Imaging retina to study dementia and stroke

Alzheimer's disease pathophysiology in the Retina

The retina is an emerging CNS target for potential noninvasive diagnosis and tracking of Alzheimer's disease (AD). Studies have identified the pathological hallmarks of AD, including amyloid β-protein (Aβ) deposits and abnormal tau protein isoforms, in the retinas of AD patients and animal models. Moreover, structural and functional vascular abnormalities such as reduced blood flow, vascular Aβ deposition, and blood-retinal barrier damage, along with inflammation and neurodegeneration, have been described in retinas of patients with mild cognitive impairment and AD dementia. Histological, biochemical, and clinical studies have demonstrated that the nature and severity of AD pathologies in the retina and brain correspond. Proteomics analysis revealed a similar pattern of dysregulated proteins and biological pathways in the retina and brain of AD patients, with enhanced inflammatory and neurodegenerative processes, impaired oxidative-phosphorylation, and mitochondrial dysfunction. Notably, investigational imaging technologies can now detect AD-specific amyloid deposits, as well as vasculopathy and neurodegeneration in the retina of living AD patients, suggesting alterations at different disease stages and links to brain pathology. Current and exploratory ophthalmic imaging modalities, such as optical coherence tomography (OCT), OCT-angiography, confocal scanning laser ophthalmoscopy, and hyperspectral imaging, may offer promise in the clinical assessment of AD. However, further research is needed to deepen our understanding of AD's impact on the retina and its progression. To advance this field, future studies require replication in larger and diverse cohorts with confirmed AD biomarkers and standardized retinal imaging techniques. This will validate potential retinal biomarkers for AD, aiding in early screening and monitoring.

Enhancing stroke risk and prognostic timeframe assessment with deep learning and a broad range of retinal biomarkers

Stroke stands as a major global health issue, causing high death and disability rates and significant social and economic burdens. The effectiveness of existing stroke risk assessment methods is questionable due to their use of inconsistent and varying biomarkers, which may lead to unpredictable risk evaluations. This study introduces an automatic deep learning-based system for predicting stroke risk (both ischemic and hemorrhagic) and estimating the time frame of its occurrence, utilizing a comprehensive set of known retinal biomarkers from fundus images. Our system, tested on the UK Biobank and DRSSW datasets, achieved AUROC scores of 0.83 (95% CI: 0.79-0.85) and 0.93 (95% CI: 0.9-0.95), respectively. These results not only highlight our system's advantage over established benchmarks but also underscore the predictive power of retinal biomarkers in assessing stroke risk and the unique effectiveness of each biomarker. Additionally, the correlation between retinal biomarkers and cardiovascular diseases broadens the potential application of our system, making it a versatile tool for predicting a wide range of cardiovascular conditions.

Artificial Intelligence Applications in Diabetic Retinopathy: What We Have Now and What to Expect in the Future

Diabetic retinopathy (DR) is a major complication of diabetes mellitus and is a leading cause of vision loss globally. A prompt and accurate diagnosis is crucial for ensuring favorable visual outcomes, highlighting the need for increased access to medical care. The recent remarkable advancements in artificial intelligence (AI) have raised high expectations for its role in disease diagnosis and prognosis prediction across various medical fields. In addition to achieving high precision comparable to that of ophthalmologists, AI-based diagnosis of DR has the potential to improve medical accessibility, especially through telemedicine. In this review paper, we aim to examine the current role of AI in the diagnosis of DR and explore future directions.

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.

Increased retinal venule diameter as a prognostic indicator for recurrent cerebrovascular events: a prospective observational study

Microvasculature of the retina is considered an alternative marker of cerebral vascular risk in healthy populations. However, the ability of retinal vasculature changes, specifically focusing on retinal vessel diameter, to predict the recurrence of cerebrovascular events in patients with ischemic stroke has not been determined comprehensively. While previous studies have shown a link between retinal vessel diameter and recurrent cerebrovascular events, they have not incorporated this information into a predictive model. Therefore, this study aimed to investigate the relationship between retinal vessel diameter and subsequent cerebrovascular events in patients with acute ischemic stroke. Additionally, we sought to establish a predictive model by combining retinal veessel diameter with traditional risk factors. We performed a prospective observational study of 141 patients with acute ischemic stroke who were admitted to the First Affiliated Hospital of Jinan University. All of these patients underwent digital retinal imaging within 72 hours of admission and were followed up for 3 years. We found that, after adjusting for related risk factors, patients with acute ischemic stroke with mean arteriolar diameter within 0.5-1.0 disc diameters of the disc margin (MAD0.5-1.0DD) of ≥ 74.14 μm and mean venular diameter within 0.5-1.0 disc diameters of the disc margin (MVD0.5-1.0DD) of ≥ 83.91 μm tended to experience recurrent cerebrovascular events. We established three multivariate Cox proportional hazard regression models: model 1 included traditional risk factors, model 2 added MAD0.5-1.0DD to model 1, and model 3 added MVD0.5-1.0DD to model 1. Model 3 had the greatest potential to predict subsequent cerebrovascular events, followed by model 2, and finally model 1. These findings indicate that combining retinal venular or arteriolar diameter with traditional risk factors could improve the prediction of recurrent cerebrovascular events in patients with acute ischemic stroke, and that retinal imaging could be a useful and non-invasive method for identifying high-risk patients who require closer monitoring and more aggressive management.

Atherosclerotic burden and cerebral small vessel disease: exploring the link through microvascular aging and cerebral microhemorrhages

Cerebral microhemorrhages (CMHs, also known as cerebral microbleeds) are a critical but frequently underestimated aspect of cerebral small vessel disease (CSVD), bearing substantial clinical consequences. Detectable through sensitive neuroimaging techniques, CMHs reveal an extensive pathological landscape. They are prevalent in the aging population, with multiple CMHs often being observed in a given individual. CMHs are closely associated with accelerated cognitive decline and are increasingly recognized as key contributors to the pathogenesis of vascular cognitive impairment and dementia (VCID) and Alzheimer's disease (AD). This review paper delves into the hypothesis that atherosclerosis, a prevalent age-related large vessel disease, extends its pathological influence into the cerebral microcirculation, thereby contributing to the development and progression of CSVD, with a specific focus on CMHs. We explore the concept of vascular aging as a continuum, bridging macrovascular pathologies like atherosclerosis with microvascular abnormalities characteristic of CSVD. We posit that the same risk factors precipitating accelerated aging in large vessels (i.e., atherogenesis), primarily through oxidative stress and inflammatory pathways, similarly instigate accelerated microvascular aging. Accelerated microvascular aging leads to increased microvascular fragility, which in turn predisposes to the formation of CMHs. The presence of hypertension and amyloid pathology further intensifies this process. We comprehensively overview the current body of evidence supporting this interconnected vascular hypothesis. Our review includes an examination of epidemiological data, which provides insights into the prevalence and impact of CMHs in the context of atherosclerosis and CSVD. Furthermore, we explore the shared mechanisms between large vessel aging, atherogenesis, microvascular aging, and CSVD, particularly focusing on how these intertwined processes contribute to the genesis of CMHs. By highlighting the role of vascular aging in the pathophysiology of CMHs, this review seeks to enhance the understanding of CSVD and its links to systemic vascular disorders. Our aim is to provide insights that could inform future therapeutic approaches and research directions in the realm of neurovascular health.

Distinct alterations of retinal structure between thalamic and extra-thalamic subcortical infarction patients: A cross-sectional and longitudinal study

AIMS

Cerebrovascular lesions in the primary visual cortex, the lateral geniculate nucleus, and the optic tract have been associated with retinal neurodegeneration via the retrograde degeneration (RD) mechanism. We aimed to use optical coherence tomography (OCT) to assess the effects of the strategic single subcortical infarction (SSI) location on retinal neurodegeneration and its longitudinal impacts.

METHODS

Patients with SSI were enrolled and stratified by lesion location on cerebral MRI into the thalamic infarction group and extra-thalamic infarction group. Healthy controls from the native communities were also recruited. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) were quantified using OCT. Generalized estimating equation (GEE) models were used for cross-sectional analyses and linear mixed models for longitudinal analyses. P < 0.05 was considered statistically significant.

RESULTS

We included a total of 283 eyes from 149 SSI patients. Of these, 115 eyes of 60 patients with follow-up were included in the longitudinal analyses. Cross-sectionally, thalamic-infarction patients had reduced retinal thickness compared with extra-thalamic infarction patients after adjustment for age, gender, disease duration, and vascular risk factors (p = 0.026 for RNFL, and p = 0.026 for GCIPL). Longitudinally, SSI patients showed greater retinal thinning compared with healthy controls over time (p = 0.040 for RNFL, and p < 0.001 for GCIPL), and thalamic infarction patients exhibited faster rates of GCIPL thinning in comparison with extra-thalamic infarction patients (p < 0.001).

