Investigative Ophthalmology & Visual Science Cover Image for Volume 59, Issue 9
July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Detection of early microvascular retinal changes in type I diabetic mice with OCT-Angiography
Author Affiliations & Notes
  • Hironori Uehara
    University of Utah, Salt Lake City, Utah, United States
  • Timilai Lesuna
    University of Utah, Salt Lake City, Utah, United States
  • Balamurali K Ambati
    University of Utah, Salt Lake City, Utah, United States
  • Footnotes
    Commercial Relationships   Hironori Uehara, None; Timilai Lesuna, None; Balamurali Ambati, None
  • Footnotes
    Support  2R01EY17182
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 5817. doi:
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    • Get Citation

      Hironori Uehara, Timilai Lesuna, Balamurali K Ambati; Detection of early microvascular retinal changes in type I diabetic mice with OCT-Angiography. Invest. Ophthalmol. Vis. Sci. 2018;59(9):5817.

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

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Abstract

Purpose : Detection of early diabetic retinopathy can be very helpful in initiating appropriate treatment. In this study, we sought to determine whether Optical Coherence Tomography Angiography (OCTA) can detect early vascular abnormalities in type I diabetic mice.

Methods : 6-8 month old male type 1 diabetic Ins2 Akita/+ and age matched C57BL6/J mice were used. OCTA was performed by Heidelberg SPECTRALIS OCT Angiography Module with 30 degree lens + mouse adapter lens. After anesthetizing mouse with ketamine/xylazine, 1% tropicamide was applied on eyes to dilate the pupil. Then, Canter-Nissel contact lens (BOZR 1.70, DIAM 3.20, PWR 0.00) was mounted to avoid corneal drying and obtain clear image. We acquired the OCTA image from the peripheral nasal position. We analyzed vascular volume density from the retinal surface (inner limiting membrane) to 120um depth with 4um steps in order to obtain vascular volume density vs depth (N=4 each group).

Results : Vascular volume density of both mouse strains showed three different peaks. By comparing with the OCT image, the first peak (surface), second peak (intermediate) and third peak (deep) were located in nerve fiber layer/ganglion cell layer, inner plexus layer/inner nuclear layer and outer plexus layer/outer nucleus layer, respectively. We calculated vascular volume density of these peaks separately. In the first peak, the vascular volume density was 14.3 ± 3.5 % (±S.D, diabetic Ins2 Akita/+) and 14.3 ± 5.9 % (control) (no significant difference). In the second peak, the vascular volume density showed 13.9 ± 5.4 % (diabetic Ins2 Akita/+) and 17.0 ± 3.8 % (control) (no significant difference). In the third peak, the vascular volume density showed 7.9 ± 2.8 % (diabetic Ins2 Akita/+) and 19.0 ± 2.0 % (control) (p<0.01 by student t-test). Also, total vascular volume density was 10.7 ± 3.2 % (diabetic Ins2 Akita/+) and 17.2 ± 2.0 % (control) (p<0.05).

Conclusions : OCTA successfully detect the retinal vascular alteration between type I diabetic mice and control mice. The diabetic mice showed the reduced vascular volume density especially in the deep vessels. Importantly, we detect the difference without retinal blood leakage/hemorrhage/neovascularization. Our analysis (vascular volume density vs retinal depth) could be useful to detect early diabetic retinopathy phenotypes.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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