Expert-Level Detection of Referable Glaucoma from Fundus Photographs in a Safety Net Population: The AI and Teleophthalmology in Los Angeles Initiative.

Purpose: To develop and test a deep learning (DL) algorithm for detecting referable glaucoma in the Los Angeles County (LAC) Department of Health Services (DHS) teleretinal screening program. Methods: Fundus photographs and patient-level labels of referable glaucoma (defined as cup-to-disc ratio [CDR] ≥ 0.6) provided by 21 trained optometrist graders were obtained from the LAC DHS teleretinal screening program. A DL algorithm based on the VGG-19 architecture was trained using patient-level labels generalized to images from both eyes. Area under the receiver operating curve (AUC), sensitivity, and specificity were calculated to assess algorithm performance using an independent test set that was also graded by 13 clinicians with one to 15 years of experience. Algorithm performance was tested using reference labels provided by either LAC DHS optometrists or an expert panel of 3 glaucoma specialists. Results: 12,098 images from 5,616 patients (2,086 referable glaucoma, 3,530 non-glaucoma) were used to train the DL algorithm. In this dataset, mean age was 56.8 ± 10.5 years with 54.8% females and 68.2% Latinos, 8.9% Blacks, 2.7% Caucasians, and 6.0% Asians. 1,000 images from 500 patients (250 referable glaucoma, 250 non-glaucoma) with similar demographics (p ≥ 0.57) were used to test the DL algorithm. Algorithm performance matched or exceeded that of all independent clinician graders in detecting patient-level referable glaucoma based on LAC DHS optometrist (AUC = 0.92) or expert panel (AUC = 0.93) reference labels. Clinician grader sensitivity (range: 0.33-0.99) and specificity (range: 0.68-0.98) ranged widely and did not correlate with years of experience (p ≥ 0.49). Algorithm performance (AUC = 0.93) also matched or exceeded the sensitivity (range: 0.78-1.00) and specificity (range: 0.32-0.87) of 6 LAC DHS optometrists in the subsets of the test dataset they graded based on expert panel reference labels. Conclusions: A DL algorithm for detecting referable glaucoma developed using patient-level data provided by trained LAC DHS optometrists approximates or exceeds performance by ophthalmologists and optometrists, who exhibit variable sensitivity and specificity unrelated to experience level. Implementation of this algorithm in screening workflows could help reallocate eye care resources and provide more reproducible and timely glaucoma care.

Relationship Between Glaucoma and Chronic Stress Quantified by Allostatic Load Score in the All of Us Research Program.

PURPOSE: To assess the relationship between glaucoma and allostatic load (AL), an established framework for quantifying the physiologic effects of chronic stress through measurements of systemic biomarkers. DESIGN: Retrospective case-control study. METHODS: Participants of the National Institutes of Health All of Us (AoU) Research Program with complete AL biomarker data between December 1984 to June 2022 and with (cases) or without (controls) primary glaucoma were identified. AL scores were calculated using the adapted Seeman AL scale consisting of 10 systemic biomarkers: body mass index, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, glomerular filtration rate, albumin, C-reactive protein, and homocysteine. AL score was defined as the number of biomarkers with measurements in the highest risk quartiles. Age was calculated as the median age at time of biomarker measurements. Logistic regression analysis was performed to assess the association between the earliest possible AL score and glaucoma adjusted for race/ethnicity. Mediation analysis was performed to estimate the relationship between race/ethnicity and glaucoma mediated by AL score. RESULTS: The study cohort consisted of 349 (16.1%) cases and 1,819 (83.9%) controls with 52.7% females, 2.2% Asians, 10.7% Blacks, 10.0% Hispanics, and 72.5% non-Hispanic Whites. At the earliest timepoint (median [IQR] = 6.4 [1.9-12.2] years prior to diagnosis), cases had higher AL score than controls (3 [1-4] versus 2 [1-3], respectively; p<0.001). On multivariable analysis, higher AL score (OR=1.09 per point), Black race (OR=2.58), and Hispanic ethnicity (OR=2.12) conferred higher risk of glaucoma (p≤0.02). AL score partially mediated higher glaucoma risk among Blacks (7.5%) and Hispanics (5.0%) compared to non-Hispanic Whites. On subgroup analysis, higher AL score was significantly associated with primary open angle glaucoma (POAG; OR=1.11; p=0.01) but not primary angle closure glaucoma (PACG; p=0.87). CONCLUSION: AoU participants with glaucoma had greater AL 6.4 years prior to diagnosis, and AL score partially mediated racial/ethnic differences in glaucoma risk. These findings suggest chronic stress may increase risk for glaucoma and contribute to racial disparities in glaucoma burden.