CONCLUSION

Our study demonstrates a distinct effect of subcortical infarction lesion site on the retina both at the early stage of disease and at the 1-year follow-up time. These results present evidence of significant associations between strategic infarction locations and retinal neurodegeneration. It may provide novel insights for further research on RD in stroke patients and ultimately facilitate individualized recovery therapeutic strategy.

The usefulness of the retina for identifying people with type 2 diabetes with prodromal stages of dementia

Type 2 diabetes (T2D) is associated with cognitive impairment and dementia. The detection of cognitive impairment is important because this population is at higher risk of experiencing difficulties in the self-management of diabetes. Mild cognitive impairment (MCI) often remains undiagnosed due to lack of simple tools for screening at large scale. This represents an important gap in the patients' management because subjects with diabetes and MCI are at high risk of progressing to dementia. Due to its developmental origin as a brain-derived tissue, the retina has been proposed as a potential means of non-invasive and readily accessible exploration of brain pathology. Recent evidence showed that retinal imaging and/or functional tests are correlated with the cognitive function and brain changes in T2D. Simple retinal functional tests (i.e. retinal microperimetry) have proven to be useful as reliable tool for the cognitive evaluation and monitoring in patients with T2D>65 years. This review gives an overall update on the usefulness of retinal imaging in identifying patients with T2D at risk of developing dementia.

Deep neural network-estimated age using optical coherence tomography predicts mortality

The concept of biological age has emerged as a measurement that reflects physiological and functional decline with ageing. Here we aimed to develop a deep neural network (DNN) model that predicts biological age from optical coherence tomography (OCT). A total of 84,753 high-quality OCT images from 53,159 individuals in the UK Biobank were included, among which 12,631 3D-OCT images from 8,541 participants without any reported medical conditions at baseline were used to develop an age prediction model. For the remaining 44,618 participants, OCT age gap, the difference between the OCT-predicted age and chronological age, was calculated for each participant. Cox regression models assessed the association between OCT age gap and mortality. The DNN model predicted age with a mean absolute error of 3.27 years and showed a strong correlation of 0.85 with chronological age. After a median follow-up of 11.0 years (IQR 10.9-11.1 years), 2,429 deaths (5.44%) were recorded. For each 5-year increase in OCT age gap, there was an 8% increased mortality risk (hazard ratio [HR] = 1.08, CI:1.02-1.13, P = 0.004). Compared with an OCT age gap within ± 4 years, OCT age gap less than minus 4 years was associated with a 16% decreased mortality risk (HR = 0.84, CI: 0.75-0.94, P = 0.002) and OCT age gap more than 4 years showed an 18% increased risk of death incidence (HR = 1.18, CI: 1.02-1.37, P = 0.026). OCT imaging could serve as an ageing biomarker to predict biological age with high accuracy and the OCT age gap, defined as the difference between the OCT-predicted age and chronological age, can be used as a marker of the risk of mortality.

Retinal microvascular function and incidence and trajectories of clinically relevant depressive symptoms: the Maastricht Study

BACKGROUND

Cerebral microvascular dysfunction may contribute to depression via disruption of brain structures involved in mood regulation, but evidence is limited. We investigated the association of retinal microvascular function, a proxy for microvascular function in the brain, with incidence and trajectories of clinically relevant depressive symptoms.

METHODS

Longitudinal data are from The Maastricht Study of 5952 participants (59.9 ± 8.5 years/49.7% women) without clinically relevant depressive symptoms at baseline (2010-2017). Central retinal arteriolar equivalent and central retinal venular equivalent (CRAE and CRVE) and a composite score of flicker light-induced retinal arteriolar and venular dilation were assessed at baseline. We assessed incidence and trajectories of clinically relevant depressive symptoms (9-item Patient Health Questionnaire score ⩾10). Trajectories included continuously low prevalence (low, n = 5225 [87.8%]); early increasing, then chronic high prevalence (early-chronic, n = 157 [2.6%]); low, then increasing prevalence (late-increasing, n = 247 [4.2%]); and remitting prevalence (remitting, n = 323 [5.4%]).

RESULTS

After a median follow-up of 7.0 years (range 1.0-11.0), 806 (13.5%) individuals had incident clinically relevant depressive symptoms. After full adjustment, a larger CRAE and CRVE were each associated with a lower risk of clinically relevant depressive symptoms (hazard ratios [HRs] per standard deviation [s.d.]: 0.89 [95% confidence interval (CI) 0.83-0.96] and 0.93 [0.86-0.99], respectively), while a lower flicker light-induced retinal dilation was associated with a higher risk of clinically relevant depressive symptoms (HR per s.d.: 1.10 [1.01-1.20]). Compared to the low trajectory, a larger CRAE was associated with lower odds of belonging to the early-chronic trajectory (OR: 0.83 [0.69-0.99]) and a lower flicker light-induced retinal dilation was associated with higher odds of belonging to the remitting trajectory (OR: 1.23 [1.07-1.43]).

CONCLUSIONS

These findings support the hypothesis that cerebral microvascular dysfunction contributes to the development of depressive symptoms.

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

OBJECTIVES

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

DESIGN, SETTING AND PARTICIPANTS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTERATION NUMBER

MIND-China study (ChiCTR1800017758).

Microvascular Dysfunction and Whole-Brain White Matter Connectivity: The Maastricht Study

BACKGROUND

Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity.

METHODS AND RESULTS

Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (β per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures.

CONCLUSIONS

These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

Coronary artery disease, its associations with ocular, genetic and blood lipid parameters

BACKGROUND/OBJECTIVES

To investigate the associations between ophthalmic parameters, CYP4F2 (rs2108622) and ABCA1 (rs1883025) polymorphisms and coronary artery disease, considering the accessibility, non-invasive origin of retinal examination and its possible resemblance to coronary arteries.

SUBJECTS/METHODS

Overall 165 participants divided into groups based on the coronary angiography results and clinical status: control group (N = 73), MI group (N = 63), 3VD (three vessel disease) (N = 24). All the participants underwent total ophthalmic examination - optical coherence tomography (OCT) and OCT angiography of the macula region were performed and evaluated. Total cholesterol, high-density lipoprotein, low-density lipoprotein and triglyceride cholesterol (Tg-C) were tested. A standard manufacturer's protocol for CYP4F2 (rs2108622) and ABCA1 (rs1883025) was used for genotyping with TaqMan probes.

RESULTS

GCL+ layer was thicker in control group vs. 3VD group (74.00; 62.67-94.67 (median; min.-max.) vs. 71.06; 51.33-78.44, p = 0.037). T allele carriers under ABCA1 rs1883025 dominant model were shown to have ticker retina and smaller foveal avascular zone in superficial capillary plexus and smaller Tg-C concentration. ABCA1 rs1883025 was associated with retinal thickness (OR = 0.575, 95% CI 0.348-0.948, p = 0.030). Univariate logistic regression showed that ABCA1 rs1883025 CT genotype is associated with decreased risk for coronary artery disease development under overdominant genetic model (OR = 0.498, 95% CI 0.254-0.976; p = 0.042) and codominant genetic model (OR = 0.468, 95% CI 0.232-0.945, p = 0.034).

CONCLUSIONS

Results of this study confirmed that non-invasive methods such as OCT of eye might be used for identification of patients at risk of CAD.

Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system

Aging in an individual refers to the temporal change, mostly decline, in the body's ability to meet physiological demands. Biological age (BA) is a biomarker of chronological aging and can be used to stratify populations to predict certain age-related chronic diseases. BA can be predicted from biomedical features such as brain MRI, retinal, or facial images, but the inherent heterogeneity in the aging process limits the usefulness of BA predicted from individual body systems. In this paper, we developed a multimodal Transformer-based architecture with cross-attention which was able to combine facial, tongue, and retinal images to estimate BA. We trained our model using facial, tongue, and retinal images from 11,223 healthy subjects and demonstrated that using a fusion of the three image modalities achieved the most accurate BA predictions. We validated our approach on a test population of 2,840 individuals with six chronic diseases and obtained significant difference between chronological age and BA (AgeDiff) than that of healthy subjects. We showed that AgeDiff has the potential to be utilized as a standalone biomarker or conjunctively alongside other known factors for risk stratification and progression prediction of chronic diseases. Our results therefore highlight the feasibility of using multimodal images to estimate and interrogate the aging process.

