Abstract
Purpose :
Laser-induced choroidal neovascularization (CNV) mouse model is one of the most widely used experimental animals for the investigation of age-related macular degeneration (AMD). However, the progression and recovery of CNV by laser-induction varies according to the age of the mouse in terms of its angiogenic and fibrotic reaction. Although the differences in progression of CNV has been widely studied with ex vivo imaging, not much has been studied with in vivo imaging yet. In this study, we present the multi-contrast in vivo imaging characteristics of CNV progression and recovery illustrating the variations in structural, vascular and molecular-specific contrasts based on the age of the mice using a polarization-diversity OCT(PD-OCT) system.
Methods :
Photocoagulation was induced at four different spots in each mouse using a green Argon laser with a center wavelength of 532 nm at the power level of 250 mW for the duration of 100 ms to C57BL/6J mice with two different age groups: young (2-months-old) and old (>7-months-old). The experiments were conducted in accordance with the ARVO statement for the use of animals in ophthalmic and vision research. Sequential in vivo imaging of the mice was conducted until the laser-induced CNV is fully recovered to monitor the progress and recovery of CNV with a custom-built small animal retinal imaging PD-OCT system.
Results :
Preliminarily, we have acquired multi-contrast images of a young mouse 7 days post laser-induction when the CNV growth is maximized. As shown in Figure, the structural deformation of RPE is clearly visible from OCT image while OCTA showing the choriocapillaris bypassing the damaged sites. Degree of polarization uniformity (DOPU) which visualizes the depolarizing components of the outer retina indicates sparsely distributed signal at the damaged sites as shown in the B-scan. The data of old mice and recovery of CNV will be introduced in the presentation.
Conclusions :
In vivo imaging with PD-OCT for visualizing the progress and recovery of CNV allows extracting multi-contrast features without sacrificing the subject. This approach may provide an effective tool for monitoring the progress of CNV and measuring the efficacy of potential treatments for AMD.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.