Towards Standardization of Quantitative Retinal Vascular Parameters: Comparison of SIVA and VAMPIRE Measurements in the Lothian Birth Cohort 1936

Applicability of Oculomics for Individual Risk Prediction: Repeatability and Robustness of Retinal Fractal Dimension Using DART and AutoMorph

Purpose

To investigate whether fractal dimension (FD)-based oculomics could be used for individual risk prediction by evaluating repeatability and robustness.

Methods

We used two datasets: "Caledonia," healthy adults imaged multiple times in quick succession for research (26 subjects, 39 eyes, 377 color fundus images), and GRAPE, glaucoma patients with baseline and follow-up visits (106 subjects, 196 eyes, 392 images). Mean follow-up time was 18.3 months in GRAPE; thus it provides a pessimistic lower bound because vasculature could change. FD was computed with DART and AutoMorph. Image quality was assessed with QuickQual, but no images were initially excluded. Pearson, Spearman, and intraclass correlation (ICC) were used for population-level repeatability. For individual-level repeatability, we introduce measurement noise parameter λ, which is within-eye standard deviation (SD) of FD measurements in units of between-eyes SD.

Results

In Caledonia, ICC was 0.8153 for DART and 0.5779 for AutoMorph, Pearson/Spearman correlation (first and last image) 0.7857/0.7824 for DART, and 0.3933/0.6253 for AutoMorph. In GRAPE, Pearson/Spearman correlation (first and next visit) was 0.7479/0.7474 for DART, and 0.7109/0.7208 for AutoMorph (all P < 0.0001). Median λ in Caledonia without exclusions was 3.55% for DART and 12.65% for AutoMorph and improved to up to 1.67% and 6.64% with quality-based exclusions, respectively. Quality exclusions primarily mitigated large outliers. Worst quality in an eye correlated strongly with λ (Pearson 0.5350-0.7550, depending on dataset and method, all P < 0.0001).

Conclusions

Repeatability was sufficient for individual-level predictions in heterogeneous populations. DART performed better on all metrics and might be able to detect small, longitudinal changes, highlighting the potential of robust methods.

Deep Learning based Retinal Vessel Caliber Measurement and the Association with Hypertension

PURPOSE

To develop a highly efficient and fully automated method that measures retinal vessel caliber using digital retinal photographs and evaluate the association between retinal vessel caliber and hypertension.

METHODS

The subjects of this study were from two sources in Beijing, China, a hypertension case-control study from Tongren Hospital (Tongren study) and a community-based atherosclerosis cohort from Peking University First Hospital (Shougang study). Retinal vessel segmentation and arteriovenous classification were achieved simultaneously by a customized deep learning model. Two experienced ophthalmologists evaluated whether retinal vessels were correctly segmented and classified. The ratio of incorrectly segmented and classified retinal vessels was used to measure the accuracy of the model's recognition. Central retinal artery equivalents, central retinal vein equivalents and arteriolar-to-venular diameter ratio were computed to analyze the association between retinal vessel caliber and the risk of hypertension. The association was then compared to that derived from the widely used semi-automated software (Integrative Vessel Analysis).

RESULTS

The deep learning model achieved an arterial recognition error rate of 1.26%, a vein recognition error rate of 0.79%, and a total error rate of 1.03%. Central retinal artery equivalents and arteriolar-to-venular diameter ratio measured by both Integrative Vessel Analysis and deep learning methods were inversely associated with the odds of hypertension in both Tongren and Shougang studies. The comparisons of areas under the receiver operating characteristic curves from the proposed deep learning method and Integrative Vessel Analysis were all not significantly different (p > .05).

CONCLUSION

The proposed deep learning method showed a comparable diagnostic value to Integrative Vessel Analysis software. Compared with semi-automatic software, our deep learning model has significant advantage in efficiency and can be applied to population screening and risk evaluation.

Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging

BACKGROUND

Artificial intelligence (AI) that utilizes deep learning (DL) has potential for systemic disease prediction using retinal imaging. The retina's unique features enable non-invasive visualization of the central nervous system and microvascular circulation, aiding early detection and personalized treatment plans for personalized care. This review explores the value of retinal assessment, AI-based retinal biomarkers, and the importance of longitudinal prediction models in personalized care.

MAIN TEXT

This narrative review extensively surveys the literature for relevant studies in PubMed and Google Scholar, investigating the application of AI-based retina biomarkers in predicting systemic diseases using retinal fundus photography. The study settings, sample sizes, utilized AI models and corresponding results were extracted and analysed. This review highlights the substantial potential of AI-based retinal biomarkers in predicting neurodegenerative, cardiovascular, and chronic kidney diseases. Notably, DL algorithms have demonstrated effectiveness in identifying retinal image features associated with cognitive decline, dementia, Parkinson's disease, and cardiovascular risk factors. Furthermore, longitudinal prediction models leveraging retinal images have shown potential in continuous disease risk assessment and early detection. AI-based retinal biomarkers are non-invasive, accurate, and efficient for disease forecasting and personalized care.

CONCLUSION

AI-based retinal imaging hold promise in transforming primary care and systemic disease management. Together, the retina's unique features and the power of AI enable early detection, risk stratification, and help revolutionizing disease management plans. However, to fully realize the potential of AI in this domain, further research and validation in real-world settings are essential.

Association of fractal dimension and other retinal vascular network parameters with cognitive performance and neuroimaging biomarkers: The Multi-Ethnic Study of Atherosclerosis (MESA)

INTRODUCTION

Retinal vascular network changes may reflect the integrity of the cerebral microcirculation, and may be associated with cognitive impairment.

METHODS

Associations of retinal vascular measures with cognitive function and MRI biomarkers were examined amongst Multi-Ethnic Study of Atherosclerosis (MESA) participants in North Carolina who had gradable retinal photographs at Exams 2 (2002 to 2004, n = 313) and 5 (2010 to 2012, n = 306), and detailed cognitive testing and MRI at Exam 6 (2016 to 2018).

RESULTS

After adjustment for covariates and multiple comparisons, greater arteriolar fractal dimension (FD) at Exam 2 was associated with less isotropic free water of gray matter regions (β = -0.0005, SE = 0.0024, p = 0.01) at Exam 6, while greater arteriolar FD at Exam 5 was associated with greater gray matter cortical volume (in mm3 , β = 5458, SE = 20.17, p = 0.04) at Exam 6.

CONCLUSION

Greater arteriolar FD, reflecting greater complexity of the branching pattern of the retinal arteries, is associated with MRI biomarkers indicative of less neuroinflammation and neurodegeneration.

AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of CVD risk plays an essential role in identifying individuals at higher risk and enables the implementation of targeted intervention strategies, leading to improved CVD prevalence reduction and patient survival rates. The ocular vasculature, particularly the retinal vasculature, has emerged as a potential means for CVD risk stratification due to its anatomical similarities and physiological characteristics shared with other vital organs, such as the brain and heart. The integration of artificial intelligence (AI) into ocular imaging has the potential to overcome limitations associated with traditional semi-automated image analysis, including inefficiency and manual measurement errors. Furthermore, AI techniques may uncover novel and subtle features that contribute to the identification of ocular biomarkers associated with CVD. This review provides a comprehensive overview of advancements made in AI-based ocular image analysis for predicting CVD, including the prediction of CVD risk factors, the replacement of traditional CVD biomarkers (e.g., CT-scan measured coronary artery calcium score), and the prediction of symptomatic CVD events. The review covers a range of ocular imaging modalities, including colour fundus photography, optical coherence tomography, and optical coherence tomography angiography, and other types of images like external eye images. Additionally, the review addresses the current limitations of AI research in this field and discusses the challenges associated with translating AI algorithms into clinical practice.

The association of global vessel width with cognitive decline and cerebral small vessel disease burden in the KaiLuan study

Background

As the retinal microvasculature shares similarities with the cerebral microvasculature, numerous studies have shown that retinal vascular is associated with cognitive decline. In addition, several population-based studies have confirmed the association between retinal vascular and cerebral small vessel disease (CSVD) burden. However, the association of retinal vascular with CSVD burden as well as cognitive function has not been explored simultaneously. This study investigated the relations of retinal microvascular parameters (RMPs) with CSVD burden and cognitive function.

Methods

We conducted a cross-sectional study of participants in the KaiLuan study. Data were collected from subjects aged ≥18 years old who could complete retinal photography and brain magnetic resonance imaging (MRI) between December 2020 to October 2021 in the Kailuan community of Tangshan. RMPs were evaluated using a deep learning system. The cognitive function was measured using the Montreal Cognitive Assessment (MoCA). We conducted logistic regression models, and mediation analysis to evaluate the associations of RMPs with CSVD burden and cognitive decline.

