Ultra-widefield Fundus Imaging Research Articles

Successful Adjunctive Treatment of Bilateral Diffuse Uveal Melanocytic Proliferation (BDUMP) with High-Dose Intravenous Immunoglobulin Therapy (IVIG).

Purpose: The management of bilateral diffuse uveal melanocytic proliferation is controversial, with most earlier reports advocating for plasmapheresis. Here, we report a case of bilateral diffuse uveal melanocytic proliferation secondary to gastric adenocarcinoma that was successfully treated with adjunctive intravenous immunoglobulin, using a loading dose followed by a treat-and-extend strategy. Methods: Clinical case report with 3 years of follow-up including serial ophthalmologic examinations. Functional assessments included visual acuity and subjective visual complaints. Periodic anatomic assessments were performed including serial optical coherence tomography, ultra-widefield fundus imaging, multimodal angiography, and ophthalmic ultrasound. Results: A 75-year-old man presented with a 6-month history of blurry vision and difficulty with dark and light adaptation in both eyes. A diagnosis of bilateral diffuse uveal melanocytic proliferation was established based on clinical findings and subsequent discovery of an underlying gastric malignancy; the diagnosis of a paraneoplastic syndrome was further substantiated by documentation of cancer-associated antiretinal antibodies and serum reactivity against human retina by immunohistochemistry. Treatment with high-dose (2 g/kg) intravenous immunoglobulin was initiated with biweekly, followed by monthly, then q2-3 monthly dosing intervals. Meanwhile, the patient received surgical resection and systemic chemotherapy resulting in complete radiographic remission of the primary cancer. Over the course of 3 years, the patient has demonstrated clinically significant improvements in visual acuity and subjective visual function. Rapid and sustained anatomic improvements were observed in serous retinopathy and choroidal thickness. Conclusion: Intravenous immunoglobulin may be a viable adjunctive treatment option for some patients with bilateral diffuse uveal melanocytic proliferation.

THE MINI-STEAMROLL: An Abbreviated Variation of the Steamroller Maneuver After Pneumatic Retinopexy for Rhegmatogenous Retinal Detachment.

To describe a novel positioning maneuver for patients with rhegmatogenous retinal detachment after pneumatic retinopexy (PnR). Single-center prospective case series of primary rhegmatogenous retinal detachments referred to St. Michael's Hospital, Toronto, Canada, between 2021 and 2023. All patients underwent PnR. Baseline ultra-widefield fundus imaging and repeat imaging 10 minutes after the gas injection was performed. After PnR, patients were instructed to perform the mini-steamroll maneuver, which consists of a face-down position for 10 minutes followed by positioning to the retinal break. The reduction of subretinal fluid volume after the initial face-down position was evaluated with clinical examination and ultra-widefield imaging. Six patients who presented with primary bullous rhegmatogenous retinal detachment and a sizable superior break were enrolled. The mini-steamroll maneuver resulted in a rapid and significant reduction of subretinal fluid in all patients with bullous rhegmatogenous retinal detachment and large superior breaks, allowing subretinal fluid to be expressed into the vitreous cavity with 10 minutes of face-down positioning. One patient required a sequential PnR. Primary retinal reattachment was achieved in all cases. This approach was well-tolerated by patients. This case series demonstrates that the mini-steamroll maneuver may be a suitable alternative for patient positioning after PnR in certain cases. The mini-steamroll is a simpler positioning regimen with the potential benefits of direct-to-break and full steamroller maneuver.

