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Label-Free Density Measurements of Radial Peripapillary Capillaries in the Human Retina.

Yu PK, Balaratnasingam C, Xu J, Morgan WH, Mammo Z, Han S, Mackenzie P, Merkur A, Kirker A, Albiani D, Sarunic MV, Yu DY - PLoS ONE (2015)

Bottom Line: Capillary density and diameter measurements from each eccentricity in svOCT and histological images were compared.The results are as follows: (1) The morphological characteristics of RPC networks on svOCT images are comparable to histological images; (2) With the exception of the nasal peripapillary region, there were no significant differences in RPC density measurements between svOCT and histological images; (3) Capillary diameter measurements were significantly greater in svOCT images compared to histology; (4) There is a positive correlation between RPC density and RNFL thickness.It may therefore be a valuable tool for aiding our understanding about vasculogenic mechanisms that are involved in RGC axonopathies.

View Article: PubMed Central - PubMed

Affiliation: Centre for Ophthalmology and Visual Science, The University of Western Australia, Australia, Perth, Australia; Lions Eye Institute, The University of Western Australia, Perth, Australia.

ABSTRACT
Radial peripapillary capillaries (RPCs) comprise a unique network of capillary beds within the retinal nerve fibre layer (RNFL) and play a critical role in satisfying the nutritional requirements of retinal ganglion cell (RGC) axons. Understanding the topographical and morphological characteristics of these networks through in vivo techniques may improve our understanding about the role of RPCs in RGC axonal health and disease. This study utilizes a novel, non-invasive and label-free optical imaging technique, speckle variance optical coherence tomography (svOCT), for quantitatively studying RPC networks in the human retina. Six different retinal eccentricities from 16 healthy eyes were imaged using svOCT. The same eccentricities were histologically imaged in 9 healthy donor eyes with a confocal scanning laser microscope. Donor eyes were subject to perfusion-based labeling techniques prior to retinal dissection, flat mounting and visualization with the microscope. Capillary density and diameter measurements from each eccentricity in svOCT and histological images were compared. Data from svOCT images were also analysed to determine if there was a correlation between RNFL thickness and RPC density. The results are as follows: (1) The morphological characteristics of RPC networks on svOCT images are comparable to histological images; (2) With the exception of the nasal peripapillary region, there were no significant differences in RPC density measurements between svOCT and histological images; (3) Capillary diameter measurements were significantly greater in svOCT images compared to histology; (4) There is a positive correlation between RPC density and RNFL thickness. The findings in this study suggest that svOCT is a reliable modality for analyzing RPC networks in the human retina. It may therefore be a valuable tool for aiding our understanding about vasculogenic mechanisms that are involved in RGC axonopathies. Further work is required to explore the reason for some of the quantitative differences between svOCT and histology.

No MeSH data available.


Related in: MedlinePlus

Methodology for quantitative measurements.Representative speckle variance optical coherence tomography (svOCT) image (A) and histology image (B) from the nasal peripapillary region illustrates the technique used to acquire quantitative measurements. Capillary density was determined by calculating the number of intersections between capillaries (circles) and a perpendicular, straight line (red line) drawn through the capillary network. Results were expressed as intersections per 100 μm. Capillary diameter was determined by calculating the perpendicular distance across the maximum chord axis of each vessel. This is as illustrated in the corresponding magnified regions (outlined in yellow dashed lines) of svOCT (C) and histology (D) images. Scale bar = 120μm (A & B) and 60μm (C and D)
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pone.0135151.g002: Methodology for quantitative measurements.Representative speckle variance optical coherence tomography (svOCT) image (A) and histology image (B) from the nasal peripapillary region illustrates the technique used to acquire quantitative measurements. Capillary density was determined by calculating the number of intersections between capillaries (circles) and a perpendicular, straight line (red line) drawn through the capillary network. Results were expressed as intersections per 100 μm. Capillary diameter was determined by calculating the perpendicular distance across the maximum chord axis of each vessel. This is as illustrated in the corresponding magnified regions (outlined in yellow dashed lines) of svOCT (C) and histology (D) images. Scale bar = 120μm (A & B) and 60μm (C and D)

Mentions: Image pro plus (v7.0) was used to analyze all images. The following quantitative measurements were acquired (Fig 2):


Label-Free Density Measurements of Radial Peripapillary Capillaries in the Human Retina.

