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PURPOSE To report a case of bilateral uveitis and hypotony associated with topical cidofovir treatment. METHODS Case report. RESULTS A 59-year-old diabetic male with HIV/AIDS presented with photophobia, ocular pain, and decreased vision. He was found to have bilateral hypotony, anterior uveitis, and serous choroidal detachments. Infectious disease workup, patient-reported history, and review of the patient's electronic medication list did not identify the etiology. Treatment with intensive topical corticosteroids led to resolution of uveitis and choroidal effusions within 3 months and resolution of hypotony within 9 months. Two years after his initial presentation, the patient developed acute recurrence of bilateral hypotony, anterior uveitis, and serous choroidal detachments shortly after intravenous cidofovir treatment. Careful re-evaluation of the patient's outside medical records revealed that he had initiated treatment for rectal herpes simplex virus with compounded topical cidofovir one month prior to his initial presentation. CONCLUSION To our knowledge, this is the first reported case of topical cidofovir causing ocular toxicity. Compounded and topical medications, like cidofovir in this case, may not appear on a patient's electronic medication list, so a focused review of outside medical records may be beneficial when a particular medication toxicity is suspected.

To describe the clinical, optical coherence tomography (OCT), fundus autofluorescence and ultrasound findings of a patient with a choroidal nevus actively exuding vitelliform material in the setting of Autosomal Dominant Best dystrophy (BD).The patient's clinical course was followed over time with ophthalmic examinations and multimodal imaging.A 71-year-old male with BD was referred for evaluation of a choroidal nevus in the right eye. Dilated fundoscopic exam showed a small pigmented choroidal nevus in the temporal periphery. Over a 3-year period the nevus developed progressive deposition of vitelliform material along its inferior border. Meanwhile, OCT and fundus photography showed only slight growth. Ultrasound showed no change in height; basal measurements were confounded by the increased vitelliform deposits. Genetic testing confirmed a heterozygous mutation in the BEST1 gene and electrophysiology was consistent with BD.Dysfunction of the retinal pigment epithelium associated with BD may cause novel presentations of other conditions such as choroidal nevi. The implications for malignant transformation of a choroidal nevus associated with vitelliform deposit accumulation in this context is unknown.

Purpose: This work describes the characteristics and unique features of ocular syphilis. Methods: Ten serologically proven cases of ocular syphilis were retrospectively analyzed. Results: Eighteen eyes of 10 patients were affected. Nine of 10 patients were male and the mean age was 58 years (range, 36-81 years). HIV antibody testing was positive in 3 patients (30%). Five cases were first diagnosed by an ophthalmologist. One patient presented with a syphilitic rash. The most common ocular findings were panuveitis (n = 6) and cystoid macular edema (n = 4). Ocular involvement was unilateral in 2 cases and bilateral in 8. Best-corrected visual acuity improved in 13 of 18 eyes (72%) after treatment. Three cases developed recurrent retinal detachments that required repair with silicone oil. Conclusions: Most cases were HIV negative. Syphilitic uveitis can be the initial presentation of syphilis without classic systemic manifestation. Ophthalmologists play an important role in the diagnosis and treatment of syphilis.

We report novel case of a 57-year-old woman who developed bilateral ocular ischemic syndrome in the setting of chronic angle closure glaucoma without associated angle neovascularization. Detailed is a course in which markedly prolonged, elevated intraocular pressure led to significantly reduced arterial perfusion at the level of the central retinal artery, leading to the clinical picture of ocular ischemic syndrome.

Retinal swelling due to the accumulation of fluid is associated with the most vision-threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of care in assessing the presence and quantity of retinal fluid and image-guided treatment management. Deep learning methods have made their impact across medical imaging, and many retinal OCT analysis methods have been proposed. However, it is currently not clear how successful they are in interpreting the retinal fluid on OCT, which is due to the lack of standardized benchmarks. To address this, we organized a challenge RETOUCH in conjunction with MICCAI 2017, with eight teams participating. The challenge consisted of two tasks: fluid detection and fluid segmentation. It featured for the first time: all three retinal fluid types, with annotated images provided by two clinical centers, which were acquired with the three most common OCT device vendors from patients with two different retinal diseases. The analysis revealed that in the detection task, the performance on the automated fluid detection was within the inter-grader variability. However, in the segmentation task, fusing the automated methods produced segmentations that were superior to all individual methods, indicating the need for further improvements in the segmentation performance.

