Racial differences and determinants of macular thickness profiles in multiethnic Asian population: the Singapore Epidemiology of Eye Diseases Study

The AI revolution in glaucoma: Bridging challenges with opportunities

Recent advancements in artificial intelligence (AI) herald transformative potentials for reshaping glaucoma clinical management, improving screening efficacy, sharpening diagnosis precision, and refining the detection of disease progression. However, incorporating AI into healthcare usages faces significant hurdles in terms of developing algorithms and putting them into practice. When creating algorithms, issues arise due to the intensive effort required to label data, inconsistent diagnostic standards, and a lack of thorough testing, which often limits the algorithms' widespread applicability. Additionally, the "black box" nature of AI algorithms may cause doctors to be wary or skeptical. When it comes to using these tools, challenges include dealing with lower-quality images in real situations and the systems' limited ability to work well with diverse ethnic groups and different diagnostic equipment. Looking ahead, new developments aim to protect data privacy through federated learning paradigms, improving algorithm generalizability by diversifying input data modalities, and augmenting datasets with synthetic imagery. The integration of smartphones appears promising for using AI algorithms in both clinical and non-clinical settings. Furthermore, bringing in large language models (LLMs) to act as interactive tool in medicine may signify a significant change in how healthcare will be delivered in the future. By navigating through these challenges and leveraging on these as opportunities, the field of glaucoma AI will not only have improved algorithmic accuracy and optimized data integration but also a paradigmatic shift towards enhanced clinical acceptance and a transformative improvement in glaucoma care.

Analysis of macular thickness and peripapillary retinal nerve fiber layer thickness in various ABO and Rh blood groups

PURPOSE

To determine the association between ABO and Rh blood groups with retinal structural indices including macular thickness and peripapillary retinal nerve fiber layer (RNFL) thickness.

METHODS

This cross-sectional study was conducted using convenience sampling in a tertiary referral eye hospital in Tehran, Iran. Study participants were referred to the hospital laboratory to test their blood group. Ocular examinations were performed including measurement of visual acuity, auto-refraction, subjective refraction, and slit-lamp biomicroscopy. Retinal imaging was carried out using Spectral-domain OCT under dilated papillary conditions.

RESULTS

Three hundred and twenty-eight individuals were recruited in this study. Of these, 219 (60.7%) were female and the mean age of the participants was 63.29 ± 5.57 years (range: 56 to 83 years). According to the multiple linear regression model, the global peripapillary RNFL thickness [coefficient: -3.05 (95% CI: -5.30 to -0.74); P = 0.010] and peripapillary RNFL thickness in the superior [coefficient: -4.65 (95% CI: -8.40 to -0.89), P < 0.001] and inferior [coefficient: -4.00 (95% CI: -7.81 to -0.19); P = 0.040] quadrants were significantly thinner in individuals with blood type B compared to those with other ABO blood groups. The average [coefficient: 12.69 (95% CI: 4.12-21.64); P = 0.004) and central [coefficient: 16.21 (95%: 6.44-25.97); P = 0.001) macular thicknesses were significantly thicker in AB group compared to other blood groups. The average macular thickness was significantly thinner in Rh + compared to the Rh- group [coefficient: -8.33 (95% CI: -15.4 to -1.25); P = 0.021].

CONCLUSION

Retinal structural indices may be related to blood groups implying a genetic linkage. Considering the lack of consistency among various studies, larger trials are needed to explore the effect of ABO and Rh grouping on peripapillary RNFL and macular thicknesses.

Deep learning-based image quality assessment for optical coherence tomography macular scans: a multicentre study

AIMS

To develop and externally test deep learning (DL) models for assessing the image quality of three-dimensional (3D) macular scans from Cirrus and Spectralis optical coherence tomography devices.

METHODS

We retrospectively collected two data sets including 2277 Cirrus 3D scans and 1557 Spectralis 3D scans, respectively, for training (70%), fine-tuning (10%) and internal validation (20%) from electronic medical and research records at The Chinese University of Hong Kong Eye Centre and the Hong Kong Eye Hospital. Scans with various eye diseases (eg, diabetic macular oedema, age-related macular degeneration, polypoidal choroidal vasculopathy and pathological myopia), and scans of normal eyes from adults and children were included. Two graders labelled each 3D scan as gradable or ungradable, according to standardised criteria. We used a 3D version of the residual network (ResNet)-18 for Cirrus 3D scans and a multiple-instance learning pipline with ResNet-18 for Spectralis 3D scans. Two deep learning (DL) models were further tested via three unseen Cirrus data sets from Singapore and five unseen Spectralis data sets from India, Australia and Hong Kong, respectively.