Yu PK, Balaratnasingam C, Xu J, Morgan WH, Mammo Z, Han S, Mackenzie P, Merkur A, Kirker A, Albiani D, Sarunic MV, Yu DY - PLoS ONE (2015)

Methodology for quantitative measurements.Representative speckle variance optical coherence tomography (svOCT) image (A) and histology image (B) from the nasal peripapillary region illustrates the technique used to acquire quantitative measurements. Capillary density was determined by calculating the number of intersections between capillaries (circles) and a perpendicular, straight line (red line) drawn through the capillary network. Results were expressed as intersections per 100 μm. Capillary diameter was determined by calculating the perpendicular distance across the maximum chord axis of each vessel. This is as illustrated in the corresponding magnified regions (outlined in yellow dashed lines) of svOCT (C) and histology (D) images. Scale bar = 120μm (A & B) and 60μm (C and D)
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4529151&req=5

pone.0135151.g002: Methodology for quantitative measurements.Representative speckle variance optical coherence tomography (svOCT) image (A) and histology image (B) from the nasal peripapillary region illustrates the technique used to acquire quantitative measurements. Capillary density was determined by calculating the number of intersections between capillaries (circles) and a perpendicular, straight line (red line) drawn through the capillary network. Results were expressed as intersections per 100 μm. Capillary diameter was determined by calculating the perpendicular distance across the maximum chord axis of each vessel. This is as illustrated in the corresponding magnified regions (outlined in yellow dashed lines) of svOCT (C) and histology (D) images. Scale bar = 120μm (A & B) and 60μm (C and D)
Mentions: Image pro plus (v7.0) was used to analyze all images. The following quantitative measurements were acquired (Fig 2):

Bottom Line: Capillary density and diameter measurements from each eccentricity in svOCT and histological images were compared.The results are as follows: (1) The morphological characteristics of RPC networks on svOCT images are comparable to histological images; (2) With the exception of the nasal peripapillary region, there were no significant differences in RPC density measurements between svOCT and histological images; (3) Capillary diameter measurements were significantly greater in svOCT images compared to histology; (4) There is a positive correlation between RPC density and RNFL thickness.It may therefore be a valuable tool for aiding our understanding about vasculogenic mechanisms that are involved in RGC axonopathies.

View Article: PubMed Central - PubMed

Affiliation: Centre for Ophthalmology and Visual Science, The University of Western Australia, Australia, Perth, Australia; Lions Eye Institute, The University of Western Australia, Perth, Australia.

ABSTRACT
Radial peripapillary capillaries (RPCs) comprise a unique network of capillary beds within the retinal nerve fibre layer (RNFL) and play a critical role in satisfying the nutritional requirements of retinal ganglion cell (RGC) axons. Understanding the topographical and morphological characteristics of these networks through in vivo techniques may improve our understanding about the role of RPCs in RGC axonal health and disease. This study utilizes a novel, non-invasive and label-free optical imaging technique, speckle variance optical coherence tomography (svOCT), for quantitatively studying RPC networks in the human retina. Six different retinal eccentricities from 16 healthy eyes were imaged using svOCT. The same eccentricities were histologically imaged in 9 healthy donor eyes with a confocal scanning laser microscope. Donor eyes were subject to perfusion-based labeling techniques prior to retinal dissection, flat mounting and visualization with the microscope. Capillary density and diameter measurements from each eccentricity in svOCT and histological images were compared. Data from svOCT images were also analysed to determine if there was a correlation between RNFL thickness and RPC density. The results are as follows: (1) The morphological characteristics of RPC networks on svOCT images are comparable to histological images; (2) With the exception of the nasal peripapillary region, there were no significant differences in RPC density measurements between svOCT and histological images; (3) Capillary diameter measurements were significantly greater in svOCT images compared to histology; (4) There is a positive correlation between RPC density and RNFL thickness. The findings in this study suggest that svOCT is a reliable modality for analyzing RPC networks in the human retina. It may therefore be a valuable tool for aiding our understanding about vasculogenic mechanisms that are involved in RGC axonopathies. Further work is required to explore the reason for some of the quantitative differences between svOCT and histology.

No MeSH data available.


Related in: MedlinePlus