Novel hyperparallel optical coherence tomography for angle closure assessment: comparison with swept-source OCT and gonioscopy.

AIM: To evaluate reproducibility and agreement of angle closure assessment by a novel hyperparallel optical coherence tomography (OCT) system (HP-OCT, Cylite Optics, Melbourne, Australia), in comparison with swept-source OCT (SS-OCT, CASIA SS-1000, Tomey Corporation, Nagoya, Japan) and gonioscopy. METHODS: Cross-sectional study. Phakic subjects >40 years, with no relevant ophthalmic history were consecutively recruited from the glaucoma clinic. Subjects underwent same-day evaluation with HP-OCT, SS-OCT and gonioscopy. The primary outcome was the presence of angle closure, defined as iridotrabecular contact in HP-OCT and SS-OCT images at 0°-180° meridional and as non-visibility of the posterior trabecular meshwork (TM) by gonioscopy. Visibility of TM was also assessed (secondary outcome). Intra and interdevice agreement analysis (Gwet AC1) and logistic regression analysis were performed for primary and secondary outcomes, respectively. RESULTS: 154 sectors from horizontal scans of 77 subjects were analysed. The reproducibility of angle closure assessment by HP-OCT was excellent (AC1 of 0.95 for temporal angle and 1.00 for nasal). Agreement for angle closure detection was very good between HP-OCT and SS-OCT (AC1 of 0.88 for temporal and 0.81 for nasal angle) and good between HP-OCT and gonioscopy (AC1 of 0.71 for temporal and 0.78 for nasal angle). TM was identifiable in 64.4% (94/146) of unprocessed HP-OCT images (both open and closed angles), however not visible in any of the SS-OCT unprocessed images. CONCLUSIONS: HP-OCT showed excellent reproducibility for angle closure assessment and good agreement with SS-OCT and gonioscopy. HP-OCT technology also provides a unique capability to visualise regions around TM and Schlemm's canal, opening new avenues for clinical research of distal outflow pathways.

The HEALthy Brain and Child Development Study (HBCD): NIH collaboration to understand the impacts of prenatal and early life experiences on brain development.

The human brain undergoes rapid development during the first years of life. Beginning in utero, a wide array of biological, social, and environmental factors can have lasting impacts on brain structure and function. To understand how prenatal and early life experiences alter neurodevelopmental trajectories and shape health outcomes, several NIH Institutes, Centers, and Offices collaborated to support and launch the HEALthy Brain and Child Development (HBCD) Study. The HBCD Study is a multi-site prospective longitudinal cohort study, that will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Influenced by the success of the ongoing Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) and in partnership with the NIH Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®, the HBCD Study aims to establish a diverse cohort of over 7000 pregnant participants to understand how early life experiences, including prenatal exposure to addictive substances and adverse social environments as well as their interactions with an individual's genes, can affect neurodevelopmental trajectories and outcomes. Knowledge gained from the HBCD Study will help identify targets for early interventions and inform policies that promote resilience and mitigate the neurodevelopmental effects of adverse childhood experiences and environments.

Gap Analysis of Glaucoma Examination Concept Representations within Standard Systemized Nomenclature of Medicine - Clinical Terms.

