Automated Assessment of Hemodynamics in the Conjunctival Microvasculature Network

Image-Based Experimental Measurement Techniques to Characterize Velocity Fields in Blood Microflows

Predicting blood microflow in both simple and complex geometries is challenging because of the composition and behavior of the blood at microscale. However, characterization of the velocity in microchannels is the key for gaining insights into cellular interactions at the microscale, mechanisms of diseases, and efficacy of therapeutic solutions. Image-based measurement techniques are a subset of methods for measuring the local flow velocity that typically utilize tracer particles for flow visualization. In the most basic form, a high-speed camera and microscope setup are the only requirements for data acquisition; however, the development of image processing algorithms and equipment has made current image-based techniques more sophisticated. This mini review aims to provide a succinct and accessible overview of image-based experimental measurement techniques to characterize the velocity field of blood microflow. The following techniques are introduced: cell tracking velocimetry, kymographs, micro-particle velocimetry, and dual-slit photometry as entry techniques for measuring various velocity fields either in vivo or in vitro.

Identifying diabetes from conjunctival images using a novel hierarchical multi-task network

Diabetes can cause microvessel impairment. However, these conjunctival pathological changes are not easily recognized, limiting their potential as independent diagnostic indicators. Therefore, we designed a deep learning model to explore the relationship between conjunctival features and diabetes, and to advance automated identification of diabetes through conjunctival images. Images were collected from patients with type 2 diabetes and healthy volunteers. A hierarchical multi-tasking network model (HMT-Net) was developed using conjunctival images, and the model was systematically evaluated and compared with other algorithms. The sensitivity, specificity, and accuracy of the HMT-Net model to identify diabetes were 78.70%, 69.08%, and 75.15%, respectively. The performance of the HMT-Net model was significantly better than that of ophthalmologists. The model allowed sensitive and rapid discrimination by assessment of conjunctival images and can be potentially useful for identifying diabetes.

Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm

The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunctival microvessel is imaged in several seconds, eye motion during image acquisition causes motion artifacts limiting the accuracy of image segmentation performance and measurement of the blood flow velocity. In this paper, we introduce a novel customized optical imaging system for human conjunctiva with deep learning-based segmentation and motion correction. The image segmentation process is performed by the Attention-UNet structure to achieve high-performance segmentation results in conjunctiva images with motion blur. Motion correction processes with two steps—registration and template matching—are used to correct for large displacements and fine movements. The image displacement values decrease to 4–7 μm during registration (first step) and less than 1 μm during template matching (second step). With the corrected images, the blood flow velocity is calculated for selected vessels considering temporal signal variances and vessel lengths. These methods for resolving motion artifacts contribute insights into studies quantifying the hemodynamics of the conjunctiva, as well as other tissues.

Assessment of the conjunctival microcirculation for patients presenting with acute myocardial infarction compared to healthy controls

Microcirculatory dysfunction occurs early in cardiovascular disease (CVD) development. Acute myocardial infarction (MI) is a late consequence of CVD. The conjunctival microcirculation is readily-accessible for quantitative assessment and has not previously been studied in MI patients. We compared the conjunctival microcirculation of acute MI patients and age/sex-matched healthy controls to determine if there were differences in microcirculatory parameters. We acquired images using an iPhone 6s and slit-lamp biomicroscope. Parameters measured included diameter, axial velocity, wall shear rate and blood volume flow. Results are for all vessels as they were not sub-classified into arterioles or venules. The conjunctival microcirculation was assessed in 56 controls and 59 inpatients with a presenting diagnosis of MI. Mean vessel diameter for the controls was 21.41 ± 7.57 μm compared to 22.32 ± 7.66 μm for the MI patients (p < 0.001). Axial velocity for the controls was 0.53 ± 0.15 mm/s compared to 0.49 ± 0.17 mm/s for the MI patients (p < 0.001). Wall shear rate was higher for controls than MI patients (162 ± 93 s-1 vs 145 ± 88 s-1, p < 0.001). Blood volume flow did not differ significantly for the controls and MI patients (153 ± 124 pl/s vs 154 ± 125 pl/s, p = 0.84). This pilot iPhone and slit-lamp assessment of the conjunctival microcirculation found lower axial velocity and wall shear rate in patients with acute MI. Further study is required to correlate these findings further and assess long-term outcomes in this patient group with a severe CVD phenotype.

Repeatability of ocular surface vessel density measurements with optical coherence tomography angiography

Background

To determine the repeatability of measurements of ocular surface vessel density in normal and diseased eyes using optical coherence tomography angiography (OCTA).

