June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
In vivo retinal vascular wall imaging in patients with diabetic retinopathy using non-confocal Split Detection Adaptive Optics Scanning Light Ophthalmoscopy
Author Affiliations & Notes
  • Nikhil Menon
    Department of Ophthalmology, New York Eye and Ear Infirmary of Mount Sinai, New York, NY
    Icahn School of Medicine at Mount Sinai, New York, NY
  • Nadim Choudhury
    Department of Ophthalmology, New York Eye and Ear Infirmary of Mount Sinai, New York, NY
    Icahn School of Medicine at Mount Sinai, New York, NY
  • Toco Yuen Ping Chui
    Department of Ophthalmology, New York Eye and Ear Infirmary of Mount Sinai, New York, NY
    Icahn School of Medicine at Mount Sinai, New York, NY
  • Alexander Pinhas
    Department of Ophthalmology, New York Eye and Ear Infirmary of Mount Sinai, New York, NY
    Icahn School of Medicine at Mount Sinai, New York, NY
  • Yusufu N B Sulai
    Department of Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
  • Alfredo Dubra
    Department of Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
    Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI
  • Richard B Rosen
    Department of Ophthalmology, New York Eye and Ear Infirmary of Mount Sinai, New York, NY
    Icahn School of Medicine at Mount Sinai, New York, NY
  • Footnotes
    Commercial Relationships Nikhil Menon, None; Nadim Choudhury, None; Toco Chui, None; Alexander Pinhas, None; Yusufu Sulai, None; Alfredo Dubra, Canon USA Inc. (C), RPB Career Development Award (F), US Patent No: 8,226,236 (P); Richard Rosen, Advanced Cellular Technologies (C), Allergan (C), Carl Zeiss Meditech (C), Clarity (C), OD-OS (C), Opticology (I), Optovue (C)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 5300. doi:
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    • Get Citation

      Nikhil Menon, Nadim Choudhury, Toco Yuen Ping Chui, Alexander Pinhas, Yusufu N B Sulai, Alfredo Dubra, Richard B Rosen; In vivo retinal vascular wall imaging in patients with diabetic retinopathy using non-confocal Split Detection Adaptive Optics Scanning Light Ophthalmoscopy. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):5300.

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

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Abstract

Purpose: To measure lumen diameter and wall thickness of perfused retinal vasculature, and to quantify changes in diabetic retinopathy (DR) relative to healthy control eyes.

Methods: The retinal vasculature of 5 subjects with DR [2 background DR (BDR), 1 nonproliferative DR (NPDR), 2 proliferative DR (PDR)] secondary to type II diabetes mellitus (mean age 54, range 41-62; mean HbA1c 8.2) and 5 healthy control subjects (mean age 31, range 25-55, mean HbA1c 5.2) was imaged with non-confocal split detection adaptive optics scanning light ophthalmoscopy (SD AOSLO; Scoles et al., 2014) using 790 nm light. Images of arterioles and venules along the retinal vascular arcades starting at the optic disc margin, as well as of the capillaries adjacent to the foveal avascular zone were acquired. After sinusoidal distortion and eye motion were removed, lumen diameter, vessel wall thickness, and wall to lumen ratio (WLR) were estimated in averaged images semiautomatically using custom Matlab software (MathWorks, Natick, MA) (Hillard et al, IOVS 2013. E-Abstract 6061).

Results: Lumen (diameter) of arterioles and venules ranged between 8 and 135 μm. Mean ±SD of arteriolar wall thickness in DR subjects was 14±2 μm (range 5-27) as compared to 12±2μm (range 5-23) in controls (p<0.07). Mean±SD venular wall thickness was 9±1 μm (range 5-18) in DR as compared to 8±1 μm (range 4-17) in controls (p=0.50). DR subject eyes had significantly higher arteriolar WLR than control eyes (mean±SD: 0.35±0.06 vs. 0.26±0.03, unpaired t test, p<0.03). The same was also true of venular WLR in DR subject eyes as compared to controls (mean±SD: 0.19±0.03 vs. 0.15±0.02, unpaired t test, p<0.02).

Conclusions: Microscopic non-invasive imaging of the fine retinal vasculature using SD AOSLO allows quantification of lumen and wall thickness. This technique has potential both for early detection of DR, as well as accurate monitoring of progression and personalizing treatment.

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