Functional slit lamp biomicroscopy metrics correlate with cardiovascular risk

AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of CVD risk plays an essential role in identifying individuals at higher risk and enables the implementation of targeted intervention strategies, leading to improved CVD prevalence reduction and patient survival rates. The ocular vasculature, particularly the retinal vasculature, has emerged as a potential means for CVD risk stratification due to its anatomical similarities and physiological characteristics shared with other vital organs, such as the brain and heart. The integration of artificial intelligence (AI) into ocular imaging has the potential to overcome limitations associated with traditional semi-automated image analysis, including inefficiency and manual measurement errors. Furthermore, AI techniques may uncover novel and subtle features that contribute to the identification of ocular biomarkers associated with CVD. This review provides a comprehensive overview of advancements made in AI-based ocular image analysis for predicting CVD, including the prediction of CVD risk factors, the replacement of traditional CVD biomarkers (e.g., CT-scan measured coronary artery calcium score), and the prediction of symptomatic CVD events. The review covers a range of ocular imaging modalities, including colour fundus photography, optical coherence tomography, and optical coherence tomography angiography, and other types of images like external eye images. Additionally, the review addresses the current limitations of AI research in this field and discusses the challenges associated with translating AI algorithms into clinical practice.

Conjunctival microcirculation in ocular and systemic microvascular disease

The conjunctival microcirculation is an accessible complex network of micro vessels whose quantitative assessment can reveal microvascular haemodynamic properties. Currently, algorithms for the measurement of conjunctival haemodynamics use either manual or semi-automated systems, which may provide insight into overall conjunctival health, as well as in ocular and systemic disease. These algorithms include functional slit-lamp biomicroscopy, laser doppler flowmetry, optical coherence tomography angiography, orthogonal polarized spectral imaging, computer-assisted intravitral microscopy, diffuse reflectance spectroscopy and corneal confocal microscopy. Furthermore, several studies have demonstrated a relationship between conjunctival microcirculatory haemodynamics and many diseases such as dry eye disease, Alzheimer's disease, diabetes, hypertension, sepsis, coronary microvascular disease, and sickle cell anaemia. This review aims to describe conjunctival microcirculation, its characteristics, and techniques for its measurement, as well as the association between conjunctival microcirculation and microvascular abnormalities in disease states.

A normative blood velocity model in the exchange microvessels for discriminating health from disease: Healthy controls versus COVID-19 cases

A usual practice in medicine is to search for "biomarkers" which are measurable quantities of a normal or abnormal biological process. Biomarkers can be biochemical or physical quantities of the body and although commonly used statistically in clinical settings, it is not usual for them to be connected to basic physiological models or equations. In this work, a normative blood velocity model framework for the exchange microvessels was introduced, combining the velocity-diffusion (V-J) equation and statistics, in order to define the normative range (NR) and normative area (NA) diagrams for discriminating normal (normemic) from abnormal (hyperemic or underemic) states, taking into account the microvessel diameter D. This is different from the usual statistical processing since there is a basis on the well-known physiological principle of the flow diffusion equation. The discriminative power of the average axial velocity model was successfully tested using a group of healthy individuals (Control Group) and a group of post COVID-19 patients (COVID-19 Group).

Assessment of hemodynamic indices of conjunctival microvascular function in patients with coronary microvascular dysfunction

OBJECTIVE

Coronary microvascular dysfunction (CMD) is a cause of ischaemia with non-obstructive coronary arteries (INOCA). It is notoriously underdiagnosed due to the need for invasive microvascular function testing. We hypothesized that systemic microvascular dysfunction could be demonstrated non-invasively in the microcirculation of the bulbar conjunctiva in patients with CMD.

METHODS

Patients undergoing coronary angiography for the investigation of chest pain or dyspnoea, with physiologically insignificant epicardial disease (fractional flow reserve ≥0.80) were recruited. All patients underwent invasive coronary microvascular function testing. We compared a cohort of patients with evidence of CMD (IMR ≥25 or CFR <2.0); to a group of controls (IMR <25 and CFR ≥2.0). Conjunctival imaging was performed using a previously validated combination of a smartphone and slit-lamp biomicroscope. This technique allows measurement of vessel diameter and other indices of microvascular function by tracking erythrocyte motion.

RESULTS

A total of 111 patients were included (43 CMD and 68 controls). There were no differences in baseline demographics, co-morbidities or epicardial coronary disease severity. The mean number of vessel segments analysed per patient was 21.0 ± 12.8 (3.2 ± 3.5 arterioles and 14.8 ± 10.8 venules). In the CMD cohort, significant reductions were observed in axial/cross-sectional velocity, blood flow, wall shear rate and stress.

