Identification of Retinal Biomarkers in Alzheimer's Disease Using Optical Coherence Tomography: Recent Insights, Challenges, and Opportunities

Optical coherence tomography as a potential surrogate marker of dopaminergic modulation across the life span

The retina has been considered a "window to the brain" and shares similar innervation by the dopaminergic system with the cortex in terms of an unequal distribution of D1 and D2 receptors. Here, we provide a comprehensive overview that Optical Coherence Tomography (OCT), a non-invasive imaging technique, which provides an "in vivo" representation of the retina, shows promise to be used as a surrogate marker of dopaminergic neuromodulation in cognition. Overall, most evidence supports reduced retinal thickness in individuals with dopaminergic dysregulation (e.g., patients with Parkinson's Disease, non-demented older adults) and with poor cognitive functioning. By using the theoretical framework of metacontrol, we derive hypotheses that retinal thinning associated to decreased dopamine (DA) levels affecting D1 families, might lead to a decrease in the signal-to-noise ratio (SNR) affecting cognitive persistence (depending on D1-modulated DA activity) but not cognitive flexibility (depending on D2-modulated DA activity). We argue that the use of OCT parameters might not only be an insightful for cognitive neuroscience research, but also a potentially effective tool for individualized medicine with a focus on cognition. As our society progressively ages in the forthcoming years and decades, the preservation of cognitive abilities and promoting healthy aging will hold of crucial significance. OCT has the potential to function as a swift, non-invasive, and economical method for promptly recognizing individuals with a heightened vulnerability to cognitive deterioration throughout all stages of life.

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).

Non-invasive in vivo imaging of brain and retinal microglia in neurodegenerative diseases

Microglia play crucial roles in immune responses and contribute to fundamental biological processes within the central nervous system (CNS). In neurodegenerative diseases, microglia undergo functional changes and can have both protective and pathogenic roles. Microglia in the retina, as an extension of the CNS, have also been shown to be affected in many neurological diseases. While our understanding of how microglia contribute to pathological conditions is incomplete, non-invasive in vivo imaging of brain and retinal microglia in living subjects could provide valuable insights into their role in the neurodegenerative diseases and open new avenues for diagnostic biomarkers. This mini-review provides an overview of the current brain and retinal imaging tools for studying microglia in vivo. We focus on microglia targets, the advantages and limitations of in vivo microglia imaging approaches, and applications for evaluating the pathogenesis of neurological conditions, such as Alzheimer's disease and multiple sclerosis.

Structural and Functional Retinal Changes in Patients with Mild Cognitive Impairment with and without Diabetes

Our objective is to analyze retinal changes using optical coherence tomography angiography (OCT-A) in patients with mild cognitive impairment (MCI) to characterize structural and vascular alterations. This cross-sectional study involved 117 eyes: 39 eyes from patients with MCI plus diabetes (DM-MCI), 39 eyes from patients with MCI but no diabetes (MCI); and 39 healthy control eyes (C). All patients underwent a visual acuity measurement, a structural OCT, an OCT-A, and a neuropsychological examination. Our study showed a thinning of retinal nerve fiber layer thickness (RNFL) and a decrease in macular thickness when comparing the MCI-DM group to the C group (p = 0.008 and p = 0.016, respectively). In addition, an increase in arteriolar thickness (p = 0.016), a reduction in superficial capillary plexus density (p = 0.002), and a decrease in ganglion cell thickness (p = 0.027) were found when comparing the MCI-DM group with the MCI group. Diabetes may exacerbate retinal vascular changes when combined with mild cognitive impairment.

Potential Ocular Biomarkers for Early Detection of Alzheimer's Disease and Their Roles in Artificial Intelligence Studies

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is believed to be essential to disease management because it enables physicians to initiate treatment in patients with early-stage AD (early AD), with the possibility of stopping the disease or slowing disease progression, preserving function and ultimately reducing disease burden. The purpose of this study was to review prior research on the use of eye biomarkers and artificial intelligence (AI) for detecting AD and early AD. The PubMed database was searched to identify studies for review. Ocular biomarkers in AD research and AI research on AD were reviewed and summarized. According to numerous studies, there is a high likelihood that ocular biomarkers can be used to detect early AD: tears, corneal nerves, retina, visual function and, in particular, eye movement tracking have been identified as ocular biomarkers with the potential to detect early AD. However, there is currently no ocular biomarker that can be used to definitely detect early AD. A few studies that used AI with ocular biomarkers to detect AD reported promising results, demonstrating that using AI with ocular biomarkers through multimodal imaging could improve the accuracy of identifying AD patients. This strategy may become a screening tool for detecting early AD in older patients prior to the onset of AD symptoms.

Early visual alterations in individuals at-risk of Alzheimer's disease: a multidisciplinary approach

BACKGROUND

The earliest pathological features of Alzheimer's disease (AD) appear decades before the clinical symptoms. The pathology affects the brain and the eye, leading to retinal structural changes and functional visual alterations. Healthy individuals at high risk of developing AD present alterations in these ophthalmological measures, as well as in resting-state electrophysiological activity. However, it is unknown whether the ophthalmological alterations are related to the visual-related electrophysiological activity. Elucidating this relationship is paramount to understand the mechanisms underlying the early deterioration of the system and an important step in assessing the suitability of these measures as early biomarkers of disease.