RESULTS

In the internal validation, the models achieved the area under curves (AUCs) of 0.930 (0.885-0.976) and 0.906 (0.863-0.948) for assessing the Cirrus 3D scans and Spectralis 3D scans, respectively. In the external testing, the models showed robust performance with AUCs ranging from 0.832 (0.730-0.934) to 0.930 (0.906-0.953) and 0.891 (0.836-0.945) to 0.962 (0.918-1.000), respectively.

CONCLUSIONS

Our models could be used for filtering out ungradable 3D scans and further incorporated with a disease-detection DL model, allowing a fully automated eye disease detection workflow.

Exploring ethnic and racial differences in intraocular pressure and glaucoma: The Canadian Longitudinal Study on aging

Purpose

To determine whether self-reported race/ethnicity is associated with intraocular pressure (IOP) and glaucoma and to explore whether any associations are due to social, behavioral, genetic, or health differences.

Design

Cross-sectional analysis of population-based data.

Methods

We used the Canadian Longitudinal Study on Aging Comprehensive Cohort, which consists of 30,097 adults aged 45-85 years. Race/ethnicity was self-reported. Corneal-compensated intraocular pressure (IOP) was measured in mmHg using the Reichert Ocular Response Analyzer. Participants were asked to report if they have ever had a diagnosis of glaucoma and whether they used eye care in the past year. A glaucoma polygenic risk score (PRS) was calculated. Logistic and linear regression models were used.

Results

Black individuals had higher mean IOP levels (beta coefficient (β) = 1.46; 95% confidence interval [CI], 0.62, 2.30) while Chinese, Japanese and Korean (β = -1.00; 95% CI, -1.63, -0.38) and Southeast Asian and Filipino individuals (β = -1.56; 95% CI, -2.68, -0.43) had lower mean IOP levels as compared to White individuals after adjustment for sociodemographic, behavioral, genetic, and health-related variables. Black people were more likely to report glaucoma as compared to White people after adjustment (odds ratio [OR] = 2.43; 95% CI, 1.27, 4.64).

Conclusion

Racial and ethnic differences in IOP and glaucoma were identified. Adjusting for sociodemographic, behavioral, genetic, and health-related variables did not fully explain these differences. Longitudinal research is needed to further explore the reasons for these differences and to understand their relevance to disease pathogenesis and progression.

Quantitative assessments of retinal macular structure among rural-dwelling older adults in China: a population-based, cross-sectional, optical coherence tomography study

OBJECTIVES

To quantitatively assess and compare retinal macular structures of rural-dwelling older adults in China using two different optical coherence tomography (OCT) scanners and to examine their associations with demographic, lifestyle, clinical and ocular factors.

DESIGN, SETTING AND PARTICIPANTS

This population-based, cross-sectional study included 971 participants (age ≥60 years) derived from the Multimodal Interventions to Delay Dementia and Disability in Rural China study. We collected data on demographics, lifestyle factors, clinical conditions (eg, cardiovascular disease (CVD)) and ocular factors (eg, visual acuity and spherical equivalent). We used two models of spectral-domain OCT to measure macular parameters in nine Early Treatment Diabetic Retinopathy Study subfields. Data were analysed using the multiple general linear models.

RESULTS

Spectralis OCT demonstrated higher macular thickness but a lower macular volume than Primus 200 OCT (p<0.05). Nasal quadrant of the inner and outer subfields was the thickest, followed by superior quadrant. Adjusting for multiple potential confounding variables, older age was significantly correlated with lower average inner and outer macular thicknesses and overall macular volume. Men had higher macular parameters than women. The presence of CVD was correlated with lower central macular thickness (β=-6.83; 95% CI: -13.08 to -0.58; p=0.032). Middle school or above was associated with higher average inner macular thickness (β=7.85; 95% CI: 1.14 to 14.55; p=0.022) and higher spherical equivalent was correlated with lower average inner macular thickness (β=-1.78; 95% CI: -3.50 to -0.07; p=0.042).

