Quantitative morphometry of perifoveal capillary networks in the human retina.

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Abstract

Purpose. To quantify the distribution and morphometric characteristics of capillary networks in the human perifovea. To determine correlations between the location of neuronal subcellular compartments and the morphometric features of regional capillary networks in the layered retina. Methods. The perifoveal region, located 2 mm nasal to the fovea, was studied in 17 human donor eyes. Novel micropipette technology was used to cannulate the central retinal artery and label the retinal microcirculation using a phalloidin perfusate. γ-synuclein, Goα, and parvalbumin antibodies were also used to co-localize the nerve fiber layer (NFL), retinal ganglion cell layer (RGCL), inner plexiform layer (IPL), and inner nuclear layer (INL). Confocal scanning laser microscopy was used for capillary imaging. Capillary diameter, capillary density, and capillary loop area measurements were compared between networks. Results. Four capillary networks were identified in the following retinal layers: (1) NFL, (2) RGCL and superficial portion of IPL, (3) deep portion of IPL and superficial portion of INL, and (4) deep portion of INL. Laminar configurations were present in NFL and deep INL networks. Remaining networks demonstrated three-dimensional configurations. Capillary density was greatest in the networks serving the IPL. Capillary loop area was smallest in the two innermost networks. There was no difference in capillary diameter between networks. Conclusions. Capillary networks in the human perifovea are morphometrically heterogeneous. Morphometric features of regional capillary networks in the layered retina may serve a critical role in supporting neuronal homeostasis. Improved knowledge of these features may be important for understanding pathogenic mechanisms underlying retinal vascular diseases. Copyright © Association for Research in Vision and Ophthalmology
Original languageEnglish
Pages (from-to)5502-5514
JournalInvestigative ophthalmology & visual science
Volume53
Issue number9
Early online date19 Jul 2012
DOIs
Publication statusPublished - 13 Aug 2012

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