Corneal Endothelium Evaluation With 2 Noncontact Specular Microscopes and Their Semiautomated Methods of Analysis

Sanctis, Ugo de; Machetta, Federica; Razzano, Luca; Dalmasso, Paola; Grignolo, Fm

doi:10.1097/01.ico.0000214217.83119.af

Cited by 39 publications

(39 citation statements)

References 18 publications

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“…Moreover, when comparing studies that performed ECD measurement with specular microscopy between them, significantly different ECD values may occur. [30][31][32] However, we report and compare our results with other studies using specular microscopy in terms of percentage change, measured in each case with the same method, and therefore allowing for valid comparisons.…”

Section: Discussionmentioning

confidence: 95%

Coupling of HRT II and AS-OCT to evaluate corneal endothelial cell loss and in vivo visualization of the Ahmed glaucoma valve implant

Mendrinos

Dosso

Sommerhalder

et al. 2008

Eye

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Section: Discussionmentioning

confidence: 95%

Coupling of HRT II and AS-OCT to evaluate corneal endothelial cell loss and in vivo visualization of the Ahmed glaucoma valve implant

Mendrinos

Dosso

Sommerhalder

et al. 2008

Eye

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“…The particular estimation of cell area distribution usually reported is that of the coefficient of variation (COV) = standard deviation of cell area/average cell area x 100, which is often referred to as the degree of polymegathism and expres- sed as a percentage (16) . Previous studies with centre-dot methods reported that while the average values recorded were similar (for the same sets of images), the range of COV values could differ by around 20 per cent (17)(18) or even more than this (19) , leading that the agreement between COV data was weak. In this study the COV was close in both uveitis groups, it can be reliably used to generate useful data on cell area and cell density, however it should be used cautiously for polymegathism estimations (16) .…”

Section: Discussionmentioning

confidence: 87%

“…As instructed by the user manual, we identified the centers of on average 15 (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) cells per image. The software in this model measures the distances between individual cell centers and then computes the mean endothelial cell area and hence the endothelial cell density (15) .…”

Section: Discussionmentioning

confidence: 99%

Corneal specular microscopy in infectious and noninfectious uveitis

Oliveira¹,

Motta²,

Muccioli³

2009

Arq. Bras. Oftalmol.

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“…9 -right panel, Table 1 -3rd and 5th column) is the true variability of measurements caused by the semi-automated barrier tracing method used by the current operator as the reference data is known. Inter-operator and intersystem studies typically result in higher variations (de Sanctis et al 2006;Deb-Joardar et al 2007a,b) associated with variabilities among systems and operators. Such variabilities could be analysed with a standardize strategy based on a standard set of images generated with the currently developed simulator, but such analysis is beyond the scope of the present project.…”

Section: Standard For Calibration Of Csm Measurementsmentioning

confidence: 99%

“…The detection of the cell borders requires time-consuming operator involvement in a majority of the cases (Cheung & Cho 2000;van Schaick et al 2005). Variability in morphometric data among CSM systems and among operators and calibration differences between systems are also limiting factors for measurements (Landesz et al 1995a,b;van Schaick et al 2005;de Sanctis et al 2006;Deb-Joardar et al 2007a,b).…”

Section: Introductionmentioning

confidence: 99%

Simulation of specular microscopy images of corneal endothelium, a tool for control of measurement errors

Bucht

Söderberg

Manneberg

2011

Acta Ophthalmologica

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Purpose:We aimed at developing simulation software capable of producing images of corneal endothelium close to identical to images captured by clinical specular microscopy with defined morphometrical characteristics. It was further planned to demonstrate the usefulness of the simulator by analysing measurement errors associated with a trained operator using a commercially available semi-automatic algorithm for analysis of simulated images.Methods: Software was developed that allows creation of unique images of the corneal endothelium expressing morphology close to identical with that seen in images of corneal specular microscopy. Several hundred unique images of the corneal endothelium were generated with randomization, spanning a physiological range of endothelial cell density. As an example of the usefulness of the simulator for analysis of measurement errors in corneal specular microscopy, a total of 12 of all the images generated were randomly selected such that the endothelial cell density expressed was evenly distributed over the physiological range of endothelial cell density. The images were transferred to a personal computer. The imagenet-640 software was used to analyse endothelial cell size variation, percentage of hexagonal endothelial cells, and endothelial cell density. Results:The simulator developed allows randomized generation of corneal specular microscopy images with a preset expected average and variation of cell structure. Calculated morphometric information of each cell is stored in the simulator. The image quality can secondarily be varied with a toolbox of filters to approximate a large spectrum of clinically captured images. As an example of the use of the simulator, measurement errors associated with one trained operator using the imagenet-640 software, and focusing on endothelial cell density, were examined. The functional dependence between morphometric information estimated with the imagenet-640 software algorithm and real morphometric information as provided by the simulator was analysed with regression. It was demonstrated that that the estimations of endothelial cell size variation was associated with a scaling error and that the random error was strongly dependent on the operator. Conclusion:The newly developed simulator for randomized generation of morphometrically defined corneal specular microscopy images for the first time makes it possible to estimate a spatial scaling error of an available semi-automatic algorithm and to determine the random measurement error of important morphometric estimates in a defined reference sample of images. It is anticipated that the simulator will be a valuable tool for the generation of a large set of morphometrically well-characterized corneal specular microscopy images that can be used for calibration among research centres, for minimization of random errors and for measurement of quality control. Simulated images will be useful for the development of fully automatic analysis of corneal endothelial cell morphometry.

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Corneal Endothelium Evaluation With 2 Noncontact Specular Microscopes and Their Semiautomated Methods of Analysis

Cited by 39 publications

References 18 publications

Coupling of HRT II and AS-OCT to evaluate corneal endothelial cell loss and in vivo visualization of the Ahmed glaucoma valve implant

Coupling of HRT II and AS-OCT to evaluate corneal endothelial cell loss and in vivo visualization of the Ahmed glaucoma valve implant

Corneal specular microscopy in infectious and noninfectious uveitis

Simulation of specular microscopy images of corneal endothelium, a tool for control of measurement errors

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