OBJECTIVE/PURPOSE: Standardization of eye care data is important for clinical interoperability and research. We aimed to address gaps in the representations of glaucoma examination concepts within Systemized Nomenclature of Medicine - Clinical Terms (SNOMED-CT), the preferred terminology of the American Academy of Ophthalmology. DESIGN: Study of data elements. METHODS: Structured eye examination data fields from 2 electronic health records (EHR) systems (Epic Systems and Medisoft) were compared against existing SNOMED-CT codes for concepts representing glaucoma examination findings. Glaucoma specialists from multiple institutions were surveyed to identify high-priority gaps in representation, which were discussed among the SNOMED International Eye Care Clinical Reference Group. Proposals for new codes to address the gaps were formulated and submitted for inclusion in SNOMED-CT. MAIN OUTCOME MEASURES: Gaps in SNOMED-CT glaucoma examination concept representations. RESULTS: We identified several gaps in SNOMED-CT regarding glaucoma examination concepts. A survey of glaucoma specialists identified high-priority data elements within the categories of tonometry and gonioscopy. For tonometry, there was consensus that we need to define new codes related to maximum intraocular pressure (IOP) and target IOP and delineate all methods of measuring IOP. These new codes were proposed and successfully added to SNOMED-CT for future use. Regarding gonioscopy, the current terminology did not include the ability to denote the gonioscopic grading system used (e.g., Shaffer or Spaeth), degree of angle pigmentation, iris configuration (except for plateau iris), and iris approach. There was also no ability to specify eye laterality or angle quadrant for gonioscopic findings. We proposed a framework for representing gonioscopic findings as observable entities in SNOMED-CT. CONCLUSION: There are existing gaps in the standardized representation of findings related to tonometry and gonioscopy within SNOMED-CT. These are important areas for evaluating clinical outcomes and enabling secondary use of EHR data for glaucoma research. This international multi-institutional collaborative process enabled identification of gaps, prioritization, and development of data standards to address these gaps. Addressing these gaps and augmenting SNOMED-CT coverage of glaucoma examination findings could enhance clinical documentation and future research efforts related to glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical presentations, making diagnosis and management challenging. The lack of a consensus definition for glaucoma or glaucomatous optic neuropathy further complicates the development of universal diagnostic tools. Developing robust artificial intelligence (AI) models for glaucoma screening is essential for early detection and treatment but faces significant obstacles. Effective deep learning algorithms require large, well-curated datasets from diverse patient populations and imaging protocols. However, creating centralized data repositories is hindered by concerns over data sharing, patient privacy, regulatory compliance, and intellectual property. Federated Learning (FL) offers a potential solution by enabling data to remain locally hosted while facilitating distributed model training across multiple sites. METHODS: A comprehensive literature review was conducted on the application of Federated Learning in training AI models for glaucoma screening. Publications from 1950 to 2024 were searched using databases such as PubMed and IEEE Xplore with keywords including "glaucoma," "federated learning," "artificial intelligence," "deep learning," "machine learning," "distributed learning," "privacy-preserving," "data sharing," "medical imaging," and "ophthalmology." Articles were included if they discussed the use of FL in glaucoma-related AI tasks or addressed data sharing and privacy challenges in ophthalmic AI development. RESULTS: FL enables collaborative model development without centralizing sensitive patient data, addressing privacy and regulatory concerns. Studies show that FL can improve model performance and generalizability by leveraging diverse datasets while maintaining data security. FL models have achieved comparable or superior accuracy to those trained on centralized data, demonstrating effectiveness in real-world clinical settings. CONCLUSIONS: Federated Learning presents a promising strategy to overcome current obstacles in developing AI models for glaucoma screening. By balancing the need for extensive, diverse training data with the imperative to protect patient privacy and comply with regulations, FL facilitates collaborative model training without compromising data security. This approach offers a pathway toward more accurate and generalizable AI solutions for glaucoma detection and management. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references in the Footnotes and Disclosures at the end of this article.

Comparative Single Vesicle Analysis of Aqueous Humor Extracellular Vesicles before and after Radiation in Uveal Melanoma Eyes.

Small extracellular vesicles (sEVs) have been shown to promote tumorigenesis, treatment resistance, and metastasis in multiple cancer types; however, sEVs in the aqueous humor (AH) of uveal melanoma (UM) patients have never previously been profiled. In this study, we used single particle analysis to characterize sEV subpopulations in the AH of UM patients by quantifying their size, concentration, and phenotypes based on cell surface markers, specifically the tetraspanin co-expression patterns of CD9, CD63, and CD81. sEVs were analyzed from paired pre- and post-treatment (brachytherapy, a form of radiation) AH samples collected from 19 UM patients. In post-brachytherapy samples, two subpopulations, CD63/81+ and CD9/63/81+ sEVs, were significantly increased. These trends existed even when stratified by tumor location and GEP class 1 and class 2 (albeit not significant for GEP class 2). In this initial report of single vesicle profiling of sEVs in the AH of UM patients, we demonstrated that sEVs can be detected in the AH. We further identified two subpopulations that were increased post-brachytherapy, which may suggest radiation-induced release of these particles, potentially from tumor cells. Further study of the cargo carried by these sEV subpopulations may uncover important biomarkers and insights into tumorigenesis for UM.

Patterns and Disparities in Recorded Gonioscopy During Initial Glaucoma Evaluations in the United States.

