June 2015
Volume 56, Issue 7
ARVO Annual Meeting Abstract  |   June 2015
Automated measurement of vascular parameters in mouse retinal flat-mounts
Author Affiliations & Notes
  • Behzad Aliahmad
    RMIT University, Melbourne, VIC, Australia
  • Dinesh Kant Kumar
    RMIT University, Melbourne, VIC, Australia
  • Marc Sarossy
    Royal Victorian Eye and Ear Hospital, Melbourne, VIC, Australia
  • Elsa Chan
    Centre for Eye Research Australia & Department of Ophthalmology, The University of Melbourne, Melbourne, VIC, Australia
  • Peter Van Wijngaarden
    Centre for Eye Research Australia & Department of Ophthalmology, The University of Melbourne, Melbourne, VIC, Australia
  • Footnotes
    Commercial Relationships Behzad Aliahmad, None; Dinesh Kumar, None; Marc Sarossy, None; Elsa Chan, None; Peter Wijngaarden, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 3324. doi:
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      Behzad Aliahmad, Dinesh Kant Kumar, Marc Sarossy, Elsa Chan, Peter Van Wijngaarden; Automated measurement of vascular parameters in mouse retinal flat-mounts. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):3324.

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

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Geometric changes of the retinal vasculature may precede or form part of the pathophysiology of eye diseases such as diabetic retinopathy or retinal vascular occlusion. Quantitative vasculature parameters are used clinically and in research for risk assessment, disease monitoring and as markers of therapeutic efficacy. This study describes a new method for rapid automated measurement of vascular geometric parameters within a selectable region. Baseline measurements for the adult C57BL/6J mouse retina are defined.


Retinal flat-mounts were prepared from adult C57BL/6 mice, stained with fluorophore-conjugated isolectin B4, and imaged by confocal microscopy. Animal care guidelines of the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research were followed and all procedures were approved by the institutional animal care and use committee (St Vincent’s AEC protocol SABC001). 8 retinal flat-mounts 4900×5800 pixels were obtained and corrected for uneven illumination. Images were binarized using an SVM classifier. Vessel bifurcations and crossover points were automatically detected using a novel backward morphological shrinking operation as shown in Figure 1. Flat-mount images were partitioned into 5 non-overlapping regions 1200×1200 pixels centred on the optic disc (OD) and each retinal quadrant (RQ). Vascular parameters including the branching angles (value and count), vessel to background (V/B) ratio and fractal dimension (FD), were obtained for each region.


FDs for OD (mean±SD=1.522 ± 0.012) and RQ (1.526 ± 0.021) regions were similar. Similarity was also found in V/B ratio (OD=18.86 ± 1.54 %, RQ= 18.80 ± 2.83%). However, OD had fewer branch points (bp) (255± 39.55) and acute angle(aa) (88.64± 24.08 degrees) compared to RQ (bp=355.5±97.71, aa =92.16 ± 21.09).


This novel technique provides a fast, automated and reliable method for quantification of vascular parameters including estimates of the mean and variance of branching angles which is not feasible manually or by other software modules such as VESGEN (VESsel GENeration Analysis. Also unlike VESGEN, our method does not require a binary vascular image as the input and works with any grayscale image format. The reliable quantification of retinal vascular parameters is likely to be of value to studies of retinal vascular disease, including angiogenesis, and putative therapies for these disorders.  


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