Development and Validation of an Automatic Ultrawide-Field Fundus Imaging Enhancement System for Facilitating Clinical Diagnosis: A Cross-Sectional Multicenter Study

In ophthalmology, the quality of fundus images is critical for accurate diagnosis, both in clinical practice and in artificial intelligence (AI)-assisted diagnostics. Despite the broad view provided by ultrawide-field (UWF) imaging, pseudocolor images may conceal critical lesions necessary for precise diagnosis. To address this, we introduce UWF-Net, a sophisticated image enhancement algorithm that takes disease characteristics into consideration. Using the Fudan University ultra-wide-field image (FDUWI) dataset, which includes 11 294 Optos pseudocolor and 2415 Zeiss true-color UWF images, each of which is rigorously annotated, UWF-Net combines global style modeling with feature-level lesion enhancement. Pathological consistency loss is also applied to maintain fundus feature integrity, significantly improving image quality. Quantitative and qualitative evaluations demonstrated that UWF-Net outperforms existing methods such as contrast limited adaptive histogram equalization (CLAHE) and structure and illumination constrained generative adversarial network (StillGAN), delivering superior retinal image quality, higher quality scores, and preserved feature details after enhancement. In disease classification tasks, images enhanced by UWF-Net showed notable improvements when processed with existing classification systems over those enhanced by StillGAN, demonstrating a 4.62% increase in sensitivity (SEN) and a 3.97% increase in accuracy (ACC). In a multicenter clinical setting, UWF-Net-enhanced images were preferred by ophthalmologic technicians and doctors, and yielded a significant reduction in diagnostic time ((13.17 ± 8.40) s for UWF-Net enhanced images vs (19.54 ± 12.40) s for original images) and an increase in diagnostic accuracy (87.71% for UWF-Net enhanced images vs 80.40% for original images). Our research verifies that UWF-Net markedly improves the quality of UWF imaging, facilitating better clinical outcomes and more reliable AI-assisted disease classification. The clinical integration of UWF-Net holds great promise for enhancing diagnostic processes and patient care in ophthalmology.

Comparison of B-Scan ultrasonography, ultra-widefield fundus imaging, and indirect ophthalmoscopy in detecting retinal breaks in cataractous eyes.

To evaluate the diagnostic performance of B-scan kinetic ultrasonography (USG), standard ultra-widefield (UWF) imaging, and indirect ophthalmoscopy (IDO) in retinal break detection in cataractous eyes. We consecutively enrolled 126 cataract patients (including 246 eyes) with no comorbidities that could decrease best corrected visual acuity (BCVA). Three index tests (USG, nonmydriatic UWF, and mydriatic IDO) were performed preoperatively to screen for retinal breaks. One week after cataract extraction, a dilated IDO examination was repeated for the definitive diagnosis of retinal break as the reference standard. The sensitivity, specificity, Youden index (YI), and predictive values of each index test were calculated according to postoperative ophthalmoscopic findings. A deep-learning nomogram was developed to quantify the risk of retinal break presence using patients' baseline data and findings reported from preoperative ophthalmic tests. Fifty-two eyes (21%) were excluded from appropriate preoperative UWF imaging because of massive lens opacity. The BCVA cutoff point with maximum YI indicating UWF applicability was 0.6 logMAR (YI = 0.3; area under curve [AUC] = 0.7). Among all 246 eyes, preoperative IDO, USG, and UWF showed fair interobserver agreement (all κ > 0.2). According to postoperative IDO findings, the index tests with the highest sensitivity and specificity were USG (100%) and preoperative IDO (99%), respectively. For cataractous eyes without vision-impairing comorbidities, a BCVA better than 0.6 logMAR (Snellen acuity, 20/80) allows for appropriate nonmydriatic standard UWF imaging. In a high-volume clinic equipped with skilled ophthalmic examiners, screening with USG followed by directed IDO allows the efficient identification of retinal breaks in cataractous eyes.

The role of ultra-widefield imaging with navigated central and peripheral cross-sectional and three-dimensional swept source optical coherence tomography in ophthalmology: Clinical applications.

