Comparison of Noncontact Specular and Confocal Microscopy for Evaluation of Corneal Endothelium

Tomographic, Biomechanical, and In Vivo Confocal Microscopic Changes in Cornea in Chronic Gout Disease

PURPOSE

This study aimed to evaluate the tomographic, biomechanical, and in vivo confocal microscopic (IVCM) effects of chronic gout disease on human cornea.

METHODS

This prospective study included 60 eyes of 30 participants with chronic gout disease and 60 eyes of 30 healthy controls. Corneal thickness, keratometry (K) readings, and corneal aberrations were measured with Sirius 3 D corneal tomography system (Sirius, CSO, Italy). Corneal biomechanical properties (corneal hysteresis [CH], corneal resistance factor [CRF], and intraocular pressure [IOP] parameters) were assessed with an ocular response analyzer (ORA, Reichert Ophthalmic Instruments). The number and morphology of corneal endothelial cells and the number of basal epithelial cells were evaluated with IVCM (Confoscan 4.0). Tear breakup time (TBUT) was also evaluated.

RESULTS

The mean diagnosis time of the patients with gout was 91.2 ± 69.6 months (12-300 month). Among corneal tomography measurements, K readings were similar between the two groups, while total and higher-order aberrations(coma, trefoil,s pherical, and quadrafoil) were significantly higher in the gout group. In the evaluation of biomechanical measurements, the CH value was significantly lower and the corneal-compensated IOP value was significantly higher in the gout group (p = 0.02, p = 0.01, respectively). The two groups did not significantly differ regarding the CRF or Goldmann IOP (p = 0.61, p = 0.15, respectively). Among the IVCM parameters, the number of corneal basal epithelial cells and the percentage of corneal endothelial hexagonality were significantly lower in the gout group, but no significant difference was detected in terms of the number of endothelial cells or polymegathism (p = 0.02, p < 0.001, p = 0.18, p = 0.59, respectively). While TBUT was significantly lower in the gout group (p < 0.001).

CONCLUSION

This study showed that chronic gout disease increases the corneal aberrations and decreases the basal epithelial cell count, hexagonality ratio of endothelial cell and corneal biomechanics.

Management of Glaucoma-Related Dry Eye Disease with Intense Pulsed Light: A Randomized Control Study

Purpose

The objective of this study was to assess the effectiveness of intense pulsed light (IPL) therapy in individuals diagnosed with glaucoma and dry eye disease (DED).

Methods

This randomized control study recruited 22 individuals diagnosed with glaucoma, ranging in age from 33 to 82 years. These participants were undergoing treatment with hypotensive eyedrops and had clinical indications and subjective complaints associated with dry eye. Each patient underwent three sessions of IPL therapy in one eye, while the contralateral eye served as the control eye (CT). The following parameters were assessed at three time points: baseline, week-2, and week-4. These parameters include non-invasive breakup time (NITBUT), tear meniscus height (TMH), conjunctivocorneal epithelial staining score (CS), tear film lipid layer (TFLL), meibomian gland expressibility score (MGEx), Schirmer I test, ocular bulbar redness score (OBRS), and ocular surface disease index (OSDI). Intraocular pressure (IOP), best-corrected visual acuity (BCVA), and corneal endothelial cell count (ECC) were assessed for safety. The clinical trial was registered on 25/12/2023 at ClinicalTrials.gov website (NCT06158984).

Results

Comparing baseline and 4-week measurements revealed that the IPL group found significant improvements in NITBUT (IPL: 8.74±2.60 sec. vs CT: 5.76±1.75 sec. p<0.01), TMH (IPL: 0.23±0.05mm vs CT: 0.19±0.06mm, p=0.011), C.S. (IPL: 1.14±0.56 vs CT: 1.95±1.17, p=0.005), TFLL (IPL: 2.91±2.91 vs CT:3.36±0.58, p=0.047), MGEx score (IPL: 1.14±0.35 vs CT: 1.45±0.51, p=0.020) and OSDI scores (IPL: 31.77±15.59 vs 50.59±21.55, p=0.002) significantly improved. Conversely, other parameters showed no significant improvements (p>0.05).

