Potential Ocular Biomarkers for Early Detection of Alzheimer's Disease and Their Roles in Artificial Intelligence Studies.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is believed to be essential to disease management because it enables physicians to initiate treatment in patients with early-stage AD (early AD), with the possibility of stopping the disease or slowing disease progression, preserving function and ultimately reducing disease burden. The purpose of this study was to review prior research on the use of eye biomarkers and artificial intelligence (AI) for detecting AD and early AD. The PubMed database was searched to identify studies for review. Ocular biomarkers in AD research and AI research on AD were reviewed and summarized. According to numerous studies, there is a high likelihood that ocular biomarkers can be used to detect early AD: tears, corneal nerves, retina, visual function and, in particular, eye movement tracking have been identified as ocular biomarkers with the potential to detect early AD. However, there is currently no ocular biomarker that can be used to definitely detect early AD. A few studies that used AI with ocular biomarkers to detect AD reported promising results, demonstrating that using AI with ocular biomarkers through multimodal imaging could improve the accuracy of identifying AD patients. This strategy may become a screening tool for detecting early AD in older patients prior to the onset of AD symptoms.

A 10-Year Single-Center Study of the Clinical Characteristics of Optic Neuritis-Related NMOSD, MS, and Double Seronegative Optic Neuritis, Together with Factors Predicting Visual Outcomes.

The clinical characteristics of three types of optic neuritis (double seronegative optic neuritis; DN-ON, Neuromyelitis optica spectrum disorder-related optic neuritis; NMOSD-ON, and multiple sclerosis-related optic neuritis; MS-ON) were examined in order to identify factors that may affect good visual recovery in Thai patients. The study included patients diagnosed with three types of optic neuritis at Rajavithi Hospital between 2011 and 2020. Visual acuity at the end of 12 months was used as the treatment outcome. Multiple logistic regression analysis was used to evaluate potential predictors of good visual recovery. Of the 76 patients, 61 had optic neuritis, with DN-ON as the most common subtype (52.6%). MS-ON patients were significantly younger (28.3 ± 6.6 years, p = 0.002) and there was a female predominance in all subgroups (p = 0.076). NMOSD-ON patients had a significantly higher proportion of poor baseline VA (p < 0.001). None of the NMOSD-ON patients achieved 0.3 logMAR visual recovery in the 12-month period (p = 0.022). A delay in treatment with intravenous methylprednisolone (IVMP) for more than 7 days increased the risk of failure to gain 0.3 logMAR visual recovery by five times (OR 5.29, 95% CI 1.359-20.616, p = 0.016), with NMOSD-ON as the strongest predictor (OR 10.47, 95% CI; 1.095-99.993, p = 0.041). Early treatment with intravenous methylprednisolone may be important for achieving at least 0.3 logMAR visual recovery in Thai patients with optic neuritis.

Polypoidal Choroidal Vasculopathy: Updates on Risk Factors, Diagnosis, and Treatments.

There have been recent advances in basic research and clinical studies in polypoidal choroidal vasculopathy (PCV). A recent, large-scale, population-based study found systemic factors, such as male gender and smoking, were associated with PCV, and a recent systematic review reported plasma C-reactive protein, a systemic biomarker, was associated with PCV. Growing evidence points to an association between pachydrusen, recently proposed extracellular deposits associated with the thick choroid, and the risk of development of PCV. Many recent studies on diagnosis of PCV have focused on applying criteria from noninvasive multimodal retinal imaging without requirement of indocyanine green angiography. There have been attempts to develop deep learning models, a recent subset of artificial intelligence, for detecting PCV from different types of retinal imaging modality. Some of these deep learning models were found to have high performance when they were trained and tested on color retinal images with corresponding images from optical coherence tomography. The treatment of PCV is either a combination therapy using verteporfin photodynamic therapy and anti-vascular endothelial growth factor (VEGF), or anti-VEGF monotherapy, often used with a treat-and-extend regimen. New anti-VEGF agents may provide more durable treatment with similar efficacy, compared with existing anti-VEGF agents. It is not known if they can induce greater closure of polypoidal lesions, in which case, combination therapy may still be a mainstay. Recent evidence supports long-term follow-up of patients with PCV after treatment for early detection of recurrence, particularly in patients with incomplete closure of polypoidal lesions.

The Classification of Common Macular Diseases Using Deep Learning on Optical Coherence Tomography Images with and without Prior Automated Segmentation.

We compared the performance of deep learning (DL) in the classification of optical coherence tomography (OCT) images of macular diseases between automated classification alone and in combination with automated segmentation. OCT images were collected from patients with neovascular age-related macular degeneration, polypoidal choroidal vasculopathy, diabetic macular edema, retinal vein occlusion, cystoid macular edema in Irvine-Gass syndrome, and other macular diseases, along with the normal fellow eyes. A total of 14,327 OCT images were used to train DL models. Three experiments were conducted: classification alone (CA), use of automated segmentation of the OCT images by RelayNet, and the graph-cut technique before the classification (combination method 1 (CM1) and 2 (CM2), respectively). For validation of classification of the macular diseases, the sensitivity, specificity, and accuracy of CA were found at 62.55%, 95.16%, and 93.14%, respectively, whereas the sensitivity, specificity, and accuracy of CM1 were found at 72.90%, 96.20%, and 93.92%, respectively, and of CM2 at 71.36%, 96.42%, and 94.80%, respectively. The accuracy of CM2 was statistically higher than that of CA (p = 0.05878). All three methods achieved AUC at 97%. Applying DL for segmentation of OCT images prior to classification of the images by another DL model may improve the performance of the classification.

