Human photoreceptor cone density measured with adaptive optics technology (rtx1 device) in healthy eyes: Standardization of measurements

Medicine (Baltimore). 2017 Jun;96(25):e7300. doi: 10.1097/MD.0000000000007300.

Abstract

The anatomic structures of the anterior segment of the eye enable correct reception of stimuli by the retina, which contains receptors that receive light impulses and transmit them to the visual cortex. The aim of this study was to assess the effect of the size of the sampling window in an adaptive optics (AO) flood-illumination retinal camera (rtx1) on cone density measurements in the eyes of healthy individuals and to investigate the differences in cone density and spacing in different quadrants of the retina. Thirty-three subjects with no ophthalmic or systemic disease underwent a detailed ophthalmologic examination. Photographs of retinal fragments 3 degrees from the fovea were taken using the rtx1 AO retinal camera. We used sampling windows with 3 sizes (50 × 50, 100 × 100, and 250 × 250 μm). Cone density, spacing, and shape were determined using AOdetect software. The median (interquartile range) cone density was 19,269 (4964) cones/mm. There were statistically significant differences between measurements taken with the 50/50 and 250/250-m windows. There were no significant differences in the cone spacing results between any of the windows examined, but the measurements differed according to location between the superior and temporal quadrants. The most common cone shape was hexagonal (47.6%) for all window sizes and locations. These findings may help in the development of a normative database for variation in cone density in healthy subjects and to allow the best window to be chosen for obtain the most correct values for eccentricity measurements of 3 degrees. In our study, the optimal sampling window was 100 × 100 μm.

MeSH terms

  • Adult
  • Cell Count
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Male
  • Optical Imaging / instrumentation
  • Optical Imaging / standards*
  • Pattern Recognition, Automated
  • Quality Improvement
  • Retina / cytology*
  • Retina / diagnostic imaging*
  • Retinal Cone Photoreceptor Cells / cytology*
  • Software