PURPOSE: To assess patterns in gonioscopy during initial glaucoma evaluations in the United States. DESIGN: Retrospective, case-control study. METHODS: Patients undergoing initial glaucoma evaluation between 2009-2020 were identified in the Optum Clinformatics DataMart. Initial evaluation was defined as follows: (1) glaucoma suspect, anatomical narrow angle (ANA), or primary/secondary glaucoma diagnosed by an ophthalmologist; (2) continuously observable during a 36-month lookback period; (3) no history of glaucoma medications, laser, or surgical procedures; and (4) optical coherence tomography (OCT) or visual field performed within 6 months of initial diagnosis. Logistic regression models were developed to identify factors associated with no record of gonioscopy based on Current Procedural Terminology (CPT) codes. RESULTS: Among 198,995 patients, 20.4% and 29.5% had recorded gonioscopy on the day of diagnosis or within 6 months, respectively. On multivariable analysis, odds of recorded gonioscopy within 6 months of initial evaluation was lower (P < .001) among non-Hispanic Whites (OR=0.84) but similar for Blacks (OR=1.02) and Hispanics (OR=0.96) compared with Asians. Age ≥60 years (OR<0.82), pseudophakia/aphakia (OR=0.58), or residence outside of the Northeast region (OR=0.66-0.84) conferred lower odds of recorded gonioscopy (P < .001). Angle closure glaucoma (OR=0.85), secondary glaucoma (OR=0.31), or open angle glaucoma/suspect (OR=0.12/0.24, respectively) patients were less likely to have recorded gonioscopy compared to ANA patients (P < .01). CONCLUSIONS: More than 70% patients undergoing initial glaucoma evaluation in the United States do not have a record of gonioscopy, especially elderly, non-Hispanic White, and pseudophakic patients in non-Northeast regions. This pattern does not conform to current practice guidelines and could contribute to misdiagnosed disease and suboptimal outcomes.

Advances and Challenges in Wearable Glaucoma Diagnostics and Therapeutics.

Glaucoma is a leading cause of irreversible blindness, and early detection and treatment are crucial for preventing vision loss. This review aims to provide an overview of current diagnostic and treatment standards, recent medical and technological advances, and current challenges and future outlook for wearable glaucoma diagnostics and therapeutics. Conventional diagnostic techniques, including the rebound tonometer and Goldmann Applanation Tonometer, provide reliable intraocular pressure (IOP) measurement data at single-interval visits. The Sensimed Triggerfish and other emerging contact lenses provide continuous IOP tracking, which can improve diagnostic IOP monitoring for glaucoma. Conventional therapeutic techniques include eye drops and laser therapies, while emerging drug-eluting contact lenses can solve patient noncompliance with eye medications. Theranostic platforms combine diagnostic and therapeutic capabilities into a single device. Advantages of these platforms include real-time monitoring and personalized medication dosing. While there are many challenges to the development of wearable glaucoma diagnostics and therapeutics, wearable technologies hold great potential for enhancing glaucoma management by providing continuous monitoring, improving medication adherence, and reducing the disease burden on patients and healthcare systems. Further research and development of these technologies will be essential to optimizing patient outcomes.

Practice Patterns and Sociodemographic Disparities in the Clinical Care of Anatomical Narrow Angles in the United States.

PURPOSE: To assess treatment and visit patterns among patients with newly diagnosed anatomical narrow angle (ANA) and identify sociodemographic factors associated with disparities in care. DESIGN: Retrospective practice pattern evaluation study. METHODS: A total of 263,422 patients diagnosed with ANA between 2007 and 2019 were identified in the Optum Clinformatics Data Mart. Inclusion was limited to newly diagnosed ANA, defined as (1) continuous enrollment during a 2-year lookback period and 1-year study period from first diagnosis; (2) diagnosis by an ophthalmologist or optometrist; and (3) no history of pseudophakia, ANA treatments, or prior primary angle closure glaucoma diagnosis. Outcome measures were treatment with laser peripheral iridotomy (LPI), cataract surgery, or intraocular pressure-lowering medications and number of eye care visits. Logistic and Poisson regression were performed to assess factors associated with treatment and eye care visits, respectively. RESULTS: Among 52,405 eligible cases, 27.7% received LPI, 13.9% received drops, and 15.1% received cataract surgery. Odds of LPI were higher in Asians and Hispanics (odds ratio [OR] ≥ 1.16, P < .001). Non-Whites had higher odds of drops (OR ≥ 1.19, P < .001), but Hispanics had lower odds of cataract surgery (OR = 0.79, P < .001). The mean number of eye care visits was 2.6±2.1 including the day of diagnosis. Older age and treatment were associated with higher rates of eye care visits (rate ratio > 1.15, P < .001). CONCLUSION: More than a quarter of patients with newly diagnosed ANA receive treatment with LPI. Racial minorities are more likely to receive ANA-specific treatments but less likely to receive cataract surgery. These differences may reflect racial differences in disease severity and the need for clearer practice guidelines in ANA care.