METHODS

In total, 144 healthy subjects: 105 with family history of AD and 39 without, underwent ophthalmologic analysis, magnetoencephalography recording, and genotyping. A subdivision was made to compare groups with less demographic and more risk differences: 28 high-risk subjects (relatives/APOEɛ4 +) and 16 low-risk (non-relatives/APOEɛ4 -). Differences in visual acuity, contrast sensitivity, and macular thickness were evaluated. Correlations between each variable and visual-related electrophysiological measures (M100 latency and time-frequency power) were calculated for each group.

RESULTS

High-risk groups showed increased visual acuity. Visual acuity was also related to a lower M100 latency and a greater power time-frequency cluster in the high-risk group. Low-risk groups did not show this relationship. High-risk groups presented trends towards a greater contrast sensitivity that did not remain significant after correction for multiple comparisons. The highest-risk group showed trends towards the thinning of the inner plexiform and inner nuclear layers that did not remain significant after correction. The correlation between contrast sensitivity and macular thickness, and the electrophysiological measures were not significant after correction. The difference between the high- and low- risk groups correlations was no significant.

CONCLUSIONS

To our knowledge, this paper is the first of its kind, assessing the relationship between ophthalmological and electrophysiological measures in healthy subjects at distinct levels of risk of AD. The results are novel and unexpected, showing an increase in visual acuity among high-risk subjects, who also exhibit a relationship between this measure and visual-related electrophysiological activity. These results have not been previously explored and could constitute a useful object of research as biomarkers for early detection and the evaluation of potential interventions' effectiveness.

Evaluation of retinal and choroidal parameters as neurodegeneration biomarkers in patients with post-covid-19 syndrome

BACKGROUND

To investigate the neurodegenerative effects of post-COVID-19 syndrome.

METHODS

This comparative, cross-sectional study included patients who had post-COVID-19 prolonged neurologic symptoms. The control group was selected from volunteer participants with similar age, sex, and spherical equivalent characteristics. After detailed ophthalmic examinations, spectral-domain optic coherence tomography (SD-OCT) analysis of the macula and peripapillary retinal nerve fiber layer (m-RNFL, p-RNFL respectively) were obtained. We also evaluated the choroidal parameters with the ImageJ software. Post-COVID-19 symptoms and disease severity of the patients were also questioned.

RESULTS

Thirty-four eyes of 20 patients, and 39 eyes of 23 healthy individuals were included in the study. Thinning was found in the inner superior quadrant of mRNFL (p < 0.05). More prominent and common thinning of retinal layers was observed in the ganglion cell layer (GCL) and inner plexiform layer (IPL) segments in the patient group. There was no difference between the groups in the calculated choroidal parameters (p > 0.05). In the regression models created, lung involvement was the most prominent parameter associated with thinning of the OCT layers. The other factors were male sex, and the presence of loss of taste and smell also led to deterioration in some parameters.

CONCLUSIONS

We detected an overall thinning of the GCL and IPL layers with no significant change in CMT, pRNFL, and CVI in the post-COVID-19 period, indicating the direct or indirect effect of SARS-CoV-2 on these layers, rather than a long-term neurodegenerative effect.

A systematic survey of advances in retinal imaging modalities for Alzheimer's disease diagnosis

Recent advances in retinal imaging pathophysiology have shown a new function for biomarkers in Alzheimer's disease diagnosis and prognosis. The significant improvements in Optical coherence tomography (OCT) retinal imaging have led to significant clinical translation, particularly in Alzheimer's disease detection. This systematic review will provide a comprehensive overview of retinal imaging in clinical applications, with a special focus on biomarker analysis for use in Alzheimer's disease detection. Articles on OCT retinal imaging in Alzheimer's disease diagnosis were identified in PubMed, Google Scholar, IEEE Xplore, and Research Gate databases until March 2021. Those studies using simultaneous retinal imaging acquisition were chosen, while those using sequential techniques were rejected. "Alzheimer's disease" and "Dementia" were searched alone and in combination with "OCT" and "retinal imaging". Approximately 1000 publications were searched, and after deleting duplicate articles, 145 relevant studies focused on the diagnosis of Alzheimer's disease utilizing retinal imaging were chosen for study. OCT has recently been demonstrated to be a valuable technique in clinical practice as according to this survey, 57% of the researchers employed optical coherence tomography, 19% used ocular fundus imaging, 13% used scanning laser ophthalmoscopy, and 11% have used multimodal imaging to diagnose Alzheimer disease. Retinal imaging has become an important diagnostic technique for Alzheimer's disease. Given the scarcity of available literature, it is clear that future prospective trials involving larger and more homogeneous groups are necessary, and the work can be expanded by evaluating its significance utilizing a machine-learning platform rather than simply using statistical methodologies.