Purpose To report a case of Nocardia cyriacigeorgica endophthalmitis. Methods Case report. Results A 71-year-old man on long-term steroid therapy for poor respiratory function from lung carcinoma and presumed recent liver metastases presented with a four week history of blurry vision in the left eye. Ophthalmic examination revealed a white elevated mass in the macula with hemorrhage, concerning for metastasis. The patient was treated for presumed ocular metastases but had poor response to radiotherapy and was diagnosed four weeks later with N. cyriacigeorgica by retinal biopsy. Despite intravitreal and systemic antibiotics, the patient had progression of disease and died of respiratory involvement. Conclusion Nocardia endogenous endophthalmitis can present as a mass retinal lesion in immunosuppressed patients with metastatic disease. Early vitreous and retinal biopsy may be required for definitive diagnosis and treatment. A pulmonary source of infection should be suspected and monitored closely.

Purpose: To report the association of optic nerve head (ONH) drusen with Best vitelliform macular dystrophy (BVMD). Methods: Chart review. Patients: Five patients from 3 families. Results: Multimodal imaging and ophthalmic examination demonstrated findings consistent with ONH drusen, in association with BVMD, in 5 patients. Conclusion: We report the association of BVMD with ONH drusen in 5 patients. This combination has previously been reported only once. We recommend that patients with a diagnosis of BVMD undergo autofluorescence and ultrasound imaging of the optic nerve to help facilitate this diagnosis, as some ONH drusen can be buried.

Purpose:The objective of this study is to perform a systematic review and provide an update on the diagnosis and management of retinopathy associated with incontinentia pigmenti (IP).Design:This is a systematic review.Methods:A literature search was performed for articles related to IP-associated retinopathy on PubMed, Embase, and ScienceDirect with no date limitations. Articles published on ophthalmology journals were screened and original human studies pertaining to the diagnosis and management of IP retinopathy were included for data analysis. The clinical and imaging findings, treatment, follow-up frequency and duration, and final visual outcomes were recorded.Results:The literature search retrieved 388 articles across the databases. Forty-two full-text peer-reviewed original human studies, containing 100 eyes of 60 unique patients of IP retinopathy, met our inclusion criteria. The majority of patients (68%) presented with IP retinopathy during the first 2 years of life, and 12 eyes of 8 patients who progressed from mild to severe IP retinopathy were all presented before the age of 4 months. Thirty-one (31%) eyes developed retinal detachment, 24 (24%) eyes had a final visual acuity of light perception or no light perception, and 14 (14%) eyes had a visual acuity of 20/50 or better.Conclusion:The results of this systematic review suggest that early detection and early frequent reevaluation of retinopathy in patients with IP in the first 2 years of life are key in obtaining optimal visual outcomes. Therefore, we propose an updated IP retinopathy management algorithm.

Background Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath’s four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated. Results Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18–20 years after DNAm measurement. However, higher PhenoAge (β = 0.023, p = 0.007) and GrimAge (β = 0.029, p = 0.002) were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy (OR = 1.07, p = 9.24E−3) and cardiovascular autonomic neuropathy (OR = 1.06, p = 0.011). Both HbA1c (β = 0.38, p = 0.026) and T1D duration (β = 0.01, p = 0.043) were associated with higher PhenoAge. Employment (β = − 1.99, p = 0.045) and leisure time (β = − 0.81, p = 0.022) physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI (β = 0.09, p = 0.048) and current smoking (β = 7.13, p = 9.03E−50) were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used. Conclusions Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others.