Results

Of the 905 subjects (mean age: 55.42±12.02 years, 54.5% female), 488 (53.9%) were classified with cognitive decline. The fractal dimension (FD) [odds ratio (OR), 0.098, 95% confidence interval (CI): 0.015-0.639, P=0.015] and global vein width (OR: 1.010, 95% CI: 1.005-1.015, P<0.001) were independent risk factors for cognitive decline after adjustment for potential confounding factors. The global artery width was significantly associated with severe CSVD burden (OR: 0.985, 95% CI: 0.974-0.997, P=0.013). The global vein width was sightly associated with severe CSVD burden (OR: 1.005, 95% CI: 1.000-1.010, P=0.050) after adjusting for potential confounders. The multivariable-adjusted odds ratios (95% CI) in highest tertile versus lowest tertile of global vein width were 1.290 (0.901-1.847) for cognitive decline and 1.546 (1.004-2.290) for severe CSVD burden, respectively. Moreover, CSVD burden played a partial mediating role in the association between global vein width and cognitive function (mediating effect 6.59%).

Conclusions

RMPs are associated with cognitive decline and the development of CSVD. A proportion of the association between global vein width and cognitive decline may be attributed to the presence of CSVD burden.

Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives

The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment (SIVA), and Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE), has led to the accumulation of a formidable body of evidence regarding the prognostic value of retinal vessel analysis (RVA) for cardiovascular and cerebrovascular disease (including arterial hypertension in children). There is also the potential to monitor the response of retinal vessels to therapies such as physical activity or bariatric surgery. The dynamic vessel analyzer (DVA) remains a unique way of studying neurovascular coupling, helping to understand the pathogenesis of cerebrovascular and neurodegenerative conditions and also being complementary to techniques that measure macrovascular dysfunction. Beyond cardiovascular disease, retinal vessel analysis has shown associations with and prognostic value for neurological conditions, inflammation, kidney function, and respiratory disease. Artificial intelligence (AI) (represented by algorithms such as QUantitative Analysis of Retinal vessel Topology and siZe (QUARTZ), SIVA-DLS (SIVA-deep learning system), and many others) seems efficient in extracting information from fundus photographs, providing prognoses of various general conditions with unprecedented predictive value. The future challenges will be integrating RVA and other qualitative and quantitative risk factors in a unique, comprehensive prediction tool, certainly powered by AI, while building the much-needed acceptance for such an approach inside the medical community and reducing the "black box" effect, possibly by means of saliency maps.

Comparing Common Retinal Vessel Caliber Measurement Software with an Automatic Deep Learning System

PURPOSE

To compare the Retina-based Microvascular Health Assessment System (RMHAS) with Integrative Vessel Analysis (IVAN) for retinal vessel caliber measurement.

METHODS

Eligible fundus photographs from the Lingtou Eye Cohort Study were obtained alongside their corresponding participant data. Vascular diameter was automatically measured using IVAN and RMHAS software, and intersoftware variations were assessed by intra-class correlation coefficients (ICC), and 95% confidence intervals (CIs). Scatterplots and Bland-Altman plots assessed the agreement between programs, and a Pearson's correlation test assessed the strength of associations between systemic variables and retinal calibers. An algorithm was proposed to convert measurements between software for interchangeability.

RESULTS

ICCs between IVAN and RMHAS were moderate for CRAE and AVR (ICC; 95%CI)(0.62; 0.60 to 0.63 and 0.42; 0.40 to 0.44 respectively) and excellent for CRVE (0.76; 0.75 to 0.77). When comparing retinal vascular calibre measurements between tools, mean differences (MD, 95% confidence intervals) in CRAE, CRVE, and AVR were 22.34 (-7.29 to 51.97 µm),-7.01 (-37.68 to 23.67 µm), and 0.12 (-0.02 to 0.26 µm), respectively. The correlation of systemic parameters with CRAE/CRVE was poor and the correlation of CRAE with age, sex, systolic blood pressure, and CRVE with age, sex, and serum glucose were significantly different between IVAN and RMHAS (p < 0.05).

CONCLUSIONS

CRAE and AVR correlated moderately between retinal measurement software systems while CRVE correlated well. Further studies confirming this agreeability and interchangeability in large-scale datasets are needed before softwares are deemed comparable in clinical practice.

A narrative review of retinal vascular parameters and the applications (Part I): Measuring methods

The retina is often used to evaluate the vascular health status of eyes and the whole body directly and noninvasively in vivo. Retinal vascular parameters included caliber, tortuosity and fractal dimension. These variables represent the density or geometric characteristics of the vascular network apart from reflecting structural changes in the retinal vessel system. Currently, these parameters are often used as indicators of retinal disease, cardiovascular and cerebrovascular disease. Advanced digital fundus photography apparatus and computer-assisted analysis techniques combined with artificial intelligence, make the quantitative calculation of these parameters easier, objective, and labor-saving.

Cohort profile: rationale and methods of UK Biobank repeat imaging study eye measures to study dementia

PURPOSE

The retina provides biomarkers of neuronal and vascular health that offer promising insights into cognitive ageing, mild cognitive impairment and dementia. This article described the rationale and methodology of eye and vision assessments with the aim of supporting the study of dementia in the UK Biobank Repeat Imaging study.

PARTICIPANTS

UK Biobank is a large-scale, multicentre, prospective cohort containing in-depth genetic, lifestyle, environmental and health information from half a million participants aged 40-69 enrolled in 2006-2010 across the UK. A subset (up to 60 000 participants) of the cohort will be invited to the UK Biobank Repeat Imaging Study to collect repeated brain, cardiac and abdominal MRI scans, whole-body dual-energy X-ray absorptiometry, carotid ultrasound, as well as retinal optical coherence tomography (OCT) and colour fundus photographs.

FINDINGS TO DATE

UK Biobank has helped make significant advances in understanding risk factors for many common diseases, including for dementia and cognitive decline. Ophthalmic genetic and epidemiology studies have also benefited from the unparalleled combination of very large numbers of participants, deep phenotyping and longitudinal follow-up of the cohort, with comprehensive health data linkage to disease outcomes. In addition, we have used UK Biobank data to describe the relationship between retinal structures, cognitive function and brain MRI-derived phenotypes.

FUTURE PLANS

The collection of eye-related data (eg, OCT), as part of the UK Biobank Repeat Imaging study, will take place in 2022-2028. The depth and breadth and longitudinal nature of this dataset, coupled with its open-access policy, will create a major new resource for dementia diagnostic discovery and to better understand its association with comorbid diseases. In addition, the broad and diverse data available in this study will support research into ophthalmic diseases and various other health outcomes beyond dementia.

Relationships between quantitative retinal microvascular characteristics and cognitive function based on automated artificial intelligence measurements

Introduction: The purpose of this study is to assess the relationship between retinal vascular characteristics and cognitive function using artificial intelligence techniques to obtain fully automated quantitative measurements of retinal vascular morphological parameters. Methods: A deep learning-based semantic segmentation network ResNet101-UNet was used to construct a vascular segmentation model for fully automated quantitative measurement of retinal vascular parameters on fundus photographs. Retinal photographs centered on the optic disc of 3107 participants (aged 50-93 years) from the Beijing Eye Study 2011, a population-based cross-sectional study, were analyzed. The main parameters included the retinal vascular branching angle, vascular fractal dimension, vascular diameter, vascular tortuosity, and vascular density. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Results: The results showed that the mean MMSE score was 26.34 ± 3.64 (median: 27; range: 2-30). Among the participants, 414 (13.3%) were classified as having cognitive impairment (MMSE score < 24), 296 (9.5%) were classified as mild cognitive impairment (MMSE: 19-23), 98 (3.2%) were classified as moderate cognitive impairment (MMSE: 10-18), and 20 (0.6%) were classified as severe cognitive impairment (MMSE < 10). Compared with the normal cognitive function group, the retinal venular average diameter was significantly larger (p = 0.013), and the retinal vascular fractal dimension and vascular density were significantly smaller (both p < 0.001) in the mild cognitive impairment group. The retinal arteriole-to-venular ratio (p = 0.003) and vascular fractal dimension (p = 0.033) were significantly decreased in the severe cognitive impairment group compared to the mild cognitive impairment group. In the multivariate analysis, better cognition (i.e., higher MMSE score) was significantly associated with higher retinal vascular fractal dimension (b = 0.134, p = 0.043) and higher retinal vascular density (b = 0.152, p = 0.023) after adjustment for age, best corrected visual acuity (BCVA) (logMAR) and education level. Discussion: In conclusion, our findings derived from an artificial intelligence-based fully automated retinal vascular parameter measurement method showed that several retinal vascular morphological parameters were correlated with cognitive impairment. The decrease in retinal vascular fractal dimension and decreased vascular density may serve as candidate biomarkers for early identification of cognitive impairment. The observed reduction in the retinal arteriole-to-venular ratio occurs in the late stages of cognitive impairment.