CONCLUSIONS

Macular thickness and volume assessed by Spectralis and Primus 200 OCT scanners differ. Older age and female sex are associated with lower macular thickness and volume. Macular parameters are associated with education, CVD and spherical equivalent.

TRIAL REGISTERATION NUMBER

MIND-China study (ChiCTR1800017758).

Relationship Between Retinal Layer Thickness and Genetic Susceptibility to Age-Related Macular Degeneration in Asian Populations

Purpose

For OCT retinal thickness measurements to be used as a prodromal age-related macular degeneration (AMD) risk marker, the 3-dimensional (3D) topographic variation of the relationship between genetic susceptibility to AMD and retinal thickness needs to be assessed. We aimed to evaluate individual retinal layer thickness changes and topography at the macula that are associated with AMD genetic susceptibility.

Design

Genetic association study.

Participants

A total of 1579 healthy participants (782 Chinese, 353 Malays, and 444 Indians) from the multiethnic Singapore Epidemiology of Eye Diseases study were included.

Methods

Spectral-domain OCT and automatic segmentation of individual retinal layers were performed to produce 10 retinal layer thickness measurements at each ETDRS subfield, producing 3D topographic information. Age-related macular degeneration genetic susceptibility was represented via single nucleotide polymorphisms (SNPs) and aggregated via whole genome (overall) and pathway-specific age-related macular degeneration polygenic risk score (PRSAMD).

Main Outcome Measures

Associations of individual SNPs, overall PRSAMD, and pathway-specific PRSAMD with retinal thickness were analyzed by individual retinal layer and ETDRS subfield.

Results

CFH rs10922109, ARMS2-HTRA1 rs3750846, and LIPC rs2043085 were the top AMD susceptibility SNPs associated with retinal thickness of individual layers (P < 1.67 × 10-3), all at the central subfield. The overall PRSAMD was most associated with thinner L9 (outer segment photoreceptor/retinal pigment epithelium complex) thickness at the central subfield (β = -0.63 μm; P = 5.45 × 10-9). Pathway-specific PRSAMD for the complement cascade (β = -0.53 μm; P = 9.42 × 10-7) and lipoprotein metabolism (β = -0.05 μm; P = 0.0061) were associated with thinner photoreceptor layers (L9 and L7 [photoreceptor inner/outer segments], respectively) at the central subfield. The mean PRSAMD score was larger among Indians compared with that of the Chinese and had the thinnest thickness at the L9 central subfield (β = -1.00 μm; P = 2.91 × 10-7; R2 = 5.5%). Associations at other retinal layers and ETDRS regions were more heterogeneous.

Conclusions

Overall genetic susceptibility to AMD and the aggregate effects of the complement cascade and lipoprotein metabolism pathway are associated most significantly with L7 and L9 photoreceptor thinning at the central macula in healthy individuals. Photoreceptor thinning has potential to be a prodromal AMD risk marker, and topographic variation should be considered.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Macular thickness and its associated factors in a Chinese rural adult population: the Handan Eye Study

PURPOSE

To describe the normal macular thickness and assess its associations.

METHODS

The Handan Eye Follow-up Study was conducted between 2012 and 2013. Macular thickness was scanned by spectral-domain optical coherence tomography (OCT). The built-in software generated a retinal thickness (RT) map, which was divided into three regions (central, internal and external regions) and nine quadrants (one in central and four in internal and external regions each).

RESULTS

For 5394 subjects in the Handan Eye Follow-up Study, 4793 received OCT examination, 2946 of whom (accounting for 61.46% of the total subjects, mean age 58.91±10.95, 55.6% were women) were included for analysis. The mean RT in central macula, inner and outer rings were (237.38 µm±23.05 µm), (309.77 µm±18.36 µm) and (278.29 µm±14.38 µm), respectively (overall difference, p＜0.001). In inner ring, the RT in temporal was thinnest, followed by nasal, superior and inferior. In outer ring, the RT in superior was thinnest, with the next subfields being temporal, inferior and nasal, respectively. The RT in central macula, inner and outer rings were significantly thicker in men than in women. Multivariate linear regression analysis showed that in central macula, RT increased in subjects younger than 60 years and thinned above the age of 60. In inner and outer rings, RT thinned along with age (p＜0.001).

