Retinal Venular Tortuosity Jointly with Retinal Amyloid Burden Correlates with Verbal Memory Loss: A Pilot Study.

INTRODUCTION: Retinal imaging is a non-invasive tool to study both retinal vasculature and neurodegeneration. In this exploratory retinal curcumin-fluorescence imaging (RFI) study, we sought to determine whether retinal vascular features combined with retinal amyloid burden correlate with the neurocognitive status. METHODS: We used quantitative RFI in a cohort of patients with cognitive impairment to automatically compute retinal amyloid burden. Retinal blood vessels were segmented, and the vessel tortuosity index (VTI), inflection index, and branching angle were quantified. We assessed the correlations between retinal vascular and amyloid parameters, and cognitive domain Z-scores using linear regression models. RESULTS: Thirty-four subjects were enrolled and twenty-nine (55% female, mean age 64 ± 6 years) were included in the combined retinal amyloid and vascular analysis. Eleven subjects had normal cognition and 18 had impaired cognition. Retinal VTI was discriminated among cognitive scores. The combined proximal mid-periphery amyloid count and venous VTI index exhibited significant differences between cognitively impaired and cognitively normal subjects (0.49 ± 1.1 vs. 0.91 ± 1.4, p = 0.006), and correlated with both the Wechsler Memory Scale-IV and SF-36 mental component score Z-scores (p < 0.05). CONCLUSION: This pilot study showed that retinal venular VTI combined with the proximal mid-periphery amyloid count could predict verbal memory loss. Future research is needed to finesse the clinical application of this retinal imaging-based technology.

Past, present and future role of retinal imaging in neurodegenerative disease.

Retinal imaging technology is rapidly advancing and can provide ever-increasing amounts of information about the structure, function and molecular composition of retinal tissue in humans in vivo. Most importantly, this information can be obtained rapidly, non-invasively and in many cases using Food and Drug Administration-approved devices that are commercially available. Technologies such as optical coherence tomography have dramatically changed our understanding of retinal disease and in many cases have significantly improved their clinical management. Since the retina is an extension of the brain and shares a common embryological origin with the central nervous system, there has also been intense interest in leveraging the expanding armamentarium of retinal imaging technology to understand, diagnose and monitor neurological diseases. This is particularly appealing because of the high spatial resolution, relatively low-cost and wide availability of retinal imaging modalities such as fundus photography or OCT compared to brain imaging modalities such as magnetic resonance imaging or positron emission tomography. The purpose of this article is to review and synthesize current research about retinal imaging in neurodegenerative disease by providing examples from the literature and elaborating on limitations, challenges and future directions. We begin by providing a general background of the most relevant retinal imaging modalities to ensure that the reader has a foundation on which to understand the clinical studies that are subsequently discussed. We then review the application and results of retinal imaging methodologies to several prevalent neurodegenerative diseases where extensive work has been done including sporadic late onset Alzheimer's Disease, Parkinson's Disease and Huntington's Disease. We also discuss Autosomal Dominant Alzheimer's Disease and cerebrovascular small vessel disease, where the application of retinal imaging holds promise but data is currently scarce. Although cerebrovascular disease is not generally considered a neurodegenerative process, it is both a confounder and contributor to neurodegenerative disease processes that requires more attention. Finally, we discuss ongoing efforts to overcome the limitations in the field and unmet clinical and scientific needs.

3D Retinal Vessel Density Mapping With OCT-Angiography.