Automatic Segmentation of the Optic Nerve Head Region in Optical Coherence Tomography: A Methodological Review

The optic nerve head (ONH) represents the intraocular section of the optic nerve, which is prone to damage by intraocular pressure (IOP). The advent of optical coherence tomography (OCT) has enabled the evaluation of novel ONH parameters, namely the depth and curvature of the lamina cribrosa (LC). Together with the Bruch's membrane minimum-rim-width (BMO-MRW), these seem to be promising ONH parameters for diagnosis and monitoring of retinal diseases such as glaucoma. Nonetheless, these OCT derived biomarkers are mostly extracted through manual segmentation, which is time-consuming and prone to bias, thus limiting their usability in clinical practice. The automatic segmentation of ONH in OCT scans could further improve the current clinical management of glaucoma and other diseases. This review summarizes the current state-of-the-art in automatic segmentation of the ONH in OCT. PubMed and Scopus were used to perform a systematic review. Additional works from other databases (IEEE, Google Scholar and ARVO IOVS) were also included, resulting in a total of 29 reviewed studies. For each algorithm, the methods, the size and type of dataset used for validation, and the respective results were carefully analysed. The results show a lack of consensus regarding the definition of segmented regions, extracted parameters and validation approaches, highlighting the importance and need of standardized methodologies for ONH segmentation. Only with a concrete set of guidelines, these automatic segmentation algorithms will build trust in data-driven segmentation models and be able to enter clinical practice.

Schizophrenia in Translation: Why the Eye?

Schizophrenia is increasingly recognized as a systemic disease, characterized by dysregulation in multiple physiological systems (eg, neural, cardiovascular, endocrine). Many of these changes are observed as early as the first psychotic episode, and in people at high risk for the disorder. Expanding the search for biomarkers of schizophrenia beyond genes, blood, and brain may allow for inexpensive, noninvasive, and objective markers of diagnosis, phenotype, treatment response, and prognosis. Several anatomic and physiologic aspects of the eye have shown promise as biomarkers of brain health in a range of neurological disorders, and of heart, kidney, endocrine, and other impairments in other medical conditions. In schizophrenia, thinning and volume loss in retinal neural layers have been observed, and are associated with illness progression, brain volume loss, and cognitive impairment. Retinal microvascular changes have also been observed. Abnormal pupil responses and corneal nerve disintegration are related to aspects of brain function and structure in schizophrenia. In addition, studying the eye can inform about emerging cardiovascular, neuroinflammatory, and metabolic diseases in people with early psychosis, and about the causes of several of the visual changes observed in the disorder. Application of the methods of oculomics, or eye-based biomarkers of non-ophthalmological pathology, to the treatment and study of schizophrenia has the potential to provide tools for patient monitoring and data-driven prediction, as well as for clarifying pathophysiology and course of illness. Given their demonstrated utility in neuropsychiatry, we recommend greater adoption of these tools for schizophrenia research and patient care.

Intraretinal Layer Segmentation Using Cascaded Compressed U-Nets

Reliable biomarkers quantifying neurodegeneration and neuroinflammation in central nervous system disorders such as Multiple Sclerosis, Alzheimer's dementia or Parkinson's disease are an unmet clinical need. Intraretinal layer thicknesses on macular optical coherence tomography (OCT) images are promising noninvasive biomarkers querying neuroretinal structures with near cellular resolution. However, changes are typically subtle, while tissue gradients can be weak, making intraretinal segmentation a challenging task. A robust and efficient method that requires no or minimal manual correction is an unmet need to foster reliable and reproducible research as well as clinical application. Here, we propose and validate a cascaded two-stage network for intraretinal layer segmentation, with both networks being compressed versions of U-Net (CCU-INSEG). The first network is responsible for retinal tissue segmentation from OCT B-scans. The second network segments eight intraretinal layers with high fidelity. At the post-processing stage, we introduce Laplacian-based outlier detection with layer surface hole filling by adaptive non-linear interpolation. Additionally, we propose a weighted version of focal loss to minimize the foreground-background pixel imbalance in the training data. We train our method using 17,458 B-scans from patients with autoimmune optic neuropathies, i.e., multiple sclerosis, and healthy controls. Voxel-wise comparison against manual segmentation produces a mean absolute error of 2.3 μm, outperforming current state-of-the-art methods on the same data set. Voxel-wise comparison against external glaucoma data leads to a mean absolute error of 2.6 μm when using the same gold standard segmentation approach, and 3.7 μm mean absolute error in an externally segmented data set. In scans from patients with severe optic atrophy, 3.5% of B-scan segmentation results were rejected by an experienced grader, whereas this was the case in 41.4% of B-scans segmented with a graph-based reference method. The validation results suggest that the proposed method can robustly segment macular scans from eyes with even severe neuroretinal changes.

Abnormalities of Retinal Structure and Microvasculature are Associated with Cerebral White Matter Hyperintensities

PURPOSE

While retinal microvasculature represents cerebral small vessels, the retinal nerve fiber layer is the extended white matter of the brain. We aimed to investigate the correlation between changes in retina and white matter hyperintensities (WMH).