Long-Term Risk and Prediction of Progression in Primary Angle Closure Suspect.

Importance: Identifying primary angle closure suspect (PACS) eyes at risk of angle closure is crucial for its management. However, the risk of progression and its prediction are still understudied in long-term longitudinal studies about PACS. Objective: To explore baseline predictors and develop prediction models for the 14-year risk of progression from PACS to primary angle closure (PAC). Design, Setting, and Participants: This cohort study involved participants from the Zhongshan Angle Closure Prevention trial who had untreated eyes with PACS. Baseline examinations included tonometry, ultrasound A-scan biometry, and anterior segment optical coherence tomography (AS-OCT) under both light and dark conditions. Primary angle closure was defined as peripheral anterior synechiae in 1 or more clock hours, intraocular pressure (IOP) greater than 24 mm Hg, or acute angle closure. Based on baseline covariates, logistic regression models were built to predict the risk of progression from PACS to PAC during 14 years of follow-up. Results: The analysis included 377 eyes from 377 patients (mean [SD] patient age at baseline, 58.28 [4.71] years; 317 females [84%]). By the 14-year follow-up visit, 93 eyes (25%) had progressed from PACS to PAC. In multivariable models, higher IOP (odds ratio [OR], 1.14 [95% CI, 1.04-1.25] per 1-mm Hg increase), shallower central anterior chamber depth (ACD; OR, 0.81 [95% CI, 0.67-0.97] per 0.1-mm increase), and shallower limbal ACD (OR, 0.96 [95% CI, 0.93-0.99] per 0.01 increase in peripheral corneal thickness) at baseline were associated with an increased 14-year risk of progression from PACS to PAC. As for AS-OCT measurements, smaller light-room trabecular-iris space area (TISA) at 500 µm from the scleral spur (OR, 0.86 [95% CI, 0.77-0.96] per 0.01-mm2 increase), smaller light-room angle recess area (ARA) at 750 µm from the scleral spur (OR, 0.93 [95% CI, 0.88-0.98] per 0.01-mm2 increase), and smaller dark-room TISA at 500 µm (OR, 0.89 [95% CI, 0.80-0.98] per 0.01-mm2 increase) at baseline were identified as predictors for the 14-year risk of progression. The prediction models based on IOP and central and limbal ACDs showed moderate performance (area under the receiver operating characteristic curve, 0.69; 95% CI, 0.63-0.75) in predicting progression from PACS to PAC, and inclusion of AS-OCT metrics did not improve the model's performance. Conclusions and Relevance: This cohort study suggests that higher IOP, shallower central and limbal ACDs, and smaller TISA at 500 µm and light-room ARA at 750 µm may serve as baseline predictors for progression to PAC in PACS eyes. Evaluating these factors can aid in customizing PACS management.

Prevalence and Risk Factors of Blindness Among Primary Angle Closure Glaucoma Patients in the United States: An IRIS Registry Analysis.

PURPOSE: To assess the prevalence and risk factors of blindness among patients newly diagnosed with primary angle closure glaucoma (PACG) in the United States. DESIGN: Retrospective cross-sectional study. METHODS: Eligible patients from the American Academy of Ophthalmology (AAO) Intelligent Research in Sight (IRIS) Registry had newly diagnosed PACG, defined as: 1) observable during a 24-month lookback period from index date of PACG diagnosis; 2) no history of eye drops, laser, or cataract surgery unless preceded by a diagnosis of anatomical narrow angle (ANA); and 3) no history of glaucoma surgery. Logistic regression models were developed to identify risk factors for any (one or both eyes) or bilateral (both eyes) blindness (visual acuity ≤20/200) at first diagnosis of PACG. RESULTS: Among 43,901 eligible patients, overall prevalence of any and bilateral blindness were 11.5% and 1.8%, respectively. Black and Hispanic patients were at higher risk of any (odds ratios [ORs] 1.42 and 1.21, respectively; P < .001) and bilateral (ORs 2.04 and 1.53, respectively; P < .001) blindness compared with non-Hispanic White patients adjusted for ocular comorbidities. Age <50 or >80 years, male sex, Medicaid or Medicare insurance product, and Southern or Western practice region also conferred a higher risk of blindness (OR > 1.28; P ≤ .01). CONCLUSIONS: Blindness affects 1 of 9 patients with newly diagnosed PACG in the IRIS Registry. Black and Hispanic patients and Medicaid and Medicare recipients are at significantly higher risk. These findings highlight the severe ocular morbidity among patients with PACG and the need for improved disease awareness and detection methods.