Purpose To analyze and provide an overview of the incidence, management, and prevention of conjunctival erosion in Argus II clinical trial subjects and postapproval patients. Methods This retrospective analysis followed the results of 274 patients treated with the Argus II Retinal Prosthesis System between June 2007 and November 2017, including 30 subjects from the US and European clinical trials, and 244 patients in the postapproval phase. Results were gathered for incidence of a serious adverse event, incidence of conjunctival erosion, occurrence sites, rates of erosion, and erosion timing. Results Overall, 60% of subjects in the clinical trial subjects versus 83% of patients in the postapproval phase did not experience device- or surgery-related serious adverse events. In the postapproval phase, conjunctival erosion had an incidence rate of 6.2% over 5 years and 11 months. In 55% of conjunctival erosion cases, erosion occurred in the inferotemporal quadrant, 25% in the superotemporal quadrant, and 20% in both. Sixty percent of the erosion events occurred in the first 15 months after implantation, and 85% within the first 2.5 years. Conclusion Reducing occurrence of conjunctival erosion in patients with the Argus II Retinal Prosthesis requires identification and minimization of risk factors before and during implantation. Implementing inverted sutures at the implant tabs, use of graft material at these locations as well as Mersilene rather than nylon sutures, and accurate Tenon's and conjunctiva closure are recommended for consideration in all patients.

This paper presents a novel classification-based optic disc (OD) segmentation algorithm that detects the OD boundary and the location of vessel origin (VO) pixel. First, the green plane of each fundus image is resized and morphologically reconstructed using a circular structuring element. Bright regions are then extracted from the morphologically reconstructed image that lie in close vicinity of the major blood vessels. Next, the bright regions are classified as bright probable OD regions and non-OD regions using six region-based features and a Gaussian mixture model classifier. The classified bright probable OD region with maximum Vessel-Sum and Solidity is detected as the best candidate region for the OD. Other bright probable OD regions within 1-disc diameter from the centroid of the best candidate OD region are then detected as remaining candidate regions for the OD. A convex hull containing all the candidate OD regions is then estimated, and a best-fit ellipse across the convex hull becomes the segmented OD boundary. Finally, the centroid of major blood vessels within the segmented OD boundary is detected as the VO pixel location. The proposed algorithm has low computation time complexity and it is robust to variations in image illumination, imaging angles, and retinal abnormalities. This algorithm achieves 98.8%–100% OD segmentation success and OD segmentation overlap score in the range of 72%–84% on images from the six public datasets of DRIVE, DIARETDB1, DIARETDB0, CHASE_DB1, MESSIDOR, and STARE in less than 2.14 s per image. Thus, the proposed algorithm can be used for automated detection of retinal pathologies, such as glaucoma, diabetic retinopathy, and maculopathy.

Introduction To assess the anatomical changes taking place in the choroid after a scleral buckle (SB) procedure for retinal detachment repair. Methods This cross-sectional study looked at 23 adults with a history of unilateral retinal detachment repaired with a SB or other encircling element. The subjects underwent bilateral Enhanced Depth Spectral Domain Optical Coherence Tomography to image the choroid. The choroidal thickness (CT) was measured, and the non-operative eye was used as an internal control. Results CT was measured to be 170.8 ± 60.9 µm (mean ± SD) in eyes with SBs compared to 175.1 ± 61.9 µm in non-operative eyes. There was no statistically significant difference between the two groups (mean 4.3 µm, 95% CI −8.7, 17.3, p value 0.4973, paired t test). Conclusion Placement of an SB as part of a surgery to repair retinal detachment did not significantly alter CT at the macula.

Purpose To report a rare case of a unilateral choroidal mast cell infiltration in a patient with aggressive systemic mastocytosis (ASM). Observations The patient is a man in his fifties with a diagnosis of ASM. He developed visual complaints in the right eye associated with an area of subretinal fluid on fundus examination. Visual acuity at presentation was 20/150 in the right eye and 20/25 in the left eye. After ophthalmic and radiologic imaging workup, the patient was diagnosed with presumed choroidal mast cell infiltrate. The index of suspicion was high due to the prior ASM diagnosis. External beam radiation and intravitreal injection treatments were offered but the patient declined. The patient was switched from interferon to a new targeted systemic therapy for ASM, midostaurin. Despite some mixed, temporary response in systemic symptoms/signs of ASM at four months, the choroidal lesion and subretinal fluid were stable with visual acuity at 20/125. Conclusion and importance Mast cell choroidal infiltration in ASM should be considered as part of the differential with acute/subacute vision changes. Diagnosis requires exclusion of other possibilities with ocular imaging and in this case, monitoring for development of other malignancies in which there were none. Midostaurin's ocular response was not on par with systemic response. Additional localized ocular therapies may be required.