Artificial intelligence in retinal imaging: current status and future prospects

INTRODUCTION

The steadily growing and aging world population, in conjunction with continuously increasing prevalences of vision-threatening retinal diseases, is placing an increasing burden on the global healthcare system. The main challenges within retinology involve identifying the comparatively few patients requiring therapy within the large mass, the assurance of comprehensive screening for retinal disease and individualized therapy planning. In order to sustain high-quality ophthalmic care in the future, the incorporation of artificial intelligence (AI) technologies into our clinical practice represents a potential solution.

AREAS COVERED

This review sheds light onto already realized and promising future applications of AI techniques in retinal imaging. The main attention is directed at the application in diabetic retinopathy and age-related macular degeneration. The principles of use in disease screening, grading, therapeutic planning and prediction of future developments are explained based on the currently available literature.

EXPERT OPINION

The recent accomplishments of AI in retinal imaging indicate that its implementation into our daily practice is likely to fundamentally change the ophthalmic healthcare system and bring us one step closer to the goal of individualized treatment. However, it must be emphasized that the aim is to optimally support clinicians by gradually incorporating AI approaches, rather than replacing ophthalmologists.

Initiation of China Alliance of Research in High Myopia (CHARM): protocol for an AI-based multimodal high myopia research biobank

INTRODUCTION

High myopia is a pressing public health concern due to its increasing prevalence, younger trend and the high risk of blindness, particularly in East Asian countries, including China. The China Alliance of Research in High Myopia (CHARM) is a newly established consortium that includes more than 100 hospitals and institutions participating across the nation, aiming to promote collaboration and data sharing in the field of high myopia screening, classification, diagnosis and therapeutic development.

METHODS AND ANALYSIS

The CHARM project is an ongoing study, and its initiation is distinguished by its unprecedented scale, encompassing plans to involve over 100 000 Chinese patients. This initiative stands out not only for its extensive scope but also for its innovative application of artificial intelligence (AI) to assist in diagnosis and treatment decisions. The CHARM project has been carried out using a 'three-step' strategy. The first step involves the collection of basic information, refraction, axial length and fundus photographs from participants with high myopia. In the second step, we will collect multimodal imaging data to expand the scope of clinical information, for example, optical coherence tomography and ultra-widefield fundus images. In the final step, genetic testing will be conducted by incorporating patient family histories and blood samples. The majority of data collected by CHARM is in the form of images that will be used to detect and predict the progression of high myopia through the identification and quantification of biomarkers such as fundus tessellation, optic nerve head and vascular parameters.

ETHICS AND DISSEMINATION

The study has received approval from the Ethics Committee of Beijing Tongren Hospital (TREC2022-KY045). The establishment of CHARM represents an opportunity to create a collaborative platform for myopia experts and facilitate the dissemination of research findings to the global community through peer-reviewed publications and conference presentations. These insights can inform clinical decision-making and contribute to the development of new treatment modalities that may benefit patients worldwide.

TRIAL REGISTRATION NUMBER

ChiCTR2300071219.

Arterial hypertension and retinal layer thickness: the Beijing Eye Study

PURPOSE

To investigate relationships between blood pressure and the thickness of single retinal layers in the macula.

METHODS

Participants of the population-based Beijing Eye Study, free of retinal or optic nerve disease, underwent medical and ophthalmological examinations including optical coherence tomographic examination of the macula. Applying a multiple-surface segmentation solution, we automatically segmented the retina into its various layers.

RESULTS

The study included 2237 participants (mean age 61.8±8.4 years, range 50-93 years). Mean thicknesses of the retinal nerve fibre layer (RNFL), ganglion cell layer (GCL), inner plexiform layer, inner nuclear layer (INL), outer plexiform layer, outer nuclear layer/external limiting membrane, ellipsoid zone, photoreceptor outer segments (POS) and retinal pigment epithelium-Bruch membrane were 31.1±2.3 µm, 39.7±3.5 µm, 38.4±3.3 µm, 34.8±2.0 µm, 28.1±3.0 µm, 79.2±7.3 µm, 22.9±0.6 µm, 19.2±3.3 µm and 20.7±1.4 µm, respectively. In multivariable analysis, higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) were associated with thinner GCL and thicker INL, after adjusting for age, sex and axial length (all p<0.0056). Higher SBP was additionally associated with thinner POS and higher DBP with thinner RNFL. For an elevation of SBP/DBP by 10 mm Hg, the RNFL, GCL, INL and POS changed by 2.0, 3.0, 1.5 and 2.0 µm, respectively.

CONCLUSIONS

Thickness of RNFL, GCL and POS was inversely and INL thickness was positively associated with higher blood pressure, while the thickness of the other retinal layers was not significantly correlated with blood pressure. The findings may be helpful for refinement of the morphometric detection of retinal diseases.

Looking beyond the brain: Insights into vascular parkinsonism with optical coherence tomography

BACKGROUND

Vascular Parkinsonism (VP) is characterized by rigidity and bradykinesia predominantly affecting the lower limbs. Optical Coherence tomography (OCT) facilitates the visualization of retina and choroid and may help in delineating differential involvement of retina and choroid in patients with VP. In this study, we report the pattern of changes in the retinal and choroidal layers in patients with VP with the help of spectral domain OCT (SD-OCT).

METHODS

We adopted a case-control design and evaluated 24 patients with VP with complete history, clinical examination, Montreal Cognitive Assessment (MOCA), Unified Parkinson's Disease Rating Scale (UPDRS) motor part in OFF state, and retinal and choroidal imaging with SD-OCT. The peripapillary retinal nerve fiber layer (RNFL) thickness, peripapillary choroidal layer thickness (PPChT), central macular thickness (CMT) and subfoveal choroid thickness (SFChT) were assessed. Twenty-two age and gender-matched healthy control subjects were also recruited.

RESULTS

The peripapillary RNFL, in most of the segments and CMT were significantly thinner in patients with VP compared to controls. The subfoveal and peripapillary ChT did not differ significantly between patients and controls.

CONCLUSION

This is the first study that has evaluated the role of OCT in patients with VP and these patients have significant involvement of the retina. In addition to providing pathophysiological insights, OCT parameters may serve as disease biomarkers in VP. This study lays the foundation for carrying out future studies with larger sample sizes and a longitudinal design.

Evaluation of peripapillary retinal nerve fiber layer thickness in intracranial atherosclerotic stenosis

PURPOSE

To evaluate the peripapillary retinal nerve fiber layer thickness (pRNFL) in patients with intracranial atherosclerotic stenosis (ICAS).

METHODS

A cross-sectional study was performed in a general hospital. The intracranial atherosclerotic stenosis was evaluated by digital subtraction angiography (DSA), computed tomography angiography (CTA) or magnetic resonance angiography (MRA). High-definition optical coherence tomography (HD-OCT) was used to evaluate the peripapillary retinal nerve fiber layer thickness.

RESULTS

A total of 102 patients, including 59(57.8%) patients with ICAS and 43(42.2%) patients without ICAS, were finally analysed in the study. The peripapillary retinal nerve fiber layer thickness (pRNFL) was reduced significantly in the average, the superior and the inferior quadrants of the ipsilateral eyes and in the superior quadrant of the contralateral eyes in patients with ICAS compared with patients without ICAS. After multivariate analysis, only the superior pRNFL thickness in the ipsilateral eyes was significantly associated with ICAS (OR,0.968; 95% CI,0.946-0.991; p = 0.006). The area under receiver operator curve was 0.679 (95% CI,0.576-0.782) for it to identify the presence of ICAS. The cut-off value of the superior pRNFL was 109.5 μm, and the sensitivity and specificity were 50.8% and 83.7%, respectively.

CONCLUSION

The superior pRNFL in the ipsilateral eye was significantly associated with ICAS in this study. Larger studies are needed to explore the relation between pRNFL and ICAS further.

The retina-brain axis and diabetic retinopathy

Diabetic retinopathy (DR) is a major contributor to permanent vision loss and blindness. Changes in retinal neurons, glia, and microvasculature have been the focus of intensive study in the quest to better understand DR. However, the impact of diabetes on the rest of the visual system has received less attention. There are reports of associations of changes in the visual system with preclinical and clinical manifestations of diabetes. Simultaneous investigation of the retina and the brain may shed light on the mechanisms underlying neurodegeneration in diabetics. Additionally, investigating the links between DR and other neurodegenerative disorders of the brain including Alzheimer's and Parkinson's disease may reveal shared mechanisms for neurodegeneration and potential therapy options.