Quantifying the Expanding Landscape of Clinical Actionability for Patients with Cancer.

There is a continuing debate about the proportion of cancer patients that benefit from precision oncology, attributable in part to conflicting views as to which molecular alterations are clinically actionable. To quantify the expansion of clinical actionability since 2017, we annotated 47,271 solid tumors sequenced with the MSK-IMPACT clinical assay using two temporally distinct versions of the OncoKB knowledge base deployed 5 years apart. Between 2017 and 2022, we observed an increase from 8.9% to 31.6% in the fraction of tumors harboring a standard care (level 1 or 2) predictive biomarker of therapy response and an almost halving of tumors carrying nonactionable drivers (44.2% to 22.8%). In tumors with limited or no clinical actionability, TP53 (43.2%), KRAS (19.2%), and CDKN2A (12.2%) were the most frequently altered genes. SIGNIFICANCE: Although clear progress has been made in expanding the availability of precision oncology-based treatment paradigms, our results suggest a continued unmet need for innovative therapeutic strategies, particularly for cancers with currently undruggable oncogenic drivers. See related commentary by Horak and Fröhling, p. 18. This article is featured in Selected Articles from This Issue, p. 5.

Assessment of angle closure disease in the age of artificial intelligence: A review.

Primary angle closure glaucoma is a visually debilitating disease that is under-detected worldwide. Many of the challenges in managing primary angle closure disease (PACD) are related to the lack of convenient and precise tools for clinic-based disease assessment and monitoring. Artificial intelligence (AI)- assisted tools to detect and assess PACD have proliferated in recent years with encouraging results. Machine learning (ML) algorithms that utilize clinical data have been developed to categorize angle closure eyes by disease mechanism. Other ML algorithms that utilize image data have demonstrated good performance in detecting angle closure. Nonetheless, deep learning (DL) algorithms trained directly on image data generally outperformed traditional ML algorithms in detecting PACD, were able to accurately differentiate between angle status (open, narrow, closed), and automated the measurement of quantitative parameters. However, more work is required to expand the capabilities of these AI algorithms and for deployment into real-world practice settings. This includes the need for real-world evaluation, establishing the use case for different algorithms, and evaluating the feasibility of deployment while considering other clinical, economic, social, and policy-related factors.

Multicentre analysis of nucleic acid quantification using aqueous humour liquid biopsy in uveal melanoma: implications for clinical testing.

OBJECTIVE: Uveal melanoma (UM) tumour biopsy is limited by size and intratumour heterogeneity. We explored the potential of aqueous humour (AH) liquid biopsy for UM by quantifying analytes in samples collected at diagnosis and after brachytherapy to look for clinical correlations with tumour features. DESIGN: Case-series study. PARTICIPANTS: Sixty-six UM patients and 16 control subjects from a tertiary care hospital. METHODS: The study included 119 UM AH samples and 16 control samples analyzed for unprocessed analytes (i.e., dsDNA, miRNA, and protein) using Qubit fluorescence assays. RESULTS: Analytes were widely quantifiable among available UM AH samples (dsDNA: 94.1%; miRNA: 88.0%; protein: 95.2%) at significantly higher concentrations than among control samples (dsDNA, p = 0.008; miRNA, p < 0.0001; protein, p = 0.007). In samples taken at diagnosis, concentrations were higher at more advanced American Joint Cancer Commission stages; when comparing most advanced stage III with least advanced stage I, median dsDNA was 4 times greater (p < 0.0001), miRNA was 2 times greater (p = 0.001), and protein was 3 times greater (p < 0.0001). Analytes were quantifiable in >70% of diagnostic samples from eyes with tumours <2 mm tall. Height had a positive association with diagnostic analyte concentrations (dsDNA: R = 0.43, p = 0.0007; miRNA: R = 0.35, p = 0.01; protein: R = 0.39, p = 0.005). Samples taken after brachytherapy showed significantly higher concentrations than diagnostic samples (p < 0.01 for all). CONCLUSIONS: UM AH is a rich repository of analytes. Samples from eyes with more advanced stage and larger tumours had higher concentrations, though analytes also were quantifiable in eyes with smaller, less advanced tumours. Future analysis of AH analytes may be informative in the pursuit of personalized UM treatments.