CONCLUSIONS

This study finds that RT in central macula is the thinnest, followed by the outer ring, the RT in the inner ring is the thickest. Age and gender are related to RT. These associated factors need to be considered when explaining RT.

Assessment of the Retinal Vessels in Keratoconus: An OCT Angiography Study

This study investigated vascular density and foveal avascular zone (FAZ) parameters using optical coherence tomography angiography (OCT-A) in patients with keratoconus (KC). Participants with KC and healthy controls were included and underwent best-corrected visual acuity (BCVA), keratometry, anterior segment OCT, and macular OCT-A examinations. Of the 70 subjects (mean age 42.9 ± 15.31 years), 79 KC and 47 healthy eyes were included. Significant reductions in the KC group were recorded for the FAZ area, with a mean (±SD) of 0.19 ± 0.12 vs. 0.25 ± 0.09 mm2 p < 0.001. Central vascular density in KC patients was lower compared with the controls: 6.78 ± 4.74 vs. 8.44 ± 3.33 mm−1 p = 0.049; the inner density was also decreased in the study group (13.64 ± 5.13 vs. 16.54 ± 2.89 mm−1, p = 0.002), along with the outer density (14.71 ± 4.12 vs. 16.88 ± 2.42 mm−1, p = 0.004) and full density (14.25 ± 4.30 vs. 16.57 ± 2.48) p = 0.003. Furthermore, BCVA was positively correlated with central vascular density (R = 0.42 p = 0.004, total R = 0.40, p = 0.006) and inner density (R = 0.44, p = 0.002) in patients with KC but not in controls. Additionally, we found a correlation between K2 and inner vascular density (R = −0.30, p = 0.043) and central epithelium thickness and outer density (R = 0.03, p = 0.046). KC patients had lower macular vascular density and a smaller FAZ than healthy participants. The BCVA in KC patients was correlated with the vascular density.

Comparison of peripapillary retinal nerve fiber layer and macular thickness in non-diabetic chronic kidney disease and controls

Objective

This study aimed to compare the peripapillary retinal nerve fiber layer (pRNFL) thickness and macular thickness (MT) between patients with non-diabetic chronic kidney disease (NDCKD) and controls, as well as between different stages of NDCKD. We also evaluated the correlation between pRNFL thickness and MT with duration of NDCKD.

Methods

This was a comparative cross-sectional study. Subjects were divided into NDCKD and control groups. Both pRNFL thickness and MT, including center subfield thickness (CST), average MT as well as average ganglion cell-inner plexiform layer (GC-IPL) were measured using spectral-domain optical coherence tomography. One-way ANCOVA test was used to compare the differences in pRNFL and MT between NDCKD and controls, as well as between the different stages of NDCKD. Spearman rank-order correlation coefficients were employed to determine the effects of NDCKD duration on pRNFL thickness and MT.

Results

A total of 132 subjects were recruited, 66 with NDCKD and 66 controls. There was a statistically significant difference in superior (110.74 ± 23.35 vs 117.36 ± 16.17 μm, p = 0.022), nasal (65.97 ± 12.90 vs 69.35 ± 10.17 μm, p = 0.006), inferior quadrant (117.44 ± 23.98 vs 126.15 ± 14.75 μm, p = 0.006), average pRNFL (90.36 ± 14.93 vs 95.42 ± 9.87 μm, p = 0.005), CST (231.89 ± 26.72 vs 243.30 ± 21.05 μm, p = 0.006), average MT (268.88 ± 20.21 vs 274.92 ± 12.79 μm, p = 0.020) and average GC-IPL (75.48 ± 12.44 vs 81.56 ± 6.48, p = 0.001) values between the NDCKD group and controls. The superior quadrant (p = 0.007), nasal quadrant (p = 0.030), inferior quadrant (p = 0.047), average pRNFL (p = 0.006), average MT (p = 0.001) and average GC-IPL (p = 0.001) differed significantly between different stages of NDCKD. There was no correlation between pRNFL thickness and MT with duration of NDCKD.