Using a dual-stream attention neural network to characterize mild cognitive impairment based on retinal images

Mild cognitive impairment (MCI) is a critical transitional stage between normal cognition and dementia, for which early detection is crucial for timely intervention. Retinal imaging has been shown as a promising potential biomarker for MCI. This study aimed to develop a dual-stream attention neural network to classify individuals with MCI based on multi-modal retinal images. Our approach incorporated a cross-modality fusion technique, a variable scale dense residual model, and a multi-classifier mechanism within the dual-stream network. The model utilized a residual module to extract image features and employed a multi-level feature aggregation method to capture complex context information. Self-attention and cross-attention modules were utilized at each convolutional layer to fuse features from optical coherence tomography (OCT) and fundus modalities, resulting in multiple output losses. The neural network was applied to classify individuals with MCI, Alzheimer's disease, and control participants with normal cognition. Through fine-tuning the pre-trained model, we classified community-dwelling participants into two groups based on cognitive impairment test scores. To identify retinal imaging biomarkers associated with accurate prediction, we used the Gradient-weighted Class Activation Mapping technique. The proposed method achieved high precision rates of 84.96% and 80.90% in classifying MCI and positive test scores for cognitive impairment, respectively. Notably, changes in the optic nerve head on fundus photographs or OCT images among patients with MCI were not used to discriminate patients from the control group. These findings demonstrate the potential of our approach in identifying individuals with MCI and emphasize the significance of retinal imaging for early detection of cognitive impairment.

Influence of secondhand smoke exposure on the retinal vasculature of children in Hong Kong

BACKGROUND

A recent prospective demonstrated that cardiovascular risk factors in early childhood were associated with later cardiovascular events. However, the impact of secondhand smoke (SHS) on children is unclear. The aims of this study is to determine the effects of SHS exposure on the retinal vasculature of children.

METHODS

This is a population-based cross-sectional study of children aged 6 to 8 years. All participants received comprehensive ophthalmic examinations and retinal photography. Data on SHS exposure was derived from a validated questionnaire. A validated deep-learning system was used to automatically estimate retinal arteriolar and venular calibers from retinal photographs. Associations of quantitative retinal vessel caliber values with SHS exposure, number of smokers in the household, and total number of cigarettes smoked were determined by analyses of covariance (ANCOVA) after adjusting for potential confounders. Test of trend was determined by treating categorical risk factors as continuous ordinal variables.

RESULTS

Here we show children exposed to SHS have wider retinal arteriolar (CRAE 152.1 µm vs. 151.3 µm, p < 0.001) and venular (CRVE 216.7 µm vs. 215.5 µm, p < 0.001) calibers compared to those in smoke-free homes, after adjustment for different factors. Wider arteriolar and venular calibers are also associated with increasing number of smokers in the family (p trend < 0.001) and more cigarettes smoked among family smokers (p trend<0.001).

CONCLUSIONS

Exposure to SHS at home is associated with changes in retinal vasculature among children. This reinforces the adverse effect of secondhand smoking around children though further research incorporating comprehensive assessment of potential confounders is necessary.

Targeting circular RNA-Glra2 alleviates retinal neurodegeneration induced by ocular hypertension

Glaucoma is a leading cause of irreversible vision loss characterized by retinal neurodegeneration. Circular RNAs (circRNAs) have emerged as the potential biomarkers and therapeutic targets for neurodegenerative diseases. However, the expression profiling of circRNAs in glaucomatous neurodegeneration has not been fully understood. In this study, we built a glaucomatous neurodegeneration model via the injection of microbeads into anterior chamber. circRNA expression profile and bioinformatics analysis revealed that compared with normal retinas, 171 circRNAs were dysregulated in the glaucomatous retinas, including 101 up-regulated circRNAs and 70 down-regulated circRNAs. Detecting the level of circular RNA-glycine receptor α2 subunit gene (cGlra2) in aqueous humor made it possible to distinguish glaucoma patients from cataract patients. Silencing of cGlra2 protected against oxidative stress- or hydrostatic pressure-induced retinal ganglion cell (RGC) injury in vitro. Moreover, silencing of cGlra2 retarded ocular hypertension-induced retinal neurodegeneration in vivo as shown by increased TUJ1 staining, reduced reactive gliosis, decreased retinal cell apoptosis, enhanced visual acuity, and improved retinal function. cGlra2 acted as a miRNA sponge to regulate RGC function through cGlra2/miR-144/BCL2L11 signaling axis. Collectively, this study provides novel insights into the underlying mechanism of retinal neurodegeneration and highlights the potential of cGlra2 as a target for the diagnosis and treatment of glaucoma.

Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review

Microvascular changes in diabetes affect the function of several critical organs, such as the kidneys, heart, brain, eye, and skin, among others. The possibility of detecting such changes early enough in order to take appropriate actions renders the development of appropriate tools and techniques an imperative need. To this end, several sensing and imaging techniques have been developed or employed in the assessment of microangiopathy in patients with diabetes. Herein, we present such techniques; we provide insights into their principles of operation while discussing the characteristics that make them appropriate for such use. Finally, apart from already established techniques, we present novel ones with great translational potential, such as optoacoustic technologies, which are expected to enter clinical practice in the foreseeable future.

The Association Between Eye Disease and Incidence of Dementia: Systematic Review and Meta-Analysis

OBJECTIVES

To better demonstrate the relationship between common eye diseases and the risk of dementia, we conducted a systematic review and meta-analysis of cohort studies to investigate the relationship between common eye diseases and dementia.

DESIGN

Systematic review and meta-analysis.

SETTING AND PARTICIPANTS

Patients with common eye diseases.

METHODS

We conducted a systematic search of articles published up to August 25, 2022, of online databases including PubMed, EMBASE, and Web of Science. We included cohort studies that evaluated the association of glaucoma, age-related macular degeneration (AMD), diabetic retinopathy (DR), and cataracts with all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD). Relative risks (RRs) and 95% CIs were pooled using random effects model, and heterogeneity was assessed by the I2 statistic. Subgroup analysis and sensitivity analysis were also performed.

RESULTS

In total, 25 studies were included in the meta-analysis, with a total of 11,410,709 participants. Pooled estimates suggested an increased risk of all-cause dementia associated with AMD (RR, 1.29; 95% CI, 1.13-1.48), glaucoma (RR, 1.16; 95% CI, 1.03-1.32), DR (RR, 1.40; 95% CI, 1.21-1.63), and cataract (RR,1.23; 95% CI, 1.09-1.40); an increased risk of AD associated with AMD (RR, 1.27; 95% CI, 1.06-1.52), glaucoma (RR, 1.18; 95% CI, 1.02-1.38), DR (RR, 1.21; 95% CI, 1.04-1.41), and cataracts (RR,1.22; 95% CI, 1.07-1.38). No association was observed between incident VaD and any eye diseases. The results of subgroup analyses were consistent with those in meta-analysis of DR and risk of all-cause dementia. Meta-regressions suggested geographic regions as potential sources of heterogeneity for the association between AMD and all-cause dementia, AMD and AD, glaucoma and dementia, glaucoma, and AD, respectively.

CONCLUSIONS AND IMPLICATIONS

AMD, glaucoma, DR, and cataract may be associated with an increased risk of all-cause dementia and AD, but not VaD. However, the results should be interpreted cautiously because of the high heterogeneity and unstable findings in some subgroup analyses.

Association of retinal nerve layers thickness and brain imaging in healthy young subjects from the i-Share-Bordeaux study

Given the anatomical and functional similarities between the retina and the brain, the retina could be a "window" for viewing brain structures. We investigated the association between retinal nerve fiber layers (peripapillary retinal nerve fiber layer, ppRNFL; macular ganglion cell-inner plexiform layer, GC-IPL; and macular ganglion cell complex, GCC), and brain magnetic resonance imaging (MRI) parameters in young health adults. We included 857 students (mean age: 23.3 years, 71.3% women) from the i-Share study. We used multivariate linear models to study the cross-sectional association of each retinal nerve layer thickness assessed by spectral-domain optical coherence tomography (SD-OCT) with structural (volumes and cortical thickness), and microstructural brain markers, assessed on MRI globally and regionally. Microstructural MRI parameters included diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI). On global brain analysis, thicker ppRNFL, GC-IPL and GCC were all significantly associated with patterns of diffusion metrics consistent with higher WM microstructural integrity. In regional analyses, after multiple testing corrections, our results suggested significant associations of some retinal nerve layers with brain regional gray matter occipital volumes and with diffusion MRI parameters in a region involved in the visual pathway and in regions containing associative tracts. No associations were found with global volumes or with global or regional cortical thicknesses. Results of this study suggest that some retinal nerve layers may reflect brain structures. Further studies are needed to confirm these results in young subjects.

