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Correlation between retinal vessel density profile and circumpapillary RNFL thickness measured with Fourier-domain optical coherence tomography
  1. Ivania Pereira1,
  2. Stephanie Weber1,
  3. Stephan Holzer1,
  4. Hemma Resch1,
  5. Barbara Kiss1,
  6. Georg Fischer2,
  7. Clemens Vass1
  1. 1Department of Ophthalmology & Optometry, Medical University Vienna, Vienna, Austria
  2. 2Center for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management and Imaging, Medical University Vienna, Vienna, Austria
  1. Correspondence to Professor Clemens Vass, Department of Ophthalmology and Optometry, Medical University of Vienna, General Hospital, Währinger Gürtel 18-20, Vienna A-1090, Austria; clemens.vass{at}meduniwien.ac.at

Abstract

Aim To assess circumpapillary retinal vessel density (RVD) profiles and correlate them with retinal nerve fibre layer (RNFL) thickness measured by Fourier domain optical coherence tomography (FD-OCT).

Methods RNFL thickness of 106 healthy volunteers was measured using Cirrus FD-OCT. A proprietary software was developed in MATLAB to assess the thickness and position of circumpapillary retinal vessels using the scanning laser ophthalmoscopy fundus image, centred on the optic disc. The individual retinal vessel positions and thickness values were integrated in a 256-sector RVD profile, and intrasubject and intersubject correlations were calculated.

Results The mean value±SD for intrasubject correlation between RVD and RNFL was 0.5349±0.1639, with 101 of 106 subjects presenting significant correlation (p<0.05). 181 (out of 256) sectors presented a significant correlation between RVD and RNFL, with a mean value±SD of 0.2600±0.1140 (p<0.05).

Conclusions Using our model of the circumpapillary retinal vessel distribution, 70% of the RNFL thickness is influenced by RVD. On average, 7% of the interindividual variance of the RNFL thickness may be explained by RVD. A normative database that takes into account the circumpapillary blood vessels might slightly improve the diagnostic power of RNFL measurement.

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