Optical Coherence Tomography Angiography (OCTA) is a novel, non-invasive imaging modality of retinal capillaries at micron resolution. Recent studies have correlated macular OCTA vascular measures with retinal disease severity and supported their use as a diagnostic tool. However, these measurements mostly rely on a few summary statistics in retinal layers or regions of interest in the two-dimensional (2D) en face projection images. To enable 3D and localized comparisons of retinal vasculature between longitudinal scans and across populations, we develop a novel approach for mapping retinal vessel density from OCTA images. We first obtain a high-quality 3D representation of OCTA-based vessel networks via curvelet-based denoising and optimally oriented flux (OOF). Then, an effective 3D retinal vessel density mapping method is proposed. In this framework, a vessel density image (VDI) is constructed by diffusing the vessel mask derived from OOF-based analysis to the entire image volume. Subsequently, we utilize a non-linear, 3D OCT image registration method to provide localized comparisons of retinal vasculature across subjects. In our experimental results, we demonstrate an application of our method for longitudinal qualitative analysis of two pathological subjects with edema during the course of clinical care. Additionally, we quantitatively validate our method on synthetic data with simulated capillary dropout, a dataset obtained from a normal control (NC) population divided into two age groups and a dataset obtained from patients with diabetic retinopathy (DR). Our results show that we can successfully detect localized vascular changes caused by simulated capillary loss, normal aging, and DR pathology even in presence of edema. These results demonstrate the potential of the proposed framework in localized detection of microvascular changes and monitoring retinal disease progression.

Assessment of retinal vascular oxygenation and morphology at stages of diabetic retinopathy in African Americans.

BACKGROUND: Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of blindness in working-age adults. The likelihood of visual impairment associated with DR is two-fold higher in the African-American (AA) compared to non-Hispanic white. Although alterations in retinal vessel oxygenation and morphology have been reported in DR, there is limited knowledge about these vascular changes in AA subjects. The purpose of the current study was to investigate alterations in retinal vascular oxygen saturation (SO2), vessel diameter (D) and tortuosity at severity stages of DR in AA subjects. METHODS: A nested case-control study of 56 AA subjects was conducted. Right eyes were grouped as non-diabetic (ND) (N = 26), no clinical DR (NDR) (N = 19), or moderate/severe non-proliferative DR (NPDR) (N = 11). Imaging was performed using a commercially available scanning laser ophthalmoscope. Images were analyzed to determine retinal arterial and venous SO2 (SO2A and SO2V), diameter (DA and DV), and vessel tortuosity index (VTI) (VTIA and VTIV). RESULTS: SO2V and DV were higher in NPDR compared to ND and NDR groups (P < 0.05). There were no significant differences in SO2A and DA among ND, NDR, and NPDR groups (P > 0.8). Maximum VTIA was higher in diabetics (NDR and NPDR) compared to non-diabetics (P < 0.03). There was no significant difference in maximum VTIV among the 3 groups (P = 0.5). CONCLUSIONS: The findings advance our understanding of DR pathophysiology in the AA population and may propel identification of race-specific retinal vascular biomarkers for improved diagnosis and monitoring of DR.

Automated Deformation-Based Analysis of 3D Optical Coherence Tomography in Diabetic Retinopathy.

Diabetic retinopathy (DR) is a significant microvascular complication of diabetes mellitus and a leading cause of vision impairment in working age adults. Optical coherence tomography (OCT) is a routinely used clinical tool to observe retinal structural and thickness alterations in DR. Pathological changes that alter the normal anatomy of the retina, such as intraretinal edema, pose great challenges for conventional layer-based analysis of OCT images. We present an alternative approach for the automated analysis of OCT volumes in DR research based on nonlinear registration. In this paper, we first obtain an anatomically consistent volume of interest (VOI) in different OCT images via carefully designed masking and affine registration. After that, efficient B-spline transformations are computed using stochastic gradient descent optimization. Using the OCT volumes of normal controls, for which layer-based segmentation works well, we demonstrate the accuracy of our registration-based analysis in aligning layer boundaries. By nonlinearly registering the OCT volumes of DR subjects to an atlas constructed from normal controls and measuring the Jacobian determinant of the deformation, we can simultaneously visualize tissue contraction and expansion due to DR pathology. Tensor-based morphometry (TBM) can also be performed for quantitative analysis of local structural changes. In our experimental results, we apply our method to a dataset of 105 subjects and demonstrate that volumetric OCT registration and TBM analysis can successfully detect local retinal structural alterations due to DR.