Fine-mapping of retinal vascular complexity loci identifies Notch regulation as a shared mechanism with myocardial infarction outcomes

There is increasing evidence that the complexity of the retinal vasculature measured as fractal dimension, Df, might offer earlier insights into the progression of coronary artery disease (CAD) before traditional biomarkers can be detected. This association could be partly explained by a common genetic basis; however, the genetic component of Df is poorly understood. We present a genome-wide association study (GWAS) of 38,000 individuals with white British ancestry from the UK Biobank aimed to comprehensively study the genetic component of Df and analyse its relationship with CAD. We replicated 5 Df loci and found 4 additional loci with suggestive significance (P < 1e-05) to contribute to Df variation, which previously were reported in retinal tortuosity and complexity, hypertension, and CAD studies. Significant negative genetic correlation estimates support the inverse relationship between Df and CAD, and between Df and myocardial infarction (MI), one of CAD's fatal outcomes. Fine-mapping of Df loci revealed Notch signalling regulatory variants supporting a shared mechanism with MI outcomes. We developed a predictive model for MI incident cases, recorded over a 10-year period following clinical and ophthalmic evaluation, combining clinical information, Df, and a CAD polygenic risk score. Internal cross-validation demonstrated a considerable improvement in the area under the curve (AUC) of our predictive model (AUC = 0.770 ± 0.001) when comparing with an established risk model, SCORE, (AUC = 0.741 ± 0.002) and extensions thereof leveraging the PRS (AUC = 0.728 ± 0.001). This evidences that Df provides risk information beyond demographic, lifestyle, and genetic risk factors. Our findings shed new light on the genetic basis of Df, unveiling a common control with MI, and highlighting the benefits of its application in individualised MI risk prediction.

Association Between Retinal Features From Multimodal Imaging and Schizophrenia

Importance

The potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts.

Objective

To investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population.

Design, Setting, and Participants

This cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022.

Main Outcomes and Measures

Retinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers.

Results

A total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (-4.05 μm, 95% CI, -5.40 to -2.69; P = 5.4 × 10-9), which persisted when investigating only patients without diabetes (-3.99 μm; 95% CI, -6.67 to -1.30; P = .004) or just those 55 years and younger (-2.90 μm; 95% CI, -5.55 to -0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (-0.14 units; 95% CI, -0.22 to -0.05; P = .001), although this was not present when excluding patients with diabetes.

Conclusions and Relevance

In this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.

Using Artificial Intelligence to Analyse the Retinal Vascular Network: The Future of Cardiovascular Risk Assessment Based on Oculomics? A Narrative Review

The healthcare burden of cardiovascular diseases remains a major issue worldwide. Understanding the underlying mechanisms and improving identification of people with a higher risk profile of systemic vascular disease through noninvasive examinations is crucial. In ophthalmology, retinal vascular network imaging is simple and noninvasive and can provide in vivo information of the microstructure and vascular health. For more than 10 years, different research teams have been working on developing software to enable automatic analysis of the retinal vascular network from different imaging techniques (retinal fundus photographs, OCT angiography, adaptive optics, etc.) and to provide a description of the geometric characteristics of its arterial and venous components. Thus, the structure of retinal vessels could be considered a witness of the systemic vascular status. A new approach called "oculomics" using retinal image datasets and artificial intelligence algorithms recently increased the interest in retinal microvascular biomarkers. Despite the large volume of associated research, the role of retinal biomarkers in the screening, monitoring, or prediction of systemic vascular disease remains uncertain. A PubMed search was conducted until August 2022 and yielded relevant peer-reviewed articles based on a set of inclusion criteria. This literature review is intended to summarize the state of the art in oculomics and cardiovascular disease research.

The impact of the image conversion factor and image centration on retinal vessel geometric characteristics

Background

This study aims to use fundus image material from a long-term retinopathy follow-up study to identify problems created by changing imaging modalities or imaging settings (e.g., image centering, resolution, viewing angle, illumination wavelength). Investigating the relationship of image conversion factor and imaging centering on retinal vessel geometric characteristics (RVGC), offers solutions for longitudinal retinal vessel analysis for data obtained in clinical routine.

Methods

Retinal vessel geometric characteristics were analyzed in scanned fundus photographs with Singapore-I-Vessel-Assessment using a constant image conversion factor (ICF) and an individual ICF, applying them to macula centered (MC) and optic disk centered (ODC) images. The ICF is used to convert pixel measurements into μm for vessel diameter measurements and to establish the size of the measuring zone. Calculating a constant ICF, the width of all analyzed optic disks is included, and it is used for all images of a cohort. An individual ICF, in turn, uses the optic disk diameter of the eye analyzed. To investigate agreement, Bland-Altman mean difference was calculated between ODC images analyzed with individual and constant ICF and between MC and ODC images.

Results

With constant ICF (n = 104 eyes of 52 patients) the mean central retinal equivalent was 160.9 ± 17.08 μm for arteries (CRAE) and 208.7 ± 14.7.4 μm for veins (CRVE). The individual ICFs resulted in a mean CRAE of 163.3 ± 15.6 μm and a mean CRVE of 219.0 ± 22.3 μm. On Bland–Altman analysis, the individual ICF RVGC are more positive, resulting in a positive mean difference for most investigated parameters. Arteriovenous ratio (p = 0.86), simple tortuosity (p = 0.08), and fractal dimension (p = 0.80) agreed well between MC and ODC images, while the vessel diameters were significantly smaller in MC images (p &lt; 0.002).

Conclusion

Scanned images can be analyzed using vessel assessment software. Investigations of individual ICF versus constant ICF point out the asset of utilizing an individual ICF. Image settings (ODC vs. MC) were shown to have good agreement.

Neurovascular correlates of retinal microvascular caliber in adolescent bipolar disorder

BACKGROUND

The connection between vascular and brain metrics is well-studied in older adults, but neglected in youth and in psychiatric populations at increased cardiovascular risk. We therefore examined the association of retinal vascular caliber with cerebral blood flow (CBF) in adolescents with and without bipolar disorder (BD).

METHODS

Ninety-four adolescents (n = 48 BD, n = 46 controls) completed retinal fundus imaging, yielding estimates of arteriolar and venular diameter. Arterial spin labelling MRI was performed to measure CBF. We tested for associations between retinal vascular caliber and CBF in regions of interest; anterior cingulate cortex (ACC), middle frontal gyrus, and hippocampus in BD and controls separately. Complementary voxel-wise analyses were also performed.

RESULTS

In the BD group, higher arteriovenous ratio (AVR) was associated with greater ACC CBF (β = 0.34, p_uncorrected = 0.02), after controlling for age, sex, and BMI, however this finding did not survive correction for multiple comparisons. The control group did not show any associations (β = 0.13, p_uncorrected = 0.40). Voxel-wise analyses within the BD group detected a significant positive association between AVR and regional CBF in two distinct clusters: i) left hippocampus (p < 0.0001); ii) right middle temporal gyrus (p = 0.04).

LIMITATIONS

Limited sample size; young, medically healthy sample limits signal detection; cross-sectional design.

CONCLUSION

This study reveals that higher AVR is associated with higher regional CBF in adolescents with BD. Present findings advance understanding of potential neurofunctional mechanisms linking retinal vascular caliber with psychiatric diagnoses. This proof-of-concept study was designed to generate initial insights to guide future studies focusing on the vascular-brain connection in youth and in psychiatry.

Deep-learning retinal vessel calibre measurements and risk of cognitive decline and dementia

Previous studies have explored the associations of retinal vessel calibre, measured from retinal photographs or fundus images using semi-automated computer programs, with cognitive impairment and dementia, supporting the concept that retinal blood vessels reflect microvascular changes in the brain. Recently, artificial intelligence deep-learning algorithms have been developed for the fully automated assessment of retinal vessel calibres. Therefore, we aimed to determine whether deep-learning-based retinal vessel calibre measurements are predictive of risk of cognitive decline and dementia. We conducted a prospective study recruiting participants from memory clinics at the National University Hospital and St. Luke's Hospital in Singapore; all participants had comprehensive clinical and neuropsychological examinations at baseline and annually for up to 5 years. Fully automated measurements of retinal arteriolar and venular calibres from retinal fundus images were estimated using a deep-learning system. Cox regression models were then used to assess the relationship between baseline retinal vessel calibre and the risk of cognitive decline and developing dementia, adjusting for age, gender, ethnicity, education, cerebrovascular disease status, hypertension, hyperlipidemia, diabetes, and smoking. A total of 491 participants were included in this study, of whom 254 developed cognitive decline over 5 years. In multivariable models, narrower retinal arteriolar calibre (hazard ratio per standard deviation decrease = 1.258, P = 0.008) and wider retinal venular calibre (hazard ratio per standard deviation increase = 1.204, P = 0.037) were associated with increased risk of cognitive decline. Among participants with cognitive impairment but no dementia at baseline (n = 212), 44 progressed to have incident dementia; narrower retinal arteriolar calibre was also associated with incident dementia (hazard ratio per standard deviation decrease = 1.624, P = 0.021). In summary, deep-learning-based measurement of retinal vessel calibre was associated with risk of cognitive decline and dementia.

AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline

Purpose

To externally validate a deep learning pipeline (AutoMorph) for automated analysis of retinal vascular morphology on fundus photographs. AutoMorph has been made publicly available, facilitating widespread research in ophthalmic and systemic diseases.

Methods

AutoMorph consists of four functional modules: image preprocessing, image quality grading, anatomical segmentation (including binary vessel, artery/vein, and optic disc/cup segmentation), and vascular morphology feature measurement. Image quality grading and anatomical segmentation use the most recent deep learning techniques. We employ a model ensemble strategy to achieve robust results and analyze the prediction confidence to rectify false gradable cases in image quality grading. We externally validate the performance of each module on several independent publicly available datasets.

Results

The EfficientNet-b4 architecture used in the image grading module achieves performance comparable to that of the state of the art for EyePACS-Q, with an F1-score of 0.86. The confidence analysis reduces the number of images incorrectly assessed as gradable by 76%. Binary vessel segmentation achieves an F1-score of 0.73 on AV-WIDE and 0.78 on DR HAGIS. Artery/vein scores are 0.66 on IOSTAR-AV, and disc segmentation achieves 0.94 in IDRID. Vascular morphology features measured from the AutoMorph segmentation map and expert annotation show good to excellent agreement.

Conclusions

AutoMorph modules perform well even when external validation data show domain differences from training data (e.g., with different imaging devices). This fully automated pipeline can thus allow detailed, efficient, and comprehensive analysis of retinal vascular morphology on color fundus photographs.

Translational Relevance

By making AutoMorph publicly available and open source, we hope to facilitate ophthalmic and systemic disease research, particularly in the emerging field of oculomics.

Concordance between SIVA, IVAN, and VAMPIRE Software Tools for Semi-Automated Analysis of Retinal Vessel Caliber

We aimed to compare measurements from three of the most widely used software packages in the literature and to generate conversion algorithms for measurement of the central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) between SIVA and IVAN and between SIVA and VAMPIRE. We analyzed 223 retinal photographs from 133 human participants using both SIVA, VAMPIRE and IVAN independently for computing CRAE and CRVE. Agreement between measurements was assessed using Bland–Altman plots and intra-class correlation coefficients. A conversion algorithm between measurements was carried out using linear regression, and validated using bootstrapping and root-mean-square error. The agreement between VAMPIRE and IVAN was poor to moderate: The mean difference was 20.2 µm (95% limits of agreement, LOA, −12.2–52.6 µm) for CRAE and 21.0 µm (95% LOA, −17.5–59.5 µm) for CRVE. The agreement between VAMPIRE and SIVA was also poor to moderate: the mean difference was 36.6 µm (95% LOA, −12.8–60.4 µm) for CRAE, and 40.3 µm (95% LOA, 5.6–75.0 µm) for CRVE. The agreement between IVAN and SIVA was good to excellent: the mean difference was 16.4 µm (95% LOA, −4.25–37.0 µm) for CRAE, and 19.3 µm (95% LOA, 0.09–38.6 µm) for CRVE. We propose an algorithm converting IVAN and VAMPIRE measurements into SIVA-estimated measurements, which could be used to homogenize sets of vessel measurements obtained with different software packages.

Fenofibrate, which reduces risk of sight-threatening diabetic retinopathy in type 2 diabetes, is associated with early narrowing of retinal venules: a FIELD trial substudy

Retinal vessel calibre metrics were evaluated at baseline and 2 years in a FIELD substudy (n = 208). Central retinal venule calibre was significantly reduced by fenofibrate and unchanged by placebo. Arteriole metrics did not change. Larger studies relating retinal vessel calibre to future diabetes complications and response to therapy are merited.

Hypertensive eye disease

Hypertensive eye disease includes a spectrum of pathological changes, the most well known being hypertensive retinopathy. Other commonly involved parts of the eye in hypertension include the choroid and optic nerve, sometimes referred to as hypertensive choroidopathy and hypertensive optic neuropathy. Together, hypertensive eye disease develops in response to acute and/or chronic elevation of blood pressure. Major advances in research over the past three decades have greatly enhanced our understanding of the epidemiology, systemic associations and clinical implications of hypertensive eye disease, particularly hypertensive retinopathy. Traditionally diagnosed via a clinical funduscopic examination, but increasingly documented on digital retinal fundus photographs, hypertensive retinopathy has long been considered a marker of systemic target organ damage (for example, kidney disease) elsewhere in the body. Epidemiological studies indicate that hypertensive retinopathy signs are commonly seen in the general adult population, are associated with subclinical measures of vascular disease and predict risk of incident clinical cardiovascular events. New technologies, including development of non-invasive optical coherence tomography angiography, artificial intelligence and mobile ocular imaging instruments, have allowed further assessment and understanding of the ocular manifestations of hypertension and increase the potential that ocular imaging could be used for hypertension management and cardiovascular risk stratification.

Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study

OBJECTIVE

Improved identification of individuals with type 2 diabetes at high cardiovascular (CV) risk could help in selection of newer CV risk-reducing therapies. The aim of this study was to determine whether retinal vascular parameters, derived from retinal screening photographs, alone and in combination with a genome-wide polygenic risk score for coronary heart disease (CHD PRS) would have independent prognostic value over traditional CV risk assessment in patients without prior CV disease.

RESEARCH DESIGN AND METHODS

Patients in the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) study were linked to retinal photographs, prescriptions, and outcomes. Retinal photographs were analyzed using VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina) software, a semiautomated artificial intelligence platform, to compute arterial and venous fractal dimension, tortuosity, and diameter. CHD PRS was derived from previously published data. Multivariable Cox regression was used to evaluate the association between retinal vascular parameters and major adverse CV events (MACE) at 10 years compared with the pooled cohort equations (PCE) risk score.

RESULTS

Among 5,152 individuals included in the study, a MACE occurred in 1,017 individuals. Reduced arterial fractal dimension and diameter and increased venous tortuosity each independently predicted MACE. A risk score combining these parameters significantly predicted MACE after adjustment for age, sex, PCE, and the CHD PRS (hazard ratio 1.11 per SD increase, 95% CI 1.04-1.18, P = 0.002) with similar accuracy to PCE (area under the curve [AUC] 0.663 vs. 0.658, P = 0.33). A model incorporating retinal parameters and PRS improved MACE prediction compared with PCE (AUC 0.686 vs. 0.658, P < 0.001).

CONCLUSIONS

Retinal parameters alone and in combination with genome-wide CHD PRS have independent and incremental prognostic value compared with traditional CV risk assessment in type 2 diabetes.

Changes in retinal vascular diameters in senior and geriatric cats in association with variation in systemic blood pressure

OBJECTIVES

Early diagnosis of arterial hypertension is essential to prevent target organ damage. In humans, retinal arteriolar narrowing predicts hypertension. This blinded prospective observational study investigated the retinal vessel diameters in senior and geriatric cats of varying systolic blood pressure (SBP) status and evaluated retinal vascular changes in hypertensive cats after treatment.

METHODS

Cats with a median age of 14 years (range 9.1-22 years) were categorised into five groups: group 1, healthy normotensive (SBP <140 mmHg; n = 40) cats; group 2, pre-hypertensive (SBP 140-160 mmHg; n = 14) cats; group 3, cats with chronic kidney disease (CKD) and normotensive (n = 26); group 4, cats with CKD and pre-hypertensive (n = 13); and group 5, hypertensive cats (SBP >160 mmHg, n = 15). Colour fundus images (Optibrand ClearView) were assessed for hypertensive lesions. Retinal vascular diameters and bifurcation angles were annotated and calculated using the Vascular Assessment and Measurement Platform for Images of the Retina annotation tool (VAMPIRE-AT). When available, measurements were obtained at 3 and 6 months after amlodipine besylate treatment.

RESULTS

Ten hypertensive cats had retinal lesions, most commonly intraretinal haemorrhages and retinal exudates. Arteriole and venule diameters decreased significantly with increasing age (-0.17 ± 0.05 pixels/year [P = 0.0004]; -0.19 ± 0.05 pixels/year). Adjusted means ± SEM for arteriole and venule diameter (pixels) were 6.3 ± 0.2 and 8.9 ± 0.2 (group 1); 7.6 ± 0.3 and 10.1 ± 0.4 (group 2); 6.9 ± 0.2 and 9.5 ± 0.3 (group 3); 7.4 ± 0.3 and 10.0 ± 0.4 (group 4); and 7.0 ± 0.3 and 9.8 ± 0.4 (group 5). Group 1 arteriole and venule diameters were significantly lower than those of groups 2 and 4. Group 2 arteriole bifurcation angle was significantly narrower than those of groups 1 and 3. Post-treatment, vessel diameters decreased significantly at 3 and 6 months in seven hypertensive cats.

CONCLUSIONS AND RELEVANCE

Increased age was associated with reduced vascular diameters. Longitudinal studies are required to assess if vessel diameters are a risk indicator for hypertension in cats.