Conclusion

The progression of ocular surface disease in individuals using topical anti-glaucoma medication may worsen if the condition is not addressed. Nevertheless, IPL therapy has the potential to result in significant improvements in both objective and subjective measures of dry eye. Best-corrected visual acuity, endothelial cell count, and intraocular pressure were determined to be within the permitted limits. No adverse events were reported during the course of the study.

A Shape Memory Polymeric Shield for Protecting Corneal Endothelium During Phacoemulsification

Background

The purpose of this study was to explore the protective effect of a shape memory polymeric shield on corneal endothelium during phacoemulsification in rabbits.

Methods

Poly-(glycerol dodecanedioate) (PGD) with a transition temperature of 24.416°C was prepared to make a shape memory shield with a thickness of 100 µm, an arc length of 14 mm, and a radius of curvature of 8.8 mm. In the control group, a phaco-tip with bevel-down was used to simulate injury to the corneal endothelium by phacoemulsification in rabbits. In the experimental group, the pre-cooled and curled shape memory shield was injected into and removed from the anterior chamber before and after phaco-power release. Anterior segment optical coherence tomography (AS-OCT), confocal microscope, trypan blue/alizarin red staining, and scanning electron microscope were performed to measure endothelial damage after surgery.

Results

One day postoperatively, the lost cell ratio of the control group and the experimental group were 28.08 ± 5.21% and 3.50 ± 1.43%, respectively (P < 0.0001), the damaged cell ratios were 11.83 ± 2.30% and 2.55 ± 0.52%, respectively (P < 0.0001), and the central corneal thicknesses (CCT) were 406.75 ± 16.74 µm and 340. 5 ±13.48 µm, respectively (P < 0.0001). Seven days postoperatively, the endothelial cell density (ECD) of the control group and the experimental group were 1674 ± 285/mm2 and 2561 ± 554/mm2, respectively (P < 0.05). The above differences were all statistically significant.

Conclusions

This PGD based shape memory shield has a protective effect on corneal endothelium during phacoemulsification. It reduces postoperative corneal edema and ECD decrease in the short term after surgery.

Translational Relevance

The shape memory PGD "shield" in this study may have a use in certain human patients with vulnerable corneas of low endothelial cell count or shallow anterior chambers.

Applications of Imaging Technologies in Fuchs Endothelial Corneal Dystrophy: A Narrative Literature Review

Fuchs endothelial corneal dystrophy (FECD) is a complex genetic disorder characterized by the slow and progressive degeneration of corneal endothelial cells. Thus, it may result in corneal endothelial decompensation and irreversible corneal edema. Moreover, FECD is associated with alterations in all corneal layers, such as thickening of the Descemet membrane, stromal scarring, subepithelial fibrosis, and the formation of epithelial bullae. Hence, anterior segment imaging devices that enable precise measurement of functional and anatomical changes in the cornea are essential for the management of FECD. In this review, the authors will introduce studies on the application of various imaging modalities, such as anterior segment optical coherence tomography, Scheimpflug corneal tomography, specular microscopy, in vitro confocal microscopy, and retroillumination photography, in the diagnosis and monitoring of FECD and discuss the results of these studies. The application of novel technologies, including image processing technology and artificial intelligence, that are expected to further enhance the accuracy, precision, and speed of the imaging technologies will also be discussed.

Assessing abnormal corneal endothelial cells from in vivo confocal microscopy images using a fully automated deep learning system

BACKGROUND

The goal of this study is to develop a fully automated segmentation and morphometric parameter estimation system for assessing abnormal corneal endothelial cells (CECs) from LASER in vivo confocal microscopy (IVCM) images.