The Argus II retinal prosthesis (Second Sight Medical Products, Sylmar, CA, USA) is an electronic epiretinal implant designed for use in patients with end-stage retinitis pigmentosa, as well as for other outer retinal degenerative conditions, such as choroideremia, Leber’s congenital amaurosis, Bardet-Biedl syndrome, Usher syndrome and rod–cone disease.1 This device was tested in a clinical trial of 30 subjects in the USA and in Europe to measure the rate of serious adverse events (SAEs) and to assess its effects on functional vision and visual acuity.2–4 Subjects performed better on visual tasks with the device turned on and retained these improvements at 5 years postsurgery.4 Additionally, an acceptable safety profile enabled approval of the device for consumer use by the European regulatory authorities in 2011 (Conformite Europeenne (CE) mark) and by the US Food and Drug Administration (FDA) in 2013 (FDA approval). The implant is composed of an extraocular component, namely, an electronics case and implant coil, as well as an intraocular component involving a 60-electrode array that is tacked over the macula (figure 1). The extraocular and intraocular components are connected by a trans-scleral silicone-coated polyamide electrode cable, and the implantation procedure involves a 5.2 mm pars plana sclerotomy incision to insert the electrode array and the electrode cable into the eye. The sclerotomy is then sutured around the cable and covered by an allograft or autograft material.5 Figure 1 The Argus II retinal prosthesis. Labelled image of the Argus II implant (adapted from Humayun et al 2). As with any system having both intraocular and extraocular components, the trans-scleral electrode cable that traverses the sclerotomy permanently is a high-risk feature of the device, as leakage through the pars plana incision can result in chronic hypotony. The percentages of clinical trial subjects who experienced hypotony were 10.0% at …

Diagnosis and monitoring of retina diseases related to pathologies such as accumulated fluid can be performed using optical coherence tomography (OCT). OCT acquires a series of 2D slices (Bscans). This work presents a fully-automated method based on graph shortest path algorithms and convolutional neural network (CNN) to segment and detect three types of fluid including sub-retinal fluid (SRF), intra-retinal fluid (IRF) and pigment epithelium detachment (PED) in OCT Bscans of subjects with age-related macular degeneration (AMD) and retinal vein occlusion (RVO) or diabetic retinopathy. The proposed method achieves an average dice coefficient of 76.44%, 92.25% and 82.14% in Cirrus, Spectralis and Topcon datasets, respectively. The effectiveness of the proposed methods was also demonstrated in segmenting fluid in OCT images from the 2017 Retouch challenge.

Purpose: A 59-year-old man with retinitis pigmentosa, who received an Argus II retinal prosthesis in the left eye 3 years prior, presented with left-sided involuntary facial contractions that occurred only after turning on the Argus II device. Methods: A case report. Results: Given that this patient's reported and visualized lower eyelid twitching corresponds to the location of the external region of the implanted coil, we hypothesize that heat or wirelessly transmitted electrical signals from the external coil to the implanted coil may induce spasm of the facial nerve and thus play a role in hemifacial spasm onset. Conclusions: To our knowledge, this is the first report of hemifacial spasm associated with Argus II use.

This paper presents a novel unsupervised iterative blood vessel segmentation algorithm using fundus images. First, a vessel enhanced image is generated by tophat reconstruction of the negative green plane image. An initial estimate of the segmented vasculature is extracted by global thresholding the vessel enhanced image. Next, new vessel pixels are identified iteratively by adaptive thresholding of the residual image generated by masking out the existing segmented vessel estimate from the vessel enhanced image. The new vessel pixels are, then, region grown into the existing vessel, thereby resulting in an iterative enhancement of the segmented vessel structure. As the iterations progress, the number of false edge pixels identified as new vessel pixels increases compared to the number of actual vessel pixels. A key contribution of this paper is a novel stopping criterion that terminates the iterative process leading to higher vessel segmentation accuracy. This iterative algorithm is robust to the rate of new vessel pixel addition since it achieves 93.2–95.35% vessel segmentation accuracy with 0.9577–0.9638 area under ROC curve (AUC) on abnormal retinal images from the STARE dataset. The proposed algorithm is computationally efficient and consistent in vessel segmentation performance for retinal images with variations due to pathology, uneven illumination, pigmentation, and fields of view since it achieves a vessel segmentation accuracy of about 95% in an average time of 2.45, 3.95, and 8 s on images from three public datasets DRIVE, STARE, and CHASE_DB1, respectively. Additionally, the proposed algorithm has more than 90% segmentation accuracy for segmenting peripapillary blood vessels in the images from the DRIVE and CHASE_DB1 datasets.