The association between markers of inflammation and retinal microvascular parameters: A systematic review and meta-analysis

BACKGROUND AND AIMS

Adverse changes to the microcirculation play an important role in the pathogenesis of cardiovascular disease (CVD), and inflammation is a key causal mechanism. We investigated the relationship between inflammatory markers and retinal microvascular parameters.

METHODS

Studies up to April 2021 were identified in Medline, Embase and PubMed with the following terms: retinal microvascular parameters, inflammatory markers, and observational studies. Correlation coefficients of inflammatory markers and retinal vascular caliber were pooled using the random-effects model.

RESULTS

Of 4783 studies identified, 36 met the inclusion criteria (general population 26, patients with diseases 10). C-reactive protein (CRP) and white blood cell count (WBC) were most frequently reported. We conducted meta-analysis with 12 CRP studies (22422 participants) and six WBC studies (15209 participants), and also performed a narrative review of all studies. There was consistent evidence of a modest association between CRP and venular caliber (r = 0.09, 95%CI 0.05 to 0.12), but little evidence of an association between CRP with retinal arteriolar caliber (r = 0.00, 95%CI -0.02 to 0.02). Similarly, WBC had stronger associations with venular (r = 0.18, 95%CI 0.05 to 0.31) than arteriolar caliber (r = 0.05, 95%CI 0.01 to 0.09). Narrative review of other inflammatory markers showed consistent findings. There was little evidence of associations between inflammation markers and other microvascular parameters, fractal dimension and tortuosity.

CONCLUSIONS

There was more evidence for an association of inflammation with retinal venular than with arterial caliber. The findings suggest a potential druggable mechanism contributing to microvascular damage that has been relatively overlooked in CVD pathogenesis and treatment.

Retinal arteriolar tortuosity and fractal dimension are associated with long-term cardiovascular outcomes in people with type 2 diabetes

AIMS/HYPOTHESIS

Our aim was to determine whether quantitative retinal traits in people with type 2 diabetes are independently associated with incident major cardiovascular events including CHD and stroke.

METHODS

A total of 1066 men and women with type 2 diabetes, aged 65-74 years, were followed up over 8 years in the population-based Edinburgh Type 2 Diabetes Study. Using retinal photographs taken at baseline and specialist software, a number of quantitative retinal traits were measured, including arteriolar and venular widths and tortuosity as well as fractal dimension (a measure of the branching pattern complexity of the retinal vasculature network). Incident CHD events occurring during follow-up included fatal and non-fatal myocardial infarction, first episodes of angina and coronary interventions for CHD. Incident cerebrovascular events included fatal and non-fatal stroke or transient ischaemic attack. Cox proportional hazard regression analyses were performed to identify the association of the retinal traits with cardiovascular events in the population with retinal data available (n = 1028).

RESULTS

A total of 200 participants had an incident cardiovascular event (139 CHD and 61 cerebrovascular events). Following adjustment for age and sex, arteriolar tortuosity and fractal dimension were associated with cerebrovascular events (HR 1.27 [95% CI 1.02, 1.58] and HR 0.74 [95% CI 0.57, 0.95], respectively), including with stroke alone (HR 1.30 [95% CI 1.01, 1.66] and HR 0.73 [95% CI 0.56, 0.97], respectively). These associations persisted after further adjustment for established cardiovascular risk factors (HR 1.26 [95% CI 1.01, 1.58] and HR 0.73 [95% CI 0.56, 0.94], respectively). Associations generally reduced in strength after a final adjustment for the presence of diabetic retinopathy, but the association of fractal dimension with incident cerebrovascular events and stroke retained statistical significance (HR 0.73 [95% CI 0.57, 0.95] and HR 0.72 [95% CI 0.54, 0.97], respectively). Associations of retinal traits with CHD were generally weak and showed no evidence of statistical significance.

CONCLUSIONS/INTERPRETATION

Arteriolar tortuosity and fractal dimension were associated with incident cerebrovascular events, independent of a wide range of traditional cardiovascular risk factors including diabetic retinopathy. These findings suggest potential for measurements of early retinal vasculature change to aid in the identification of people with type 2 diabetes who are at increased risk from stroke.

Comparison of Static Retinal Vessel Caliber Measurements by Different Commercially Available Platforms

SIGNIFICANCE

Commercially available platforms show good agreement in clinical outcomes for retinal vessel caliber measurements, despite differing absolute values. Tighter agreement is observed when right and left eye data are averaged, suggesting an approach suitable for clinical practice.

PURPOSE

The purpose of this study was to compare the retinal vessel caliber measurements generated by different commercially available platforms and their associations with systemic blood pressure and age.

METHODS

A total of 209 participants were recruited from a UK optometric practice. After a routine eye examination, participants had disc-centered retinal photographs and systemic blood pressure taken. Retinal vessel calibers (central retinal artery equivalent, central retinal vein equivalent, and arteriovenous ratio) were calculated using both MONA REVA and VesselMap.

RESULTS

An inverse Pearson correlation was observed between central retinal artery equivalent and mean arterial blood pressure on both platforms (r = -0.275 [P ≤ .001] and r = -0.388 [P ≤ .001] for MONA REVA and VesselMap, respectively); this correlation was also observed with arteriovenous ratio and blood pressure. An inverse correlation was observed between central retinal artery equivalent and age (r = -0.362 [P ≤ .001] and r = -0.404 [P ≤ .001] for MONA REVA and VesselMap, respectively); this was also seen between central retinal vein equivalent and age (r = -0.322 [P ≤ .001] and r = -0.369 [P ≤ .001]). Arteriovenous ratio remained independent from age for both platforms. Bland-Altman plots demonstrated good agreement between the platforms for all three variables.

CONCLUSIONS

Although absolute caliber measurements differed between the platforms, the correlations observed were of similar magnitudes, with good agreement between the two platforms. Tighter spaced limits of agreement were observed when right and left eye data were averaged for each subject. In the absence of localized ocular pathology, this approach should be used.

Imaging the eye and its relevance to diabetes care

Diabetes is a major cause of vision loss globally, yet this devastating complication is largely preventable. Early detection and treatment of diabetic retinopathy necessitates screening. Ocular imaging is widely used clinically, both for the screening and management of diabetic retinopathy. Common eye conditions, such as glaucoma, cataracts and retinal vessel thrombosis, and signs of systemic conditions, such as hypertension, are frequently revealed. As well as imaging by a skilled clinician during an eye examination, non-ophthalmic clinicians, such as general practitioners, endocrinologists, nurses and trained health workers, can also can carry out diabetic eye screening. This process usually comprises local imaging with remote grading, mostly human grading. However, grading incorporating artificial intelligence is emerging. In a clinical research context, retinal vasculature analyses using semi-automated software in many populations have identified associations between retinal vessel geometry, such as vessel caliber, and the risk of diabetic retinopathy and other chronic complications of type 1 and type 2 diabetes. Similarly, evaluation of corneal nerves by corneal confocal microscopy is revealing diabetes-related abnormalities, and associations with and predictive power for other chronic diabetes complications. As yet, the value of retinal vessel geometry and corneal confocal microscopy measures at an individual level is uncertain. In this article, targeting non-ocular clinicians and researchers, we review existent and emerging ocular imaging and grading tools, including artificial intelligence, and their associations between ocular imaging findings and diabetes and its chronic complications.

Retinal venular tortuosity and fractal dimension predict incident retinopathy in adults with type 2 diabetes: the Edinburgh Type 2 Diabetes Study

AIMS/HYPOTHESIS

Our aim was to determine whether a range of prespecified retinal vessel traits were associated with incident diabetic retinopathy in adults with type 2 diabetes.

METHODS

In the prospective observational cohort Edinburgh Type 2 Diabetes Study of 1066 adults with type 2 diabetes, aged 60-75 years at recruitment, 718 were free from diabetic retinopathy at baseline. Baseline retinal traits including vessel widths, tortuosity (curvature) and fractal dimensions (network complexity), were quantified using fundus camera images and semiautomated software, and analysed using logistic regression for their association with incident diabetic retinopathy over 10 years.

RESULTS

The incidence of diabetic retinopathy was 11.4% (n = 82) over 10 years. After adjustment for a range of vascular and diabetes-related risk factors, both increased venular tortuosity (OR 1.51; 95% CI 1.15, 1.98; p = 0.003) and decreased fractal dimension (OR 0.75; 95% CI 0.58, 0.96; p = 0.025) were associated with incident retinopathy. There was no evidence of an association with arterial tortuosity, and associations between measurements of vessel widths and retinopathy lost statistical significance after adjustment for diabetes-related factors and vascular disease. Adding venular tortuosity to a model including established risk factors for diabetic retinopathy (HbA_1c, BP and kidney function) improved the discriminative ability (C statistic increased from 0.624 to 0.640, p = 0.013), but no such benefit was found with fractal dimension.