METHODS

First, we developed a fully automated deep learning system for assessing abnormal CECs using a previous development set composed of normal images and a newly constructed development set composed of abnormal images. Second, two testing sets, one with 169 normal images and the other with 211 abnormal images, were used to evaluate the clinical validity and effectiveness of the proposed system on LASER IVCM images with different corneal endothelial conditions, particularly on abnormal images. Third, the automatically calculated endothelial cell density (ECD) and the manually calculated ECD were compared using both the previous and proposed systems.

RESULTS

The automated morphometric parameter estimations of the average number of cells, ECD, coefficient of variation in cell area and percentage of hexagonal cells were 257 cells, 2648 ± 511 cells/mm², 32.18 ± 6.70% and 56.23 ± 8.69% for the normal CEC testing set and 83 cells, 1450 ± 656 cells/mm², 34.87 ± 10.53% and 42.55 ± 20.64% for the abnormal CEC testing set. Furthermore, for the abnormal CEC testing set, Pearson's correlation coefficient between the automatically and manually calculated ECDs was 0.9447; the 95% limits of agreement between the manually and automatically calculated ECDs were between 329.0 and - 579.5 (concordance correlation coefficient = 0.93).

CONCLUSIONS

This is the first report to count and analyze the morphology of abnormal CECs in LASER IVCM images using deep learning. Deep learning produces highly objective evaluation indicators for LASER IVCM corneal endothelium images and greatly expands the range of applications for LASER IVCM.

DenseUNets with feedback non-local attention for the segmentation of specular microscopy images of the corneal endothelium with guttae

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.

U-Net Convolutional Neural Network for Segmenting the Corneal Endothelium in a Mouse Model of Fuchs Endothelial Corneal Dystrophy

PURPOSE

The purpose of this study was to assess the U-Net-based convolutional neural network performance for segmenting corneal endothelium and guttae of Fuchs endothelial corneal dystrophy.

METHODS

Twenty-eight images of corneal endothelial cells and guttae of Col8a2L450W/L450W knock-in mice were obtained by specular microscopy. We used 20 images as training data to develop the U-Net for analyzing guttae and cell borders. The proposed network was validated using independent test data of 8 images. Cell density, hexagonality, and coefficient of variation were calculated from the predicted cell borders and compared with ground truth.

RESULTS

U-Net allowed the prediction of cell borders and guttae, and overlays of those segmentations on specular microscopy images highly corresponded to ground truth. The average number of guttae per field was 6.25 ± 8.07 for ground truth and 6.25 ± 7.87 when predicted by the network (Pearson correlation coefficient 0.989, P = 3.25 × 10 -6 ). The guttae areas were 1.60% ± 1.79% by manual determination and 1.90% ± 2.02% determined by the network (Pearson correlation coefficient 0.970, P = 6.72 × 10 -5 ). Cell density, hexagonality, and coefficient of variation analyzed by the proposed network for cell borders showed very strong correlations with ground truth (Pearson correlation coefficient 0.989, P = 3.23 × 10 -6 , Pearson correlation coefficient 0.978, P = 2.66 × 10 -5 , and Pearson correlation coefficient 0.936, P = 6.20 × 10 -4 , respectively).

CONCLUSIONS

We demonstrated proof of concept for application of U-Net for objective analysis of corneal endothelial cells and guttae in Fuchs endothelial corneal dystrophy, based on limited ground truth data.