The authors describe the implantation of the Argus II Retinal Prosthesis System (Argus II) (Second Sight Medical Products, Sylmar, CA) into a short axial length (AL) eye. The authors' main modification is the use of endocyclophotocoagulation (endo-CPC) to the ciliary processes in the area that the cable enters through the sclerotomy. This case describes the surgical technique necessary for successful implantation of the Argus II into a short AL eye. The use of endo-PC prevents chaffing to the ciliary processes, does not affect postoperative intraocular pressure, and facilitates direct visualization of the structures during the surgery, preventing damage during implantation. [ Ophthalmic Surg Lasers Imaging Retina . 2016;47:369–371.]

A fully-automated method based on graph shortest path, graph cut and neutrosophic (NS) sets is presented for fluid segmentation in OCT volumes for exudative age related macular degeneration (EAMD) subjects. The proposed method includes three main steps: 1) The inner limiting membrane (ILM) and the retinal pigment epithelium (RPE) layers are segmented using proposed methods based on graph shortest path in NS domain. A flattened RPE boundary is calculated such that all three types of fluid regions, intra-retinal, sub-retinal and sub-RPE, are located above it. 2) Seed points for fluid (object) and tissue (background) are initialized for graph cut by the proposed automated method. 3) A new cost function is proposed in kernel space, and is minimized with max-flow/min-cut algorithms, leading to a binary segmentation. Important properties of the proposed steps are proven and quantitative performance of each step is analyzed separately. The proposed method is evaluated using a publicly available dataset referred as Optima and a local dataset from the UMN clinic. For fluid segmentation in 2D individual slices, the proposed method outperforms the previously proposed methods by 18%, 21% with respect to the dice coefficient and sensitivity, respectively, on the Optima dataset, and by 16%, 11% and 12% with respect to the dice coefficient, sensitivity and precision, respectively, on the local UMN dataset. Finally, for 3D fluid volume segmentation, the proposed method achieves true positive rate (TPR) and false positive rate (FPR) of 90% and 0.74%, respectively, with a correlation of 95% between automated and expert manual segmentations using linear regression analysis.

Automated classification of retinal vessels in fundus images is the first step towards measurement of retinal characteristics that can be used to screen and diagnose vessel abnormalities for cardiovascular and retinal disorders. This paper presents a novel approach to vessel classification to compute the artery/vein ratio (AVR) for all blood vessel segments in the fundus image. The features extracted are then subjected to a selection procedure using Random Forests (RF) where the features that contribute most to classification accuracy are chosen as input to a polynomial kernel Support Vector Machine (SVM) classifier. The most dominant feature was found to be the vessel information obtained from the Light plane of the LAB color space. The SVM is then subjected to one time training using 10-fold cross validation on images randomly selected from the VICAVR dataset before testing on an independent test dataset, derived from the same database. An Area Under the ROC Curve (AUC) of 97.2% was obtained on an average of 100 runs of the algorithm. The proposed algorithm is robust due to the feature selection procedure, and it is possible to get similar accuracies across many datasets.

This paper presents a computer-aided screening system (DREAM) that analyzes fundus images with varying illumination and fields of view, and generates a severity grade for diabetic retinopathy (DR) using machine learning. Classifiers such as the Gaussian Mixture model (GMM), k-nearest neighbor (kNN), support vector machine (SVM), and AdaBoost are analyzed for classifying retinopathy lesions from nonlesions. GMM and kNN classifiers are found to be the best classifiers for bright and red lesion classification, respectively. A main contribution of this paper is the reduction in the number of features used for lesion classification by feature ranking using Adaboost where 30 top features are selected out of 78. A novel two-step hierarchical classification approach is proposed where the nonlesions or false positives are rejected in the first step. In the second step, the bright lesions are classified as hard exudates and cotton wool spots, and the red lesions are classified as hemorrhages and micro-aneurysms. This lesion classification problem deals with unbalanced datasets and SVM or combination classifiers derived from SVM using the Dempster-Shafer theory are found to incur more classification error than the GMM and kNN classifiers due to the data imbalance. The DR severity grading system is tested on 1200 images from the publicly available MESSIDOR dataset. The DREAM system achieves 100% sensitivity, 53.16% specificity, and 0.904 AUC, compared to the best reported 96% sensitivity, 51% specificity, and 0.875 AUC, for classifying images as with or without DR. The feature reduction further reduces the average computation time for DR severity per image from 59.54 to 3.46 s.

