June 2015
Volume 56, Issue 7
ARVO Annual Meeting Abstract  |   June 2015
VESGEN Analysis of Generational Branching Patterns in Arteries and Veins for Investigating Diabetic Retinopathy by Spectralis® Angiographic Imaging
Author Affiliations & Notes
  • Patricia A Parsons-Wingerter
    Space Biosciences Research Branch, NASA Ames Research Center, Moffett Field, CA
  • Krishnan Radhakrishnan
    Internal Medicine, University of Kentucky, Lexington, KY
  • K V Chalam
    Ophthalmology, University of Florida, Jacksonville, FL
  • Maria B Grant
    Ophthalmology, Glick Eye Institute, Indiana University, Indianapolis, IN
  • Footnotes
    Commercial Relationships Patricia Parsons-Wingerter, NASA (P); Krishnan Radhakrishnan, None; K V Chalam, None; Maria Grant, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 5960. doi:
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      Patricia A Parsons-Wingerter, Krishnan Radhakrishnan, K V Chalam, Maria B Grant; VESGEN Analysis of Generational Branching Patterns in Arteries and Veins for Investigating Diabetic Retinopathy by Spectralis® Angiographic Imaging. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):5960.

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

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Purpose: We hypothesize that site-specific patterning within branching generations of arterial and venous trees in the human retina can be mapped and quantified by VESsel GENeration Analysis (VESGEN) software. Using images acquired by 30° Spectralis® fluorescein angiography (FA), we demonstrate that the methodology may be useful for analysis of longitudinal progression of diabetic retinopathy (DR).

Methods: The retina of a patient diagnosed with mild nonproliferative DR was photographed at 12.5μm/pixel with 30° Heidelberg Spectralis® imaging following fluorescein injection. Binary (black/white) vascular patterns of branching arterial and venous trees were extracted from the grayscale photograph (768✕768 pixels) as described previously for 50° FA (IOVS 2010, 51:498). The resulting arterial and venous images served as sole inputs to the VESGEN software. The vascular patterns were automatically mapped by VESGEN to generate vessel branching generations (Gx) and to quantitatively analyze them by computing numerous vascular parameters, including the densities of vessel length (Lv), area (Av), number (Nv), and the fractal dimension (Df). Results for the branching generations were further assigned by VESGEN into two groups of large (G1-3) and small (G≥4) vessels.

Results: Lv1-3 and Av1-3 were 5.02E-4 μm/μm2 and 4.50E-2 μm2/μm2 for large arteries, and 5.42E-4 μm/μm2 and 4.85E-2 μm2/μm2 for large veins. For small arteries, Lv≥4 and Av≥4 were 9.26E-4 μm/μm2 and 3.37E-2 μm2/μm2, compared to 1.10E-3 μm/μm2 and 4.41E-2 μm2/μm2 for small veins. Trends for Av and Lv were confirmed by Df and Nv. Agreement among these several key parameters reveal that the density of small veins was greater than that of small arteries.

Conclusions: Our study supports the future feasibility of VESGEN analysis for highly sensitive mapping and quantification of remodeling of retinal arterial and venous trees from clinical images obtained by 30° Spectralis® fluorescein angiography. The VESGEN mapping methodology will support evidence-based conclusions for ongoing longitudinal studies on how and where site-specific remodeling occurs and progresses within the human retina.


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