April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
VESGEN Analysis of Fractal-Based Branching in Arterial and Venous Trees for Investigating Diabetic Retinopathy with Spectralis® Angiographic Imaging
Author Affiliations & Notes
  • Krishnan Radhakrishnan
    Department of Preventive Medicine and Environmental Health, College of Public Health, University of Kentucky, Lexington, KY
  • Patricia A Parsons-Wingerter
    Research and Technology Directorate, NASA Glenn Research Center, Cleveland, OH
  • Kakarla V Chalam
    Department of Ophthalmology, University of Florida, Jacksonville, FL
  • Robert N Mames
    The Retina Center, Gainesville, FL
  • Christine Kay
    Department of Ophthalmology, University of Florida, Jacksonville, FL
  • Maria Grant
    Department of Ophthalmology, Glick Eye Institute, Indiana University, Indianapolis, IN
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 275. doi:
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      Krishnan Radhakrishnan, Patricia A Parsons-Wingerter, Kakarla V Chalam, Robert N Mames, Christine Kay, Maria Grant; VESGEN Analysis of Fractal-Based Branching in Arterial and Venous Trees for Investigating Diabetic Retinopathy with Spectralis® Angiographic Imaging. Invest. Ophthalmol. Vis. Sci. 2014;55(13):275.

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

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Abstract
 
Purpose
 

We hypothesized that site-specific features within the branching generations of arterial and venous trees imaged by 30° Spectralis® fluorescein angiography (FA) can be mapped and quantified by VESsel GENeration Analysis (VESGEN) software, and that this methodology would be useful for longitudinal analysis of diabetic retinopathy (DR) progression.

 
Methods
 

The retina of a patient diagnosed with mild nonproliferative DR was photographed at12.5 μm/pixel with 30° Heidelberg Spectralis® imaging following injection of fluorescein (Fig 1). Binary (black/white) vascular patterns of the branching arterial and venous trees were extracted from the photograph (768x768 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 analyzed to first map vessel branching generations (Gx, Fig 2) and then to quantify the resulting vascular maps by vascular parameters that include the fractal dimension (Df), vessel number (Nv), and densities of vessel length (Lv) and area (Av). Branching generations mapped by VESGEN were further assigned into two groups of large and small vessels.

 
Results
 

Overall vascular density by Df was 1.57 for the arterial tree and 1.60 for the venous tree. Nv1-3 was 21 for large arteries and 15 for large veins (Figure 1). For small arteries, Nv≥4 was 161, compared to 234 for small veins. Trends for Df and Nv were confirmed by Av and Lv. Several key parameters revealed that the density of small veins was greater than that of small arteries.

 
Conclusions
 

Our study demonstrates the feasibility of VESGEN analysis for mapping and quantifying the remodeling of arterial and venous trees during progressive DR from clinical images obtained by 30° Spectralis® fluorescein angiography. This methodology will enable evidence-based conclusions for ongoing longitudinal studies on how and where site-specific remodeling occurs and progresses within retinal vasculature.

 
 
Fig 1 Spectralis® image of patient diagnosed with mild NPDR.
 
Fig 1 Spectralis® image of patient diagnosed with mild NPDR.
 
 
Fig 2 Branching generations in the arterial and venous trees (legend, G1-G7) mapped by VESGEN according to weighted vascular rules for bifurcational branching, vessel diameter and tapering, and fluid mechanics of laminar blood flow. All mapped vessels enlarged slightly to visualize the small vessels.
 
Fig 2 Branching generations in the arterial and venous trees (legend, G1-G7) mapped by VESGEN according to weighted vascular rules for bifurcational branching, vessel diameter and tapering, and fluid mechanics of laminar blood flow. All mapped vessels enlarged slightly to visualize the small vessels.
 
Keywords: 688 retina • 499 diabetic retinopathy • 550 imaging/image analysis: clinical  
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