DESIGN: Population-based, cross-sectional study.

SUBJECTS: Adults aged > 50 years were recruited from the third examination of the population-based Singapore Malay Eye Study.

METHODS: All participants underwent a standardized comprehensive examination and spectral-domain OCTA (Optovue) of the macula. OCT angiography scans that revealed pre-existing retinal disease, revealed macular pathology, and had poor quality were excluded.

MAIN OUTCOME MEASURES: The normative quantitative vessel densities of the superficial layer, deep layer, and foveal avascular zone (FAZ) were evaluated. Ocular and systemic associations with macular retinal vasculature parameters were also evaluated in a multivariable analysis using linear regression models with generalized estimating equation models.

RESULTS: We included 1184 scans (1184 eyes) of 749 participants. The mean macular superficial vessel density (SVD) and deep vessel density (DVD) were 45.1 ± 4.2% (95% confidence interval [CI], 37.8%-51.4%) and 44.4 ± 5.2% (95% CI, 36.9%-53.2%), respectively. The mean SVD and DVD were highest in the superior quadrant (48.7 ± 5.9%) and nasal quadrant (52.7 ± 4.6%), respectively. The mean FAZ area and perimeter were 0.32 ± 0.11 mm2 (95% CI, 0.17-0.51 mm) and 2.14 ± 0.38 mm (95% CI, 1.54-2.75 mm), respectively. In the multivariable regression analysis, female sex was associated with higher SVD (β = 1.25, P ≤ 0.001) and DVD (β = 0.75, P = 0.021). Older age (β = -0.67, P < 0.001) was associated with lower SVD, whereas longer axial length (β = -0.42, P = 0.003) was associated with lower DVD. Female sex, shorter axial length, and worse best-corrected distance visual acuity were associated with a larger FAZ area. No association of a range of systemic parameters with vessel density was found.

METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning.

RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83.