METHODS

64 candidates with WMH received the optical coherence tomography angiography (OCTA) examination. WMH were divided into mild or moderate/severe groups according to the Fazekas score. After imaging superficial capillary plexus (SCP) and deep capillary plexus (DCP), we revealed the microvascular density parameters (vascular perfusion density (VPD), vascular length density (VLD), and fovea avascular zone area (FAZ-A)) and morphological parameters (vessel diameter index (VDI), fractal dimension (FD), and vessel tortuosity (VT)). The software algorithm measured the thickness of the peripapillary retina nerve fiber layer (PRNFL).

RESULTS

32 were classified as having mild WMH and 32 were moderate/severe. The Median (interquartile range) ages of the two groups were 58 (54-64) and 61 (57-67) years, respectively. A decrease of FD, VPD and VLD in either SCP or DCP appeared with an increased risk of moderate/severe WMH. Although changes of capillary plexus were not associated with PWMH, decreased FD, VPD, VLD and FAZ-A in either SCP or DCP was associated with an increased risk of moderate/severe DWMH. Participants with moderate/severe WMH demonstrated reduced PRNFL thickness, particularly in the DWMH, compared with mild WMH.

CONCLUSIONS

Abnormalities of retinal microvascular density, morphological parameters, and PRNFL thickness are correlated with the incidence of moderate/severe WMH, particularly the DWMH, suggesting that arteriosclerosis and hypoperfusion are the causes of DWMH.

Retinal imaging biomarkers of neurodegenerative diseases

The timely detection of neurodegenerative diseases is central to improving clinical care as well as enabling the development and deployment of disease-modifying therapies. Retinal imaging is emerging as a method to detect features of a number of neurodegenerative diseases, given the anatomical and functional similarities between the retina and the brain. This review provides an overview of the current status of retinal imaging biomarkers of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Lewy body dementia, frontotemporal dementia, Huntington's disease and multiple sclerosis. Whilst research findings are promising, efforts to harmonise study designs and imaging methods will be important in translating these findings into clinical care. Doing so may mean that eye care providers will play important roles in the detection of a variety of neurodegenerative diseases in future.

Optic Nerve Head Optical Coherence Tomography Angiography Findings after Coronavirus Disease

Purpose

To quantify the microvasculature density of the optic nerve head (ONH) using optical coherence tomography angiography (OCTA) analysis in patients recovered from Coronavirus Disease 2019 (COVID-19).

Methods

In a comparative cross-sectional, observational study, patients recovered from COVID-19 whose initial diagnosis was confirmed by a rRT-PCR of a nasopharyngeal sample were included in this study. OCTA of ONH was performed in included patients and normal controls. Vascular density (VD) of the all vessels (AV) and small vessels (SV) inside the disc and radial peripapillary capillary (RPC) network density were measured in COVID-19 recovered patients and compared with similar parameters in an age-matched group of normal controls.

Results

Twenty-five COVID-19 patients and twenty-two age-matched normal controls were enrolled in the study and one eye per participant was evaluated. The mean whole image SV VD in the COVID-19 group (49.31 ± 1.93) was not statistically significantly different from that in the control group (49.94 ±. 2.22; P = 0.308). A decrease in RPC VD was found in all AV and SV VD measured, which became statistically significant in whole peripapillary SV VD, peripapillary inferior nasal SV VD, peripapillary inferior temporal SV VD, peripapillary superior nasal SV VD, and grid-based AV VD inferior sector (P< 0.05). Inside disc SV VD in the COVID-19 group (49.43 ± 4.96) was higher than in the control group (45.46 ± 6.22) which was statistically significant (P = 0.021).

Conclusion

Unremarkable decrease was found in ONH microvasculature in patients who had recovered from COVID-19. These patients may be at risk of ONH vascular complications. Increase in inner disc SV VD may be an indicator of ONH hyperemia and edema.

Evaluation of optical coherence tomography findings in adolescents with genetic generalized epilepsy

OBJECTIVE

To evaluate retinal nerve fiber layer (RNFL) thickness, central macular thickness (CMT), and subfoveal choroid thickness (CT) by using optical coherence tomography (OCT) in adolescents with newly diagnosed epilepsy and patients who had been using Na valproate (VPA) for at least 1 year.

METHODS

We examined 60 patients with genetic generalized epilepsy (GGE) aged 8-17 years. Thirty patients with newly diagnosed GGE who were evaluated before the beginning of the therapy and another 30 patients who were chosen from among adolescents with epilepsy using VPA for at least 1 year were included in the study.

RESULTS

Nasal quadrant RNFL thickness and CMT measurements were significantly lower in the monotherapy group compared with the newly diagnosed group (p = 0.044 and p = 0.032, respectively). CT measurements were not significantly different between the groups (p = 0.413). There was a negative correlation in regression analysis between the duration of drug use and RNFL thickness in all quadrants.