To assess central and peripheral retinal and choroidal diseases using ultra-widefield (UWF) fundus imaging in combination with navigated central and peripheral cross-sectional and three-dimensional (3D) swept source optical coherence tomography (SS-OCT) scans. Retrospective study involving 332 consecutive patients, with a nearly equal distribution of males and females. The mean age of patients was 52 years (range 18-92 years). Average refractive error was -3.80 D (range +7.75 to -20.75 D). The observations in this study demonstrate the efficacy of peripheral navigated SS-OCT in assessing various ocular conditions. The technology provides high-quality images of the peripheral vitreous, vitreoretinal interface, retina, and choroid, enabling visualization of vitreous floaters and opacities, retinal holes and tears, pigmented lesions, and peripheral retinal degenerations. 3D OCT scans enhance the visualization of these abnormalities and improve diagnostic and therapeutic decisions. Navigated central and peripheral cross-sectional and 3D SS-OCT scans offer significant complementary benefits in the assessment and management of retinal diseases. Their addition to UWF imaging provides a comprehensive view of central and peripheral ocular structures, aiding in early detection, precise anatomical measurements, and objective monitoring of disease progression. In addition, this technology serves as a valuable tool for patient education, a teaching tool for trainees, and documentation for medico-legal purposes.

Analysis of the Retinal and Choroidal Vasculature Using Ultrawidefield Fundus Imaging in Mild Cognitive Impairment and Normal Cognition

PurposeTo utilize ultra-widefield (UWF) imaging to evaluate retinal and choroidal vasculature and structure in individuals with mild cognitive impairment (MCI) compared to controls with normal cognition. DesignProspective cross-sectional study ParticipantsOne hundred thirty-one eyes of 82 MCI patients and 231 eyes of 133 cognitively normal participants from the Eye Multimodal Imaging in Neurodegenerative Disease (iMIND) Study. MethodsA scanning laser ophthalmoscope (SLO) (California, Optos Inc, Marlborough, MA) was used to obtain UWF fundus color images. Images were analyzed with the Vasculature Assessment Platform for Images of the Retina UWF (VAMPIRE-UWF 2.0, Universities of Edinburgh and Dundee, United Kingdom) software. Main outcome measuresImaging parameters included vessel width gradient, vessel width intercept, large vessel choroidal vascular density, vessel tortuosity, and vessel fractal dimension. ResultsBoth retinal artery and vein width gradients were less negative in MCI patients compared to controls, demonstrating decreased rates of vessel thinning at the periphery (p < 0.001, p = 0.027). Retinal artery and vein width intercepts, a metric that extrapolates the width of vessel at the center of the optic disc, were smaller in MCI patients compared to controls (p < 0.001, p = 0.017). The large vessel choroidal vascular density, which quantifies the vascular area versus total choroidal area, was greater in MCI patients compared to controls (p = 0.025). ConclusionsWhen compared to controls with normal cognition, MCI patients had thinner retinal vasculature manifested in both the retinal arteries and in the veins. In MCI, these thinner arteries and veins attenuated at a lower rate when traveling towards the periphery. MCI patients also had increased choroidal vascular density.

AUTOMATED DETECTION OF VITRITIS USING ULTRAWIDE-FIELD FUNDUS PHOTOGRAPHS AND DEEP LEARNING.

Evaluate the performance of a deep learning algorithm for the automated detection and grading of vitritis on ultrawide-field imaging. Cross-sectional noninterventional study. Ultrawide-field fundus retinophotographs of uveitis patients were used. Vitreous haze was defined according to the six steps of the Standardization of Uveitis Nomenclature classification. The deep learning framework TensorFlow and the DenseNet121 convolutional neural network were used to perform the classification task. The best fitted model was tested in a validation study. One thousand one hundred eighty-one images were included. The performance of the model for the detection of vitritis was good with a sensitivity of 91%, a specificity of 89%, an accuracy of 0.90, and an area under the receiver operating characteristics curve of 0.97. When used on an external set of images, the accuracy for the detection of vitritis was 0.78. The accuracy to classify vitritis in one of the six Standardization of Uveitis Nomenclature grades was limited (0.61) but improved to 0.75 when the grades were grouped into three categories. When accepting an error of one grade, the accuracy for the six-class classification increased to 0.90, suggesting the need for a larger sample to improve the model performances. A new deep learning model based on ultrawide-field fundus imaging that produces an efficient tool for the detection of vitritis was described. The performance of the model for the grading into three categories of increasing vitritis severity was acceptable. The performance for the six-class grading of vitritis was limited but can probably be improved with a larger set of images.