Conclusion

CST, average MT, average GC-IPL thickness, average pRNFL and all quadrants of pRNFL except the temporal quadrant were significantly thinner in NDCKD patients compared to controls. These changes were associated with the severity of CKD, but not its duration.

Retinal microvascular abnormalities in patients after COVID-19 depending on disease severity

BACKGROUND

Global pandemic SARS-CoV-2 causes a prothrombotic state without fully elucidated effects. This study aims to analyse and quantify the possible retinal microvascular abnormalities.

MATERIALS AND METHODS

Case-control study. Patients between 18 and 55 years old with PCR-confirmed SARS-CoV-2 infection within the last 3 months were included.

RISK STRATIFICATION

group 1-mild disease (asymptomatic/paucisymptomatic); group 2-moderate disease (required hospital admission with no acute respiratory distress) and group 3-severe disease (subjects who developed an acute respiratory distress were admitted in the intensive care unit and presented interleukin 6 values above 40 pg/mL). Age-matched volunteers with negative serology tests were enrolled to control group. A colour photograph, an optical coherence tomography (OCT) and an angiography using OCT centred on the fovea were performed.

RESULTS

Control group included 27 subjects: group 1 included 24 patients, group 2 consisted of 24 patients and 21 participants were recruited for group 3. There were no funduscopic lesions, neither in the colour images nor in the structural OCT. Fovea-centred vascular density (VD) was reduced in group 2 and group 3 compared with group 1 and control group (control group vs group 2; 16.92 vs 13.37; p=0.009) (control group vs group 3; 16.92 vs .13.63; p=0.026) (group 1 vs group 2; 17.16 vs 13.37; p=0.006) (group 1 vs group 3; 17.16 vs 13.63 p=0.017).

CONCLUSION

Patients with moderate and severe SARS-CoV-2 pneumonia had decreased central retinal VD as compared with that of asymptomatic/paucisymptomatic cases or control subjects.

Normative Database for All Retinal Layer Thicknesses Using SD-OCT Posterior Pole Algorithm and the Effects of Age, Gender and Axial Lenght

Our aim was to provide, for the first time, reference thickness values for the SD-OCT posterior pole algorithm (PPA) available for Spectralis OCT device (Heidelberg Engineering, Heidelberg, Germany) and to analyze the correlations with age, gender and axial length. We recruited 300 eyes of 300 healthy Caucasian subjects between 18 and 84 years. By PPA, composed of 64 (8 × 8) cells, we analyzed the thickness of the following macular layers: retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), retinal pigment epithelium (RPE), inner retina, outer retina and full retina. Mean ± SD, 1st, 5th, 95th percentiles were obtained for each cell at all macular layers. Significant negative correlations were found between age and thickness for most macular layers. The mean thickness of most macular layers was thicker for men than women, except for RNFL, OPL and RPE, with no gender differences. GCL, IPL and INL thicknesses positively correlated with axial length in central cells, and negatively in the cells near the optic disk. The mean RNFL thickness was positively associated with axial length. This is the first normative database for PPA. Age, gender and axial length should be taken into account when interpreting PPA results.

Diagnostic Ability of Individual Macular Layers by Spectral-Domain OCT in Different Stages of Glaucoma

PURPOSE

To compare the diagnostic ability of macular intraretinal layer thickness with circumpapillary retinal nerve fiber layer (cpRNFL) thickness, either when used individually or in combination with cpRNFL for detecting early, moderate, and advanced glaucoma.

DESIGN

Cross-sectional study.

PARTICIPANTS

A total of 423 glaucoma participants and 423 age- and gender-matched normal participants.

METHODS

Participants underwent Cirrus spectral-domain OCT (SD-OCT) imaging (Carl Zeiss Meditec, Dublin, CA) using the optic disc and macular scanning protocols. Iowa Reference Algorithms (version 3.8.0) were used for intraretinal layer segmentation, and mean thickness of intraretinal layers was rescaled with magnification correction using axial length value. Thickness measurements of each layer/sector and their corresponding areas under the receiver operating characteristic curve (AUCs) were obtained. Glaucoma eyes were subdivided based on of their visual field severity (early, n = 234; moderate, n = 107; advanced, n = 82).

MAIN OUTCOME MEASURES

Intraretinal layers.