An 87-year-old woman presented 11 months after routine phacoemulsification cataract extraction and posterior chamber intraocular lens implantation in her left eye complaining of the abrupt onset of redness and decreased vision in that eye. Examination revealed a mild anterior chamber reaction and significant corneal edema. The eye was minimally responsive to topical steroid therapy, and initial serial slitlamp examinations with gonioscopy were unrevealing. After multiple head-positioning maneuvers were performed, a retained nuclear fragment was uncovered. The nuclear fragment was aspirated and liquefied by the phacoemulsification device in the anterior chamber. A retained nuclear fragment with an intact posterior capsule is a recognized cause of inflammation in the immediate postoperative presentation. Delayed presentation of symptoms is rare and presumably secondary to sequestration of the fragment behind the iris. We present a case and a review of the literature regarding sequestered retained nuclear fragments following what is initially thought to be uneventful cataract extraction. Financial Disclosure No author has a financial or proprietary interest in any material or method mentioned.

Neovascularization is the primary manifestation of proliferative diabetic retinopathy (PDR) that can lead to acquired blindness. This paper presents a novel method that classifies neovascularizations in the 1-optic disc (OD) diameter region (NVD) and elsewhere (NVE) separately to achieve low false positive rates of neovascularization classification. First, the OD region and blood vessels are extracted. Next, the major blood vessel segments in the 1-OD diameter region are classified for NVD, and minor blood vessel segments elsewhere are classified for NVE. For NVD and NVE classifications, optimal region-based feature sets of 10 and 6 features, respectively, are used. The proposed method achieves classification sensitivity, specificity and accuracy for NVD and NVE of 74%, 98.2%, 87.6%, and 61%, 97.5%, 92.1%, respectively. Also, the proposed method achieves 86.4% sensitivity and 76% specificity for screening images with PDR from public and local data sets. Thus, the proposed NVD and NVE detection methods can play a key role in automated screening and prioritization of patients with diabetic retinopathy.

Fundus autofluorescence has been used in Stargardt macular dystrophy and fundus flavimaculatus to better understand disease status and progression. Fundus autofluorescence images delineate atrophic regions with great clarity and high contrast. The authors investigated whether fundus autofluorescence images revealed more atrophy than color fundus photographs by studying a family of three siblings with long-standing disease that demonstrated a heterogeneous fundus appearance. Findings on fundus autofluorescence were compared with color fundus photographs and fluorescein images. Optical coherence tomography images were also analyzed. Areas of atrophic lesions were measured and compared on fundus autofluorescence and color fundus photographs. Autofluorescence images delineated atrophic regions more clearly than color fundus photographs. However, the measured areas of atrophy were only modestly larger in fundus autofluorescence images than in color fundus photographs. The optical coherence tomography images showed severe outer retinal atrophy and loss of foveal contour.

This paper presents a novel automated system that segments 3-D thickness maps of sub-retinal layers from healthy and abnormal OCT image stacks with Diabetic Macular Edema (DME). These automated thickness maps are well correlated (r > 0.7) with the manually segmented thickness maps. The thickness maps demonstrate highly irregular regions in the inner and outer nuclear layers for patients with DME when compared to the healthy images. The combined area of irregularity in the inner and outer nuclear layers can thereby be extracted as a novel metric with correlation r = 0.99 to track the severity of DME. No other existing automated algorithm has extracted inner sub-retinal layer thickness maps from OCT image stacks of DME patients. The proposed system is fast and robust in locating the sub-retinal changes caused by DME in the 3-D sub-retinal micro-structure.

