Search

Background: To accurately measure ultrathin Descemet stripping automated endothelial keratoplasty (DSAEK) donor lamella thickness during the first postoperative year and to correlate this with pre-operative and other postoperative measurements., Methods: Donor lamella thickness in 41 eyes undergoing DSAEK for Fuchs endothelial dystrophy (FED) was measured using the Tomey Casia OCT directly after graft preparation and at 1 week and 1, 3, 6 and 12 months postoperatively. Visual acuity and endothelial cell density were measured as the secondary parameters., Results: Individual graft thickness profiles were shown to be fairly regular within the optically relevant area. There was a strong and highly significant correlation between the pre- and postoperative lamellar thicknesses at all time points (p < 0.0001). Compared with the measurements directly after preparation at the cornea bank, the lamella thickness decreased by 12% after 12 months. Between 1 and 12 months postoperatively, the lamella thickness (mean ± SD) changed from 112 ± 27 μm to 101 ± 21 μm. Best spectacle-corrected visual acuity (BSCVA) changed from 0.46 ± 0.30 logMAR pre-operatively through 0.36 ± 0.33 at 1 month to 0.13 ± 0.16 at 1 year postoperatively. The endothelial cell counts were comparable to those reported in previous studies., Conclusions: Thickness profiles of individual grafts were fairly regular within the optically relevant area. A strong relationship between pre- and postoperative graft thicknesses was detected, and ultrathin DSAEK grafts prepared using methods similar to that applied in this study are expected to show a deswelling of around 12% during the first postoperative year. No correlation was detected between graft thickness and BSCVA., (© 2023. The Author(s).)

Corneal guttae, which are the abnormal growth of extracellular matrix in the corneal endothelium, are observed in specular images as black droplets that occlude the endothelial cells. To estimate the corneal parameters (endothelial cell density [ECD], coefficient of variation [CV], and hexagonality [HEX]), we propose a new deep learning method that includes a novel attention mechanism (named fNLA), which helps to infer the cell edges in the occluded areas. The approach first derives the cell edges, then infers the well-detected cells, and finally employs a postprocessing method to fix mistakes. This results in a binary segmentation from which the corneal parameters are estimated. We analyzed 1203 images (500 contained guttae) obtained with a Topcon SP-1P microscope. To generate the ground truth, we performed manual segmentation in all images. Several networks were evaluated (UNet, ResUNeXt, DenseUNets, UNet++, etc.) and we found that DenseUNets with fNLA provided the lowest error: a mean absolute error of 23.16 [cells/mm[Formula: see text]] in ECD, 1.28 [%] in CV, and 3.13 [%] in HEX. Compared with Topcon's built-in software, our error was 3-6 times smaller. Overall, our approach handled notably well the cells affected by guttae, detecting cell edges partially occluded by small guttae and discarding large areas covered by extensive guttae., (© 2022. The Author(s).)

Purpose: To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty., Methods: We analyzed 383 post ultrathin Descemet stripping automated endothelial keratoplasty images from 41 eyes acquired with a Topcon SP-1P specular microscope at 1, 3, 6, and 12 months after surgery. The estimated parameters were endothelial cell density (ECD), coefficient of variation (CV), and hexagonality (HEX). Manual segmentation was performed in all images., Results: Our method provided an estimate for ECD, CV, and HEX in 98.4% of the images, whereas Topcon's software had a success rate of 71.5% for ECD/CV and 30.5% for HEX. For the images with estimates, the percentage error in our method was 2.5% for ECD, 5.7% for CV, and 5.7% for HEX, whereas Topcon's software provided an error of 7.5% for ECD, 17.5% for CV, and 18.3% for HEX. Our method was significantly better than Topcon's ( P < 0.0001) and was not statistically significantly different from the manual assessments ( P > 0.05). At month 12, the subjects presented an average ECD = 1377 ± 483 [cells/mm 2 ], CV = 26.1 ± 5.7 [%], and HEX = 58.1 ± 7.1 [%]., Conclusions: The proposed method obtains reliable and accurate estimations even in challenging specular images of pathologic corneas., Translational Relevance: CV and HEX, not currently used in the clinic owing to a lack of reliability in automatic methods, are useful biomarkers to analyze the postoperative healing process. Our accurate estimations allow now for their clinical use., Competing Interests: Disclosure: J.P. Vigueras-Guillén, None; J. van Rooij, None; A. Engel, None; H.G. Lemij, None; L.J. van Vliet, None; K.A. Vermeer, None, (Copyright 2020 The Authors.)