Identifying, Understanding, and Addressing Disparities in Glaucoma Care in the United States.

Glaucoma is the leading cause of irreversible blindness worldwide, currently affecting around 80 million people. Glaucoma prevalence is rapidly rising in the United States due to an aging population. Despite recent advances in the diagnosis and treatment of glaucoma, significant disparities persist in disease detection, management, and outcomes among the diverse patient populations of the United States. Research on disparities is critical to identifying, understanding, and addressing societal and healthcare inequalities. Disparities research is especially important and impactful in the context of irreversible diseases such as glaucoma, where earlier detection and intervention are the primary approach to improving patient outcomes. In this article, we first review recent studies identifying disparities in glaucoma care that affect patient populations based on race, age, and gender. We then review studies elucidating and furthering our understanding of modifiable factors that contribute to these inequities, including socioeconomic status (particularly age and education), insurance product, and geographic region. Finally, we present work proposing potential strategies addressing disparities in glaucoma care, including teleophthalmology and artificial intelligence. We also discuss the presence of non-modifiable factors that contribute to differences in glaucoma burden and can confound the detection of glaucoma disparities. Translational Relevance: By recognizing underlying causes and proposing potential solutions, healthcare providers, policymakers, and other stakeholders can work collaboratively to reduce the burden of glaucoma and improve visual health and clinical outcomes in vulnerable patient populations.

Investigating the determinants of iridolenticular contact area: a novel parameter for angle closure.

BACKGROUND/AIMS: To identify ocular determinants of iridolenticular contact area (ILCA), a recently introduced swept-source optical coherence tomography (SSOCT) derived parameter, and assess the association between ILCA and angle closure. METHODS: In this population-based cross-sectional study, right eyes of 464 subjects underwent SSOCT (SS-1000, CASIA, Tomey Corporation, Nagoya, Japan) imaging in the dark. Eight out of 128 cross-sectional images (evenly spaced 22.5° apart) were selected for analysis. Matlab (Matworks, Massachusetts, USA) was used to measure ILCA, defined as the circumferential extent of contact area between the pigmented iris epithelium and anterior lens surface. Gonioscopic angle closure (GAC) was defined as non-visibility of the posterior trabecular meshwork in two or more angle quadrants. RESULTS: The mean age of subjects was 62±6.6 years, with the majority being female (65.5%). 143/464 subjects (28.6%) had GAC. In multivariable linear regression analysis, ILCA was significantly associated with anterior chamber width (ß=1.03, p=0.003), pupillary diameter (ß=-1.9, p<0.001) and iris curvature (ß=-17.35, p<0.001). ILCA was smaller in eyes with GAC compared with those with open angles (4.28±1.6 mm2 vs 6.02±2.71 mm2, p<0.001). ILCA was independently associated with GAC (ß=-0.03, p<0.001), iridotrabecular contact index (ß=-6.82, p<0.001) or angle opening distance (ß=0.02, p<0.001) after adjusting for covariates. The diagnostic performance of ILCA for detecting GAC was acceptable (AUC=0.69). CONCLUSIONS: ILCA is a significant predictor of angle closure independent of other biometric factors and may reflect unique anatomical information associated with pupillary block. ILCA represents a novel biometric risk factor in eyes with angle closure.

Automated expert-level scleral spur detection and quantitative biometric analysis on the ANTERION anterior segment OCT system.

AIM: To perform an independent validation of deep learning (DL) algorithms for automated scleral spur detection and measurement of scleral spur-based biometric parameters in anterior segment optical coherence tomography (AS-OCT) images. METHODS: Patients receiving routine eye care underwent AS-OCT imaging using the ANTERION OCT system (Heidelberg Engineering, Heidelberg, Germany). Scleral spur locations were marked by three human graders (reference, expert and novice) and predicted using DL algorithms developed by Heidelberg Engineering that prioritise a false positive rate <4% (FPR4) or true positive rate >95% (TPR95). Performance of human graders and DL algorithms were evaluated based on agreement of scleral spur locations and biometric measurements with the reference grader. RESULTS: 1308 AS-OCT images were obtained from 117 participants. Median differences in scleral spur locations from reference locations were significantly smaller (p<0.001) for the FPR4 (52.6±48.6 µm) and TPR95 (55.5±50.6 µm) algorithms compared with the expert (61.1±65.7 µm) and novice (79.4±74.9 µm) graders. Intergrader reproducibility of biometric measurements was excellent overall for all four (intraclass correlation coefficient range 0.918-0.997). Intergrader reproducibility of the expert grader (0.567-0.965) and DL algorithms (0.746-0.979) exceeded that of the novice grader (0.146-0.929) for images with narrow angles defined by OCT measurement of angle opening distance 500 µm anterior to the scleral spur (AOD500)<150 µm. CONCLUSIONS: DL algorithms on the ANTERION approximate expert-level measurement of scleral spur-based biometric parameters in an independent patient population. These algorithms could enhance clinical utility of AS-OCT imaging, especially for evaluating patients with angle closure and performing intraocular lens calculations.