The association between retina thinning and hippocampal atrophy in Alzheimer's disease and mild cognitive impairment: a meta-analysis and systematic review

Introduction

The retina is the "window" of the central nervous system. Previous studies discovered that retinal thickness degenerates through the pathological process of the Alzheimer's disease (AD) continuum. Hippocampal atrophy is one of the typical clinical features and diagnostic criteria of AD. Former studies have described retinal thinning in normal aging subjects and AD patients, yet the association between retinal thickness and hippocampal atrophy in AD is unclear. The optical coherence tomography (OCT) technique has access the non-invasive to retinal images and magnetic resonance imaging can outline the volume of the hippocampus. Thus, we aim to quantify the correlation between these two parameters to identify whether the retina can be a new biomarker for early AD detection.

Methods

We systematically searched the PubMed, Embase, and Web of Science databases from inception to May 2023 for studies investigating the correlation between retinal thickness and hippocampal volume. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the study quality. Pooled correlation coefficient r values were combined after Fisher's Z transformation. Moderator effects were detected through subgroup analysis and the meta-regression method.

Results

Of the 1,596 citations initially identified, we excluded 1,062 studies after screening the titles and abstract (animal models, n = 99; irrelevant literature, n = 963). Twelve studies met the inclusion criteria, among which three studies were excluded due to unextractable data. Nine studies were eligible for this meta-analysis. A positive moderate correlation between the retinal thickness was discovered in all participants of with AD, mild cognitive impairment (MCI), and normal controls (NC) (r = 0.3469, 95% CI: 0.2490-0.4377, I2 = 5.0%), which was significantly higher than that of the AD group (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%) (p < 0.05). Among different layers, the peripapillary retinal nerve fiber layer (pRNFL) indicated a moderate positive correlation with hippocampal volume (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%). The retinal pigmented epithelium (RPE) was also positively correlated [r = 0.1421, 95% CI:(-0.0447-0.3192), I2 = 84.1%]. The retinal layers and participants were the main overall heterogeneity sources. Correlation in the bilateral hemisphere did not show a significant difference.

Conclusion

The correlation between RNFL thickness and hippocampal volume is more predominant in both NC and AD groups than other layers. Whole retinal thickness is positively correlated to hippocampal volume not only in AD continuum, especially in MCI, but also in NC.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, CRD42022328088.

The impact of Alzheimer's disease risk factors on the pupillary light response

Alzheimer's disease (AD) is the leading cause of dementia, and its prevalence is increasing and is expected to continue to increase over the next few decades. Because of this, there is an urgent requirement to determine a way to diagnose the disease, and to target interventions to delay and ideally stop the onset of symptoms, specifically those impacting cognition and daily livelihood. The pupillary light response (PLR) is controlled by the sympathetic and parasympathetic branches of the autonomic nervous system, and impairments to the pupillary light response (PLR) have been related to AD. However, most of these studies that assess the PLR occur in patients who have already been diagnosed with AD, rather than those who are at a higher risk for the disease but without a diagnosis. Determining whether the PLR is similarly impaired in subjects before an AD diagnosis is made and before cognitive symptoms of the disease begin, is an important step before using the PLR as a diagnostic tool. Specifically, identifying whether the PLR is impaired in specific at-risk groups, considering both genetic and non-genetic risk factors, is imperative. It is possible that the PLR may be impaired in association with some risk factors but not others, potentially indicating different pathways to neurodegeneration that could be distinguished using PLR. In this work, we review the most common genetic and lifestyle-based risk factors for AD and identify established relationships between these risk factors and the PLR. The evidence here shows that many AD risk factors, including traumatic brain injury, ocular and intracranial hypertension, alcohol consumption, depression, and diabetes, are directly related to changes in the PLR. Other risk factors currently lack sufficient literature to make any conclusions relating directly to the PLR but have shown links to impairments in the parasympathetic nervous system; further research should be conducted in these risk factors and their relation to the PLR.

A narrative review of retinal vascular parameters and the applications (Part II): Diagnosis in stroke

The retina, as an external extension of the diencephalon, can be directly, noninvasively observed by ocular fundus photography. Therefore, it offers a convenient and feasible mode to study nervous system diseases. Caliber, tortuosity, and fractal dimension, as three commonly used retinal vascular parameters, are not only the reflection of structural changes in the retinal microcirculation but also capture the branching pattern or density changes of the retinal microvascular network. Therefore, it contributes to better reflecting the subclinical pathological changes (e.g., lacunar stroke and small cerebral vascular disease) and predicting the risk of incident stroke and recurrent stroke.

Analysis of Plasma Metabolic Profile on Ganglion Cell-Inner Plexiform Layer Thickness With Mortality and Common Diseases

Importance

The neural retina is considered a unique window to systemic health, but its biological link with systemic health remains unknown.

Objective

To investigate the independent associations of retinal ganglion cell-inner plexiform layer thickness (GCIPLT) metabolic profiles with rates of mortality and morbidity of common diseases.

Design, Setting, and Participants

This cohort study evaluated UK Biobank participants enrolled between 2006 and 2010, and prospectively followed them up for multidisease diagnosis and mortality. Additional participants from the Guangzhou Diabetes Eye Study (GDES) underwent optical coherence tomography scanning and metabolomic profiling and were included for validation.

Main Outcomes and Measures

Systematic analysis of circulating plasma metabolites to identify GCIPLT metabolic profiles; prospective associations of these profiles with mortality and morbidity of 6 common diseases with their incremental discriminative value and clinical utility.

Results

Among 93 838 community-based participants (51 182 [54.5%] women), the mean (SD) age was 56.7 (8.1) years and mean (SD) follow-up was 12.3 (0.8) years. Of 249 metabolic metrics, 37 were independently associated with GCIPLT, including 8 positive and 29 negative associations, and most were associated with the rates of future mortality and common diseases. These metabolic profiles significantly improved the models for discriminating type 2 diabetes over clinical indicators (C statistic: 0.862; 95% CI, 0.852-0.872 vs clinical indicators only, 0.803; 95% CI, 0.792-0.814; P < .001), myocardial infarction (0.792; 95% CI, 0.775-0.808 vs 0.768; 95% CI, 0.751-0.786; P < .001), heart failure (0.803; 95% CI, 0.786-0.820 vs 0.790; 95% CI, 0.773-0.807; P < .001), stroke (0.739; 95% CI, 0.714-0.764 vs 0.719; 95% CI, 0.693-0.745; P < .001), all-cause mortality (0.747; 95% CI, 0.734-0.760 vs 0.724; 95% CI, 0.711-0.738; P < .001), and cardiovascular disease mortality (0.790; 95% CI, 0.767-0.812 vs 0.763; 95% CI, 0.739-0.788; P < .001). Additionally, the potential of GCIPLT metabolic profiles for risk stratification of cardiovascular diseases were further confirmed in the GDES cohort using a different metabolomic approach.

Conclusions and Relevance

In this prospective study of multinational participants, GCIPLT-associated metabolites demonstrated the potential to inform mortality and morbidity risks. Incorporating information on these profiles may facilitate individualized risk stratification for these health outcomes.

Vitamin K and the Visual System-A Narrative Review

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting, however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic-related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in mice. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with those with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is, therefore, the intention of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and provide some historical context for recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon in the hope of raising awareness and encouraging continued VK-related investigations in this important and highly specialized sensory system.

Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy

The retina, behind the transparent optics of the eye, is the only neural tissue whose physiology and pathology can be non-invasively probed by optical microscopy. The aberrations intrinsic to the mouse eye, however, prevent high-resolution investigation of retinal structure and function in vivo. Optimizing the design of a two-photon fluorescence microscope (2PFM) and sample preparation procedure, we found that adaptive optics (AO), by measuring and correcting ocular aberrations, is essential for resolving putative synaptic structures and achieving three-dimensional cellular resolution in the mouse retina in vivo. Applying AO-2PFM to longitudinal retinal imaging in transgenic models of retinal pathology, we characterized microvascular lesions with sub-capillary details in a proliferative vascular retinopathy model, and found Lidocaine to effectively suppress retinal ganglion cell hyperactivity in a retinal degeneration model. Tracking structural and functional changes at high-resolution longitudinally, AO-2PFM enables microscopic investigations of retinal pathology and pharmacology for disease diagnosis and treatment in vivo.

