September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Modulation of VAMPIRE retinal vasculature analysis software to extend utility and provide secondary value from optical coherence tomography imaging
Author Affiliations & Notes
  • James R Cameron
    University of Edinburgh, Edinburgh, United Kingdom
  • Lucia Ballerini
    University of Edinburgh, Edinburgh, United Kingdom
  • Clare Langan
    University of Edinburgh, Edinburgh, United Kingdom
  • Claire Warren
    University of Edinburgh, Edinburgh, United Kingdom
  • Nicholas Denholm
    University of Edinburgh, Edinburgh, United Kingdom
  • Katie Smart
    University of Edinburgh, Edinburgh, United Kingdom
  • Tom J MacGillivray
    University of Edinburgh, Edinburgh, United Kingdom
  • Footnotes
    Commercial Relationships   James Cameron, None; Lucia Ballerini, None; Clare Langan, None; Claire Warren, None; Nicholas Denholm, None; Katie Smart, None; Tom MacGillivray, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5957. doi:
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      James R Cameron, Lucia Ballerini, Clare Langan, Claire Warren, Nicholas Denholm, Katie Smart, Tom J MacGillivray; Modulation of VAMPIRE retinal vasculature analysis software to extend utility and provide secondary value from optical coherence tomography imaging. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5957.

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

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Abstract

Purpose : We describe how existing and well established retinal vasculature segmentation and measurement software for fundus camera images has been modulated to analyse scanning laser ophthalmoscope retinal images generated by the dual modality Heidelberg Spectralis® OCT instrument. This evolution of the software was then evaluated for reliability of its measurement algorithms.

Methods : Evaluation of our modulated software was performed via a cross-sectional study of SLO retinal images analysed by 2 independent graders. These images were optic disc centred, one eye from each of 78 participants.
Each image was uploaded to VAMPIRE, with the grader manually identifying the optic disc and fovea. The software automatically detects the vessels, and with grader supervision, calculates the standard measures of AVR, CRAE, CRVE, and vessel tortuosity. The two graders were blinded to each other’s process and measurements, with comparison between their results assessed as as an outcome measure of the successful modulation of VAMPIRE.
Inter-grader reliability was assessed using intraclass correlation coefficients (ICC). Statistical analyses were performed using MedCalc for Windows, version 15.11 (MedCalc Software, Ostend, Belgium).

Results : Of the 78 images available, 4 were not analysed due to insufficient image quality or insufficient vessel selection.
Each grader analysed the images independently, recording values for AVR, CRAE, CRVE, arteriolar tortuosity and venous tortuosity.
The intraclass correlation coefficients for inter-grader reliability were: AVR – 0.961 (95% confidence interval (CI) 0.939-0.975), CRAE – 0.936 (95% CI 0.900-0.959), CRVE – 0.961 (95% CI 0.938-0.975), arteriolar tortuosity – 0.955 (95% CI 0.930-0.971) and venular tortuosity – 0.958 (95% CI 0.934 – 0.973).
This demonstrates very high reliability and repeatability of these vasculature measurements with the modulated software.

Conclusions : We have successfully modulated the VAMPIRE software to analyse the SLO retinal images acquired by the SPECTRALIS® OCT machine. In addition, our initial evaluation has demonstrated a high reliability of the vascular measurements that can be made on these images. This development of retinal image analysis holds tremendous potential for use as part of multi-modal retinal analysis, from one single patient acquisition, using the patient-friendly OCT device.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

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