CONCLUSION

According to our study, we observed thinning of the nasal RNFL and macular thickness in adolescents with epilepsy who were using Na valproate for at least 1 year and that as the duration of use increased, the thinning occurred in all RNFL quadrants. Further studies with larger series are needed to better understand the effects of both epilepsy and VPA on the eye.

Modular deep neural networks for automatic quality control of retinal optical coherence tomography scans

Retinal optical coherence tomography (OCT) with intraretinal layer segmentation is increasingly used not only in ophthalmology but also for neurological diseases such as multiple sclerosis (MS). Signal quality influences segmentation results, and high-quality OCT images are needed for accurate segmentation and quantification of subtle intraretinal layer changes. Among others, OCT image quality depends on the ability to focus, patient compliance and operator skills. Current criteria for OCT quality define acceptable image quality, but depend on manual rating by experienced graders and are time consuming and subjective. In this paper, we propose and validate a standardized, grader-independent, real-time feedback system for automatic quality assessment of retinal OCT images. We defined image quality criteria for scan centering, signal quality and image completeness based on published quality criteria and typical artifacts identified by experienced graders when inspecting OCT images. We then trained modular neural networks on OCT data with manual quality grading to analyze image quality features. Quality analysis by a combination of these trained networks generates a comprehensive quality report containing quantitative results. We validated the approach against quality assessment according to the OSCAR-IB criteria by an experienced grader. Here, 100 OCT files with volume, circular and radial scans, centered on optic nerve head and macula, were analyzed and classified. A specificity of 0.96, a sensitivity of 0.97 and an accuracy of 0.97 as well as a Matthews correlation coefficient of 0.93 indicate a high rate of correct classification. Our method shows promising results in comparison to manual OCT grading and may be useful for real-time image quality analysis or analysis of large data sets, supporting standardized application of image quality criteria.

Neural and Retinal Characteristics in Relation to Working Memory in Older Adults with Mild Cognitive Impairment

OBJECTIVE

This study investigated the relationship between neural activities and retinal structures associated with working memory (WM) in older adults with mild cognitive impairment (MCI).

METHODS

Eleven older adults with MCI and 29 healthy controls (60 to 73 years old) were tested. All participants underwent an event-related potential (ERP) recording while performing the two-back memory task. The Optical coherence tomography angiography (OCT-A) was administered to examine the perfusion and vessel density in the retina.

RESULTS

Results showed that WM performance in the MCI group was negatively associated with ERP latencies in central parietal regions (CP6 and CP8) (ps< 0.05). The left nasal vessel and perfusion densities were negatively correlated with the latencies in these two central parietal regions and positively related to WM performance only in the MCI group (ps< 0.05).

CONCLUSION

The findings on WM, central parietal brain activity, and left nasal vessel and perfusion densities in the retina help us gain a better understanding of the neural and retinal underpinnings of WM in relation to MCI.

The relationship between cerebral and retinal microbleeds in cerebral amyloid angiopathy (CAA): A pilot study

BACKGROUND

The standard in vivo diagnostic imaging technique for cerebral amyloid angiopathy (CAA) is costly and thereby of limited utility for point-of-care diagnosis and monitoring of treatment efficacy. Recent recognition that retinal changes may reflect cerebral changes in neurodegenerative disease provides an ideal opportunity for development of accessible and cost-effective biomarkers for point-of-care use in the detection and monitoring of CAA. In this pilot study, we examined structural and angiographic retinal changes in CAA patients relative to a control group, and compared retinal and cerebral pathology in a group of CAA patients.

METHODS

We used spectral domain optical coherence tomography (SD-OCT) to image the retina and compared retinal microbleeds to both cerebral microbleeds and white matter hyperintensities (WMH) in CAA patients, as seen on MRI. We compared retinal angiographic changes, along with structural retinal neuronal layer changes in CAA patients and cognitively normal older adults, and examined the relationship between retinal and cerebral microbleeds and cognition in CAA patients.

RESULTS

We found a trend level correlation between retinal and cerebral microbleeds in CAA patients. Moreover, we found a significant correlation between retinal microbleeds and episodic memory performance in CAA patients. There were no significant group differences between CAA patients and cognitively normal older adults on retinal angiographic or structural measurements.

CONCLUSION

Retinal microbleeds may reflect degree of cerebral microbleed burden in CAA. This picture was complicated by systolic hypertension in the CAA group, which is a confounding factor for the interpretation of these data. Our results stimulate motivation for pursuit of a more comprehensive prospective study to determine the feasibility of retinal biomarkers in CAA.

OctNET: A Lightweight CNN for Retinal Disease Classification from Optical Coherence Tomography Images

BACKGROUND AND OBJECTIVE

Retinal diseases are becoming a major health problem in recent years. Their early detection and ensuing treatment are essential to prevent visual damage, as the number of people affected by diabetes is expected to grow exponentially. Retinal diseases progress slowly, without any discernible symptoms. Optical Coherence Tomography (OCT) is a diagnostic tool capable of analyzing and identifying the quantitative discrimination in the disease affected retinal layers with high resolution. This paper proposes a deep neural network-based classifier for the computer-aided classification of Diabetic Macular Edema (DME), drusen, Choroidal NeoVascularization (CNV) from normal OCT images of the retina.