Trainable watershed-based model for cornea endothelial cell segmentation

Segmentation of the medical image plays a significant role when it comes to diagnosis using computer aided system. This article focuses on the human corneal endothelium’s health, which is one of the filed research interests, especially in the human cornea. Various pathological environments fasten the extermination of the endothelial cells, which in turn decreases the cell density in an abnormal manner. Dead cells worsen the hexagonal design. The mutilated endothelial cells can no longer revive back and that gives room for neighbouring cells to migrate and expand so that they can fill in the space. The latter results in cell elongation that is unpredictable as well as increase in size and thinning. Cell density and shape are therefore considered major parameters when it comes to explaining the health condition attributed to corneal endothelium. In this study, medical feature extraction was obtained depending on the segmentation of the endothelial cell boundary, and the task of segmentation of such objects especially the thin, transparent, and unclear cell boundary is considered challenging due to the nature of the image capture during endothelium layer examination by ophthalmologists using confocal or specular microscopy. The resulting image suffers from various issues that affect the quality of the image. Low quality is due to non-uniformity of illumination and the presence of a lot of noise and artefacts resulting from high amounts of distortion, and most of these limitations are present because of the nature of the imaging modality. Usually, images contain certain kind of noise and also continuous shadow. Furthermore, the cells are separated by poor border, thereby leading to great difficulty in the segmentation of the images. The irregular shape of cell and also the contrast of such images seem to be low as they possess blurry boundaries with diverse objects existing in addition to the lack of homogeneity. The main aim of the study is to propose and develop a totally automatic, robust, and real-time model for the segmentation of endothelial cells of the human cornea obtained by in vivo microscopy and computation of different clinical features of endothelial cells. To achieve the aim of this study a new scheme of image enhancement was proposed such as the Contrast-Limited Adaptive Histogram Equalisation (CLAHE) technique to enhance contrast. After that, a new image denoising technique called Wavelet Transform Filter and Butterworth Bandpass for Segmentation is used. Subsequently, brightness level correction is applied by using the moving average filter and the CLAHE to reduce the effects of the non-uniform image lighting produced as a result of the previous step. The main aim of this article is the segmentation of endothelial cells, which involves precise detection of the endothelial contours. So a new segmentation model was proposed such that the shape of the cells will be extracted, and the contours were highlighted. This stage is followed by clinical feature extraction and uses the features for diagnosis. In this stage, several relevant clinical features such as pleomorphism mean cell perimeter, mean cell density, mean cell area, and polymegathism are extracted. The role of these clinical features is crucial for the early detection of corneal pathologies as well as the evaluation of the health of the corneal endothelium layer. The findings of this study were promising.

An automatic approach for cell detection and segmentation of corneal endothelium in specular microscope

PURPOSE

Specular microscopy is an indispensable tool for clinicians seeking to monitor the corneal endothelium. Automated methods of determining endothelial cell density (ECD) are limited in their ability to analyze images of poor quality. We describe and assess an image processing algorithm to analyze corneal endothelial images.

METHODS

A set of corneal endothelial images acquired with a Konan CellChek specular microscope was analyzed using three methods: flex-center, Konan Auto Tracer, and the proposed method. In this technique, the algorithm determines the region of interest, filters the image to differentiate cell boundaries from their interiors, and utilizes stochastic watershed segmentation to draw cell boundaries and assess ECD based on the masked region. We compared ECD measured by the algorithm with manual and automated results from the specular microscope.

RESULTS

We analyzed a total of 303 images manually, using the Auto Tracer, and with the proposed image processing method. Relative to manual analysis across all images, the mean error was 0.04% in the proposed method (p = 0.23 for difference) whereas Auto Tracer demonstrated a bias towards overestimation, with a mean error of 5.7% (p = 2.06× 10^-8). The relative mean absolute errors were 6.9% and 7.9%, respectively, for the proposed and Auto Tracer. The average time for analysis of each image using the proposed method was 2.5 s.

CONCLUSION

We demonstrate a computationally efficient algorithm to analyze corneal endothelial cell density that can be implemented on devices for clinical and research use.

