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M. Ruggeri, J. C. Major, Jr., H. Wehbe, S. Jiao, M. E. Jockovich, C. Cebulla, P. Rosenfeld, G. Tsechpenakis, J. Wang, T. Murray; Advances in High Throughput Small Animal Ocular Imaging With Spectral Domain OCT. Invest. Ophthalmol. Vis. Sci. 2008;49(13):4271.
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© ARVO (1962-2015); The Authors (2016-present)
To present the advances in high throughput in vivo small animal ocular imaging with high resolution Spectral Domain Optical Coherence Tomography (SD-OCT).
An ultrahigh-resolution SD-OCT with two dedicated optical delivery systems for imaging the retina and anterior segment of small animals in vivo was built. An advanced 5-axis animal positioning and alignment system was developed for high throughput applications. An algorithm for automatic segmentation of the tumor boundaries and tumor volume calculation for LHBETATAG mouse model of retinoblastoma was developed.
The OCT system was applied in imaging mice, rats, rabbits, and raptors in the study of various ocular diseases and treatment procedures. One of the exciting applications is that the retina of Broad-winged hawk, Barred owl and Great-horned owl were imaged in vivo for the first time with high quality. The OCT images revealed various fine anatomic layers of the raptor retinas and retinal features like the deep fovea and the pecten. Another example of the applications is that we for the first time monitored the retinal tumor growth in the mouse model of retinoblastoma by imaging the same tumor at 4 time points. In each OCT B-scan image the retinal tumor boundary was automatically segmented and the volume of the tumor at each time point was calculated.
The SD-OCT system accomplished the goal of non-invasive, non-contact, in vivo imaging of small animal retinal structures with high imaging quality and short imaging time (~2 minutes, acquisition time 2.7 seconds). These results make the system suitable for routine high throughput applications. Together with the segmentation algorithm, the acquired 3D data allows quantitative volumetric information extraction and provides means for precise comparison of the images acquired at different time, which make possible longitudinal studies of retinal diseases and treatment effects.
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