METHODS

In the proposed method, we demonstrate the feasibility of classifying and detecting severe retinal pathologies from OCT images using a deep convolutional neural network having six convolutional blocks. The classification results are explained using a gradient-based class activation mapping algorithm.

RESULTS

Training and validation of the model are performed on a public dataset of 83,484 images with expert-level disease grading of CNV, DME, and drusen, in addition to normal retinal image. We achieved a precision of 99.69%, recall of 99.69%, and accuracy of 99.69% with only three misclassifications out of 968 test cases.

CONCLUSION

In the proposed work, downsampling and weight sharing were introduced to improve the training efficiency and were found to reduce the trainable parameters significantly. The class activation mapping was also performed, and the output image was similar to the retina's actual color OCT images. The proposed network used only 6.9% of learnable parameters compared to the existing ResNet-50 model and yet outperformed it in classification. The proposed work can be potentially employed in real-time applications due to reduced complexity and fewer learnable parameters over other models.

Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death.

INTRODUCTION

In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD.

AIM

In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed.

FINDINGS

Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure.

CONCLUSIONS

Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.

Optic Nerve Head Parameters and Peripapillary Retinal Nerve Fiber Layer Thickness in Patients with Coronavirus Disease 2019

Purpose: To quantify the optic nerve head (ONH) and peripapillary retinal nerve fiber layer (pRNFL) thickness in patients with Coronavirus Disease-2019 (COVID-19) and compare the measurements with a healthy control group.Methods: In a comparative cross-sectional observational study, ONH and pRNFL thickness were evaluated in patients with a history of COVID-19, at least 2 weeks after recovery from the systemic disease, and compared with an age-matched, normal control group.Results: Thirty COVID-19 patients along with 60 age- and gender-matched healthy controls were studied. Mean average pRNFL thickness was 105.0 ± 16.3 µm in the COVID-19 patients, compared to 99.0 ± 9.0 µm in the controls (p = .31). The pRNFL thicknesses in all sectors was higher in patients with a history of COVID-19; however, this did not reach statistical significance. Similarly, ONH parameters were not significantly different between the groups.Conclusion: Patients recovered from COVID-19 had unremarkable alterations in the peripapillary RNFL thickness.Abbreviations: ONH: Optic Nerve HeadRNFL: Retinal Nerve Fiber LayerSD-OCT: Spectral-Domain Optical Coherence TomographyCOVID-19: Coronavirus Disease 2019SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus 2CNS: Central Nervous SystemACE: Angiotensin-Converting EnzymeRT-PCR: Reverse Transcription-Polymerase Chain Reaction.

Retinal imaging in Alzheimer's and neurodegenerative diseases

In the last 20 years, research focused on developing retinal imaging as a source of potential biomarkers for Alzheimer's disease and other neurodegenerative diseases, has increased significantly. The Alzheimer's Association and the Alzheimer's & Dementia: Diagnosis, Assessment, Disease Monitoring editorial team (companion journal to Alzheimer's & Dementia) convened an interdisciplinary discussion in 2019 to identify a path to expedite the development of retinal biomarkers capable of identifying biological changes associated with AD, and for tracking progression of disease severity over time. As different retinal imaging modalities provide different types of structural and/or functional information, the discussion reflected on these modalities and their respective strengths and weaknesses. Discussion further focused on the importance of defining the context of use to help guide the development of retinal biomarkers. Moving from research to context of use, and ultimately to clinical evaluation, this article outlines ongoing retinal imaging research today in Alzheimer's and other brain diseases, including a discussion of future directions for this area of study.

Ocular Vascular Changes in Mild Alzheimer's Disease Patients: Foveal Avascular Zone, Choroidal Thickness, and ONH Hemoglobin Analysis

In Alzheimer’s disease (AD), vascular changes could be caused by amyloid beta (Aβ) aggregates replacing the contractile smooth musculature of the arteriole walls. These changes happen in the brain vascular network, but also in the eye, and are related to decreased vascular density and low blood flow. In patients with Alzheimer’s disease, thinning of the choroid and the retina has been shown. The aim of this prospective study was to assess the retinal and choroidal vascular systems, analyzing the choroidal thickness with optical coherence tomography (OCT), the foveal avascular zone (FAZ) with OCT-angiography (OCTA), and the optic nerve head (ONH) hemoglobin with the Laguna ONhE program, to evaluate which of the two ocular vascular systems shows earlier changes in mild AD patients. These patients, compared to controls, showed a significantly thinner choroid at all the analyzed points, with the exception of the temporal macula (at 1000 and 1500 µm from the fovea). On the other hand, the FAZ and ONH hemoglobin did not show significant differences. In conclusion, a thinner choroid was the main ocular vascular change observed in mild AD patients, while the retinal vessels were not yet affected. Therefore, choroidal thickness could be used an early biomarker in AD.