Relating retinal blood flow and vessel morphology in sickle cell retinopathy.

PURPOSE: The purpose of the current study was to determine associations between retinal blood flow and vessel morphology metrics in sickle cell retinopathy (SCR) and healthy normal control (NC) subjects. METHODS: Optical coherence tomography angiography (OCTA) and Doppler OCT imaging were performed in 12 SCR (15 eyes) and 19 NC (26 eyes) subjects. Vessel tortuosity was measured using a dedicated image analysis algorithm applied to OCTA images. Vessel density and spacing between vessels were determined from OCTA images by a fractal dimension analysis method. Retinal blood flow was quantified using a phase-resolved technique applied to en face Doppler OCT images. RESULTS: There was a significant association between increased retinal blood flow and increased vessel tortuosity (P = 0.03). Furthermore, increased retinal blood flow was associated with increased vessel density (P = 0.03) and decreased spacing between small vessels (P = 0.01). There was no significant association between retinal blood flow and spacing between large vessels (P = 0.11). Vessel tortuosity and blood flow were increased, whereas spacing between small vessels was decreased in SCR compared to NC group (P ≤ 0.03). There were no significant differences in vessel density or spacing between large vessels between the SCR and NC groups (P ≥ 0.31). CONCLUSIONS: Associations between retinal hemodynamics and vessel morphology were reported, providing better understanding of retinal pathophysiology and insight into potential quantitative biomarkers to evaluate SCR.

3D Shape Modeling and Analysis of Retinal Microvasculature in OCT-Angiography Images.

3D optical coherence tomography angiography (OCT-A) is a novel and non-invasive imaging modality for analyzing retinal diseases. The studies of microvasculature in 2D en face projection images have been widely implemented, but comprehensive 3D analysis of OCT-A images with rich depth-resolved microvascular information is rarely considered. In this paper, we propose a robust, effective, and automatic 3D shape modeling framework to provide a high-quality 3D vessel representation and to preserve valuable 3D geometric and topological information for vessel analysis. Effective vessel enhancement and extraction steps by means of curvelet denoising and optimally oriented flux (OOF) filtering are first designed to produce 3D microvascular networks. Afterwards, a novel 3D data representation of OCT-A microvasculature is reconstructed via advanced mesh reconstruction techniques. Based on the 3D surfaces, shape analysis is established to extract novel shape-based microvascular area distortion via the Laplace-Beltrami eigen-projection. The extracted feature is integrated into a graph-cut segmentation system to categorize large vessels and small capillaries for more precise shape analysis. The proposed framework is validated on a dedicated repeated scan dataset including 260 volume images and shows high repeatability. Statistical analysis using the surface area biomarker is performed on small capillaries to avoid the effect of tailing artifact from large vessels. It shows significant differences ( ) between DR stages on 100 subjects in a OCTA-DR dataset. The proposed shape modeling and analysis framework opens the possibility for further investigating OCT-A microvasculature in a new perspective.

Relationship between retinal vessel tortuosity and oxygenation in sickle cell retinopathy.