CONCLUSION

The changes in microvascular function linked to CMD can be observed non-invasively in the bulbar conjunctiva. Conjunctival vascular imaging may have utility as a non-invasive tool to both diagnose CMD and augment conventional cardiovascular risk assessment.

COVID-19 hemodynamic and thrombotic effect on the eye microcirculation after hospitalization: A quantitative case-control study

BACKGROUND & OBJECTIVE

To quantify the hemodynamic and thrombotic effect of COVID-19 on the eye microcirculation of patients with thromboprophylaxis, shortly after hospital discharge.

METHODS

This case-control study included 17 COVID-19 survivors (named "COVID-19 Group") and 17 healthy volunteers (named "Control Group"). Axial blood velocity (Vax) and percentage of occluded vessels (POV) were quantified by Conjunctival Video Capillaroscopy (CVC). Microvessels were identified and classified as "capillaries" (CAP), "postcapillary venules of size 1" (PC1), and "postcapillary venules of size 2" (PC2).

RESULTS

The COVID-19 Group did not differ significantly in basic demographics from the Control Group. In the COVID-19 Group, there was a statistically significant (p < 0.001) reduction of Vax (39%, 49% and 47%, for CAP, PC1, and PC2, respectively) in comparison to the Control Group and a sizeable (p < 0.001) increase of POV (600%) in comparison to the Control Group.

CONCLUSIONS

COVID-19 not only reduces significantly axial blood velocity in the capillaries and postcapillary venules of the eye but has also a devastating effect on microthrombosis (POV) despite thromboprophylaxis treatment. This gives a possible explanation for long COVID and a hint about the existence of a possibly unknown coagulation factor.

EVA: Fully automatic hemodynamics assessment system for the bulbar conjunctival microvascular network

BACKGROUND AND OBJECTIVE

Conjunctival microcirculation has been used to quantitatively assess microvascular changes due to systemic disorders. The space between red blood cell clusters in conjunctival microvessels is essential for assessing hemodynamics. However, it causes discontinuities in vessel image segmentation and increases the difficulty of automatically measuring blood velocity. In this study, we developed an EVA system based on deep learning to maintain vessel segmentation continuity and automatically measure blood velocity.

METHODS

The EVA system sequentially performs image registration, vessel segmentation, diameter measurement, and blood velocity measurement on conjunctival images. A U-Net model optimized with a connectivity-preserving loss function was used to solve the problem of discontinuities in vessel segmentation. Then, an automatic measurement algorithm based on line segment detection was proposed to obtain accurate blood velocity. Finally, the EVA system assessed hemodynamic parameters based on the measured blood velocity in each vessel segment.

RESULTS

The EVA system was validated for 23 videos of conjunctival microcirculation captured using functional slit-lamp microscopy. The U-Net model produced the longest average vessel segment length, 158.03 ± 181.87 µm, followed by the adaptive threshold method and Frangi filtering, which produced lengths of 120.05 ± 151.47 µm and 99.94 ± 138.12 µm, respectively. The proposed method and one based on cross-correlation were validated to measure blood velocity for a dataset consisting of 30 vessel segments. Bland-Altman analysis showed that compared with the cross-correlation method (bias: 0.36, SD: 0.32), the results of the proposed method were more consistent with a manual measurement-based gold standard (bias: -0.04, SD: 0.14).

CONCLUSIONS

The proposed EVA system provides an automatic and reliable solution for quantitative assessment of hemodynamics in conjunctival microvascular images, and potentially can be applied to hypoglossal microcirculation images.

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.

Conjunctival Vessels in Diabetes Using Functional Slit Lamp Biomicroscopy

PURPOSE

This study used functional slit lamp biomicroscopy (FSLB) to quantify conjunctival microvessel parameters in individuals with and without diabetes and examined whether these metrics could be used as surrogate markers of diabetes-related complications.

METHODS

A cross-sectional study of 98 controls (C), 13 individuals with diabetes without complications (D-C), and 21 with diabetes and related complications (D+C), which included retinopathy, nephropathy, neuropathy, and cardiovascular-, peripheral vascular-, and cerebrovascular diseases, was performed. Bulbar conjunctival metrics (venule diameter, length, axial velocity [Va], cross-sectional velocity [Vs], flow [Q], and branching complexity) were measured using FSLB (digital camera mounted on traditional slit lamp).

RESULTS

The mean age was 60 ± 11 years, and demographics were similar across the groups. Va and Vs significantly differed between groups. Va was 0.51 ± 0.17 mm/s, 0.62 ± 0.17 mm/s, and 0.45 ± 0.17 mm/s in the C, D-C, and D+C groups, respectively (P = 0.025). Similarly, Vs was 0.35 ± 01.12, 0.43 ± 0.13, and 0.32 ± 0.13 mm/s in the C, D-C, and D+C groups, respectively (P = 0.031). Black individuals had increased Va, Vs, and Q compared with White individuals (P < 0.05), but differences in velocities persisted after accounting for race. Among patients with diabetes, Va and Vs correlated with number of organ systems affected (Va: ρ = -0.42, P = 0.016; Vs: ρ = -0.41, P = 0.021). Va, Vs, and Q significantly (P ≤ 0.005) discriminated between diabetic patients with and without complications (area under the receiver operating curve for Va = 0.81, Vs = 0.79, Q = 0.81).