Diabetic vascular diseases: molecular mechanisms and therapeutic strategies

Vascular complications of diabetes pose a severe threat to human health. Prevention and treatment protocols based on a single vascular complication are no longer suitable for the long-term management of patients with diabetes. Diabetic panvascular disease (DPD) is a clinical syndrome in which vessels of various sizes, including macrovessels and microvessels in the cardiac, cerebral, renal, ophthalmic, and peripheral systems of patients with diabetes, develop atherosclerosis as a common pathology. Pathological manifestations of DPDs usually manifest macrovascular atherosclerosis, as well as microvascular endothelial function impairment, basement membrane thickening, and microthrombosis. Cardiac, cerebral, and peripheral microangiopathy coexist with microangiopathy, while renal and retinal are predominantly microangiopathic. The following associations exist between DPDs: numerous similar molecular mechanisms, and risk-predictive relationships between diseases. Aggressive glycemic control combined with early comprehensive vascular intervention is the key to prevention and treatment. In addition to the widely recommended metformin, glucagon-like peptide-1 agonist, and sodium-glucose cotransporter-2 inhibitors, for the latest molecular mechanisms, aldose reductase inhibitors, peroxisome proliferator-activated receptor-γ agonizts, glucokinases agonizts, mitochondrial energy modulators, etc. are under active development. DPDs are proposed for patients to obtain more systematic clinical care requires a comprehensive diabetes care center focusing on panvascular diseases. This would leverage the advantages of a cross-disciplinary approach to achieve better integration of the pathogenesis and therapeutic evidence. Such a strategy would confer more clinical benefits to patients and promote the comprehensive development of DPD as a discipline.

Childhood Social Isolation as a Predictor of Retinal Neuronal Thickness in Middle Age: A Lifecourse Birth Cohort Study

OBJECTIVE

We investigated whether childhood social isolation was associated with retinal neural layer changes in adulthood, and whether this association was independent of other childhood or adulthood risk factors, including adult social isolation.

METHODS

Participants were members of the Dunedin Multidisciplinary Health and Development Study, a longitudinal population-based birth cohort from Aotearoa New Zealand ( n = 1037), born 1972 to 1973 and followed until age 45 years, with 94% of the living cohort still participating. Social isolation was recorded prospectively at ages 5, 7, 9, and 11 years, from teacher and parent report. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer thicknesses were measured via optical coherence tomography at age 45 years.

RESULTS

Childhood social isolation was associated with thinner average RNFL ( B = -0.739, p = .02), nasal RNFL ( B = -1.118, p = .005), and inferior RNFL ( B = -1.524, p = .007), although only nasal RNFL remained significant after adjustment. These associations were not fully explained by other psychosocial or physical health risk factors in childhood or adulthood, nor were they mediated by adult loneliness or social support.

CONCLUSIONS

Childhood social isolation was an independent predictor of RNFL thickness in middle age. Highlighting prospective links between childhood psychosocial adversity and retinal neuronal measures will help to inform future research into the utility of retinal neuronal thickness as a biomarker for neurodegeneration.

Associations Between Thinner Retinal Neuronal Layers and Suboptimal Brain Structural Integrity in a Middle-Aged Cohort

Purpose

The retina has potential as a biomarker of brain health and Alzheimer's disease (AD) because it is the only part of the central nervous system which can be easily imaged and has advantages over brain imaging technologies. Few studies have compared retinal and brain measurements in a middle-aged sample. The objective of our study was to investigate whether retinal neuronal measurements were associated with structural brain measurements in a middle-aged population-based cohort.

Participants and Methods

Participants were members of the Dunedin Multidisciplinary Health and Development Study (n=1037; a longitudinal cohort followed from birth and at ages 3, 5, 7, 9, 11, 13, 15, 18, 21, 26, 32, 38, and most recently at age 45, when 94% of the living Study members participated). Retinal nerve fibre layer (RNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness were measured by optical coherence tomography (OCT). Brain age gap estimate (brainAGE), cortical surface area, cortical thickness, subcortical grey matter volumes, white matter hyperintensities, were measured by magnetic resonance imaging (MRI).

Results

Participants with both MRI and OCT data were included in the analysis (RNFL n=828, female n=413 [49.9%], male n=415 [50.1%]; GC-IPL n=825, female n=413 [50.1%], male n=412 [49.9%]). Thinner retinal neuronal layers were associated with older brain age, smaller cortical surface area, thinner average cortex, smaller subcortical grey matter volumes, and increased volume of white matter hyperintensities.

Conclusion

These findings provide evidence that the retinal neuronal layers reflect differences in midlife structural brain integrity consistent with increased risk for later AD, supporting the proposition that the retina may be an early biomarker of brain health.

Consumption of Coffee and Tea Is Associated with Macular Retinal Nerve Fiber Layer Thickness: Results from the UK Biobank

Coffee and tea drinking are thought to be protective for the development and progression of neurodegenerative disorders. This study aims to investigate associations between coffee and tea consumption with macular retinal nerve fiber layer (mRNFL) thickness, a marker of neurodegeneration. After quality control and eligibility screening, 35,557 out of 67,321 United Kingdom (UK) Biobank participants from six assessment centers were included in this cross-sectional study. In the touchscreen questionnaire, participants were asked how many cups of coffee and tea were consumed daily on average over the last year. Self-reported coffee and tea consumption were divided into four categories including 0 cup/day, 0.5-1 cups/day, 2-3 cups/day, and ≥4 cups/day, respectively. The mRNFL thickness was measured by the optical coherence tomography (Topcon 3D OCT-1000 Mark II) and automatically analyzed by segmentation algorithms. After adjusting for covariates, coffee consumption was significantly associated with an increased mRNFL thickness (β = 0.13, 95% CI = 0.01~0.25), which was more prominent in those who drank 2~3 cups coffee per day (β = 0.16, 95% CI = 0.03~0.30). The mRNFL thickness was also significantly increased in tea drinkers (β = 0.13, 95% CI = 0.01~0.26), especially for those who drank more than 4 cups of tea per day (β = 0.15, 95% CI = 0.01~0.29). The positive associations with mRNFL thickness, indicating that both coffee and tea consumptions had likely neuroprotective potentials. Causal links and underlying mechanisms for these associations should be explored further.

Oxidative stress in the brain and retina after traumatic injury

The brain and the retina share many physiological similarities, which allows the retina to serve as a model of CNS disease and disorder. In instances of trauma, the eye can even indicate damage to the brain via abnormalities observed such as irregularities in pupillary reflexes in suspected traumatic brain injury (TBI) patients. Elevation of reactive oxygen species (ROS) has been observed in neurodegenerative disorders and in both traumatic optic neuropathy (TON) and in TBI. In a healthy system, ROS play a pivotal role in cellular communication, but in neurodegenerative diseases and post-trauma instances, ROS elevation can exacerbate neurodegeneration in both the brain and the retina. Increased ROS can overwhelm the inherent antioxidant systems which are regulated via mitochondrial processes. The overabundance of ROS can lead to protein, DNA, and other forms of cellular damage which ultimately result in apoptosis. Even though elevated ROS have been observed to be a major cause in the neurodegeneration observed after TON and TBI, many antioxidants therapeutic strategies fail. In order to understand why these therapeutic approaches fail further research into the direct injury cascades must be conducted. Additional therapeutic approaches such as therapeutics capable of anti-inflammatory properties and suppression of other neurodegenerative processes may be needed for the treatment of TON, TBI, and neurodegenerative diseases.

The cross-sectional and longitudinal relationship of diabetic retinopathy to cognitive impairment: a systematic review and meta-analysis

OBJECTIVES

To establish a potential relationship between diabetic retinopathy (DR) and different stages of cognitive impairment METHODS: Literature searches were conducted on PubMed and EMBASE, with keywords "diabetic retinopathy" and "cognitive impairment". Inclusion criteria were original human studies, and English language. Quality of studies was assessed by the Newcastle-Ottawa Quality Assessment (NOSGEN). The register number of this study on the International Prospective Register of Systematic Reviews (PROSPERO) is CRD42021236747. The main outcome measures were odds ratios (OR) and risk ratios (RR) for cross-sectional and longitudinal studies, respectively. Meta-regression was performed to evaluate the effects of potential moderator variables, including, age, onset age of diabetes mellitus (DM), duration of DM, and HbA1c.