Optical coherence tomography (OCT) is a new ophthalmic imaging modality generating cross sectional views of the retina. OCT systems are essentially Michelson interferometers that form images in 1.5 s by directing a superluminescent diode (SLD) beam over the retinal surface. Involuntary eye motions frequently cause incorrect locations to be imaged. This motion may leave no obvious artifacts in the scan data and can easily go undetected. For glaucoma monitoring especially, knowing the measurement path, typically a circle concentric with the nerve head, is crucial. The commercially available OCT system displays a near-infrared video of the retina showing the SLD beam. This paper presents a prototype system to detect the nerve head and SLD beam in the video, and report the true scan path relative to the nerve head. Low image contrast and limited resolution make the reliable detection of retinal features difficult. In an adaptive model construction phase, the system directly detects retinal vasculature and the nerve head and incrementally builds a model of the current subject's vascular pattern relative to the optic disk. The nerve head identification is multitiered, using a novel dual eigenspace technique and a geometric comparison of detected vessel positions and nerve head hypotheses. In its operational phase, a correspondence is achieved between the currently detected vasculature and the model. Using subjects not included in training, the system located the optic nerve head to within 5 pixels (0.07 optic disk diameters, an error well below clinical significance) in 99.75% of 2800 video fields. In current clinical practice, motions as large as 1-2 disc diameters may go undetected, so this is a vast improvement.

Implementation of multicenter and/or longitudinal studies requires an effective quality assurance program to identify trends, data inconsistencies and process variability of results over time. The Diabetes Control and Complications Trial (DCCT) and the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study represent over 30 years of data collection among a cohort of participants across 27 clinical centers. The quality assurance plan is overseen by the Data Coordinating Center and is implemented across the clinical centers and central reading units. Each central unit incorporates specific DCCT/EDIC quality monitoring activities into their routine quality assurance plan. The results are reviewed by a data quality assurance committee whose function is to identify variances in quality that may impact study results from the central units as well as within and across clinical centers, and to recommend implementation of corrective procedures when necessary. Over the 30-year period, changes to the methods, equipment, or clinical procedures have been required to keep procedures current and ensure continued collection of scientifically valid and clinically relevant results. Pilot testing to compare historic processes with contemporary alternatives is performed and comparability is validated prior to incorporation of new procedures into the study. Details of the quality assurance plan across and within the clinical and central reading units are described, and quality outcomes for core measures analyzed by the central reading units (e.g. biochemical samples, fundus photographs, ECGs) are presented.

This paper presents a novel three-stage blood vessel segmentation algorithm using fundus photographs. In the first stage, the green plane of a fundus image is preprocessed to extract a binary image after high-pass filtering, and another binary image from the morphologically reconstructed enhanced image for the vessel regions. Next, the regions common to both the binary images are extracted as the major vessels . In the second stage, all remaining pixels in the two binary images are classified using a Gaussian mixture model (GMM) classifier using a set of eight features that are extracted based on pixel neighborhood and first and second-order gradient images. In the third postprocessing stage, the major portions of the blood vessels are combined with the classified vessel pixels. The proposed algorithm is less dependent on training data, requires less segmentation time and achieves consistent vessel segmentation accuracy on normal images as well as images with pathology when compared to existing supervised segmentation methods. The proposed algorithm achieves a vessel segmentation accuracy of 95.2%, 95.15%, and 95.3% in an average of 3.1, 6.7, and 11.7 s on three public datasets DRIVE, STARE, and CHASE_DB1, respectively.

Presents a system for detecting retinal boundaries in optical coherence tomography (OCT) B-scans. OCT is a relatively new imaging modality giving cross-sectional images that are qualitatively similar to ultrasound. However, the axial resolution with OCT is much higher, on the order of 10 /spl mu/m. Objective, quantitative measures of retinal thickness may be made from OCT images. Knowledge of retinal thickness is important in the evaluation and treatment of many ocular diseases. The boundary-detection system presented here uses a one-dimensional edge-detection kernel to yield edge primitives. These edge primitives are rated, selected, and organized to form a coherent boundary structure by use of a Markov model of retinal boundaries as detected by OCT. Qualitatively, the boundaries detected by the automated system generally agreed extremely well with the true retinal structure for the vast majority of OCT images. Only one of the 1450 evaluation images caused the algorithm to fail. A quantitative evaluation of the retinal boundaries was performed as well, using the clinical application of automatic retinal thickness determination. Retinal thickness measurements derived from the algorithm's results were compared with thickness measurements from manually corrected boundaries for 1450 test images. The algorithm's thickness measurements over a 1-mm region near the fovea differed from the corrected thickness measurements by less than 10 /spl mu/m for 74% of the images and by less than 25 /spl mu/m (10% of normal retinal thickness) for 98.4% of the images. These errors are near the machine's resolution limit and still well below clinical significance. Current, standard clinical practice involves a qualitative, visual assessment of retinal thickness. A robust, quantitatively accurate system such as the authors' can be expected to improve patient care.