Alu complementary DNA is enriched in atrophic macular degeneration and triggers retinal pigmented epithelium toxicity via cytosolic innate immunity

Long interspersed nuclear element-1 (L1)–mediated reverse transcription (RT) of Alu RNA into cytoplasmic Alu complementary DNA (cDNA) has been implicated in retinal pigmented epithelium (RPE) degeneration. The mechanism of Alu cDNA–induced cytotoxicity and its relevance to human disease are unknown. Here we report that Alu cDNA is highly enriched in the RPE of human eyes with geographic atrophy, an untreatable form of age-related macular degeneration. We demonstrate that the DNA sensor cGAS engages Alu cDNA to induce cytosolic mitochondrial DNA escape, which amplifies cGAS activation, triggering RPE degeneration via the inflammasome. The L1-extinct rice rat was resistant to Alu RNA–induced Alu cDNA synthesis and RPE degeneration, which were enabled upon L1-RT overexpression. Nucleoside RT inhibitors (NRTIs), which inhibit both L1-RT and inflammasome activity, and NRTI derivatives (Kamuvudines) that inhibit inflammasome, but not RT, both block Alu cDNA toxicity, identifying inflammasome activation as the terminal effector of RPE degeneration.

Corneal endothelial cell loss after trabeculectomy and phacoemulsification in one or two steps: a prospective study

Objective

The objective of this study was to analyse the results of the surgical treatment of coexisting cataract and glaucoma and its effects on corneal endothelial cell density (CECD).

Methods

We include two longitudinal prospective studies: one randomised that included 40 eyes with open angle glaucoma that received one- (n = 20) or two-step (n = 20) phacotrabeculectomy and another that included 20 eyes that received phacoemulsification. We assess the impact of surgery on different clinical variables and in particular in CECD using Confoscan 4™ confocal microscopy and semiautomatic counting methods.

Results

Phacoemulsification and phacotrabeculectomy, but not trabeculectomy, increase significantly best-corrected visual acuity and anterior chamber depth and trabeculectomy and one- or two-step phacotrabeculectomy decreased similarly the intraocular pressure. We document percentages of endothelial cell loss of 3.1%, 17.9%, 31.6% and 42.6% after trabeculectomy, phacoemulsification and one- or two-step phacotrabeculectomy, respectively. The coefficient of variation did not increase significantly after surgery but the percentage of hexagonality decreased significantly after phacoemulsification and after two-step phacotrabeculectomy.

Conclusions

Trabeculectomy, phacoemulsification and phacotrabeculectomy are surgical techniques that cause morphological changes and decrease the densities of the corneal endothelial cells. Trabeculectomy produces lesser endothelial cell loss than phacoemulsification, and phacoemulsification lesser cell loss than phacotrabeculectomy. Two-step phacotrabeculectomy (trabeculectomy followed 3 months later by phacoemulsification) causes more cell loss than one-step phacotrabeculectomy, and this could be due to the cumulative effects of two separate surgical traumas or to a negative conditioning lesion effect of the first surgery. For the treatment of coexisting glaucoma and cataract, one-step phacotrabeculectomy is the treatment of choice.

Deep Learning for Assessing the Corneal Endothelium from Specular Microscopy Images up to 1 Year after Ultrathin-DSAEK Surgery

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/mm2], 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.

One-year natural course of corneal densitometry in high myopic patients after implantation of an implantable collamer lens (model V4c)

BACKGROUND

Corneal densitometry, which is also known as corneal backscattering, is a surrogate measure of corneal clarity. The purpose of the study was to investigate the changes in corneal densitometry (CD) after implanting an implantable collamer lens (ICL-V4c).

METHOD

Twenty-six high myopic patients (aged 29.3 ± 6.6 years, 6 males and 20 females) who underwent ICL-V4c implantation were enrolled. Intraocular pressure (IOP), corneal topography, corneal densitometry, uncorrected distance visual acuity (UCDVA), manifest refraction, and best corrected distance visual acuity (BCDVA) were evaluated pre-operatively and at 1 day, 1 week, and 1, 3, 6, and 12 months post-operatively. Endothelial cell density (ECD) was measured pre-operatively and at 3, 6, and 12 months post-operatively. The efficacy index (mean post-operative UCDVA / mean pre-operative BCDVA) and the safety index (mean post-operative BCDVA / mean pre-operative BCDVA) were evaluated at 1 month, 3 months, 6 months and 12 months post-operatively.

