In Vivo Vascular Injury Readouts in Mouse Retina to Promote Reproducibility
April 21st, 2022
Here, we present three data analysis protocols for fluorescein angiography (FA) and optical coherence tomography (OCT) images in the study of Retinal Vein Occlusion (RVO).
This protocol allows the user to quantitatively measure clinically analogous markers of damage in mouse retinal imaging, which bolsters the translatability of subsequent findings. These methods allow us to streamline analysis and give us the ability to reliably compare imaging between experimental animals. While these methods were developed to study a mouse model overview, they can easily extend to research on any retinal diseases that use the same imaging techniques.
Turn the retinal imaging microscope light box, the optical coherence tomography machine, and the heated mouse platform on. Turn the computer on and open the imaging program. Add one drop of phenylephrine and tropicamide to each eye.
Inject 100 microliters of 1%fluorescein intraperitoneal. Accommodate the mouse on the platform. Adjust the height and angle of the platform until the view of the retinal fundus is clear and focused.
Take a picture of the fundus. Open the imaging and optical coherence tomography software. In the optical coherence tomography program adjust nudge to 10.
Take an optical coherence tomography image, add 75 micrometers distal from the burn. Repeat for the other three quadrants of the retina. Switch the camera to a 488 nanometer filter.
Increase the camera gain to 5. Take a picture of the fundus exactly 5 minutes after fluorescein injection. Open the fluorescein image on the image processing software.
Duplicate the image. Using a selection tool, carefully trace the major vessels. Ignore any vessels branching out from these vessels.
In the first image, delete the selection, leaving only the vessel. Save this masked image. Move the selection to the second image, invert the selection and delete, isolating the background.
Save this masked image. Open the background image and measure the integrated density. Open the vessels image, select the outline of the vessels, and then measure the mean intensity.
Divide the integrated density of the background by the mean intensity of the vessels, generating the leakage ratio for the eye. Record this leakage ratio for each eye in an experimental cohort. To further control for background, normalize experimental eyes to the mean leakage ratio of uninjured control eyes.
Open the optical coherence tomography image in the image processing software. Trace the borders of the ganglion cell layer, inner plexiform layer, inner nuclear layer, outer plexiform layer, photoreceptor layer, and RPE layer. Export the files as CSV.
Measure the mean thickness of each layer and repeat for each eye in the experimental cohort. Open the optical coherence tomography image in image J.Using the line tool, measure the distance where the upper border of the outer plexiform layer is indistinct. Measure horizontally, maintaining the latitude where the disorganization begins.
Calculate the sum of the disorganized distances in the image. Divide the length of disorganization by the total length of the retina to obtain the ratio of disorganization. Repeat the measurement and calculation for optical coherence tomography images from the other three quadrants of the retina.
Take the mean of the ratios of disorganization from the four optical coherence tomography images. This number represents the average disorganization for the whole retina. Repeat for each eye in the experimental cohort.
The masked images used for the calculation of ratio of leakage for each retina image can be compared to others and analyzed, separating the major vasculature from other areas of the retina. Fluorescein quantification allows for the comparison of injury severity and treatment efficacy as well as the study of changes in leakage over the injury time course. A delineation of the layers of the retina in an OCT image is observed.
The quantification of thickness for each retinal layer shows that the initial edematous response has a more profound effect on the internal retinal layers. From an analysis of a time course of retinal vein occlusion damage, the initial inflammatory swelling of retinal layers, and the eventual degenerative thinning can be observed. The inner nuclear layer experiences a much greater response to the initial injury, but the inner plexiform layer demonstrates more severe thinning after the initial edema has been stabilized and returns to baseline.
The disorganization of inner retinal layer manifests as a disappearance of the upper boundary of the outer plexiform layer, blending the outer plexiform and inner nuclear layers together. The retinal disorganization of two experimental groups were compared to investigate the efficacy of an inhibitor in mitigating retinal damage. Image quality is vitally important to analysis quality.
When acquiring retinal images, take the time to ensure that the fundus and retinal layers are as clear and focused as possible. These non-invasive methods can be used longitudinally and in conjunction with biochemical and immunohistochemical study of tissue to create more multifaceted and detailed profiles of disease. This technique enables the reliable quantification of in Vivo retinal imaging data in models of neurovascular disease so that data can be more readily translated to human disease.
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Overview
This study presents three data analysis protocols for analyzing fluorescein angiography (FA) and optical coherence tomography (OCT) images to investigate Retinal Vein Occlusion (RVO) in a mouse model. The methodologies enable quantitative measurement of retinal damage markers, facilitating comparison of imaging outcomes between experimental animals and enhancing translatability of findings.