CONCLUSIONS/INTERPRETATION

Increased retinal venular tortuosity and decreased fractal dimension are associated with incident diabetic retinopathy, independent of classical risk factors. There is some evidence that venular tortuosity may be a useful biomarker to improve the predictive ability of models based on established retinopathy risk factors, and its inclusion in further risk prediction modelling is warranted.

Vascular Patterning as Integrative Readout of Complex Molecular and Physiological Signaling by VESsel GENeration Analysis

The molecular signaling cascades that regulate angiogenesis and microvascular remodeling are fundamental to normal development, healthy physiology, and pathologies such as inflammation and cancer. Yet quantifying such complex, fractally branching vascular patterns remains difficult. We review application of NASA's globally available, freely downloadable VESsel GENeration (VESGEN) Analysis software to numerous examples of 2D vascular trees, networks, and tree-network composites. Upon input of a binary vascular image, automated output includes informative vascular maps and quantification of parameters such as tortuosity, fractal dimension, vessel diameter, area, length, number, and branch point. Previous research has demonstrated that cytokines and therapeutics such as vascular endothelial growth factor, basic fibroblast growth factor (fibroblast growth factor-2), transforming growth factor-beta-1, and steroid triamcinolone acetonide specify unique "fingerprint" or "biomarker" vascular patterns that integrate dominant signaling with physiological response. In vivo experimental examples described here include vascular response to keratinocyte growth factor, a novel vessel tortuosity factor; angiogenic inhibition in humanized tumor xenografts by the anti-angiogenesis drug leronlimab; intestinal vascular inflammation with probiotic protection by Saccharomyces boulardii, and a workflow programming of vascular architecture for 3D bioprinting of regenerative tissues from 2D images. Microvascular remodeling in the human retina is described for astronaut risks in microgravity, vessel tortuosity in diabetic retinopathy, and venous occlusive disease.

On the quantitative effects of compression of retinal fundus images on morphometric vascular measurements in VAMPIRE

BACKGROUND AND OBJECTIVES

This paper reports a quantitative analysis of the effects of joint photographic experts group (JPEG) image compression of retinal fundus camera images on automatic vessel segmentation and on morphometric vascular measurements derived from it, including vessel width, tortuosity and fractal dimension.

METHODS

Measurements are computed with vascular assessment and measurement platform for images of the retina (VAMPIRE), a specialized software application adopted in many international studies on retinal biomarkers. For reproducibility, we use three public archives of fundus images (digital retinal images for vessel extraction (DRIVE), automated retinal image analyzer (ARIA), high-resolution fundus (HRF)). We generate compressed versions of original images in a range of representative levels.

RESULTS

We compare the resulting vessel segmentations with ground truth maps and morphological measurements of the vascular network with those obtained from the original (uncompressed) images. We assess the segmentation quality with sensitivity, specificity, accuracy, area under the curve and Dice coefficient. We assess the agreement between VAMPIRE measurements from compressed and uncompressed images with correlation, intra-class correlation and Bland-Altman analysis.

CONCLUSIONS

Results suggest that VAMPIRE width-related measurements (central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), arteriolar-venular width ratio (AVR)), the fractal dimension (FD) and arteriolar tortuosity have excellent agreement with those from the original images, remaining substantially stable even for strong loss of quality (20% of the original), suggesting the suitability of VAMPIRE in association studies with compressed images.

Retinal arteriolar calibre and venular fractal dimension predict progression of proliferative diabetic retinopathy 6 months after panretinal photocoagulation: a prospective, clinical interventional study

Objective

We examined the hypothesis that baseline retinal vascular geometry in patients with proliferative diabetic retinopathy (PDR) predicts disease activity 6 months after panretinal photocoagulation (PRP).

Methods and analysis

We included 47 eyes from 40 patients with treatment-naïve PDR in a 6-month prospective study. Diagnosis of PDR and disease activity was evaluated by wide-field fluorescein angiography (Optomap, Optos, Dunfermline, Scotland, UK). At baseline and 6-month follow-up, the retinal vessel geometry was measured on optic disc centred images using semiautomated software Vessel Assessment and Measurement Platform for Images of the Retina (VAMPIRE, Dundee, Scotland).

Results

At baseline, mean age and duration of diabetes was 51.6 and 21.4 years, and 62.5% were men. Seventeen eyes (36.2%) had progression of PDR during follow-up. At baseline, we found higher retinal arteriolar calibre (31.3±0.8 vs 28.8±0.8 pixels, p=0.02) and venous fractal dimension (F_D) (1.257±0.011 vs 1.222±0.011, p=0.02) in eyes with progression of PDR as compared with eyes with non-progression. In a multiple logistic regression model, both higher retinal arteriolar calibre (OR 1.34, 95% CI, 1.09 to 1.64, p<0.01) and venular F_D (OR 1.15, 95% CI, 1.04 to 1.27, p<0.01) predicted progression of PDR. Venular calibre was seen to increase from baseline to month six regardless of disease progression (non-progression 45.0±0.7 vs 52.7±1.8 pixels, p<0.01; progression 46.2±0.8 vs 51.0±1.7 pixels, p<0.01).

Conclusion

Our prospective study showed that arteriolar calibre and venular F_D at baseline were predictive of disease activity 6 months after PRP treatment in patients with treatment-naïve PDR.

Retinal Vasculature Fractal and Stroke Mortality

BACKGROUND AND PURPOSE

Fractal analysis is a method of quantifying the branching complexity and density of the retinal vessels. We hypothesized that reduced fractal dimension, signifying a sparser vascular network, is associated with long-term stroke mortality.

METHODS

We examined the relationship of fractal dimension and stroke mortality in a prospective, population-based cohort of 3143 participants aged 49 years or older. Fractal dimension was measured from digitized fundus photographs using a computer-automated method. Stroke mortality was documented from Australian National Death Index records. We defined reduced fractal dimension as values in the lowest quartile.

RESULTS

Over 12 years, there were 132 (4.2%) stroke-related deaths. Stroke-related mortality was higher in participants with reduced fractal dimension (lowest quartile) compared with the highest quartile (7.7% versus 1.3%, P<0.01). After controlling for age, gender, smoking, blood pressure, history of stroke, and other factors, participants with reduced fractal dimension had higher stroke mortality (hazard ratio, 2.42 [95% CI, 1.15-5.07], lowest versus highest quartile). When modeled as a continuous variable, reduced fractal dimension was associated with increased stroke mortality (multivariable-adjusted hazard ratio, 1.26 [95% CI, 1.06-1.51], per SD decrease).

CONCLUSIONS

Reduced retinal vascular fractal dimension is independently associated with 12-year stroke mortality. Reduced fractal dimension may indicate cerebral tissue hypoxia and increased risk of stroke.

Retinal vessel changes in cerebrovascular disease

PURPOSE OF REVIEW

The retina is growingly recognized as a window into cerebrovascular and systemic vascular conditions. The utility of noninvasive retinal vessel biomarkers in cerebrovascular risk assessment has expanded due to advances in retinal imaging techniques and machine learning-based digital analysis. The purpose of this review is to underscore the latest evidence linking retinal vascular abnormalities with stroke and vascular-related cognitive disorders; to highlight modern developments in retinal vascular imaging modalities and software-based vasculopathy quantification.

RECENT FINDINGS

Longitudinal studies undertaken for extended periods indicate that retinal vascular changes can predict cerebrovascular disorders (CVD). Cerebrovascular ties to dementia provoked recent explorations of retinal vessel imaging tools for conceivable early cognitive decline detection. Innovative biomedical engineering technologies and advanced dynamic and functional retinal vascular imaging methods have recently been added to the armamentarium, allowing an unbiased and comprehensive analysis of the retinal vasculature. Improved artificial intelligence-based deep learning algorithms have boosted the application of retinal imaging as a clinical and research tool to screen, risk stratify, and monitor with precision CVD and vascular cognitive impairment.

SUMMARY

Mounting evidence supports the use of quantitative retinal vessel analysis in predicting CVD, from clinical stroke to neuroimaging markers of stroke and neurodegeneration.

Retinal vascular tortuosity: Mechanisms and measurements

Retinal vessel tortuosity has been used in the diagnosis and management of different clinical situations. Notwithstanding, basic concepts, standards and tools of measurement, reliable normative data and clinical applications have many gaps or points of divergence. In this review we discuss triggering causes of retinal vessel tortuosity and resources used to assess and quantify it, as well as current limitations.

Retinal biomarkers for Alzheimer's disease and vascular cognitive impairment and dementia (VCID): implication for early diagnosis and prognosis

Cognitive impairment and dementia are major medical, social, and economic public health issues worldwide with significant implications for life quality in older adults. The leading causes are Alzheimer's disease (AD) and vascular cognitive impairment/dementia (VCID). In both conditions, pathological alterations of the cerebral microcirculation play a critical pathogenic role. Currently, the main pathological biomarkers of AD-β-amyloid peptide and hyperphosphorylated tau proteins-are detected either through cerebrospinal fluid (CSF) or PET examination. Nevertheless, given that they are invasive and expensive procedures, their availability is limited. Being part of the central nervous system, the retina offers a unique and easy method to study both neurodegenerative disorders and cerebral small vessel diseases in vivo. Over the past few decades, a number of novel approaches in retinal imaging have been developed that may allow physicians and researchers to gain insights into the genesis and progression of cerebromicrovascular pathologies. Optical coherence tomography (OCT), OCT angiography, fundus photography, and dynamic vessel analyzer (DVA) are new imaging methods providing quantitative assessment of retinal structural and vascular indicators-such as thickness of the inner retinal layers, retinal vessel density, foveal avascular zone area, tortuosity and fractal dimension of retinal vessels, and microvascular dysfunction-for cognitive impairment and dementia. Should further studies need to be conducted, these retinal alterations may prove to be useful biomarkers for screening and monitoring dementia progression in clinical routine. In this review, we seek to highlight recent findings and current knowledge regarding the application of retinal biomarkers in dementia assessment.

Retinal Vasculometry Associations With Glaucoma: Findings From the European Prospective Investigation of Cancer-Norfolk Eye Study

Purpose

To examine retinal vasculometry associations with different glaucomas in older British people.

Design

Cross-sectional study.

Methods

A total of 8,623 European Prospective Investigation into Cancer-Norfolk Eye study participants were examined, who underwent retinal imaging, ocular biometry assessment, and clinical ascertainment of ocular hypertensive or glaucoma status (including glaucoma suspect [GS], high-tension open-angle glaucoma [HTG], and normal-tension glaucoma [NTG]). Automated measures of arteriolar and venular tortuosity, area, and width from retinal images were obtained. MainOutcomeMeasures: Associations between glaucoma and retinal vasculometry outcomes were analyzed using multilevel linear regression, adjusted for age, sex, height, axial length, intraocular and systemic blood pressure, and within-person clustering, to provide absolute differences in width and area, and percentage differences in vessel tortuosity. Presence or absence of within-person-between-eye differences in retinal vasculometry by diagnoses were examined.

Results

A total of 565,593 vessel segments from 5,947 participants (mean age 67.6 years, SD 7.6 years, 57% women) were included; numbers with HTG, NTG, and GS in at least 1 eye were 87, 82, and 439, respectively. Thinner arterioles (−3.2 μm; 95% confidence interval [CI] −4.4 μm, −1.9 μm) and venules (−2.7 μm; 95% CI −4.9 μm, −0.5 μm) were associated with HTG. Reduced venular area was associated with HTG (−0.2 mm²; 95% CI −0.3 mm², −0.1 mm²) and NTG (−0.2 mm²; 95% CI −0.3 mm², −0.0 mm²). Less tortuous retinal arterioles and venules were associated with all glaucomas, but only significantly for GS (−3.9%; 95% CI −7.7%, −0.1% and −4.8%; 95% CI −7.4%, −2.1%, respectively). There was no evidence of within-person-between-eye differences in retinal vasculometry associations by diagnoses.

Conclusions

Retinal vessel width associations with glaucoma and novel associations with vessel area and tortuosity, together with no evidence of within-person-between-eye differences in retinal vasculometry, suggest a vascular cause of glaucoma.

•

Retinal vessel measurements, including (as a first report) vessel tortuosity and area, were associated with high-tension glaucoma and other glaucoma-related outcomes.

•

Novel analyses showing that within-person-between-eye glaucoma diagnoses, intraocular pressure, and retinal vasculometry were uncorrelated provides further evidence that systemic microvascular changes may cause glaucoma.

A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre

Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using diverse multiethnic multicountry datasets that comprise more than 70,000 images. Retinal-vessel calibre measured by the models and by expert human graders showed high agreement, with overall intraclass correlation coefficients of between 0.82 and 0.95. The models performed comparably to or better than expert graders in associations between measurements of retinal-vessel calibre and CVD risk factors, including blood pressure, body-mass index, total cholesterol and glycated-haemoglobin levels. In retrospectively measured prospective datasets from a population-based study, baseline measurements performed by the deep-learning system were associated with incident CVD. Our findings motivate the development of clinically applicable explainable end-to-end deep-learning systems for the prediction of CVD on the basis of the features of retinal vessels in retinal photographs.

Alterations in retinal arteriolar microvascular structure associate with higher treatment burden in patients with diabetic macular oedema: results from a 12-month prospective clinical trial

PURPOSE

This study was based on data from a 12-month prospective clinical trial and aimed to examine changes in retinal microvascular structure in eyes treated with intravitreal aflibercept in combination with focal/grid laser photocoagulation for diabetic macular oedema (DME).

METHODS

We included 32 treatment naïve eyes of 22 patients with centre involving DME. The treatment algorithm comprised a loading phase of three monthly injections of aflibercept and focal/grid laser photocoagulation [baseline (BL)-month 3 (M3)] followed by a pro re nata (PRN) aflibercept phase until month 12 (M12). Eyes were divided into groups with and without need for PRN treatment after loading. Parameters of retinal microvascular structure were measured in 45° optic disc centred fundus images at BL, M3 and M12 using a semi-automated software (VAMPIRE®, Vessel Assessment and Measurement Platform for Images of the Retina, Universities of Dundee and Edinburgh, UK).

RESULTS

A significant decrease in retinal arteriolar calibre was demonstrated at both M3 (-11.2 μm, p = 0.005) and M12 (-11.5 μm, p = 0.04) as compared to BL in eyes that needed PRN treatment during follow-up. In contrast, arteriolar calibre remained unchanged in eyes without need for PRN treatment (M3: -1.6 μm, p = 0.79 and M12: -7.0 μm, p = 0.22). For retinal venules, vessel calibre decreased both in eyes with and without need for PRN therapy at M3 (-9.5 μm, p = 0.01 and -11.6 μm, p = 0.01) as well as at M12 (-15.6 μm, p = 0.001 and -11.0 μm, p = 0.04).

CONCLUSION

Early changes in retinal arteriolar calibre are associated with an increased treatment burden during the first year of DME treatment.

Systematic Review on Fractal Dimension of the Retinal Vasculature in Neurodegeneration and Stroke: Assessment of a Potential Biomarker

Introduction: Ocular manifestations in several neurological pathologies accentuate the strong relationship between the eye and the brain. Retinal alterations in particular can serve as surrogates for cerebral changes. Offering a “window to the brain,” the transparent eye enables non-invasive imaging of these changes in retinal structure and vasculature. Fractal dimension (FD) reflects the overall complexity of the retinal vasculature. Changes in FD could reflect subtle changes in the cerebral vasculature that correspond to preclinical stages of neurodegenerative diseases. In this review, the potential of this retinal vessel metric to serve as a biomarker in neurodegeneration and stroke will be explored.

Methods: A literature search was conducted, following the PRISMA Statement 2009 criteria, in four large bibliographic databases (Pubmed, Embase, Web Of Science and Cochrane Library) up to 12 October 2019. Articles have been included based upon their relevance. Wherever possible, level of evidence (LOE) has been assessed by means of the Oxford Centre for Evidence-based Medicine Level of Evidence classification.

Results: Twenty-one studies were included for qualitative synthesis. We performed a narrative synthesis and produced summary tables of findings of included papers because methodological heterogeneity precluded a meta-analysis. A significant association was found between decreased FD and neurodegenerative disease, mainly addressing cognitive impairment (CI) and dementia. In acute, subacute as well as chronic settings, decreased FD seems to be associated with stroke. Differences in FD between subtypes of ischemic stroke remain unclear.

Conclusions: This review provides a summary of the scientific literature regarding the association between retinal FD and neurodegenerative disease and stroke. Central pathology is associated with a decreased FD, as a measure of microvascular network complexity. As retinal FD reflects the global integrity of the cerebral microvasculature, it is an attractive parameter to explore. Despite obvious concerns, mainly due to a lack of methodological standardization, retinal FD remains a promising non-invasive and low-cost diagnostic biomarker for neurodegenerative and cerebrovascular disease. Before FD can be implemented in clinic as a diagnostic biomarker, the research community should strive for uniformization and standardization.

Relation between retinal vessel diameter and posterior segment optical coherence tomography variables in middle-aged Caucasians: the Northern Finland Birth Cohort Eye Study

AIMS

Studying the relationship between retinal vessel diameter (RVD) with (1) macular thickness and volume, (2) retinal nerve fibre layer (RNFL), (3) ganglion cell-inner plexiform layer (GC-IPL) and (4) optic nerve head (ONH) in a population cohort of middle-aged Caucasians.

METHODS

We collected data from 3070 individuals. We used a semiautomated computer-assisted programme to measure central retinal arteriolar equivalent and central retinal venular equivalent. Macular and ONH parameters were assessed by optical coherence tomography.

RESULTS

Data from 2155 persons were analysed. A larger RVD was associated with a thicker macula and increased macular volume; each SD increase in average macular thickness and volume was associated with a 3.28 µm and a 3.19 µm increase in arteriolar diameter and a 5.10 µm and a 5.08 µm increase in venular diameter, respectively (p<0.001 for all). A larger rim area, greater GC-IPL and RNFL thicknesses were associated with larger RVD; each SD increase in rim area, GC-IPL thickness and RNFL thickness was associated with a 1.21 µm, 2.68 µm and a 3.29 µm increase in arteriolar diameter and a 2.13 µm, 4.02 µm and 5.04 µm increase in venular diameter, respectively (p<0.001 for all).

CONCLUSIONS

Increased macular thickness, macular volume, GC-IPL thickness, RNFL thickness and optic nerve rim area were associated with larger RVDs in all subjects. This study clarified the anatomical correlations between both macular and ONH parameters with RVD for middle-aged Caucasians; these can represent a basis for further studies investigating the vascular aetiology of eye diseases.

Structural analysis of retinal blood vessels in patients with COPD during a pulmonary rehabilitation program

Cardiovascular diseases are frequently present in chronic obstructive pulmonary disease (COPD). Population-based studies found associations between retinal vessel diameters and cardiovascular health, but it is unknown whether this also applies to COPD patients. Therefore, we measured retinal vessel diameters in COPD patients and aimed to determine the association with cardiovascular risk factors, lung function, and functional outcomes. In addition, we investigated whether an exercise-based pulmonary rehabilitation (PR) program would change retinal vessel diameters, as a proxy for improved microvascular health. Demographics and clinical characteristics, including pulmonary function, exercise capacity, blood pressure, blood measurements and level of systemic inflammation were obtained from 246 patients during routine assessment before and after PR. Retinal vessel diameters were measured from digital retinal images. Older age and higher systolic blood pressure were associated with narrower retinal arterioles (β: -0.224; p = 0.042 and β: -0.136; p < 0.001, respectively). Older age, higher systolic blood pressure and lower level of systemic inflammation were associated with narrower retinal venules (β: -0.654; -0.229; and -13.767, respectively; p < 0.05). No associations were found between retinal vessel diameters and lung function parameters or functional outcomes. After PR, no significant changes in retinal venular or arteriolar diameter were found. To conclude, retinal vessel diameters of COPD patients were significantly associated with systolic blood pressure and systemic inflammation, whilst there was no evidence for an association with lung function parameters, functional outcomes or other cardiovascular risk factors. Furthermore, an exercise-based PR program did not affect retinal vessel diameter.

Quantitative measurements of enlarged perivascular spaces in the brain are associated with retinal microvascular parameters in older community-dwelling subjects

BACKGROUND

Perivascular Spaces (PVS) become increasingly visible with advancing age on brain MRI, yet their relationship to morphological changes in the underlying microvessels remains poorly understood. Retinal and cerebral microvessels share morphological and physiological properties. We compared computationally-derived PVS morphologies with retinal vessel morphologies in older people.

METHODS

We analysed data from community-dwelling individuals who underwent multimodal brain MRI and retinal fundus camera imaging at mean age 72.55 years (SD=0.71). We assessed centrum semiovale PVS computationally to determine PVS total volume and count, and mean per-subject individual PVS length, width and size. We analysed retinal images using the VAMPIRE software suite, obtaining the Central Retinal Artery and Vein Equivalents (CRVE and CRAE), Arteriole-to-Venule ratio (AVR), and fractal dimension (FD) of both eyes. We investigated associations using general linear models, adjusted for age, gender, and major vascular risk factors.

RESULTS

In 381 subjects with all measures, increasing total PVS volume and count were associated with decreased CRAE in the left eye (volume β=-0.170, count β=-0.184, p<0.001). No associations of PVS with CRVE were found. The PVS total volume, individual width and size increased with decreasing FD of the arterioles (a) and venules (v) of the left eye (total volume: FDa β=-0.137, FDv β=-0.139, p<0.01; width: FDa β=-0.144, FDv β=-0.158, p<0.01; size: FDa β=-0.157, FDv β=-0.162, p<0.01).

CONCLUSIONS

Increase in PVS number and size visible on MRI reflect arteriolar narrowing and lower retinal arteriole and venule branching complexity, both markers of impaired microvascular health. Computationally-derived PVS metrics may be an early indicator of failing vascular health and should be tested in longitudinal studies.

Cardiovascular health and retinal microvascular geometry in Australian 11-12 year-olds

Traditional retinal microvascular parameters (smaller arteriolar and greater venular caliber) are associated with cardiovascular risk factors, pre-clinical vascular phenotypes and clinical cardiovascular events in adults. Although novel retinal microvascular geometric parameters showed analogous associations in adults, less is known whether these parameters are associated with cardiovascular health from childhood. In a population-based cross-sectional study in children (n = 1126, mean age 11.4 years, 50.3% girls), we examined associations of cardiovascular risk factors and pre-clinical arterial phenotypes with retinal geometric parameters. Cardiovascular parameters included body mass index (BMI), an inflammatory marker (GlycA), low-density lipoprotein and high-density lipoprotein (HDL) cholesterol, systolic (SBP) and diastolic blood pressure, large artery functional (pulse wave velocity, PWV and carotid arterial elasticity) and structural (carotid intima-media thickness) phenotypes. Retinal geometric parameters (fractal dimension (D_f) and tortuosity) were quantified from retinal images. Multivariable regression models were performed and adjusted for potential confounders. Higher values for BMI, SBP and PWV showed weak associations with lower (i.e. worse) arteriolar but not venular D_f (standardized mean difference (SMD) ranging from -0.07 to -0.09, 95% CIs -0.15 to -0.01). Higher HDL was associated with greater arteriolar D_f (SMD 0.07, 95% CI 0.01 to 0.13). Only higher SBP was associated with higher (i.e. worse) arteriolar but not venular tortuosity (SMD 0.09, 95% CI 0.02 to 0.16). In generally healthy children, some risk factors and pre-clinical arterial phenotypes show small associations with retinal geometric parameters. In childhood, emerging relationships between microvascular parameters and cardiometabolic risk may be better described by retinal vascular caliber than by geometric parameters.

Retinal microvascular features and cognitive change in the Lothian-Birth Cohort 1936

Introduction

We test whether measures of the retinal vasculature are associated with cognitive functioning and cognitive change.

Methods

Retinal images from a narrow-age cohort were analyzed using Vessel Assessment and Measurement Platform for Images of the Retina, producing a comprehensive range of quantitative measurements of the retinal vasculature, at mean age 72.5 years (SD = 0.7). Cognitive ability and change were measured using a battery of multiple measures of memory, visuospatial, processing speed, and crystallized cognitive abilities at mean ages 73, 76, and 79 years. We applied multivariate growth curve models to test the association between retinal vascular measurements with cognitive abilities and their changes.

Results

Almost all associations were nonsignificant. In our most parsimonious model, venular asymmetry factor was associated with speed at age 73.

Discussion

Our null findings suggest that the quantitative retinal parameters applied in this study are not significantly associated with cognitive functioning or cognitive change.

A multimodal approach to cardiovascular risk stratification in patients with type 2 diabetes incorporating retinal, genomic and clinical features

Cardiovascular diseases are a public health concern; they remain the leading cause of morbidity and mortality in patients with type 2 diabetes. Phenotypic information available from retinal fundus images and clinical measurements, in addition to genomic data, can identify relevant biomarkers of cardiovascular health. In this study, we assessed whether such biomarkers stratified risks of major adverse cardiac events (MACE). A retrospective analysis was carried out on an extract from the Tayside GoDARTS bioresource of participants with type 2 diabetes (n = 3,891). A total of 519 features were incorporated, summarising morphometric properties of the retinal vasculature, various single nucleotide polymorphisms (SNPs), as well as routine clinical measurements. After imputing missing features, a predictive model was developed on a randomly sampled set (n = 2,918) using L1-regularised logistic regression (lasso). The model was evaluated on an independent set (n = 973) and its performance associated with overall hazard rate after censoring (log-rank p < 0.0001), suggesting that multimodal features were able to capture important knowledge for MACE risk assessment. We further showed through a bootstrap analysis that all three sources of information (retinal, genetic, routine clinical) offer robust signal. Particularly robust features included: tortuousity, width gradient, and branching point retinal groupings; SNPs known to be associated with blood pressure and cardiovascular phenotypic traits; age at imaging; clinical measurements such as blood pressure and high density lipoprotein. This novel approach could be used for fast and sensitive determination of future risks associated with MACE.

Retinal Vascular Imaging in Vascular Cognitive Impairment: Current and Future Perspectives

Vascular cognitive disorders are heterogeneous and increasingly recognized entities with intricate correlation to neurodegenerative conditions. Retinal vascular analysis is a noninvasive approach to study cerebrovascular pathology, with promise to assist particularly during early disease phases. In this article, we have systematically summarized the current understanding, potential applications, and inevitable limitations of retinal vascular imaging in patients with vascular cognitive impairment. In addition, future directions in the field with support from automated technology using deep learning methods and their existing challenges are emphasized.