BACKGROUND: Reduced retinal vascular oxygen (O2) content causes tissue hypoxia and may lead to development of vision-threatening pathologies. Since increased vessel tortuosity is an early sign for some hypoxia-implicated retinopathies, we investigated a relationship between retinal vascular O2 content and vessel tortuosity indices. METHODS: Dual wavelength retinal oximetry using a commercially available scanning laser ophthalmoscope was performed in both eyes of 12 healthy (NC) and 12 sickle cell retinopathy (SCR) subjects. Images were analyzed to quantify retinal arterial and venous O2 content and determine vessel tortuosity index (VTI) and vessel inflection index (VII) in circumpapillary regions. Linear mixed model analysis was used to determine the effect of disease on vascular O2 content, VTI and VII, and relate vascular O2 content with VTI and VII. Models accounted for vessel type, fellow eyes, age and mean arterial pressure. RESULTS: Retinal arterial and venous O2 content were lower in SCR (O2A = 11 ± 4 mLO2/dL, O2V = 7 ± 2 mLO2/dL) compared to NC (O2A = 18 ± 3 mLO2/dL, O2V = 13 ± 3 mLO2/dL) subjects (p < 0.001). As expected, O2 content was higher in arteries (15 ± 5 mLO2/dL) than veins (10 ± 4 mLO2/dL) (p < 0.001), but not different between eyes (OD: 12 ± 5 mLO2/dL; OS:13 ± 5 mLO2/dL) (p = 0.3). VTI was not significantly different between SCR (0.18 ± 0.07) and NC (0.15 ± 0.04) subjects, or between arteries (0.18 ± 0.07) and veins (0.16 ± 0.04), or between eyes (OD: 0.18 ± 0.07, OS:0.17 ± 0.05) (p ≥ 0.06). VII was significantly higher in SCR (10 ± 2) compared to NC subjects (8 ± 1) (p = 0.003). VII was also higher in veins (9 ± 2) compared to arteries (8 ± 5) (p = 0.04), but not different between eyes (OD: 9 ± 2; OS: 9 ± 2) (p = 0.2). There was an inverse linear relationship between vascular O2 (13 ± 5 mLO2/dL) content and VII (9 ± 2) (ß = -0.5; p = 0.02). CONCLUSIONS: The findings augment knowledge of relationship between retinal vascular oxygenation and morphological changes and potentially contribute to identifying biomarkers for assessment of retinal hypoxia due to SCR and other retinopathies.

Detection of Subclinical Diabetic Retinopathy by Fine Structure Analysis of Retinal Images.

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is a major complication of diabetes and the leading cause of blindness among US working-age adults. Detection of subclinical DR is important for disease monitoring and prevention of damage to the retina before occurrence of vision loss. The purpose of this retrospective study is to describe an automated method for discrimination of subclinical DR using fine structure analysis of retinal images. METHODS: Discrimination between nondiabetic control (NC; N = 16) and diabetic without clinical retinopathy (NDR; N = 17) subjects was performed using ordinary least squares regression and Fisher's linear discriminant analysis. A human observer also performed the discrimination by visual inspection of the images. RESULTS: The discrimination rate for subclinical DR was 88% using the automated method and higher than the rate obtained by a human observer which was 45%. CONCLUSIONS: The method provides sensitive and rapid analysis of retinal images and could be useful in detecting subclinical DR.

Inter-visit variability of conjunctival microvascular hemodynamic measurements in healthy and diabetic retinopathy subjects.

Conjunctival microcirculation imaging provides a non-invasive means for detecting hemodynamic alterations due to systemic and ocular diseases. However, reliable longitudinal monitoring of hemodynamic changes due to disease progression requires establishment of measurement variability over time. The purpose of the current study was to determine inter-visit variability of conjunctival microvascular hemodynamic measurements in non-diabetic control (NC, N = 7) and diabetic retinopathy (DR, N = 10) subjects. Conjunctival microvascular imaging was performed during 2 visits, which were 17 ±â€¯12 weeks apart. Images were analyzed to determine vessel diameter (D), axial blood velocity (V), blood flow (Q), wall shear rate (WSR) and wall shear stress (WSS). The inter-visit variability was determined based on mean inter-visit differences. In NC, inter-visit variability of D, V, Q, WSR and WSS were 0.2 ±â€¯0.5 µm, -0.01 ±â€¯0.16 mm/s, -8 ±â€¯46 pl/s, -3 ±â€¯46 s-1 and -0.01 ±â€¯0.10 dyne/cm2, respectively. Inter-visit variability of D, V, Q, WSR and WSS were beyond the normal 95% confidence limits in 60%, 20%, 40%, 20% and 20% of DR subjects, respectively. The variability of hemodynamic measurements over time was established in non-diabetic subjects, suggestive of the potential of the method for detecting longitudinal changes due to progression of DR.

