic health records (EHR), Internet-of-Things, mHealth, telemedicine, and artificial intelligence (AI) in the recent years have significantly fuelled the interest and development in big data research. Big data refer to complex datasets that are characterized by the attributes of "5 Vs"-variety, volume, velocity, veracity, and value. Big data analytics research has so far benefitted many fields of medicine, including ophthalmology. The availability of these big data not only allow for comprehensive and timely examinations of the epidemiology, trends, characteristics, outcomes, and prognostic factors of many diseases, but also enable the development of highly accurate AI algorithms in diagnosing a wide range of medical diseases as well as discovering new patterns or associations of diseases that are previously unknown to clinicians and researchers. Within the field of ophthalmology, there is a rapidly expanding pool of large clinical registries, epidemiological studies, omics studies, and biobanks through which big data can be accessed. National corneal transplant registries, genome-wide association studies, national cataract databases, and large ophthalmology-related EHR-based registries (e.g., AAO IRIS Registry) are some of the key resources. In this review, we aim to provide a succinct overview of the availability and clinical applicability of big data in ophthalmology, particularly from the perspective of corneal diseases and cataract, the synergistic potential of big data, AI technologies, internet of things, mHealth, and wearable smart devices, and the potential barriers for realizing the clinical and research potential of big data in this field.

Deep learning system to predict the 5-year risk of high myopia using fundus imaging in children.

Our study aims to identify children at risk of developing high myopia for timely assessment and intervention, preventing myopia progression and complications in adulthood through the development of a deep learning system (DLS). Using a school-based cohort in Singapore comprising of 998 children (aged 6-12 years old), we train and perform primary validation of the DLS using 7456 baseline fundus images of 1878 eyes; with external validation using an independent test dataset of 821 baseline fundus images of 189 eyes together with clinical data (age, gender, race, parental myopia, and baseline spherical equivalent (SE)). We derive three distinct algorithms - image, clinical and mix (image + clinical) models to predict high myopia development (SE ≤ -6.00 diopter) during teenage years (5 years later, age 11-17). Model performance is evaluated using area under the receiver operating curve (AUC). Our image models (Primary dataset AUC 0.93-0.95; Test dataset 0.91-0.93), clinical models (Primary dataset AUC 0.90-0.97; Test dataset 0.93-0.94) and mixed (image + clinical) models (Primary dataset AUC 0.97; Test dataset 0.97-0.98) achieve clinically acceptable performance. The addition of 1 year SE progression variable has minimal impact on the DLS performance (clinical model AUC 0.98 versus 0.97 in primary dataset, 0.97 versus 0.94 in test dataset; mixed model AUC 0.99 versus 0.97 in primary dataset, 0.95 versus 0.98 in test dataset). Thus, our DLS allows prediction of the development of high myopia by teenage years amongst school-going children. This has potential utility as a clinical-decision support tool to identify "at-risk" children for early intervention.

Pathologic myopia: advances in imaging and the potential role of artificial intelligence.

Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia.