Retinal blood flow in critical illness and systemic disease: a review

Oculomics: A Crusade Against the Four Horsemen of Chronic Disease

Chronic, non-communicable diseases present a major barrier to living a long and healthy life. In many cases, early diagnosis can facilitate prevention, monitoring, and treatment efforts, improving patient outcomes. There is therefore a critical need to make screening techniques as accessible, unintimidating, and cost-effective as possible. The association between ocular biomarkers and systemic health and disease (oculomics) presents an attractive opportunity for detection of systemic diseases, as ophthalmic techniques are often relatively low-cost, fast, and non-invasive. In this review, we highlight the key associations between structural biomarkers in the eye and the four globally leading causes of morbidity and mortality: cardiovascular disease, cancer, neurodegenerative disease, and metabolic disease. We observe that neurodegenerative disease is a particularly promising target for oculomics, with biomarkers detected in multiple ocular structures. Cardiovascular disease biomarkers are present in the choroid, retinal vasculature, and retinal nerve fiber layer, and metabolic disease biomarkers are present in the eyelid, tear fluid, lens, and retinal vasculature. In contrast, only the tear fluid emerged as a promising ocular target for the detection of cancer. The retina is a rich source of oculomics data, the analysis of which has been enhanced by artificial intelligence-based tools. Although not all biomarkers are disease-specific, limiting their current diagnostic utility, future oculomics research will likely benefit from combining data from various structures to improve specificity, as well as active design, development, and optimization of instruments that target specific disease signatures, thus facilitating differential diagnoses.

Screening and evaluation of antioxidants for retinal pigment epithelial cell protection: L-ergothioneine as a novel therapeutic candidate through NRF2 activation

The continual exposure of retinal tissues to oxidative stress leads to discernible anatomical and physiological alterations. Specifically, the onslaught of oxidative damage escalates the irreversible death of retinal pigmented epithelium (RPE) cells, pinpointed as the fundamental pathological event in dry age-related macular degeneration (AMD). There is a conspicuous lack of effective therapeutic strategies to counteract this degenerative process. This study screened a library of antioxidants for their ability to protect RPE cells against oxidative stress and identified L-ergothioneine (EGT) as a potent cytoprotective agent. L-ergothioneine provided efficient protection against oxidative stress-damaged RPE and maintained cell redox homeostasis and normal physiological functions. It maintained the normal structure of the retina in mice under oxidative stress conditions. Transcriptomic analysis revealed that EGT counteracted major gene expression changes induced by oxidative stress. It upregulated antioxidant gene expression and inhibited NRF2 translocation. The inhibition of NRF2 abolished EGT's protective effects, suggesting that NRF2 activation contributes to its mechanism of action. In conclusion, we identified EGT as a safe and effective small-molecule compound that is expected to be a novel antioxidative agent for treating AMD.

Cross-modality Labeling Enables Noninvasive Capillary Quantification as a Sensitive Biomarker for Assessing Cardiovascular Risk

Purpose

We aim to use fundus fluorescein angiography (FFA) to label the capillaries on color fundus (CF) photographs and train a deep learning model to quantify retinal capillaries noninvasively from CF and apply it to cardiovascular disease (CVD) risk assessment.

Design

Cross-sectional and longitudinal study.

Participants

A total of 90732 pairs of CF-FFA images from 3893 participants for segmentation model development, and 49229 participants in the UK Biobank for association analysis.

Methods

We matched the vessels extracted from FFA and CF, and used vessels from FFA as labels to train a deep learning model (RMHAS-FA) to segment retinal capillaries using CF. We tested the model's accuracy on a manually labeled internal test set (FundusCapi). For external validation, we tested the segmentation model on 7 vessel segmentation datasets, and investigated the clinical value of the segmented vessels in predicting CVD events in the UK Biobank.

Main Outcome Measures

Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity for segmentation. Hazard ratio (HR; 95% confidence interval [CI]) for Cox regression analysis.

Results

On the FundusCapi dataset, the segmentation performance was AUC = 0.95, accuracy = 0.94, sensitivity = 0.90, and specificity = 0.93. Smaller vessel skeleton density had a stronger correlation with CVD risk factors and incidence (P < 0.01). Reduced density of small vessel skeletons was strongly associated with an increased risk of CVD incidence and mortality for women (HR [95% CI] = 0.91 [0.84-0.98] and 0.68 [0.54-0.86], respectively).

Conclusions

Using paired CF-FFA images, we automated the laborious manual labeling process and enabled noninvasive capillary quantification from CF, supporting its potential as a sensitive screening method for identifying individuals at high risk of future CVD events.

Financial Disclosures

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

Optical coherence tomography angiography analysis methods: a systematic review and meta-analysis

Optical coherence tomography angiography (OCTA) is widely used for non-invasive retinal vascular imaging, but the OCTA methods used to assess retinal perfusion vary. We evaluated the different methods used to assess retinal perfusion between OCTA studies. MEDLINE and Embase were searched from 2014 to August 2021. We included prospective studies including ≥ 50 participants using OCTA to assess retinal perfusion in either global retinal or systemic disorders. Risk of bias was assessed using the National Institute of Health quality assessment tool for observational cohort and cross-sectional studies. Heterogeneity of data was assessed by Q statistics, Chi-square test, and I2 index. Of the 5974 studies identified, 191 studies were included in this evaluation. The selected studies employed seven OCTA devices, six macula volume dimensions, four macula subregions, nine perfusion analyses, and five vessel layer definitions, totalling 197 distinct methods of assessing macula perfusion and over 7000 possible combinations. Meta-analysis was performed on 88 studies reporting vessel density and foveal avascular zone area, showing lower retinal perfusion in patients with diabetes mellitus than in healthy controls, but with high heterogeneity. Heterogeneity was lowest and reported vascular effects strongest in superficial capillary plexus assessments. Systematic review of OCTA studies revealed massive heterogeneity in the methods employed to assess retinal perfusion, supporting calls for standardisation of methodology.

A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images

Objective

To develop and validate an artificial intelligence diagnostic model based on fundus images for predicting Carotid Intima-Media Thickness (CIMT) in individuals with Type 2 Diabetes Mellitus (T2DM).

Methods

In total, 1236 patients with T2DM who had both retinal fundus images and CIMT ultrasound records within a single hospital stay were enrolled. Data were divided into normal and thickened groups and sent to eight deep learning models: convolutional neural networks of the eight models were all based on ResNet or ResNeXt. Their encoder and decoder modes are different, including the standard mode, the Parallel learning mode, and the Siamese mode. Except for the six unimodal networks, two multimodal networks based on ResNeXt under the Parallel learning mode or the Siamese mode were embedded with ages. Performance of eight models were compared via the confusion matrix, precision, recall, specificity, F1 value, and ROC curve, and recall was regarded as the main indicator. Besides, Grad-CAM was used to visualize the decisions made by Siamese ResNeXt network, which is the best performance.

Results

Performance of various models demonstrated the following points: 1) the RexNeXt showed a notable improvement over the ResNet; 2) the structural Siamese networks, which extracted features parallelly and independently, exhibited slight performance enhancements compared to the traditional networks. Notably, the Siamese networks resulted in significant improvements; 3) the performance of classification declined if the age factor was embedded in the network. Taken together, the Siamese ResNeXt unimodal model performed best for its superior efficacy and robustness. This model achieved a recall rate of 88.0% and an AUC value of 90.88% in the validation subset. Additionally, heatmaps calculated by the Grad-CAM algorithm presented concentrated and orderly mappings around the optic disc vascular area in normal CIMT groups and dispersed, irregular patterns in thickened CIMT groups.

Conclusion

We provided a Siamese ResNeXt neural network for predicting the carotid intimal thickness of patients with T2DM from fundus images and confirmed the correlation between fundus microvascular lesions and CIMT.

Retinal Vascular Changes in Response to Hypoxia: A High-Altitude Expedition Study

Westwood, Jessica, India Mayhook-Walker, Ciaran Simpkins, Andrew Darby-Smith, Dan Morris, and Eduardo Normando. Retinal vascular changes in response to hypoxia: a high-altitude expedition study. High Alt Med Biol. 25:49-59, 2024. Background: Increased tortuosity and engorgement of retinal vasculature are recognized physiological responses to hypoxia. This can lead to high-altitude retinopathy (HAR), but incidence reports are highly variable, and our understanding of the etiological mechanisms remains incomplete. This study quantitatively evaluated retinal vascular changes during an expedition to 4,167 m. Methods: Ten healthy participants summited Mount Toubkal, Morocco. Fundus images were taken predeparture, daily throughout the expedition, and 1 month postreturn. Diameter and tortuosity of four vessels were assessed, in addition to vessel density and features of HAR. Results: Significant (p ≤ 0.05) increases in tortuosity and diameter were observed in several vessels on high-altitude exposure days. There was a strong correlation between altitude and supratemporal retinal artery diameter on days 2, 3, and 6 of the expedition (r = 0.7707, 0.7951, 0.7401, respectively; p < 0.05). There was a significant increase in median vessel density from 6.7% at baseline to 10.0% on summit day. Notably there were no incidences of HAR. Conclusion: Physiological but not pathological changes were seen in this cohort, which gives insight into the state of the cerebral vasculature throughout this expedition. These results are likely attributable to relatively low altitude exposure, a conservative ascent profile, and the cohort's demographic. Future study must include daily retinal images at higher altitudes and take steps to mitigate environmental confounders. This study is relevant to altitude tourists, patients with diabetic retinopathy or retinal vein occlusion, and critically ill patients.

Optical Coherence Tomography Angiography Changes in Patients Diagnosed With Acute Coronary Syndrome: A Systematic Review and Meta-Analysis

We conducted a systematic review and meta-analysis to assess the association between optical coherence tomography angiography (OCTA) parameters and acute coronary syndrome (ACS). Two independent reviewers searched the electronic databases (MEDLINE (Medical Literature Analysis and Retrieval System Online), Scopus, Embase (Excerpta Medica Database), Cochrane Library, ClinicalTrials.gov, and World Health Organization International Clinical Trials Registry Platform) from inception until April 2023. According to the inclusion criteria of this review, eligible were observational studies, randomized control trials, and registry/database studies that included the eyes of adult ACS patients and assessed OCTA parameters within the macula. The pooled standardized mean differences (SMD) between patients diagnosed with ACS and healthy controls with a confidence interval (CI) of 95% were calculated using the Hartung-Knapp-Sidik-Jonkman random-effects method. The heterogeneity was assessed by I2 and the Cochran Q and a random effects model was applied. Seven studies were eligible and included in our systematic review (n = 898), of which three were included in the meta-analysis (n = 341). The pooled SMD in the superficial vascular plexus (SVP), deep vascular plexus (DVP), and foveal avascular zone (FAZ) were -0.46 (95% CI: -0.94 to 0.01, p = 0.05, I2 = 0%, three studies), -0.10 (95% CI: -3.20 to 3.00, p = 0.75, I2 = 67%, two studies), and 0.43 (95% CI: -1.22 to 2.09, p = 0.38, I2 = 92%, three studies), respectively. Our findings suggest that there are no differences in OCTA metrics between ACS patients and healthy individuals.

Evaluation of an Automated Choroid Segmentation Algorithm in a Longitudinal Kidney Donor and Recipient Cohort

Purpose

To evaluate the performance of an automated choroid segmentation algorithm in optical coherence tomography (OCT) data using a longitudinal kidney donor and recipient cohort.

Methods

We assessed 22 donors and 23 patients requiring renal transplantation over up to 1 year posttransplant. We measured choroidal thickness (CT) and area and compared our automated CT measurements to manual ones at the same locations. We estimated associations between choroidal measurements and markers of renal function (estimated glomerular filtration rate [eGFR], serum creatinine, and urea) using correlation and linear mixed-effects (LME) modeling.

Results

There was good agreement between manual and automated CT. Automated measures were more precise because of smaller measurement error over time. External adjudication of major discrepancies was in favor of automated measures. Significant differences were observed in the choroid pre- and posttransplant in both cohorts, and LME modeling revealed significant linear associations observed between choroidal measures and renal function in recipients. Significant associations were mostly stronger with automated CT (eGFR, P < 0.001; creatinine, P = 0.004; urea, P = 0.04) compared to manual CT (eGFR, P = 0.002; creatinine, P = 0.01; urea, P = 0.03).

Conclusions

Our automated approach has greater precision than human-performed manual measurements, which may explain stronger associations with renal function compared to manual measurements. To improve detection of meaningful associations with clinical endpoints in longitudinal studies of OCT, reducing measurement error should be a priority, and automated measurements help achieve this.

Translational Relevance

We introduce a novel choroid segmentation algorithm that can replace manual grading for studying the choroid in renal disease and other clinical conditions.

Variability in Capillary Perfusion Is Increased in Regions of Retinal Ischemia Due to Branch Retinal Vein Occlusion

Purpose

To investigate alterations in macular perfusion variability due to branch retinal vein occlusion (BRVO) using a novel approach based on optical coherence tomography angiography (OCTA) coefficient of variation (CoV) analysis.

Methods

Thirteen eyes of 13 patients with macular ischemia due to BRVO were studied. Multiple consecutive en face OCTA images were acquired. Bias field correction, spatial alignment, and normalization of intensities across the images were performed followed by pixelwise computation of standard deviation divided by the mean to generate a CoV map. Region of interest-based CoV values, derived from this map, for arterioles, venules, and the microvasculature were compared between regions with macular ischemia and control areas of the same eye. Control areas were regions of the same macula that were not affected by the BRVO and had normal retinal vascular structure as seen on multimodal imaging and normal retinal vascular density measurements as quantified using OCTA.

Results

CoV increased by a mean value of 17.6% within the microvasculature of ischemic regions compared to the control microvasculature (P < 0.0001). CoV measurements of microvasculature were consistently greater in the ischemic area of all 13 eyes compared to control. There were no differences in CoV measurements between ischemic and control areas for arterioles (P = 0.13) and venules (P = 1.0).

Conclusions

Greater variability in microvasculature perfusion occurs at sites of macular ischemia due to BRVO. We report a novel way for quantifying macular perfusion variability using OCTA. This technique may have applicability for studying the pathophysiology of other retinal vascular diseases.

Automated analysis of vessel morphometry in retinal images from a Danish high street optician setting

PURPOSE

To evaluate the test performance of the QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) software in detecting retinal features from retinal images captured by health care professionals in a Danish high street optician chain, compared with test performance from other large population studies (i.e., UK Biobank) where retinal images were captured by non-experts.

METHOD

The dataset FOREVERP (Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability, Pilot) contains retinal images obtained from a Danish high street optician chain. The QUARTZ algorithm utilizes both image processing and machine learning methods to determine retinal image quality, vessel segmentation, vessel width, vessel classification (arterioles or venules), and optic disc localization. Outcomes were evaluated by metrics including sensitivity, specificity, and accuracy and compared to human expert ground truths.

RESULTS

QUARTZ's performance was evaluated on a subset of 3,682 images from the FOREVERP database. 80.55% of the FOREVERP images were labelled as being of adequate quality compared to 71.53% of UK Biobank images, with a vessel segmentation sensitivity of 74.64% and specificity of 98.41% (FOREVERP) compared with a sensitivity of 69.12% and specificity of 98.88% (UK Biobank). The mean (± standard deviation) vessel width of the ground truth was 16.21 (4.73) pixels compared to that predicted by QUARTZ of 17.01 (4.49) pixels, resulting in a difference of -0.8 (1.96) pixels. The differences were stable across a range of vessels. The detection rate for optic disc localisation was similar for the two datasets.

CONCLUSION

QUARTZ showed high performance when evaluated on the FOREVERP dataset, and demonstrated robustness across datasets, providing validity to direct comparisons and pooling of retinal feature measures across data sources.

Macular microvasculature in patients with thyroid-associated orbitopathy: a cross-sectional study

PURPOSE

The aim of this study was to evaluate macular blood flow in patients with thyroid-associated orbitopathy (TAO) as compared to healthy subjects. The inflammatory nature of the disease, as well as the vascular congestion caused by the increase in the volume of orbital soft tissue and extraocular muscles, rationalize the assessment of retinal blood flow changes in these patients.

METHODS

This is a cross-sectional study with the convenience sampling method. Macular flow density was assessed using optical coherence tomography angiography (OCTA) and compared between patients with TAO and healthy individuals. We also compared macular flow density in two subgroups of patients based on clinical activity score (CAS).

RESULTS

Eighty-five cases, including 30 healthy individuals and 55 patients with TAO, participated. The foveal avascular zone (FAZ) area was significantly larger in the patient group than in the control. Patients with active TAO with CAS 3 or more had significantly larger FAZ areas than those with CAS less than 3 (p = 0.04).

CONCLUSION

We showed that the FAZ area is larger in active TAO patients and can be considered a possible candidate feature for monitoring disease activity and thyroid-associated vasculopathy.

Predicting ischemic stroke risk from atrial fibrillation based on multi-spectral fundus images using deep learning

Background

Ischemic stroke (IS) is one of the most common serious secondary diseases of atrial fibrillation (AF) within 1 year after its occurrence, both of which have manifestations of ischemia and hypoxia of the small vessels in the early phase of the condition. The fundus is a collection of capillaries, while the retina responds differently to light of different wavelengths. Predicting the risk of IS occurring secondary to AF, based on subtle differences in fundus images of different wavelengths, is yet to be explored. This study was conducted to predict the risk of IS occurring secondary to AF based on multi-spectrum fundus images using deep learning.

Methods

A total of 150 AF participants without suffering from IS within 1 year after discharge and 100 IS participants with persistent arrhythmia symptoms or a history of AF diagnosis in the last year (defined as patients who would develop IS within 1 year after AF, based on fundus pathological manifestations generally prior to symptoms of the brain) were recruited. Fundus images at 548, 605, and 810 nm wavelengths were collected. Three classical deep neural network (DNN) models (Inception V3, ResNet50, SE50) were trained. Sociodemographic and selected routine clinical data were obtained.

Results

The accuracy of all DNNs with the single-spectral or multi-spectral combination images at the three wavelengths as input reached above 78%. The IS detection performance of DNNs with 605 nm spectral images as input was relatively more stable than with the other wavelengths. The multi-spectral combination models acquired a higher area under the curve (AUC) scores than the single-spectral models.

Conclusions

The probability of IS secondary to AF could be predicted based on multi-spectrum fundus images using deep learning, and combinations of multi-spectrum images improved the performance of DNNs. Acquiring different spectral fundus images is advantageous for the early prevention of cardiovascular and cerebrovascular diseases. The method in this study is a beneficial preliminary and initiative exploration for diseases that are difficult to predict the onset time such as IS.

Modifications in Macular Perfusion and Neuronal Loss After Acute Traumatic Brain Injury

Purpose

Traumatic brain injury (TBI) causes structural damage and functional impairment in the visual system, often with retinal ganglion cell (RGC) degeneration occurring without visual symptoms. RGC degeneration is associated with reduced retinal blood-flow, however, it is not known whether reductions in perfusion precede or are secondary to neurodegeneration.

Methods

We conducted a prospective observational single-center case series. Patients were included if they were admitted to the hospital after acute TBI and underwent ophthalmic clinical examination, including optical coherence tomography (OCT) and OCT angiography (OCTA) acutely and at follow-up. Ganglion cell layer thickness (GCL) thickness, vascular density in the superficial vascular plexus (SVP), and intermediate capillary plexus (ICP) were quantified.

Results

Twenty-one patients aged 20 to 65 years (mean = 38 years) including 16 men and 5 women were examined less than 14 days after moderate to severe TBI, and again after 2 to 6 months. Macular structure and perfusion were normal at baseline in all patients. Visual function was abnormal at baseline in three patients and subsequent neurodegeneration and loss of perfusion corresponded to baseline visual function abnormalities. Nine patients (43%) had reduced macular GCL thickness at follow up. Perfusion in the SVP strongly associated with local GCL thickness. The strongest association of the SVP metrics was the sum of vessel density (P < 0.0001).

Conclusions

In cases of reduced visual function after TBI, macular perfusion remained normal until reductions in GCL thickness occurred, indicating that perfusion changes were secondary to local GCL loss.

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.

Interplay between aging and other factors of the pathogenesis of age-related macular degeneration

Age-related macular degeneration (AMD) is a complex eye disease with the retina as the target tissue and aging as per definition the most serious risk factor. However, the retina contains over 60 kinds of cells that form different structures, including the neuroretina and retinal pigment epithelium (RPE) which can age at different rates. Other established or putative AMD risk factors can differentially affect the neuroretina and RPE and can differently interplay with aging of these structures. The occurrence of β-amyloid plaques and increased levels of cholesterol in AMD retinas suggest that AMD may be a syndrome of accelerated brain aging. Therefore, the question about the real meaning of age in AMD is justified. In this review we present and update information on how aging may interplay with some aspects of AMD pathogenesis, such as oxidative stress, amyloid beta formation, circadian rhythm, metabolic aging and cellular senescence. Also, we show how this interplay can be specific for photoreceptors, microglia cells and RPE cells as well as in Bruch's membrane and the choroid. Therefore, the process of aging may differentially affect different retinal structures. As an accurate quantification of biological aging is important for risk stratification and early intervention for age-related diseases, the determination how photoreceptors, microglial and RPE cells age in AMD may be helpful for a precise diagnosis and treatment of this largely untreatable disease.

Optical coherence tomography angiography as a surrogate marker for end-organ resuscitation in sepsis: A review

Sepsis is a severe illness which results in alterations in the end organ microvascular haemodynamics and is associated with a high risk of mortality. There is currently no real-time method of monitoring microcirculatory perfusion during sepsis. Retinal microcirculation is closely linked to cerebral perfusion and may reflect systemic vascular alterations. Retinal perfusion can be assessed using the non-invasive imaging technique of optical coherence tomography angiography (OCTA). This narrative review aims to discuss the utility of using retinal imaging and OCTA in systemic illness and sepsis. OCTA can be used as a functional, non-invasive and real-time biomarker along with other haemodynamic parameters for assessing and managing patients with sepsis.

Retinal Microvascular Changes in COVID-19 Bilateral Pneumonia Based on Optical Coherence Tomography Angiography

The purpose of this study was to evaluate retinal and choroidal microvascular alterations with optical coherence tomography angiography (OCTA) in COVID-19 patients hospitalized because of bilateral pneumonia caused by SARS-CoV-2. The vessel density (VD) and foveal avascular zone (FAZ) of 63 patients with SARS-CoV-2 pneumonia who had positive polymerase chain reaction (PCR) tests and who recovered after receiving treatment and 45 healthy age- and gender-matched controls were evaluated and compared using OCTA in the superficial capillary plexus (SCP) and deep capillary plexus (DCP). The VD was also estimated in both groups in the choriocapillaris (CC). In COVID-19 patients, there was a statistically significant difference between the patients and a control group in both superficial (FAZs) and deep (FAZd) avascular zone (p = 0.000). The VD was significantly lower in the foveal area in choriocapillaris (p = 0.046). There were no statistically significant changes in the VD in the superior, inferior, nasal, and temporal quadrants in superficial and deep plexus, or in the choriocapillaris. The VD was not significantly lower in the foveal area in superficial or deep plexus. COVID-19 may affect the retinal vasculature, causing ischemia, enlargement of the FAZ, and lowering of the VD in the choriocapillaris area. Routine ophthalmic examination after SARS-CoV-2 infection should be considered in the course of post-infectious rehabilitation.

Retinal Vascular Profile in Predicting Incident Cardiometabolic Diseases among Individuals with Diabetes

OBJECTIVE

To determine the longitudinal associations between retinal vascular profile (RVP) and four major cardiometabolic diseases; and to quantify the predictive improvements when adding RVP beyond traditional risk factors in individuals with diabetes.

METHODS

Subjects were enrolled from the Singapore Epidemiology of Eye Disease (SEED) study, a multi-ethnic population-based cohort. Four incident cardiometabolic diseases, calculated over a ~6-year period, were considered: cardiovascular disease (CVD), hypertension (HTN), diabetic kidney disease (DKD) and hyperlipidaemia (HLD). The RVP - vessel tortuosity, branching angle, branching coefficient, fractal dimension, vessel calibre, and DR status - was characterized at baseline using a computer-assisted program. Traditional risk factors at baseline included age, gender, ethnicity, smoking, blood pressure (BP), HbA1c, estimated glomerular filtration rate (eGFR) or cholesterol. The improvements in predictive performance when adding RVP (compared to only traditional risk factors) was calculated using several metrics including area under the receiver operating characteristics curve (AUC) and Net Reclassification Improvement (NRI).

RESULTS

Among 1,770 individuals with diabetes, incidences were 6.3% (n=79/1259) for CVD, 48.7% (n=166/341) for HTN, 14.6% (n=175/1199) for DKD, and 59.4% (n=336/566) for HLD. DR preceded the onset of CVD (RR 1.85[1.14;3.00]) and DKD (1.44 [1.06;1.96]). Narrower arteriolar calibre preceding the onset of HTN (0.84 [0.72;0.99]), and changes in arteriolar branching angle preceded the onset of CVD (0.78 [0.62;0.98]) and HTN (1.15 [1.03;1.29]). The largest predictive improvement was found for HTN with AUC increment of 3.4% (p=0.027) and better reclassification of 11.4% of the cases and 4.6% of the controls (p=0.008).

CONCLUSION

We found that RVPs improved the prediction of HTN in individuals with diabetes, but add limited information for CVD, DKD and HLD predictions.

Artificial Intelligence in Predicting Systemic Parameters and Diseases From Ophthalmic Imaging

Artificial Intelligence (AI) analytics has been used to predict, classify, and aid clinical management of multiple eye diseases. Its robust performances have prompted researchers to expand the use of AI into predicting systemic, non-ocular diseases and parameters based on ocular images. Herein, we discuss the reasons why the eye is well-suited for systemic applications, and review the applications of deep learning on ophthalmic images in the prediction of demographic parameters, body composition factors, and diseases of the cardiovascular, hematological, neurodegenerative, metabolic, renal, and hepatobiliary systems. Three main imaging modalities are included—retinal fundus photographs, optical coherence tomographs and external ophthalmic images. We examine the range of systemic factors studied from ophthalmic imaging in current literature and discuss areas of future research, while acknowledging current limitations of AI systems based on ophthalmic images.

Retinal Microcirculation Changes in Crohn’s Disease Patients under Biologics, a Potential Biomarker of Severity: A Pilot Study

Crohn’s disease (CD) is associated with increased cardiovascular risk and the retinal microcirculation is a reflection of the systemic microcirculation. Is the retinal microcirculation altered in relation to the severity of Crohn’s disease? This cross-sectional case-controlled study was conducted in a university hospital center from November 2020 to February 2021. We prospectively included patients with moderate (biologic therapy) or severe (biologic therapy + peri-anal disease and/or digestive resection) CD and age- and sex-matched controls. Individuals with diabetes, renal disease, cardiovascular disease, ophthalmological history or poor quality images were excluded. All participants underwent OCT angiography (OCT-A) imaging (Optovue, Fremont, CA). Analysis of covariance was used. 74 CD patients (33 moderate, 41 severe) and 74 controls (66 (44.6%) men; mean (SD) age 44 (14) years) were included. Compared with the controls, the severe CD patients showed a significantly reduced mean foveal avascular zone area (p = 0.001), superficial macular capillary plexus vessel density (p = 0.009) and parafoveal thickness (p < 0.001), with no difference in mean superficial capillary flow index (p = 0.06) or deep macular capillary plexus vessel density (p = 0.67). The mean foveal avascular zone was significantly lower in the severe than the moderate CD patients (p = 0.010). OCT-A can detect alterations in retinal microcirculation in patients with severe versus moderate CD and versus age- and sex-matched controls.

Ocular microvascular alteration in Sjögren syndrome

BACKGROUND

Sjögren syndrome (SjS) is a systemic disease affecting exocrine, including ocular lacrimal, glands. It is uncertain whether ocular microvascular alterations are associated with this disease. In this study, we evaluated retinal and conjunctival microvascular changes in SjS patients using optical coherence tomography angiography (OCTA).

METHODS

Twelve SjS patients (24 eyes) and 12 normal controls (24 eyes) were recruited to this study. Three-dimensional conjunctival and retinal OCTA images of each eye were captured and microvascular density was calculated. Each image was analyzed by retinal area based on the early treatment of diabetic retinopathy study method (R, S, L, and I) hemisphere segmentation method (SR, SL, IL, and IR); and central wheel division method (C1-C6). Correlation analyses were used to look for associations between retinal and conjunctival microvascular densities.

RESULTS

Superficial and deep retinal layer microvascular density was decreased in SjS patients compared with normal controls (P<0.05). This significant difference was found in both superficial and deep layers in S, L, SL, IL and C1-C3 regions, and additionally in the I and SR regions in the superficial layer. Conversely, in the conjunctiva microvascular density was higher in SjS patients than in controls. In SjS patients, a significant negative correlation was found between conjunctival and both superficial (r=-0.641; P=0.025) and deep (r=-0.958; P<0.0001) microvascular densities.

CONCLUSIONS

The changed microvascular densities measured in deep and superficial retinal layers and in the conjunctiva demonstrate that OCTA is a promising method in differentiating the eyes from those with SjS.

Stability of OCT and OCTA in the Intensive Therapy Unit Setting

To assess the stability of retinal structure and blood flow measures over time and in different clinical settings using portable optical coherence tomography angiography (OCTA) as a potential biomarker of central perfusion in critical illness, 18 oesophagectomy patients completed retinal structure and blood flow measurements by portable OCT and OCTA in the eye clinic and intensive therapy unit (ITU) across three timepoints: (1) pre-operation in a clinic setting; (2) 24–48 h post-operation during ITU admission; and (3) seven days post-operation, if the patient was still admitted. Blood flow and macular structural measures were stable between the examination settings, with no consistent variation between pre- and post-operation scans, while retinal nerve fibre layer thickness increased in the post-operative scans (+2.31 µm, p = 0.001). Foveal avascular zone (FAZ) measurements were the most stable, with an intraclass correlation coefficient of up to 0.92 for right eye FAZ area. Blood flow and structural measures were lower in left eyes than right eyes. Retinal blood flow assessed in patients before and during an ITU stay using portable OCTA showed no systematic differences between the clinical settings. The stability of retinal blood flow measures suggests the potential for portable OCTA to provide clinically useful measures in ITU patients.

Optical coherence tomography's current clinical medical and dental applications: a review

Optical coherence tomography (OCT) is a non-invasive investigative technique that is used to obtain high-resolution three-dimensional (3D) images of biological structures. This method is useful in diagnosing diseases of specific organs like the eye, where a direct biopsy cannot be conducted. Since its inception, significant advancements have been made in its technology. Apart from its initial application in ophthalmology for retinal imaging, substantial technological innovations in OCT brought by the research community have enabled its utilization beyond its original scope and allowed its application in many new clinical areas. This review presents a summary of the clinical applications of OCT in the field of medicine (ophthalmology, cardiology, otology, and dermatology) and dentistry (tissue imaging, detection of caries, analysis of dental polymer composite restorations, imaging of root canals, and diagnosis of oral cancer). In addition, potential advantages and disadvantages of OCT are also discussed.

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease

Understanding the mechanics of blood flow is necessary for developing insights into mechanisms of physiology and vascular diseases in microcirculation. Given the limitations of technologies available for assessing in vivo flow fields, in vitro methods based on traditional microfluidic platforms have been developed to mimic physiological conditions. However, existing methods lack the capability to provide accurate assessment of these flow fields, particularly in vessels with complex geometries. Conventional approaches to quantify flow fields rely either on analyzing only visual images or on enforcing underlying physics without considering visualization data, which could compromise accuracy of predictions. Here, we present artificial-intelligence velocimetry (AIV) to quantify velocity and stress fields of blood flow by integrating the imaging data with underlying physics using physics-informed neural networks. We demonstrate the capability of AIV by quantifying hemodynamics in microchannels designed to mimic saccular-shaped microaneurysms (microaneurysm-on-a-chip, or MAOAC), which signify common manifestations of diabetic retinopathy, a leading cause of vision loss from blood-vessel damage in the retina in diabetic patients. We show that AIV can, without any a priori knowledge of the inlet and outlet boundary conditions, infer the two-dimensional (2D) flow fields from a sequence of 2D images of blood flow in MAOAC, but also can infer three-dimensional (3D) flow fields using only 2D images, thanks to the encoded physics laws. AIV provides a unique paradigm that seamlessly integrates images, experimental data, and underlying physics using neural networks to automatically analyze experimental data and infer key hemodynamic indicators that assess vascular injury.