RESULTS

Some 67% of participants were male, their average ± standard deviation age was 65±9 years. Circumpapillary retinal nerve fiber layer, macular ganglion cell layer (mGCL), and macular inner plexiform layer (mIPL) were significantly thinner in the glaucoma groups (P < 0.0005). The 2 best parameters for detecting normal eyes from early glaucoma was cpRNFL (AUC = 0.861) and mGCL (AUC = 0.842), from moderate glaucoma was mGCL combined with inner plexiform layer (IPL) (AUC = 0.915) and cpRNFL (AUC = 0 .914), and from advanced glaucoma was mGCL-IPL (AUC = 0.984) and cpRNFL (AUC = 0.977). There was no statistical significance between AUCs for the macular parameter and cpRNFL thickness measurement at any of the severities (P > 0.05). Combining macular and cpRNFL parameters improved the diagnostic performance for early glaucoma (AUC = 0.908; P = 0.002) and moderate glaucoma (AUC = 0.944; P = 0.031) but not for advanced glaucoma (AUC = 0.991; P > 0.05).

CONCLUSIONS

Single-layer mGCL thickness is comparable to the traditional cpRNFL thickness for the diagnosis of early/moderate glaucoma, whereas cpRNFL thickness remains the most efficient for advanced glaucoma. Combining macular measurements (GCL and GCL-IPL) and cpRNFL improved the discrimination of early/moderate glaucoma but not of advanced glaucoma. For the diagnosis of early glaucoma, both macular and optic disc scans should be used.

Patterns and Determinants of Choroidal Thickness in a Multiethnic Asian Population: The Singapore Epidemiology of Eye Diseases Study

PURPOSE

To describe the distribution and determinants of choroidal thickness (CT) in participants in a population study based on spectral-domain (SD)-OCT measurements.

DESIGN

Population-based, cross-sectional study.

PARTICIPANTS

Ethnic Chinese, Indian, and Malay adults aged more than 50 years without any retinal diseases (e.g., diabetic retinopathy, macular edema, age-related macular degeneration, central serous chorioretinopathy) that might affect the CT were recruited from the Singapore Epidemiology of Eye Diseases Study.

METHODS

Choroidal imaging was performed by SD-OCT (Spectralis, Heidelberg Engineering, Heidelberg, Germany) in enhanced depth imaging (EDI) mode. Subfoveal choroidal thickness (SFCT) was measured on the foveal line scan by 2 retinal experts independently (YS and KT), and the average was used in the analyses. In Chinese and Indian cohorts in whom macular raster scans were captured, the manufacturer-supplied research software (Heyex SP-X version 6.4.8.116; Heidelberg Engineering) was used to obtain automated segmentation yielding mean choroidal thickness in each of the 9 ETDRS grid sectors.

MAIN OUTCOME MEASURES

Subfoveal choroidal thickness and regional CT in the 9 ETDRS grid sectors.

RESULTS

For the SFCT analysis, 2794 eyes of 1619 participants (Chinese, Indian, and Malay ) were included. The mean age was 60.9 years (standard deviation, 7.7), and 797 (49.2%) were male. Mean SFCT was 255.2 μm (standard deviation, 102.6). The normal range of SFCT was 106 to 447 μm (corresponding to 5^th and 95^th percentile limits of SFCT, respectively). In multivariable models, thinner SFCT was associated with older age, female gender, longer axial length, and Malay (vs. Chinese) ethnicity. In the subset of Chinese and Indian eyes (n = 1842) in whom regional variation was evaluated, the choroid was thickest at the superior and temporal sectors and thinner at the inferior and nasal sectors.

CONCLUSIONS

Subfoveal choroidal thickness is influenced by age, gender, and ethnicity along with regional differences even within individual eyes. Subfoveal choroidal thickness also shows a wide range in physiologic limits. These data may be used as a reference in future studies.

