Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies

The overall goal is to assess the response of the cardiovascular system to lifestyle factors and environmental exposures, such as air pollution, using fundus photography to visualize the retinal blood vessels in order to measure cardiovascular changes. This is achieved by repeated visualization of the retinal blood vessels in a panel of healthy adults over a four month period, including an episode of high air pollution. As a second step, retinal image analysis is performed using a semi-automated software to calculate the central retinal ARTERIOLAR equivalent or CRAE and the central retinal ULAR equivalent or CRVE as proxies for microvascular responses.

Next, statistical analysis is performed using linear mixed models. In order to investigate the association between the retinal microvasculature and air pollution exposure, the results show a statistically significant decrease in CRAE and CRVE in healthy adults during a period of increased air pollution. The results indicate that the retinal microvasculature has a fast response to air pollution.

This method can help answer questions in the field of public health research and more specifically cardiovascular epidemiology. Measuring response of the smallest blood vessels in the retina is considered helpful to detect early effects that may be on the trajectory to disease development. Our approach to public health studies focuses on tracking individuals, so we try to reduce the burden for participants to keep attrition rates.

Low retinal imaging is a non-invasive and convenient technique that fits perfectly in this philosophy. This technique can even be used to study microvascular changes in vulnerable groups such as young children and elderly people, Lin Provost and Tes Luis. Both researchers in the field of cardiovascular epidemiology will be doing the demonstrations.

Lin will demonstrate the procedure of taking fundus photograph and TE will perform image analysis to characterize diameters of the blood vessels. Begin this procedure by removing the protection cells from the main block of the unit and the digital retinal camera. Open the battery compartment and place the battery in the camera.

Do not disconnect the wire connecting the battery and the main unit. Next, screw the camera onto the main unit and connect the two wires to it. After that, connect the main unit to the power grid.

Enter the computer with the supplied USB cables. Turn on the main unit in the camera, then turn on the computer. Now open the retinal imaging control software.

Then click the study icon in the upper left part of the screen for a new patient. Fill in all the details such as patient id, patient name, date of birth, et cetera. If the patient is already in the system, fill in the patient ID and use the search history list.

Double click the name of the patient to start the study. Next, ask the patient to take a seat before the camera. Place his or her chin on the chin, rest and forehead against the forehead.Rest.

Then lock the head to take a photograph. After that, ask the patient to look straight into the lens of the camera. Move the camera in horizontal plane to the right or left eye.

Then use the chin rest to position the patient's cornea inside the two circles that appear on the camera display fine. Tune by using the wheel on the joystick. Next, move the camera forward, backward, and sideways in the XY plane.

In order to position the patient's pupil within the circles, make sure the pupil forms a continuous circle. Then use the back trigger on the joystick to switch the focus from the cornea to the retina. At this stage, the patient should observe a green light.

Ask the patient to look at the green light to focus the camera. Align the two lines that pop up by turning the wheel at the base of the joystick. Turn the wheel until the two lines form a continuous line.

Subsequently, use the green light to place the eye in the optimal position for a photograph if required, move the light using the arrow buttons at the right side of the camera. Position the green light in a way that the optic disc is centered on the camera display. Now search for two white spots, which appeared after switching to the retina.

To find the spots, move the unit in the XY plane using the joystick for fine tuning, the spots are visible as blurry stains. Move the unit forward or backward until the blurry stains turn into bright white spots. The brighter and round of the spots the better the quality of the picture.

After positioning the spots until both are visible, use the little will on the joystick to bring the spots to the middle of the camera display. Confirm that the two lines form a continuous line. The optic disc is centered on the camera display and is flanked by two bright white spots.

Take the retinal photograph by pressing the button on top of the joystick afterward. Save the photograph by clicking the study complete button on the lower right corner of the computer screen. Completing study will automatically save the pictures in a map.

In this procedure, determine the scale ratio by measuring the distance between the center of the macular and the center of the optic disc in pixels, and this distance is determined to be 4, 500 microns or 2.5 times the diameter of the optic disc. With the latter being approximately 1, 800 microns, calculate the scale ratio by dividing 4, 500 by the average distance between the macular and the blind spot. Next, open the retinal vessel analysis software Ivan.

Fill in the scale ratio and proceed to the configuration. Then verify that three yellow rings appear on the retinal photograph. The scale ratio determines the radius of the inner circle that encloses the optic disc.

In addition, verify that the middle point of the inner ring is on the middle point of the optic disc. If this is not the case, adjust the location of the circle by using the cursor keys. The radii of the middle and outer circles are two and three times respectively larger than the radius of the inner circle.

In this way, zones A and B are created at a fixed distance from the optic disc. Check that the retinal image has the optic disc in the center of the photograph. This ensures a sharp focus of the image in zone B and will facilitate the grading process.

The software will automatically detect the blood vessels and assign these vessels as vees. Distinguish the vessels between arterials and vees based on physiological differences. Arterials are indicated in red and vees in blue.

Use the software tools to select vessels that were not selected by the software. The same rules apply for these vessels. As for the vessels automatically selected by the software, then determine central retinal arteriolar and ular equivalent in Ivan and calculate the CRAE and CRVE from their respective branching daughter vessels.

This figure shows the estimated change in means CRAE and CRVE in association with a 10 microgram per meter cubed increase in PM 10 or a one microgram per meter cubed. Increase in BC for different exposure lags. These data were obtained from a panel of 84 persons Once master this procedure can be done in less than five minutes during field work.

Because of its convenience, we can easily collect repeated measures over both short and long time periods, and this allows us to follow up effects over time while controlling for individual variability. So each participant serves as its own control. Retinal imaging can be used for assessing the effects of environmental factors such as air pollution and lifestyle factors such as diet and physical activity.

On the microvasculature, changes in vessel caliber have been shown to be a predictor of cardiovascular events. We believe that the micro circulation can differentiate between healthy and unhealthy aging. Also, the microcirculation is associated with early onset of diseases, for instance, early diabetes, but also early Alzheimer's disease.

We are currently developing new analysis software that will extract additional geometric features from retinal images. Automation of our analysis pipeline will also reduce the time to result, and our ambition is to develop a mobile platform for decentralized preclinical screening with applications in the broad field of healthcare.