Method for quantitative assessment of retinal vessel tortuosity in optical coherence tomography angiography applied to sickle cell retinopathy.

Tortuosity is an important geometric vessel parameter and among the first microvascular alterations observed in various retinopathies. In the current study, a quantitative vessel tortuosity index (VTI) based on a combination of local and global centerline features is presented. Performance of VTI and previously established tortuosity indices were compared against human observers' evaluation of tortuosity. An image-processing pipeline was developed for application of VTI in retinal vessels imaged by optical coherence tomography angiography (OCTA) in perifoveal (6 mm × 6 mm) and parafoveal (3 mm × 3 mm) regions centered on the fovea. Forty-one subjects (12 healthy control (NC) and 29 sickle cell retinopathy (SCR)) and 10 subjects (5 NC and 5 SCR) were imaged in the perifoveal and parafoveal regions, respectively. The relationship between VTI and age was examined in the perifoveal regions in NC subjects. VTI was measured from the OCTA images and compared between NC and SCR subjects using generalized least square regression with and without adjusting for age and race. VTI was found to correlate better than the 4 previous indices with performance of human observers. In the perifoveal region, a significant correlation was observed between VTI and age (r = -0.4, P<0.001, N = 12). VTI was higher in SCR than NC subjects in perifoveal and parafoveal regions (P≤0.001). The results demonstrate that the proposed method shows promise for detection of increased tortuosity in vessels due to retinal disorders.

Assessment of Conjunctival Microvascular Hemodynamics in Stages of Diabetic Microvasculopathy.

Diabetes impairs the microcirculation and function of various vital tissues throughout the body. The conjunctival microcirculation can be non-invasively imaged and thus enables assessment of microvascular hemodynamics. In this study, alterations in conjunctival microvascular hemodynamics were quantitatively assessed at stages of increasing diabetic microvasculopathy based on diabetic retinopathy (DR). Subjects were categorized into non-diabetic control (C, N = 34), no clinically visible DR (NDR, N = 47), non-proliferative DR (NPDR, N = 45), and proliferative DR (PDR, N = 35). Conjunctival hemodynamic descriptors, namely vessel diameter (D), blood velocity (V), blood flow (Q), wall shear rate (WSR), and wall shear stress (WSS) were measured in arterioles and venules, and compared between DR and C subjects using generalized linear mixed models. In arterioles, V, WSR, and WSS were lower in NDR (P ≤ 0.01). V was lower in NDR than NPDR and PDR subjects (P ≤ 0.02). In venules, D was higher in NDR and NPDR (P ≤ 0.03), while V was lower in PDR (P = 0.04). Venular V and Q were higher in NPDR than PDR subjects (P ≤ 0.04). WSR and WSS were lower in all stages of DR (P ≤ 0.05), suggestive of the potential of WSS as a marker of diabetic microvasculopathy. Quantitative assessment of conjunctival hemodynamics can potentially be useful for evaluation of diabetic microvasculopathy.

Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images.

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method's discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring.

Automated Assessment of Hemodynamics in the Conjunctival Microvasculature Network.

The conjunctival microcirculation is accessible for direct visualization and quantitative assessment of microvascular hemodynamic properties. Currently available methods to assess hemodynamics in the conjunctival microvasculature use manual or semi-automated algorithms, which can be inefficient for application to a large number of microvessels within the microvascular network. We present an automated image analysis method for measurements of diameter and blood velocity in microvessels. The method was applied to conjunctival microcirculation images acquired in 15 healthy human subjects. Frangi filtering, thresholding, and morphological closing were applied to automatically segment microvessels, while variance filtering was used to detect blood flow. Diameter and blood velocity were measured in arterioles and venules within the conjunctival microvascular network, and blood flow and wall shear rate were calculated. Repeatability and validity of hemodynamic measurements were established. The automated image analysis method allows reliable, rapid and quantitative assessment of hemodynamics in the conjunctival microvascular network and can be potentially applied to microcirculation images of other tissues.