Classification of Angle Closure Severity by Hierarchical Cluster Analysis of Ocular Biometrics in the Dark and Light.

Purpose: The purpose of this study was to investigate the classification of angle closure eyes based on hierarchical cluster analysis of ocular biometrics measured in the dark and light using anterior segment optical coherence tomography (AS-OCT). Methods: Participants of the Chinese American Eye Study received complete eye examinations to identify primary angle closure suspects (PACS) and primary angle closure without/with glaucoma (PAC/G). AS-OCT was performed in the dark and light. Biometric parameters describing the angle, iris, lens, and anterior chamber were analyzed. Hierarchical clustering was performed using Ward's method. Post hoc logistic regression models were developed to identify biometric predictors of angle closure staging. Results: Analysis of 159 eyes with PACS (N = 120) or PAC/G (N = 39) produced 2 clusters in the dark and light. In both analyses, cluster 1 (N = 132 in the dark and N = 126 in the light) was characterized by smaller angle opening distance (AOD)750 and trabecular iris space area (TISA)750, greater iris curvature (IC), and greater lens vault (LV; P < 0.001) than cluster 2. The proportion of PAC/PACG to PACS eyes was significantly higher in cluster 1 than 2 in the light (36:90 and 3:30, respectively; P = 0.02), but not the dark (36:96 and 3:24, respectively; P = 0.08). On multivariable regression analyses, smaller TISA750 (odds ratio [OR] = 0.84 per 0.01 mm2) and AOD750 (OR = 0.93 per 0.01 mm) in the light and smaller TISA750 (OR = 0.86 per 0.01 mm2) in the dark conferred higher risk of PAC/G (P ≤ 0.02). Conclusions: Unsupervised cluster analysis of ocular biometrics can classify angle closure eyes by severity. Static biometrics measured in the light and dark are both predictive of PAC/G. Translational Relevance: Clustering of biometrics measured in the light could provide an alternative source of information to risk-stratify angle closure eyes for more severe disease.

Role of Static and Dynamic Ocular Biometrics Measured in the Dark and Light as Risk Factors for Angle Closure Progression.

PURPOSE: To assess the role of static and dynamic ocular biometric parameters measured in the dark and light for predicting progression of primary angle closure suspect (PACS) to primary angle closure (PAC). DESIGN: Retrospective cohort study using prospective randomized controlled trial data from untreated, control eyes. METHODS: Zhongshan Angle Closure Prevention Trial subjects underwent anterior segment optical coherence tomography (AS-OCT) imaging in the dark and light. Static biometric parameters were measured, consisting of angle, iris, lens, and anterior chamber parameters. Dynamic change parameters were calculated by subtracting light measurements from dark measurements. Cox proportional hazards regression models were developed to assess risk factors for PACD progression. RESULTS: A total of 861 eyes of 861 participants were analyzed (36 progressors). On univariable analysis, TISA500 measurements in the light and dark were associated with progression (P < .001), whereas dynamic change parameters were not (P ≥ .08). In the primary multivariable model, older age (hazard ratio [HR] = 1.09 per year), higher intraocular pressure (IOP) (HR = 1.13 per mm Hg), and smaller TISA500 in the light (HR = 1.28 per 0.01 mm2) were significantly associated with greater risk of progression (P ≤ .04). Dark TISA500 had similar significance (HR = 1.28, P = .002) when replacing light TISA500. Risk of progression was more predictive among eyes in the lowest quartile of light TISA500 measurements (HR = 4.56, P < .001) compared to dark measurements (HR = 2.89, P = .003). CONCLUSION: Static parameters measured in the light are as predictive, and possibly more so, of angle closure progression as those measured in the dark. Ocular biometrics measured under light and dark conditions may provide additional information for risk-stratifying patients for angle closure progression.