RESULTS

Over the annular diameters of 0-2 mm, the pre-operative densitometry values of the anterior layer, central layer, posterior layer, and total layer were 20.1 ± 2.8, 11.8 ± 1.1, 10.5 ± 0.9 and 14.1 ± 1.5, respectively. From pre-operatively to post-operative Month 12, the values changed insignificantly (P = 0.177, P = 0.153, P = 0.543 and P = 0.207, respectively). Over the annular diameters of 2-6 mm, the pre-operative mean densitometry values were 17.9 ± 2.2, 10.5 ± 0.9, and 12.6 ± 1.2, respectively. From pre-operatively to post-operative Month 12, the values decreased to 16.5 ± 2.1, 10.0 ± 0.9, and 11.9 ± 1.2, respectively, which were similar to the pre-operative values (all P > 0.05) but significantly lower than the values obtained at post-operative Day 1 (P = 0.013, P = 0.002 and P = 0.010, respectively). The densitometry value of the posterior layer over the annular diameters of 2 to 6 mm remained unchanged (from 9.4 ± 0.7 to 9.1 ± 0.7) over time (P = 0.372). The efficacy and safety indices assessed at 12 months post-operatively were 1.04 ± 0.27 and 1.19 ± 0.23, respectively. The changes in IOP and ECD values were statistically insignificant (P = 0.896 and P = 0.968, respectively).

CONCLUSION

ICL-V4c implantation may be safe and efficient for high ametropia correction. The corneal densitometry values obtained over the annulus of 0-6 mm increased slightly from before the operation to post-operative Day 1 and then decreased gradually, which indicates that ICL-V4c implantation may not compromise corneal clarity.

Significant differences between specular microscopy and corneal bank endothelial cell counts - a pilot study

BACKGROUND

It was shown recently that endothelial cell count performed by cornea banks overestimates the real number of endothelial cells. The aim of this study was to investigate the internal quality of preclinical ECD in human donor corneas using two widely used methods for endothelial cell counting, transmitted light microscopy used in organ culture tissue bank and clinically used specular microscopy.

METHODS

Twenty human donor corneas that could not be transplanted were included in this analysis. Differences in evaluating endothelial cell density (ECD) and hexagonal endothelial cell ratio (HEX) between clinical specular microscopy (CSM) and corneal bank transmitted light microscope (CBLM) were evaluated as well as differences between automated and manual cell counts.

RESULTS

Automated CBLM showed a higher ECD of 31.85% compared to automated CSM, while manual CBLM counting is 10.51% higher compared to manual CSM (p < 0.01). Further, higher average ECD values result in a higher difference between CSM and CBLM measurements. The manual CBLM ECDs were significantly higher compared to automated derived ECD from CSM (p < 0.01). However, no systematic bias can be detected when comparing the differences of the measurements with the average ECD measurements of both methods.

CONCLUSION

This preclinical pilot study confirmed a significant higher ECD using transmitted light microscopy in organ culture compared to clinical specular microscopy. This indicates that the early rapid decrease of EC universally observed after surgery might be partly artefactual.

Comparison of automated vs manual analysis of corneal endothelial cell density and morphology in normal and corneal endothelial dystrophy-affected dogs

OBJECTIVE

To determine the efficacy of automated imaging software of the Nidek ConfoScan 4 confocal biomicroscope at analyzing canine corneal endothelial cell density and morphology in health and disease, by comparing to a manual analysis method.

ANIMAL STUDIED

Nineteen eyes of 10 dogs were evaluated and include three Beagles, three Jack Russell Terriers, and four miscellaneous breeds. Twelve clinically normal and seven eyes affected with corneal endothelial dystrophy (CED) were scanned and analyzed.