Geographic Atrophy Phenotypes in Subjects of Different Ethnicity: Asia-Pacific Ocular Imaging Society Work Group Report 3.

OBJECTIVE: To characterize geographic atrophy (GA) and evaluate differences between Asians and non-Asians. DESIGN: Multicenter, retrospective case series. PARTICIPANTS: Subjects aged ≥ 50 years with GA secondary to age-related macular degeneration in the absence of neovascularization in the study eye and follow-up of ≥ 2 years. METHODS: The GA lesion characterized at baseline and last follow-up based on multimodal imaging (fundus autofluorescence [FAF], near infrared [NIR], and spectral domain-OCT). Patients were grouped as either Asian or non-Asian. MAIN OUTCOME MEASURES: Comparison of (1) phenotypes of GA lesions (size, foveal involvement, number of foci, drusen background, and choroid background) and (2) growth rates of GA. RESULTS: A total of 144 patients (169 eyes) with distribution of 50.9% Asians and 49.1% non-Asians. The age and sex were similar between Asians and non-Asians (Asians: mean age, 77.2 ± 10.1 years, 47.9% female; non-Asians: mean age, 79.7 ± 8.4 years, 58.7% female). Asians exhibited thicker choroids (167 ± 74 versus [vs.] 134 ± 56 µm; P < 0.01) and lower prevalence of drusen (40.7% vs. 66.3%; P < 0.01). At baseline, the GA area was smaller in Asians vs. non-Asians (NIR, 3.7 ± 4.6 vs. 6.3 ± 6.8 mm2; P = 0.01: FAF, 2.4 ± 3.4 vs. 8.4 ± 9.6 mm2; P < 0.01). Asians had fewer GA foci (1.7 ± 1.3 vs. 2.7 ± 2.2; P < 0.01) compared to non-Asians. The proportion with diffused or banded FAF junctional zone pattern was similar between Asians and non-Asians (44.2% vs. 60.2%; P = 0.20). Asians had a slower GA lesion growth rate than non-Asians (NIR, 0.7 vs. 1.9 mm2/year; P < 0.01: FAF, 0.3 vs. 2.0 mm2/year; P < 0.01: NIR, 0.2 vs. 0.4 mm/year; P < 0.01 square root transformed: FAF, 0.1 vs. 0.3 mm/year; P < 0.01 square root transformed). The factors associated with GA lesion growth rate are (from the highest effect size) ethnicity, junctional zone FAF pattern, baseline GA area, and number of GA foci. Higher GA lesion growth rate was observed in both Asian and non-Asian subgroups, with drusen or lesion size and FAF patterns meeting inclusion criteria of recent therapeutic trials, but growth rate remained significantly slower in Asians. Eyes with baseline lesion ≥ 5 mm2 showed the highest growth rate, and the difference between ethnicities was no longer significant (2.6 vs. 3.3 mm2/year; P = 0.14). CONCLUSIONS: There are differences in GA lesion phenotype, associated features, and growth rate between Asians and non-Asian subjects. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

The Association Between Environmental and Social Factors and Myopia: A Review of Evidence From COVID-19 Pandemic.

Purpose: To review the association between children's behavioral changes during the restriction due to the pandemic of Coronavirus disease (COVID-19) and the development and progression of myopia. Design: A literature review. Method: We looked for relevant studies related to 1) children's behavioral changes from COVID-19 restriction and 2) children's myopia progression during COVID-19 restriction by using the following keywords. They were "Behavior," "Activity," "COVID-19," "Lockdown," "Restriction," and "Children" for the former; "Myopia," "COVID-19," "Lockdown," "Restriction" for the latter. Titles, abstracts and full texts from the retrieved studies were screened and all relevant data were summarized, analyzed, and discussed. Results: Children were less active and more sedentary during COVID-19 restriction. According to five studies from China and six studies, each from Hong Kong, Spain, Israel, South Korea, Turkey and Taiwan included in our review, all countries without myopia preventive intervention supported the association between the lockdown and myopia progression by means of negative SER change ranging from 0.05-0.6 D, more negative SER change (compared post- to pre-lockdown) ranging from 0.71-0.98 D and more negative rate of SER changes (compared post- to pre-lockdown) ranging from 0.05-0.1 D/month. The reported factor that accelerated myopia is an increase in total near work, while increased outdoor activity is a protective factor against myopia progression. Conclusion: The pandemic of COVID-19 provided an unwanted opportunity to assess the effect of the behavioral changes and myopia in the real world. There is sufficient evidence to support the association between an increase in near work from home confinement or a reduction of outdoor activities and worsening of myopia during the COVID-19 lockdown. The findings from this review of data from the real world may help better understanding of myopia development and progression, which may lead to adjustment of behaviors to prevent myopia and its progression in the future.