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      Technical Factors Influencing Cone Packing Density Estimates in Adaptive Optics Flood Illuminated Retinal Images

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      1 , * , 1 , 2 , 3
      PLoS ONE
      Public Library of Science

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          Abstract

          Purpose

          To investigate the influence of various technical factors on the variation of cone packing density estimates in adaptive optics flood illuminated retinal images.

          Methods

          Adaptive optics images of the photoreceptor mosaic were obtained in fifteen healthy subjects. The cone density and Voronoi diagrams were assessed in sampling windows of 320×320 µm, 160×160 µm and 64×64 µm at 1.5 degree temporal and superior eccentricity from the preferred locus of fixation (PRL). The technical factors that have been analyzed included the sampling window size, the corrected retinal magnification factor (RMF corr), the conversion from radial to linear distance from the PRL, the displacement between the PRL and foveal center and the manual checking of cone identification algorithm. Bland-Altman analysis was used to assess the agreement between cone density estimated within the different sampling window conditions.

          Results

          The cone density declined with decreasing sampling area and data between areas of different size showed low agreement. A high agreement was found between sampling areas of the same size when comparing density calculated with or without using individual RMF corr. The agreement between cone density measured at radial and linear distances from the PRL and between data referred to the PRL or the foveal center was moderate. The percentage of Voronoi tiles with hexagonal packing arrangement was comparable between sampling areas of different size. The boundary effect, presence of any retinal vessels, and the manual selection of cones missed by the automated identification algorithm were identified as the factors influencing variation of cone packing arrangements in Voronoi diagrams.

          Conclusions

          The sampling window size is the main technical factor that influences variation of cone density. Clear identification of each cone in the image and the use of a large buffer zone are necessary to minimize factors influencing variation of Voronoi diagrams of the cone mosaic.

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          Most cited references18

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            Measuring agreement in method comparison studies.

            Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.
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              High-resolution imaging with adaptive optics in patients with inherited retinal degeneration.

              To investigate macular photoreceptor structure in patients with inherited retinal degeneration using high-resolution images and to correlate the findings with clinical phenotypes and genetic mutations. Adaptive optics scanning laser ophthalmoscopy (AOSLO) images of photoreceptors were obtained in 16 eyes: five with retinitis pigmentosa (RP), three with cone-rod dystrophy (CRD), and eight without retinal disease. A quadratic model was used to illustrate cone spacing as a function of retinal eccentricity. Cone spacing at 1 degrees eccentricity was compared with standard measures of central visual function, including best-corrected visual acuity (BCVA), foveal threshold, and multifocal electroretinogram (mfERG) amplitude and timing. Intervisit variations were studied in one patient with RP and one patient with CRD. Screening of candidate disease genes identified mutations in two patients, one with RP (a rhodopsin mutation) and the other with CRD (a novel RPGR-ORF15 mutation). Cone spacing values were significantly different from normal for patients with RP (P = 0.01) and CRD (P < 0.0001) and demonstrated a statistically significant correlation with foveal threshold (P = 0.0003), BCVA (P = 0.01), and mfERG amplitude (P = 0.008). Although many RP patients showed normal cone spacing within 1 degrees of fixation, cones could not be unambiguously identified in several retinal regions. Cone spacing increased in all CRD patients, even those with early disease. Little variation was observed in cone spacing measured during two sessions fewer than 8 days apart. AOSLO images can be used to study macular cones with high resolution in patients with retinal degeneration. The authors present the first report of cone structure in vivo in patients with mutations in rhodopsin and RPGR-ORF15 and show that macular cones display distinct characteristics, depending on the underlying disease. AOSLO imaging, therefore, can provide new insight into possible mechanisms of cone vision loss in patients with retinal degeneration.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                9 September 2014
                : 9
                : 9
                : e107402
                Affiliations
                [1 ]Fondazione G.B. Bietti IRCCS, Rome, Italy
                [2 ]CNR-IPCF Unit of Support Cosenza, Rende, Italy
                [3 ]Vision Engineering Italy srl, Rome, Italy
                University of Modena and Reggio Emilia, Italy
                Author notes

                Competing Interests: Giuseppe Lombardo is employed by Vision Engineering Italy srl. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

                Conceived and designed the experiments: ML. Performed the experiments: ML. Analyzed the data: ML SS GL. Contributed reagents/materials/analysis tools: GL. Wrote the paper: ML SS GL. Revised the manuscript: ML SS GL.

                Article
                PONE-D-14-07328
                10.1371/journal.pone.0107402
                4159321
                25203681
                d2a7538f-cdb0-4300-b5dd-e830e673c58f
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 February 2014
                : 14 August 2014
                Page count
                Pages: 11
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Ocular System
                Ocular Anatomy
                Biotechnology
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Computer and Information Sciences
                Computing Methods
                Medicine and Health Sciences
                Diagnostic Medicine
                Ophthalmology

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                Uncategorized

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