Association between Macular Thickness Profiles and Visual Function in Healthy Eyes: The Singapore Epidemiology of Eye Diseases (SEED) Study

This study aimed to evaluate the association between optical coherence tomography (OCT)-measured retinal layer thickness parameters with clinical and patient-centred visual outcomes in healthy eyes. Participants aged 40 and above were recruited from the Singapore Epidemiology of Eye Diseases Study, a multi-ethnic population-based study. Average macular, ganglion cell-inner plexiform layer (GCIPL), and outer retinal thickness parameters were obtained using the Cirrus High Definition-OCT. Measurements of best-corrected visual acuity (BCVA) and 11-item visual functioning questionnaire (VF-11) were performed. Associations between macular thickness parameters, with BCVA and Rasch-transformed VF-11 scores (in logits) were assessed using multivariable linear regression models with generalized estimating equations, adjusted for relevant confounders. 4,540 subjects (7,744 eyes) with a mean age of 58.8 ± 8.6 years were included. The mean BCVA (LogMAR) was 0.10 ± 0.11 and mean VF-11 score was 5.20 ± 1.29. In multivariable regression analysis, thicker macula (per 20 µm; β = −0.009) and GCIPL (per 20 µm; β = −0.031) were associated with better BCVA (all p ≤ 0.001), while thicker macula (per 20 µm; β = 0.04) and GCIPL (per 20 µm, β = 0.05) were significantly associated with higher VF-11 scores (all p < 0.05). In conclusion, among healthy Asian eyes, thicker macula and GCIPL were associated with better vision and self-reported visual functioning. These findings provide further understanding on the potential influence of macular thickness on visual function.

Age-related changes of individual macular retinal layers among Asians

We characterized the age-related changes of the intra-retinal layers measured with spectral-domain optical coherence tomography (SD-OCT; Cirrus high-definition OCT [Carl Zeiss Meditec]. The Singapore Epidemiology of Eye Diseases is a population-based, cross-sectional study of Chinese, Malays and Indians living in Singapore. Iowa Reference Algorithms (Iowa Institute for Biomedical Imaging) were used for intra-retinal layer segmentation and mean thickness of 10 intra-retinal layers rescaled with magnification correction using axial length value. Linear regression models were performed to investigate the association of retinal layers with risk factors. After excluding participants with history of diabetes or ocular diseases, high-quality macular SD-OCT images were available for 2,047 participants (44–89 years old). Most of the retinal layers decreased with age except for foveal retinal nerve fiber layer (RNFL) and the inner/outer segments of photoreceptors where they increased with age. Men generally had thicker retinal layers than women. Chinese have the thickest RNFL and retinal pigment epithelium amongst the ethnic groups. Axial length and refractive error remained correlated with retinal layers in spite of magnification correction. Our data show pronounced age-related changes in retinal morphology. Age, gender, ethnicity and axial length need be considered when establishing OCT imaging biomarkers for ocular or systemic disease.

Compensation of retinal nerve fibre layer thickness as assessed using optical coherence tomography based on anatomical confounders

Background/Aims

To compensate the retinal nerve fibre layer (RNFL) thickness assessed by spectral-domain optical coherence tomography (SD-OCT) for anatomical confounders.

Methods

The Singapore Epidemiology of Eye Diseases is a population-based study, where 2698 eyes (1076 Chinese, 704 Malays and 918 Indians) with high-quality SD-OCT images from individuals without eye diseases were identified. Optic disc and macular cube scans were registered to determine the distance between fovea and optic disc centres (fovea distance) and their respective angle (fovea angle). Retinal vessels were segmented in the projection images and used to calculate the circumpapillary retinal vessel density profile. Compensated RNFL thickness was generated based on optic disc (ratio, orientation and area), fovea (distance and angle), retinal vessel density, refractive error and age. Linear regression models were used to investigate the effects of clinical factors on RNFL thickness.

Results

Retinal vessel density reduced significantly with increasing age (1487±214 µm in 40–49, 1458±208 µm in 50–59, 1429±223 µm in 60–69 and 1415±233 µm in ≥70). Compensation reduced the variability of RNFL thickness, where the effect was greatest for Chinese (10.9%; p<0.001), followed by Malays (6.6%; p=0.075) and then Indians (4.3%; p=0.192). Compensation reduced the age-related RNFL decline by 55% in all participants (β=−3.32 µm vs β=−1.50 µm/10 years; p<0.001). Nearly 62% of the individuals who were initially classified as having abnormally thin RNFL (outside the 99% normal limits) were later reclassified as having normal RNFL.

Conclusions

RNFL thickness compensated for anatomical parameters reduced the variability of measurements and may improve glaucoma detection, which needs to be confirmed in future studies.