Investigating Vascular Complexity and Neurogenic Alterations in Sectoral Regions of the Retina in Patients With Cognitive Impairment

Evidence is accumulating that cognitive function, and visual impairment may be related. In this pilot study, we investigated whether multifractal dimension and lacunarity analyses performed in sectoral regions of the retina may reveal changes in patients with cognitive impairment (CI) that may be masked in the study considering the whole retinal branching pattern. Prospective age-matched subjects (n = 69) with and with no CI and without the presence of any ophthalmic history were recruited (age > 55+ years). The Montreal Cognitive Assessment (MoCA) was used to measure CI, and full-field electroretinogram (ERG) was performed. Also, visual performance exams were conducted using the Rabin cone contrast test (CCT). Quantification of the retinal structure was performed in retinal fundus images [45^o field of view (FOV), optic disk centered] with excellent quality for all individuals [19 healthy controls (HC) and 20 patients with CI] after evaluating the inclusion and exclusion criteria in all study participants recruited (n = 69). The skeletonized vasculature network that comprised the whole branching pattern observable in the full 45° FOV was obtained for each image and divided into nine equal regions (superotemporal, superior, superonasal, macular, optic disk, nasal, inferotemporal, inferior, and inferonasal). The multifractal behavior was analyzed by calculating the generalized dimension Dq (Do, D1, and D2), the lacunarity parameter (Λ), and singularity spectrum f(α) in the nine sectoral skeletonized images as well as in the skeletons that comprised the whole branching pattern observable in the full 45° FOV. The analyses were performed using the ImageJ program together with the FracLac plug-in. Independent sample t-tests or Mann Whitney U test and Pearson correlation coefficient were used to find associations between all parameters in both groups. The effect size (Cohen’s d) of the difference between both groups was also assessed. A p-value < 0.05 was considered statistically significant. Significant correlations between multifractal and Λ parameters with the MoCA and implicit time ERG-parameter were observed in the regional analysis. In contrast, no trend was found when considering the whole retinal branching pattern. Analysis of combined structural-functional parameters in sectoral regions of the retina, instead of individual retinal biomarkers, may provide a useful clinical marker of CI.

A recommended "minimum data set" framework for SD-OCT retinal image acquisition and analysis from the Atlas of Retinal Imaging in Alzheimer's Study (ARIAS)

INTRODUCTION

We propose a minimum data set framework for the acquisition and analysis of retinal images for the development of retinal Alzheimer's disease (AD) biomarkers. Our goal is to describe methodology that will increase concordance across laboratories, so that the broader research community is able to cross-validate findings in parallel, accumulate large databases with normative data across the cognitive aging spectrum, and progress the application of this technology from the discovery stage to the validation stage in the search for sensitive and specific retinal biomarkers in AD.

METHODS

The proposed minimum data set framework is based on the Atlas of Retinal Imaging Study (ARIAS), an ongoing, longitudinal, multi-site observational cohort study. However, the ARIAS protocol has been edited and refined with the expertise of all co-authors, representing 16 institutions, and research groups from three countries, as a first step to address a pressing need identified by experts in neuroscience, neurology, optometry, and ophthalmology at the Retinal Imaging in Alzheimer's Disease (RIAD) conference, convened by the Alzheimer's Association and held in Washington, DC, in May 2019.

RESULTS

Our framework delineates specific imaging protocols and methods of analysis for imaging structural changes in retinal neuronal layers, with optional add-on procedures of fundus autofluorescence to examine beta-amyloid accumulation and optical coherence tomography angiography to examine AD-related changes in the retinal vasculature.

DISCUSSION

This minimum data set represents a first step toward the standardization of retinal imaging data acquisition and analysis in cognitive aging and AD. A standardized approach is essential to move from discovery to validation, and to examine which retinal AD biomarkers may be more sensitive and specific for the different stages of the disease severity spectrum. This approach has worked for other biomarkers in the AD field, such as magnetic resonance imaging; amyloid positron emission tomography; and, more recently, blood proteomics. Potential context of use for retinal AD biomarkers is discussed.

A machine learning approach for retinal images analysis as an objective screening method for children with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is characterised by many of features including problem in social interactions, different ways of learning, some children showing a keen interest in specific subjects, inclination to routines, challenges in typical communication, and particular ways of processing sensory information. Early intervention and suitable supports for these children may make a significant contribution to their development. However, considerable difficulties have been encountered in the screening and diagnosis of ASD. The literature has indicated that certain retinal features are significantly associated with ASD. In this study, we investigated the use of machine learning approaches on retinal images to further enhance the classification accuracy.

METHODS

Forty-six ASD participants were recruited from three special needs schools and 24 normal control were recruited from the community. Among them, 23 age-gender matched ASD and normal control participant-pairs were constructed for the primary analysis. All retinal images were captured using a nonmydriatic fundus camera. Automatic retinal image analysis (ARIA) methodology applying machine-learning technology was used to optimise the information of the retina to develop a classification model for ASD. The model's validity was then assessed using a 10-fold cross-validation approach to assess its validity.