Key Study Components
Area of Science
- Neuroscience
- Ophthalmology
- Imaging Techniques
Background
- Retinal Vein Occlusion (RVO) can lead to significant retinal damage.
- Fluorescein angiography and optical coherence tomography are vital imaging techniques in retinal studies.
- Understanding RVO allows for development of therapeutic strategies.
- Quantitative analysis enhances cross-comparison of retinal health across different study groups.
Purpose of Study
- To establish protocols for retinal imaging analysis in RVO research.
- To enhance the reliability of imaging data comparisons between experimental cohorts.
- To quantify injury severity and treatment efficacy over time.
Methods Used
- Mouse model used for studying retinal conditions.
- Fluorescein injection and OCT imaging techniques are detailed.
- Image processing methods include measurement of retinal layer thickness and leakage ratios.
- Crucial steps involve meticulous image acquisition and processing to ensure clarity and focus.
Main Results
- Quantified retinal responses to injury showed greater impact on inner retinal layers during initial phases.
- Fluorescein leakage quantification provided insights into the severity of retinal damage and the effectiveness of treatments.
- Analysis highlighted significant disorganization across retinal layers in response to RVO.
- Longitudinal imaging revealed progression from edema to degenerative changes in retinal structure.
Conclusions
- The study demonstrates effective protocols for quantifying RVO-related retinal damage.
- Longitudinal imaging combined with biochemical analyses provides a comprehensive profile of retinal disease progression.
- Findings contribute to understanding retinal disease mechanisms and potentially inform treatment strategies.
Frequently Asked Questions
Executive Industry Relevance
Quantitative in vivo retinal imaging readouts in mouse models enable reproducible assessment of neurovascular injury, directly aligning preclinical data with clinical ophthalmic endpoints. Standardized OCT and fluorescein angiography outputs support translational continuity, facilitating robust comparison of therapeutic effects and disease mechanisms across experimental cohorts. This approach strengthens predictive confidence at the discovery-to-preclinical inflection point for vascular-targeted drug portfolios.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Quantitative imaging readouts clarify vascular injury mechanisms and therapeutic hypothesis testing.
- Layer-specific retinal measurements enable functional target validation and biological de-risking.
- Standardized outputs support predictive confidence and portfolio triage for vascular and neurodegenerative targets.
Screening & Assay Development
- Validated imaging protocols prepare animal models for reproducible downstream efficacy studies.
- Quantitative leakage and disorganization metrics enable assay standardization and cross-study comparability.
- Imaging-derived endpoints facilitate reliable evaluation of candidate interventions in preclinical screens.
Translational & Preclinical Research
- Clinically analogous imaging endpoints bridge preclinical findings to human disease phenotypes.
- Longitudinal, noninvasive imaging supports risk-adjusted advancement decisions and translational biomarker alignment.
- Quantitative analysis of injury progression informs mechanistic de-risking and therapeutic window identification.
Pipeline & Workflow Integration
This imaging workflow integrates from early discovery through preclinical validation, supporting lead identification and translational research in vascular and neurodegenerative disease pipelines.
- Discovery Biology: Enables hypothesis testing and mechanistic clarification via quantitative vascular injury markers.
- Screening: Provides reproducible, quantitative imaging endpoints for assay readiness and compound evaluation.
- Analytics: Delivers standardized leakage ratios and layer thickness measurements for robust statistical comparison.
- Translational Research: Aligns animal model outputs with clinical imaging standards for preclinical-to-clinical continuity.
- Enterprise Reuse: Imaging protocols are adaptable across retinal disease models using OCT and fluorescein angiography.
Operational & Enterprise Impact
- Scientific Value: Enhances predictive confidence and reduces mechanistic ambiguity in vascular injury models.
- Operational Value: Promotes standardization, reproducibility, and scalability of imaging-based endpoints.
- Strategic Value: Supports informed go/no-go decisions and capital-efficient portfolio management.
- Portfolio Impact: Enables risk-adjusted prioritization and advancement of vascular-targeted assets.
Implementation Considerations
- Requires expertise in retinal imaging acquisition and quantitative image analysis.
- Needs access to OCT, fluorescein angiography, and compatible image processing software.
- Demands rigorous cross-team standardization of imaging protocols and analysis criteria.
- Adaptable to various retinal disease models using similar imaging modalities.
- Image quality and consistency are critical for reliable data and downstream decision-making.
