June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Developments in Optical Coherence Tomography Imaging in a Rat Model of Glaucoma
Author Affiliations & Notes
  • Jean-Remi Fenolland
    Ophthalmology, Val de Grace Military Hospital, Paris, France
    Team S12, Vision Institute, UPMC University Paris 6; UMRS968 INSERM; UMR7210 CNRS, Paris, France
  • Céline Boucher
    Team S12, Vision Institute, UPMC University Paris 6; UMRS968 INSERM; UMR7210 CNRS, Paris, France
  • Markus Mayer
    Pattern Recognition Lab, University of Erlangen-Nuremberg, Nuremberg, Germany
  • William Rostene
    Team S12, Vision Institute, UPMC University Paris 6; UMRS968 INSERM; UMR7210 CNRS, Paris, France
  • Christophe Baudouin
    Team S12, Vision Institute, UPMC University Paris 6; UMRS968 INSERM; UMR7210 CNRS, Paris, France
    Quinze-Vingts National Ophthalmology Hospital, Paris, France
  • Alexandre Denoyer
    Team S12, Vision Institute, UPMC University Paris 6; UMRS968 INSERM; UMR7210 CNRS, Paris, France
    Quinze-Vingts National Ophthalmology Hospital, Paris, France
  • Footnotes
    Commercial Relationships Jean-Remi Fenolland, None; Céline Boucher, None; Markus Mayer, None; William Rostene, None; Christophe Baudouin, None; Alexandre Denoyer, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 4833. doi:
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      Jean-Remi Fenolland, Céline Boucher, Markus Mayer, William Rostene, Christophe Baudouin, Alexandre Denoyer; Developments in Optical Coherence Tomography Imaging in a Rat Model of Glaucoma. Invest. Ophthalmol. Vis. Sci. 2013;54(15):4833.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: Optical Coherence Tomography (OCT) is a powerful imaging procedure widely used in clinical practice. In research, however, no accurate optical solution was available to perform OCT in rats. Moreover, there was no tool to assist the researcher in measuring in vivo the thickness of retinal layers, especially the nerve fiber layer (RNFL). This study aimed to evaluate OCT imaging of anterior and posterior segments and to develop an automated segmentation of retinal layers in a rat model of glaucoma.

Methods: Twenty male Long Evans rats with surgically induced glaucoma were followed during 2 months. OCT Envisu ™ and its acquisition software InVivoVue Clinic (Biotigen corporation, SC, USA) were used. Imaging was performed with a new optical system fitted to rat eye characteristics. For the anterior segment imaging, a dedicated telecentric lens was used. Acquisitions were performed at the corneal apex for anterior chamber depth (ACD) measurement. Animal was then moved using stereotaxic device toward the limbus in order to measure the iridocorneal angle (ICA). For retinal imaging, 1-mm diameter circle scans centered on the optic nerve were performed. Axial and lateral resolutions were of 2 µm and 5 μm respectively. An innovative semi-automatic segmentation of retinal layers was developed through OCTSEG software.

Results: Corneal stromal thickness was 116±18 μm and epithelial thickness was 44±7 μm. ACD was 0.75±0.05 mm and AIC was measured at 11.4±3°, further confirming the absence of angle closure and consistently with what obtained by UltraBio Microscopy. At the posterior pole, 2-month ocular hypertension was found to be associated with significant RNFL thinning as compared to normotensive control eyes (25.4 ± 1.8 µm vs 29.1 ± 1.3 µm respectively, P<0.001), which was considered as an early stage of glaucomatous neuropathy.

Conclusions: OCT may become an indispensable tool to evaluate chronic glaucoma models in animal. Anterior segment OCT can precise the corneal/iridocorneal changes and thus the true mechanism of hypertension on the one hand. Retinal imaging and automated layer segmentation is a new and only way to monitor in vivo the retinal changes on the other hand. Here we also report that it could detect an early thinning of the RNFL in our glaucoma model, further emphasizing the importance of this imaging process in animal research.

Keywords: 552 imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • 568 intraocular pressure • 610 nerve fiber layer  
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