Coats disease is a well-described clinical condition featuring peripheral leakage from telangiectatic vasculature, resulting in exudative retinal detachments and exudative deposits. It often affects pediatric patients, requiring examinations and treatments to be performed under anesthesia. It can be difficult to distinguish from retinoblastoma. The RetCam II is a wide-field fundus imaging system that can also obtain intraoperative fluorescein angiography. The case of a 5-year-old girl diagnosed with Coats disease is presented. She presented with an exudative detachment, a submacular nodule, and peripheral telangiectasis. An examination under anesthesia, including angiography, was performed. The angiograph revealed characteristic aneurysms as well as extensive areas of telangiectasis and ischemia not readily visible on examination. The angiogram allowed more diagnostic certainty and guided a more complete treatment than otherwise possible. We propose that fluorescein angiography with the RetCam II system can be a useful tool when examining and treating pediatric patients with Coats disease.

Spectral domain optical coherence tomography (SDOCT) images from an infant victim of shaken baby syndrome who presented with vitreous hemorrhage in the left eye and bilateral, large hemorrhages over both maculae. Both RetCam and SD-OCT images were obtained, demonstrating the position of the blood beneath the internal limiting membrane of the right macula. Image registration software was used to register the photographic images with the surface projection images obtained by the SD-OCT. In the left eye, the vitreous hemorrhage was removed with vitrectomy, and the retinoschisis cavity incised to allow drainage.

This paper presents a novel automated system that denoises and segments seven sub-retinal layers in optical coherence tomography (OCT) images. First, the OCT images are subjected to Wiener deconvolution by varying the noise variance from 10−1 to 10−15. A new Fourier-domain structural error is introduced in this paper, and the deconvolved OCT image with the least structural error is selected as the denoised image. The properties of the structural error metric are studied, and it is shown that the error metric satisfies convexity property. For each image, the proposed denoising method increases the image SNR by 6.9 dB on average compared to 5 dB increase reported so far, and attains a mean peak SNR (PSNR) of 23.036 dB. Next, highpass filters are applied to the denoised images in an iterative manner to extract the seven sub-retinal layers. The proposed system requires on average 10.65 seconds for denoising an image and 22.07 seconds for segmenting seven sub-retinal layers. This is a significant improvement over manual segmentation that requires up to 12 minutes per image.

This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image $g$ is transformed into three sets: $T$ (true), $I$ (indeterminate) that represents noise, and $F$ (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set $I$ , and a new $\lambda$ -correction operation is introduced to compute the set $T$ in neutrosophic domain. Second, a graph shortest-path method is applied in neutrosophic domain to segment the inner limiting membrane and the retinal pigment epithelium as regions of interest (ROI) and outer plexiform layer and inner segment myeloid as middle layers using a novel definition of the edge weights . Third, a new cost function for cluster-based fluid/cyst segmentation in ROI is presented which also includes a novel approach in estimating the number of clusters in an automated manner. Fourth, the final fluid regions are achieved by ignoring very small regions and the regions between middle layers. The proposed method is evaluated using two publicly available datasets: Duke, Optima, and a third local dataset from the UMN clinic which is available online. The proposed algorithm outperforms the previously proposed Duke algorithm by 8% with respect to the dice coefficient and by 5% with respect to precision on the Duke dataset, while achieving about the same sensitivity. Also, the proposed algorithm outperforms a prior method for Optima dataset by 6%, 22%, and 23% with respect to the dice coefficient, sensitivity, and precision, respectively. Finally, the proposed algorithm also achieves sensitivity of 67.3%, 88.8%, and 76.7%, for the Duke, Optima, and the university of minnesota (UMN) datasets, respectively.