RESULTS

Twenty-five studies (17 cross-sectional and 8 longitudinal studies) with a total of 1,963,914 subjects, were included. Among the cross-sectional studies, the pooled ORs of any cognitive impairment, early stage of cognitive impairment and dementia in subjects with DR (95% confidence interval) were 1.48 (1.08-2.02), 1.59 (1.01-2.51), and 1.13 (0.86-1.50), respectively. Among the longitudinal studies, the pooled RRs of any cognitive impairment, early stage of cognitive impairment, and dementia in subjects with DR (95% confidence interval) were 1.35 (1.12-1.65), 1.50 (1.06-2.12), and 1.31 (1.03-1.66), respectively. Meta-regression showed age, onset age of DM, duration of DM, and glycated hemoglobin (HbA1c) were not statistically associated with the outcomes.

CONCLUSIONS

The presence of DR in DM patients indicates both higher odds of prevalent cognitive impairment and escalated risks of developing cognitive impairment in the future.

Association Between Retinal Nerve Fiber Layer Thickness and Incident Dementia in the European Prospective Investigation into Cancer in Norfolk Cohort

BACKGROUND

Retinal nerve fiber layer (RNFL) thickness may reflect cerebral status.

OBJECTIVE

This study assessed the relationship between RNFL thickness and incident all-cause dementia in the European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) Eye Study.

METHODS

Glaucoma detection with variable corneal compensation (GDx-VCC) and Heidelberg Retinal Tomograph II (HRT II) derived global mean RNFL thickness from dementia-free participants at baseline within the EPIC-Norfolk Eye Study were analyzed. Incident dementia was identified through linkage to electronic medical records. Cox proportional hazard mixed-effects regression models adjusted for key confounders were used to examine the associations between RNFL thickness and incident dementia in four separate models.

RESULTS

6,239 participants were included with 322 cases of incident dementia and mean age of 67.5-years old, with 49.7% women (median follow-up 13.2-years, interquartile range (11.7 to 14.6 years). Greater RNFL thickness (GDx-VCC) was not significantly associated with a lower risk of incident dementia in the full adjusted model [HR per quartile increase 0.95; 95% CI 0.82-1.10]. Similarly, RNFL thickness assessed with HRT II was also not associated with incident dementia in any model (full adjusted model; HR per quartile increase: 1.06; [95% CI 0.93-1.19]. Gender did not modify any associations under study.

CONCLUSION

GDx-VCC and HRT II derived RNFL thickness are unlikely to be useful predictors of incident dementia. Higher resolution optical imaging technologies may clarify whether there are useful relationships between neuro-retinal morphology and brain measures.

Cognitive Performance and Diabetic Retinopathy: What Your Eyes Can Reveal About Your Brain

BACKGROUND

Diabetic retinopathy (DR) is a chronic diabetes complication. People with Type 2 Diabetes Mellitus (T2DM) have two times the risk for dementia, suggesting it is a new chronic diabetes complication.

OBJECTIVE

Evaluate the association of DR with cognitive performance in a T2DM population.

METHODS

Cross-sectional study with 400 T2DM adults from whom socio-demographic, clinical, laboratory data were collected, and screening test for depression symptoms (Patient Health Questionaire- 9 (PHQ-9)), Mini-Mental State Examination (MMSE), Semantic Verbal Fluency Test, Trail Making Test A and B, Word Memory test were performed. All cognitive test scores were converted into Global Cognition z-Score (GCS(z)). The association between GCS(z) < 0 with DR was performed using a multivariate binary logistic regression model adjusted for age ≥ 65 years, school years ≤ 6 years, DM duration ≥ 10 years, depression symptoms score > 9 at PHQ-9, arterial hypertension, physical activity, diabetic retinopathy, macular edema, and cardiovascular disease.

RESULTS

After exclusions, the 251 eligible patients were 56.6% female, with a mean age of 61.1 (±9.8) years, DM duration of 12.6 (±8.9) years, and 7.6 (±4.2) years of school education. DR prevalence was 46.5%. Multivariate Logistic Regression Model showed an association between DR and GCS(z) < 0, with odds ratio (CI95%) of 2.50 (1.18-5.34), adjusted for age, low education level, arterial hypertension and depression symptoms (OD and CI95% respectively: 5.46(2.42-12.34); 12.19 (5.62-26.46); 2.55 (0.88-7.39); 3.53 (1.55-8.07)).

CONCLUSION

In this T2DM population, having DR increased the chance for worse cognitive performance even when adjusted for age, low education level, presence of arterial hypertension, and depression symptoms.

Retinal parameters, cortical cerebral microinfarcts, and their interaction with cognitive impairment

BACKGROUND

Quantitative changes in retinal vessels and thinning of optic nerves have been associated with subclinical (atherosclerosis, inflammation) and clinical age-related brain pathologies (stroke and neurodegeneration). However, data on the association between both retinal vascular and neuronal parameters with cortical cerebral microinfarcts (CMIs) and how these factors jointly influence cognition are lacking.

AIM

We investigated the association of retinal vascular and neuronal changes with CMIs on 3 T MRI and explored their interaction with cognitive impairment in a memory-clinic population.

METHODS

A total of 538 participants were included. Retinal vascular parameters (caliber, tortuosity, and fractal dimension) were measured from retinal fundus photographs using a semi-automated computer-assisted program. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GC-IPL) thicknesses were obtained from optical coherence tomography. Cortical CMIs were defined as hypointense on T1-weighted MRI, <5 mm in diameter and restricted to the cortex. Cognition was assessed using Clinical Dementia Rating Sum-of-Boxes (CDR-SoB) score and detailed neuropsychological test. Multivariable regression analysis was conducted adjusting for age, sex, hypertension, hyperlipidemia, diabetes mellitus, smoking, diagnosis, white matter hyperintensities volume, lacunes, and cerebral microbleeds.

RESULTS

Larger venular caliber (Rate ratios (RR): 1.15, 95% CI: 1.01-1.38, p = 0.014), increased venular fractal dimension (RR: 1.58, 95% CI: 1.31-1.91, p ⩽ 0.001), increased venular tortuosity (RR: 1.54, 95% CI: 1.35-1.75, p ⩽ 0.001), and thinner GC-IPL (RR: 1.24, 95% CI: 1.13-1.36, p ⩽ 0.001) were associated with CMI counts. Among individuals in highest tertile of retinal parameters, a significant interaction was observed between venular tortuosity (RR: 1.12, 95% CI: 1.02-1.22, p-interaction = 0.014) and GC-IPL (RR: 1.05, 95% CI: 1.01-1.11, p-interaction < 0.001) with CMIs on CDR-SoB.

CONCLUSION

Retinal vascular and neuronal parameters are associated with cortical CMIs, and persons with both pathologies are likely to have cognitive impairment. Further studies may be warranted to evaluate the clinical utility of retinal parameters and CMI in risk prediction for cognitive dysfunction.

Deep Reinforcement Learning-Based Retinal Imaging in Alzheimer's Disease: Potential and Perspectives

Alzheimer's disease (AD) remains a global health challenge in the 21st century due to its increasing prevalence as the major cause of dementia. State-of-the-art artificial intelligence (AI)-based tests could potentially improve population-based strategies to detect and manage AD. Current retinal imaging demonstrates immense potential as a non-invasive screening measure for AD, by studying qualitative and quantitative changes in the neuronal and vascular structures of the retina that are often associated with degenerative changes in the brain. On the other hand, the tremendous success of AI, especially deep learning, in recent years has encouraged its incorporation with retinal imaging for predicting systemic diseases. Further development in deep reinforcement learning (DRL), defined as a subfield of machine learning that combines deep learning and reinforcement learning, also prompts the question of how it can work hand in hand with retinal imaging as a viable tool for automated prediction of AD. This review aims to discuss potential applications of DRL in using retinal imaging to study AD, and their synergistic application to unlock other possibilities, such as AD detection and prediction of AD progression. Challenges and future directions, such as the use of inverse DRL in defining reward function, lack of standardization in retinal imaging, and data availability, will also be addressed to bridge gaps for its transition into clinical use.

Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis

PURPOSE

Artificial intelligence (AI) can detect diabetic macular edema (DME) from optical coherence tomography (OCT) images. We aimed to evaluate the performance of deep learning neural networks in DME detection.

METHODS

Embase, Pubmed, the Cochrane Library, and IEEE Xplore were searched up to August 14, 2021. We included studies using deep learning algorithms to detect DME from OCT images. Two reviewers extracted the data independently, and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was applied to assess the risk of bias. The study is reported according to Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA).

RESULTS

Ninteen studies involving 41005 subjects were included. The pooled sensitivity and specificity were 96.0% (95% confidence interval (CI): 93.9% to 97.3%) and 99.3% (95% CI: 98.2% to 99.7%), respectively. Subgroup analyses found that data set selection, sample size of training set and the choice of OCT devices contributed to the heterogeneity (all P < 0.05). While there was no association between the diagnostic accuracy and transfer learning adoption or image management (all P > 0.05).