CONCLUSIONS

Bulbar conjunctival blood flow metrics measured by FSLB differed between controls, diabetic patients without complications, and diabetic patients with complications. FSLB is a quick, easily accessible, and noninvasive alternative that might estimate the burden of vascular complications in diabetes.

Improved conjunctival microcirculation in diabetic retinopathy patients with MTHFR polymorphisms after Ocufolin™ Administration

PURPOSE

To investigate conjunctival microvascular responses in patients with mild diabetic retinopathy (MDR) and methylenetetrahydrofolate reductase (MTHFR) polymorphisms (D + PM) after administration of Ocufolin™, a medical food containing 900 μg l-methylfolate (levomefolate calcium or [6S]-5-methyltetrahydrofolic acid, calcium salt), methylcobalamin, and other ingredients.

METHODS

Eight D + PM patients received Ocufolin™ for six months (6 M). Bulbar conjunctival microvasculature and microcirculation metrics, including vessel diameter (D), axial blood flow velocity (Va), cross-sectional blood flow velocity (Vs), flow rate (Q), and vessel density (VD, Dbox), were measured at baseline, 4 M, and 6 M.

RESULTS

The mean age was 54 ± 7 years. No significant demographic differences were found. Conjunctival microcirculation, measured as Va, Vs, and Q was significantly increased at 4 M and 6 M, compared to baseline. Va was 0.44 ± 0.10 mm/s, 0.58 ± 0.13 mm/s, 0.59 ± 0.13 mm/s in baseline, 4 M, and 6 M, respectively (P < 0.01). Similarly, Vs was 0.31 ± 0.07 mm/s, 0.40 ± 0.09 mm/s, 0.41 ± 0.09 mm/s in baseline, 4 M, and 6 M, respectively (P < 0.05). Q was 107.8 ± 49.4 pl/s, 178.0 ± 125.8 pl/s, 163.3 ± 85.8 mm/s in baseline, 4 M, and 6 M, respectively (P < 0.05). The VD at 6 M was significantly higher than that at baseline (P = 0.017). Changes of D were positively correlated with changes of Va, Q, and VD. Effects of MTHFR and haptoglobin polymorphisms on the improvements of conjunctival microcirculation and microvasculature were found.

CONCLUSIONS

Ocufolin™ supplementation improves conjunctival microcirculation in patients with diabetic retinopathy and common folate polymorphisms.

Quantitative assessment of the conjunctival microcirculation using a smartphone and slit-lamp biomicroscope

PURPOSE

The conjunctival microcirculation is a readily-accessible vascular bed for quantitative haemodynamic assessment and has been studied previously using a digital charge-coupled device (CCD). Smartphone video imaging of the conjunctiva, and haemodynamic parameter quantification, represents a novel approach. We report the feasibility of smartphone video acquisition and subsequent haemodynamic measure quantification via semi-automated means.

METHODS

Using an Apple iPhone 6 s and a Topcon SL-D4 slit-lamp biomicroscope, we obtained videos of the conjunctival microcirculation in 4 fields of view per patient, for 17 low cardiovascular risk patients. After image registration and processing, we quantified the diameter, mean axial velocity, mean blood volume flow, and wall shear rate for each vessel studied. Vessels were grouped into quartiles based on their diameter i.e. group 1 (<11 μm), 2 (11-16 μm), 3 (16-22 μm) and 4 (>22 μm).

RESULTS

From the 17 healthy controls (mean QRISK3 6.6%), we obtained quantifiable haemodynamics from 626 vessel segments. The mean diameter of microvessels, across all sites, was 21.1μm (range 5.8-58 μm). Mean axial velocity was 0.50mm/s (range 0.11-1mm/s) and there was a modestly positive correlation (r 0.322) seen with increasing diameter, best appreciated when comparing group 4 to the remaining groups (p < .0001). Blood volume flow (mean 145.61pl/s, range 7.05-1178.81pl/s) was strongly correlated with increasing diameter (r 0.943, p < .0001) and wall shear rate (mean 157.31 s^-1, range 37.37-841.66 s^-1) negatively correlated with increasing diameter (r - 0.703, p < .0001).

CONCLUSIONS

We, for the first time, report the successful assessment and quantification of the conjunctival microcirculatory haemodynamics using a smartphone-based system.