Methods

Ten normal eyes, 10 pinguecula eyes, and 10 pterygium eyes of 30 volunteers were subjected to OCTA (AngioVue Imaging System, Optovue, Inc.). For scanning, we used the corneal adapter module. Each eye was scanned three times in the nasal and temporal directions, separately. AngioVue software was used to generate the ocular surface vessel density. Ocular surface vessel density was defined as the proportion of vessel area with blood flow to the total measurement area (3 × 3 mm²). Intersession repeatability of the measurement was summarized as the coefficient of variation (CV), and intraclass correlation coefficients (ICC) were calculated by variance component models.

Results

The CVs were less than 5% in all subjects, and the ICCs exceeded 0.9; thus, all measurements showed good repeatability. The nasal vessels densities differed significantly between healthy eyes and eyes with pterygium (P < 0.05); however, there was no significant difference between healthy eyes and eyes with pinguecula (P = 0.466).

Conclusions

These results suggest that measurement of ocular surface vessel density by OCTA in normal eyes and eyes with pterygium and pinguecula is repeatable. This preliminary research describes a quantitative and visual method for assessing vessel density of the ocular surface with a high level of consistency.

Functional slit lamp biomicroscopy metrics correlate with cardiovascular risk

PURPOSE

Our aim was to correlate cardiovascular risk factor estimation with bulbar conjunctival blood flow metrics as measured through Functional Slit Lamp Biomicroscopy (FSLB).

METHODS

Cross-sectional study of individuals with otherwise healthy eyelid and corneal anatomy recruited from the Miami Veterans Affairs (VA) Healthcare System eye clinic. We measured conjunctival microvascular hemodynamics by mounting a camera on a slit lamp and cardiovascular risk using the Framingham risk score. Our main outcome measures were correlations between conjunctival vessel parameters (axial and cross-sectional blood flow velocity, blood flow rate) and Framingham score.

RESULTS

We included 84 patients who underwent FSLB. The mean age was 60 years, the majority were male (88%) and approximately half the patients were black (54%). Mean vessel diameter was similar between all Framingham score categories. Axial and cross-sectional blood flow velocities and blood flow rate were lower in individuals with higher Framingham risk score. Specifically, mean cross-sectional blood flow velocity in individuals with a low Framingham risk score was 0.37 ± 0.0.9 mm/s, with an intermediate score was 0.30 ± 0.09 mm/s, and with a high score was 0.29 ± 0.10 mm/s, p = 0.04. Mean blood flow rate in individuals with a low Framingham risk score was 133.4 ± 59.6 pl/s, with an intermediate score was 123.6 ± 39.3 pl/s, and with a high score was 121.9 ± 52.6 pl/s, p = 0.04. The beta coefficient of the blood flow rate for change in Framingham score was -0.73; 95% CI-1.34-0.13, p = 0.02, adjusted for race.

CONCLUSION

FSLB correlates with cardiovascular risk estimation. Future studies should evaluate if FSLB can predict cardiovascular outcomes.

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 ± 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 ± 0.5 µm, −0.01 ± 0.16 mm/s, −8 ± 46 pl/s, −3 ± 46 s−1 and −0.01 ± 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.

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.

Paradigm Shifts in Ophthalmic Diagnostics

PURPOSE

Future advances in ophthalmology will see a paradigm shift in diagnostics from a focus on dysfunction and disease to better measures of psychophysical function and health. Practical methods to define genotypes will be increasingly important and non-invasive nanotechnologies are needed to detect molecular changes that predate histopathology.

METHODS

This is not a review nor meant to be comprehensive. Specific topics have been selected to illustrate the principles of important paradigm shifts that will influence the future of ophthalmic diagnostics. It is our impression that future evaluation of vision will go beyond visual acuity to assess ocular health in terms of psychophysical function. The definition of disease will incorporate genotype into what has historically been a phenotype-centric discipline. Non-invasive nanotechnologies will enable a paradigm shift from disease detection on a cellular level to a sub-cellular molecular level.

RESULTS

Vision can be evaluated beyond visual acuity by measuring contrast sensitivity, color vision, and macular function, as these provide better insights into the impact of aging and disease. Distortions can be quantified and the psychophysical basis of vision can be better evaluated than in the past by designing tests that assess particular macular cell function(s). Advances in our understanding of the genetic basis of eye diseases will enable better characterization of ocular health and disease. Non-invasive nanotechnologies can assess molecular changes in the lens, vitreous, and macula that predate visible pathology. Oxygen metabolism and circulatory physiology are measurable indices of ocular health that can detect variations of physiology and early disease.

CONCLUSIONS

This overview of paradigm shifts in ophthalmology suggests that the future will see significant improvements in ophthalmic diagnostics. The selected topics illustrate the principles of these paradigm shifts and should serve as a guide to further research and development. Indeed, successful implementation of these paradigm shifts in ophthalmology may provide useful guidance for similar developments in all of healthcare.

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.