FINDINGS

The sensitivity and specificity were 95.7% (95% CI 76.0%, 99.8%) and 91.3% (95% CI 70.5%, 98.5%) respectively. The area under the ROC curve was 0.974 (95% CI 0.934, 1.000); however, it was noted that the specificity for female participants might not be as high as that for male participants.

INTERPRETATION

Because ARIA is a fully automatic cloud-based algorithm and relies only on retinal images, it can be used as a risk assessment tool for ASD screening. Further diagnosis and confirmation can then be made by professionals, and potential treatment may be provided at a relatively early stage.

The use of optical coherence tomography in the evaluation of patients with bipolar disorder

Bipolar disorder (BD) is a mental disorder characterised by episodes of extremal mood changes. In recent years, some researchers found neurodegeneration in patients with BD using Magnetic Resonance Imaging. Evaluation of the optic nerve and the retinal layers using optical coherence tomography (OCT) has proved to be a useful, non-invasive tool for diagnosis and monitoring of neurodegenerative diseases. Accordingly, a decrease in the retinal nerve fibre layer and the ganglion cell complex measured by OCT was found in patients with BD in different studies, suggesting that BD is a neurodegenerative process in addition to a psychiatric disorder. Therefore, the neuro-ophthalmological evaluation of these patients could be used as a marker for diagnosis of this disease. This work analyses literature on retinal degeneration in bipolar disorder patients, and evaluates the ability of OCT devices in the detection of neuronal degeneration affecting the different retinal layers in these patients, and its possible role in the diagnosis and monitoring of the disease.

Retinal involvement in Alzheimer's disease (AD): evidence and current progress on the non-invasive diagnosis and monitoring of AD-related pathology using the eye

Alzheimer's disease (AD) is a common form of age-related dementia that mostly affects the aging population. Clinically, it is a disease characterized by impaired memory and progressive cognitive decline. Although the pathological hallmarks of AD have been traditionally described with a general confinement in the brain, recent studies have shown similar pathological changes in the retina, which is a developmental outgrowth of the forebrain. These AD-related neurodegenerative changes in the retina have been implicated to cause early visual problems in AD even before cognitive impairment becomes apparent. With recent advances in research, the commonly held view that AD-related cerebral pathology causes visual dysfunction through disruption of central visual pathways has been re-examined. Currently, several studies have already explored how AD manifests in the retina and the possibility of using the same retina as a window to non-invasively examine AD-related pathology in the brain. Non-invasive screening of AD through the retina has the potential to improve on early detection and management of the disease since the majority of AD cases are usually diagnosed very late. The purpose of this review is to provide evidence on the involvement of the retina in AD and to suggest a possible direction for future research into the non-invasive screening, diagnosis, and monitoring of AD using the retina.

Retinal thickness as a potential biomarker of neurodegeneration and a predictor of early cognitive impairment in patients with multiple sclerosis

OBJECTIVES

The purpose of this research is to predict the cognitive impairment and to determine its correlation with retinal thickness, mainly (RFNL and GCIPL) in cases of multiple sclerosis.

METHODS

60 multiple sclerosis patients and 30 age and sex-matched healthy controls were included in this study. Cognitive functions were evaluated in all study participants by the Montreal Cognitive Assessment (MoCA). OCT imaging was done to determine the thickness. The correlation between the cognitive domains of MoCA and the thickness of the retinal nerve fiber layers was analyzed by Spearman correlation. ROC curve was constructed to determine the cut-off points for retinal thickness, and a binary logistic regression was performed to determine the independent predictive capacity of established cut-off points.

RESULTS

Impaired cognition was found in 26 MS patients (43.3%). Cognitively impaired patients were significantly older (P < 0.05), had significantly longer disease duration (P < 0.05), had higher average EDSS scores (4.3 ± 1.22 vs 3.1 ± 1.45, P < 0.001), and occurred more in progressive types of MS (P < 0.001). A significant positive correlation was found between cognitive function and RNFL thickness and GCIPL (P < 0.001). The retinal thickness (RNFL and GCIPL) cut-off points established for the prediction of cognitive impairment in MS patients were 79 μm and 76 μm, respectively.

CONCLUSION

The clear correlation between cognitive impairment and atrophy of inner retinal layers (RNFL and GCIPL) proposes that OCT is valuable in evaluating the neurodegeneration and prediction of early cognitive impairment in MS.

ABBREVIATIONS

EDSS: Expanded Disability Status Scale; HCs: Healthy controls; GCIPL: Ganglion cell-inner plexiform layer; ILM: Internal limiting membrane; INL:  Inner nuclear layer; MoCA: Montreal Cognitive Assessment; MS: Multiple sclerosis; PPMS: Primary progressive multiple sclerosis; RNFL:  Retinal nerve fiber layer; RRMS: Relapsing-remitting multiple sclerosis; SD: Standard deviations; SPMS: Secondary progressive multiple sclerosis; SPSS: Statistical Package for the Social Sciences.