PROCEDURES

Endothelial cell density (ECD), mean and standard deviation (SD) of cell area, percent polymegathism, mean and SD of the number of cell sides, and percent pleomorphism were calculated using automated and manual methods for each scan.

RESULTS

The automated analysis showed significantly greater ECD in comparison with the manual frame method due to misidentification of cell domains in CED-affected dogs. No significant differences in ECD were observed between normal and CED-affected dogs in automated analysis, while CED-affected dogs showed significantly lower ECD in manual frame method and planimetry. Using both automated and manual methods, CED-affected dogs showed greater variability of cell area or the number of cell sides than normal dogs.

CONCLUSION

The automated imaging software is unable to accurately identify cell borders in CED-affected dogs resulting in inaccurate estimates of ECD. Thus, manual analysis is recommended for use in clinical trials assessing adverse events associated with novel medical treatments and/or surgical procedures.

Representation of Central Endothelial Cell Density by Analysis of Single Best Specular Microscopy Image Regardless of Cell Size Variance

Purpose

The purpose of this study is to evaluate whether a single best image can represent central endothelial cell density (ECD) in corneas of differing cell size coefficient of variance (CV).

Methods

Four hundred one healthy eyes but with variant CV values were enrolled. For each eye, three nonoverlapping central cornea endothelium images were obtained with Konan NSP-9900 specular microscope. ECD and CV were evaluated by two independent graders using the well-established Center method. Only corneas with high image quality rating (IQR) and ECD >800 cell/mm² by both graders were included in the study. The study sample was stratified into five CV levels (CV ≤ 35; ≥36; ≥38; ≥40; and ≥45). In each CV level, the ECD agreement, ECD variance, and the correlation between the ECD variation and CV values were analyzed. In addition, the ECD intragrader reproducibility and interframe differences were also analyzed for all levels except CV ≤ 35.

Results

The study sample includes a total of 278 eyes. High ECD agreement for the two independent graders (intraclass correlation coefficient [ICC] > 0.99), high ECD intragrader reproducibility (ICC > 0.95), low ECD variance (2.0% ± 1.6%, overall), no correlation between the ECD variation and the CV value (P > 0.05), and no significant ECD difference among frames (P > 0.05) was found in any studied CV levels.

Conclusions

CV does not appear to be associated with ECD variance in the central cornea.

Translational Relevance

This finding highlights that in healthy corneas but with high CV values, ECD can be reliably analyzed using one single image of best quality.

Fully convolutional architecture vs sliding-window CNN for corneal endothelium cell segmentation

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.

cGAS drives noncanonical-inflammasome activation in age-related macular degeneration

Geographic atrophy is a blinding form of age-related macular degeneration characterized by death of the retinal pigmented epithelium (RPE). In this disease, the RPE displays evidence of DICER1 deficiency, resultant accumulation of endogenous Alu retroelement RNA, and NLRP3 inflammasome activation. How the inflammasome is activated in this untreatable disease is largely unknown. Here we demonstrate that RPE degeneration in human cell culture and in mouse models is driven by a non-canonical inflammasome pathway that results in activation of caspase-4 (caspase-11 in mice) and caspase-1, and requires cyclic GMP-AMP synthase (cGAS)-dependent interferon-β (IFN-β) production and gasdermin D-dependent interleukin-18 (IL-18) secretion. Reduction of DICER1 levelsor accumulation of Alu RNA triggers cytosolic escape of mitochondrial DNA, which engages cGAS. Moreover, caspase-4, gasdermin D, IFN-β, and cGAS levels are elevated in the RPE of human eyes with geographic atrophy. Collectively, these data highlight an unexpected role for cGAS in responding to mobile element transcripts, reveal cGAS-driven interferon signaling as a conduit for mitochondrial damage-induced inflammasome activation, expand the immune sensing repertoire of cGAS and caspase-4 to non-infectious human disease, and identify new potential targets for treatment of a major cause of blindness.