Purpose: To evaluate whether prolongation of interruptions of preoperative posturing by sitting upright influences retinal detachment (RD) progression. The secondary objective was to find clinical factors to identify patients with a high risk for RD progression., Design: Prospective cohort study., Participants: One hundred ninety-eight patients divided among 3 cohorts of patients with macula-on RD were included. Inclusion criteria were volume OCT scans of sufficient quality and smallest distance from the fovea to the detachment border of at least 1.25 mm. In the second and third cohort, 50 patients with only superior temporal RD were included., Methods: Patients were admitted to the ward in anticipation of surgery. Preoperative bed rest and positioning were prescribed. The position of the RD border was determined based on OCT imaging performed at baseline, before and after the usual interruptions for meals or toilet visits. The duration of interruptions was prolonged with sitting upright for 20 minutes in cohort 2 and for 40 minutes in cohort 3. Various secondary outcome measures were defined, such as the baseline area of subretinal fluid (SRF) as measured on ultrasound images in the third cohort., Main Outcome Measures: The RD border displacement was determined. The worst RD progression from baseline was given by the shortest distance to the fovea in any of the OCT scans during follow-up. The worst relative RD progression from baseline was defined as the worst RD progression from baseline as a percentage of the baseline distance between RD border and fovea., Results: The median duration of interruptions was 22, 41, and 58 minutes in cohorts 1, 2, and 3, respectively. The median RD border displacement during interruptions in patients with superior temporal RD was not significantly different among the cohorts (P = 0.28). The correlation coefficient between the SRF area at baseline and worst relative RD progression from baseline was 0.37 (95% confidence interval, 0.04-0.66; P = 0.009)., Conclusions: We did not find a significant increase in RD progression after prolongation of interruptions by sitting upright. Patients with a larger area of SRF on ultrasound showed more RD progression from baseline., (Copyright © 2019 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Background: Corneal endothelium (CE) images provide valuable clinical information regarding the health state of the cornea. Computation of the clinical morphometric parameters requires the segmentation of endothelial cell images. Current techniques to image the endothelium in vivo deliver low quality images, which makes automatic segmentation a complicated task. Here, we present two convolutional neural networks (CNN) to segment CE images: a global fully convolutional approach based on U-net, and a local sliding-window network (SW-net). We propose to use probabilistic labels instead of binary, we evaluate a preprocessing method to enhance the contrast of images, and we introduce a postprocessing method based on Fourier analysis and watershed to convert the CNN output images into the final cell segmentation. Both methods are applied to 50 images acquired with an SP-1P Topcon specular microscope. Estimates are compared against a manual delineation made by a trained observer., Results: U-net (AUC=0.9938) yields slightly sharper, clearer images than SW-net (AUC=0.9921). After postprocessing, U-net obtains a DICE=0.981 and a MHD=0.22 (modified Hausdorff distance), whereas SW-net yields a DICE=0.978 and a MHD=0.30. U-net generates a wrong cell segmentation in only 0.48% of the cells, versus 0.92% for the SW-net. U-net achieves statistically significant better precision and accuracy than both, Topcon and SW-net, for the estimates of three clinical parameters: cell density (ECD), polymegethism (CV), and pleomorphism (HEX). The mean relative error in U-net for the parameters is 0.4% in ECD, 2.8% in CV, and 1.3% in HEX. The computation time to segment an image and estimate the parameters is barely a few seconds., Conclusions: Both methods presented here provide a statistically significant improvement over the state of the art. U-net has reached the smallest error rate. We suggest a segmentation refinement based on our previous work to further improve the performance., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2019.)

Purpose: Traditionally, preoperative posturing consisting of bed rest and positioning is prescribed to patients with macula-on retinal detachment (RD) to prevent RD progression and detachment of the fovea. Execution of such advice can be cumbersome and expensive. This study aimed to investigate if preoperative posturing affects the progression of RD., Design: Prospective cohort study., Participants: Ninety-eight patients with macula-on RD were included. Inclusion criteria were volume optical coherence tomography (OCT) scans could be obtained with sufficient quality; and the smallest distance from the fovea to the detachment border was 1.25 mm or more., Methods: Patients were admitted to the ward for bed rest in anticipation of surgery and were positioned on the side where the RD was mainly located. At baseline and before and after each interruption for meals or toilet visits, a 37°×45° OCT volume scan was performed using a wide-angle Spectralis OCT (Heidelberg Engineering, Heidelberg, Germany). The distance between the nearest point of the RD border and fovea was measured using a custom-built measuring tool., Main Outcome Measures: The RD border displacement and the average RD border displacement velocity moving toward (negative) or away (positive) from the fovea were determined for intervals of posturing and interruptions., Results: The median duration of intervals of posturing was 3.0 hours (interquartile range [IQR], 1.8-14.0 hours; n = 202) and of interruptions 0.37 hours (IQR, 0.26-0.50 hours; n = 197). The median RD border displacement was 2 μm (IQR, -65 to +251 μm) during posturing and -61 μm (IQR, -140 to 0 μm) during interruptions, a statistically significant difference (P < 0.001, Mann-Whitney U test). The median RD border displacement velocity was +1 μm/hour (IQR, -21 to +49 μm/hour) during posturing and -149 μm/hour (IQR, -406 to +1 μm/hour) during interruptions, a statistically significant difference (P < 0.001)., Conclusions: By making use of usual interruptions of preoperative posturing we were able to show, in a prospective and ethically acceptable manner, that RD stabilizes during posturing and progresses during interruptions in patients with macula-on RD. Preoperative posturing is effective in reducing progression of RD., (Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)