CONCLUSIONS

Deep learning methods, particularly the convolutional neural networks (CNNs) could effectively detect clinically significant DME, which can provide referral suggestions to the patients.

Assessment of early and long-COVID related retinal neurodegeneration with optical coherence tomography

PURPOSE

The aim of this study is to investigate short-term and long-term effects of coronovirus 19 disease (COVID-19) at inner and outer retinal layers of patients recovered from COVID-19 with Spectral Domain Optical Coherence Tomography (SD-OCT) and compare these to healthy subjects.

METHODS

Twenty-seven patients recovered from COVID-19, and age- and gender-matched 27 healthy controls were included in this study. Macular and peripapillary retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer (GCIPL), inner nuclear layer (INL), outer plexiform layer (OPL) and outer nuclear layer (ONL) were analyzed with SD-OCT 1 month (V₁ visit) and 12 months (V₂ visit) after negative result of reverse transcriptase-polymerase chain reaction test.

RESULTS

Macular RNFL thickness in outer ring was thinner at V₁ and V₂ visits than healthy control (p = 0.049 and p = 0.005). Central and inferonasal quadrants of peripapillary RNFL thicknesses were reduced at V₁ and V₂ visits compared to controls (p = 0.001 and p = 0.024 for V₁ visit; p = 0.001 and p = 0.006 for V₂ visit). Thinning in ONL thickness in inner ring was observed at V₁ and V₂ visits than healthy subjects (p = 0.006 and p = 0.001).

CONCLUSION

Subclinical localized changes in macular and peripapillary RNFL and outer nuclear layer were demonstrated in early and 12-months follow-up after COVID-19 recovery.

Development and validation of a deep learning algorithm based on fundus photographs for estimating the CAIDE dementia risk score

BACKGROUND

the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk score is a recognised tool for dementia risk stratification. However, its application is limited due to the requirements for multidimensional information and fasting blood draw. Consequently, an effective and non-invasive tool for screening individuals with high dementia risk in large population-based settings is urgently needed.

METHODS

a deep learning algorithm based on fundus photographs for estimating the CAIDE dementia risk score was developed and internally validated by a medical check-up dataset included 271,864 participants in 19 province-level administrative regions of China, and externally validated based on an independent dataset included 20,690 check-up participants in Beijing. The performance for identifying individuals with high dementia risk (CAIDE dementia risk score ≥ 10 points) was evaluated by area under the receiver operating curve (AUC) with 95% confidence interval (CI).

RESULTS

the algorithm achieved an AUC of 0.944 (95% CI: 0.939-0.950) in the internal validation group and 0.926 (95% CI: 0.913-0.939) in the external group, respectively. Besides, the estimated CAIDE dementia risk score derived from the algorithm was significantly associated with both comprehensive cognitive function and specific cognitive domains.

CONCLUSIONS

this algorithm trained via fundus photographs could well identify individuals with high dementia risk in a population setting. Therefore, it has the potential to be utilised as a non-invasive and more expedient method for dementia risk stratification. It might also be adopted in dementia clinical trials, incorporated as inclusion criteria to efficiently select eligible participants.

Advanced Optical Wavefront Technologies to Improve Patient Quality of Vision and Meet Clinical Requests

Adaptive optics (AO) is employed for the continuous measurement and correction of ocular aberrations. Human eye refractive errors (lower-order aberrations such as myopia and astigmatism) are corrected with contact lenses and excimer laser surgery. Under twilight vision conditions, when the pupil of the human eye dilates to 5-7 mm in diameter, higher-order aberrations affect the visual acuity. The combined use of wavefront (WF) technology and AO systems allows the pre-operative evaluation of refractive surgical procedures to compensate for the higher-order optical aberrations of the human eye, guiding the surgeon in choosing the procedure parameters. Here, we report a brief history of AO, starting from the description of the Shack-Hartmann method, which allowed the first in vivo measurement of the eye's wave aberration, the wavefront sensing technologies (WSTs), and their principles. Then, the limitations of the ocular wavefront ascribed to the IOL polymeric materials and design, as well as future perspectives on improving patient vision quality and meeting clinical requests, are described.

Retinal age gap as a predictive biomarker of stroke risk

BACKGROUND

The aim of this study is to investigate the association of retinal age gap with the risk of incident stroke and its predictive value for incident stroke.

METHODS

A total of 80,169 fundus images from 46,969 participants in the UK Biobank cohort met the image quality standard. A deep learning model was constructed based on 19,200 fundus images of 11,052 disease-free participants at baseline for age prediction. Retinal age gap (retinal age predicted based on the fundus image minus chronological age) was generated for the remaining 35,917 participants. Stroke events were determined by data linkage to hospital records on admissions and diagnoses, and national death registers, whichever occurred earliest. Cox proportional hazards regression models were used to estimate the effect of retinal age gap on risk of stroke. Logistic regression models were used to estimate the predictive value of retinal age and well-established risk factors in 10-year stroke risk.

RESULTS

A total of 35,304 participants without history of stroke at baseline were included. During a median follow-up of 5.83 years, 282 (0.80%) participants had stroke events. In the fully adjusted model, each one-year increase in the retinal age gap was associated with a 4% increase in the risk of stroke (hazard ratio [HR] = 1.04, 95% confidence interval [CI]: 1.00-1.08, P = 0.029). Compared to participants with retinal age gap in the first quintile, participants with retinal age gap in the fifth quintile had significantly higher risks of stroke events (HR = 2.37, 95% CI: 1.37-4.10, P = 0.002). The predictive capability of retinal age alone was comparable to the well-established risk factor-based model (AUC=0.676 vs AUC=0.661, p=0.511).

CONCLUSIONS

We found that retinal age gap was significantly associated with incident stroke, implying the potential of retinal age gap as a predictive biomarker of stroke risk.

Automated Systems for Calculating Arteriovenous Ratio in Retinographies: A Scoping Review

There is evidence of an association between hypertension and retinal arteriolar narrowing. Manual measurement of retinal vessels comes with additional variability, which can be eliminated using automated software. This scoping review aims to summarize research on automated retinal vessel analysis systems. Searches were performed on Medline, Scopus, and Cochrane to find studies examining automated systems for the diagnosis of retinal vascular alterations caused by hypertension using the following keywords: diagnosis; diagnostic screening programs; image processing, computer-assisted; artificial intelligence; electronic data processing; hypertensive retinopathy; hypertension; retinal vessels; arteriovenous ratio and retinal image analysis. The searches generated 433 articles. Of these, 25 articles published from 2010 to 2022 were included in the review. The retinographies analyzed were extracted from international databases and real scenarios. Automated systems to detect alterations in the retinal vasculature are being introduced into clinical practice for diagnosis in ophthalmology and other medical specialties due to the association of such changes with various diseases. These systems make the classification of hypertensive retinopathy and cardiovascular risk more reliable. They also make it possible for diagnosis to be performed in primary care, thus optimizing ophthalmological visits.

Characterization of the Retinal Microvasculature and FAZ Changes in Ischemic Stroke and Its Different Types

Purpose

This study aimed to assess morphological changes in the retinal microvasculature and foveal avascular zone (FAZ) in patients with ischemic stroke and its different subtypes.

Methods

Thirty-three patients with ischemic stroke (14 with nonlacunar infarction and 19 with lacunar infarction) and 27 control participants were enrolled in this study. Based on optical coherence tomography angiography (OCTA), three vascular parameters, including vascular area density, vascular fractal dimension (VFD), and vascular orientation distribution (VOD), and four FAZ-related parameters, including FAZ area, FAZ axis ratio (FAR), FAZ circularity (FC), and FAZ roundness, in the superficial capillary plexus (SCP) and deep capillary plexus (DCP) were extracted and analyzed.

Results

Logistic regression results showed that worse best-corrected visual acuity (odds ratio [OR], 0.21), higher FAR (OR, 2.77) and lower FC (OR, 0.36) of the DCP were associated with ischemic stroke. Furthermore, lower VOD of the SCP was significantly associated with lacunar infarction compared with nonlacunar infarction.

Conclusions

Our study shows that the FAR and FC of the DCP may be potential biomarkers of ischemic stroke. Moreover, we demonstrated that OCT showed specific damage patterns in retinal microvascular and macular morphology in different subtypes of ischemic stroke.

Translational Relevance

This work lays the foundation for the pathophysiological characteristics of cerebrovascular diseases assisted by retinal imaging and artificial intelligence.