Design of ultra-wide-field scanning laser fundus imaging system with cascaded conicoid mirrors.

We propose and design a multi-stage cascaded scanning laser ophthalmoscope (SLO) for ultra-wide field (UWF), which uses conicoid mirrors, constructed by conjugation of pupil plane. The vergence uniformity and the angular magnification of a cascaded conicoid mirrors (CCM) system are analyzed recursively and optimized preliminarily to achieve high quality imaging with UWF, and the optimal system with the model eye are obtained by simulation and optimization. Two-stage and three-stage cascaded systems are designed with this method, and the formulas of beam vergence and angular magnification are obtained by theoretical derivation. As compared to the two-stage CCM system, the proposed three-stage cascaded UWF SLO has superior performance in imaging quality. Its average RMS radius of spot diagram is calculated to be 26.372 µm, close to the diffractive limit resolution. The image resolution of human retina can be up to 30 µm with 135° FOV in theory. The three-stage cascaded SLO is more suitable for UWF fundus imaging. This study will be helpful for early screening and accurate diagnosis of various diseases in the peripheral retina.

Retinal Disease Diagnosis Using Deep Learning on Ultra-Wide-Field Fundus Images.

Ultra-wide-field fundus imaging (UFI) provides comprehensive visualization of crucial eye components, including the optic disk, fovea, and macula. This in-depth view facilitates doctors in accurately diagnosing diseases and recommending suitable treatments. This study investigated the application of various deep learning models for detecting eye diseases using UFI. We developed an automated system that processes and enhances a dataset of 4697 images. Our approach involves brightness and contrast enhancement, followed by applying feature extraction, data augmentation and image classification, integrated with convolutional neural networks. These networks utilize layer-wise feature extraction and transfer learning from pre-trained models to accurately represent and analyze medical images. Among the five evaluated models, including ResNet152, Vision Transformer, InceptionResNetV2, RegNet and ConVNext, ResNet152 is the most effective, achieving a testing area under the curve (AUC) score of 96.47% (with a 95% confidence interval (CI) of 0.931-0.974). Additionally, the paper presents visualizations of the model's predictions, including confidence scores and heatmaps that highlight the model's focal points-particularly where lesions due to damage are evident. By streamlining the diagnosis process and providing intricate prediction details without human intervention, our system serves as a pivotal tool for ophthalmologists. This research underscores the compatibility and potential of utilizing ultra-wide-field images in conjunction with deep learning.

Evaluation of optical coherence tomography biomarkers to differentiate favourable and unfavourable responders to intravitreal anti-vascular endothelial growth factor treatment in retinopathy of prematurity.

Evaluation of optical coherence tomography biomarkers in predicting treatment response to intravitreal injection of anti-vascular endothelial growth factor (anti-VEGF) Bevacizumab, in aggressive retinopathy of prematurity (A-ROP). Non-contact ultra-widefield (NC-UWF) fundus imaging with integrated UWF guided swept source Optical coherence tomography (SS-OCT) was performed prospectively in preterm babies before and after intravitreal anti-VEGF (Bevacizumab) monotherapy. OCT biomarkers were analysed in eyes that reached complete vascularization versus others. Eyes with retinal vessels reaching near ora serrata were labelled as regressed ROP and vascularised retina (Group1). Eyes with reactivation of ROP needing laser or vitreoretinal surgery or eyes with peripheral avascular retina (PAR) at 16th week post-injection were considered as Group 2. Pre-injection baseline OCT showed a hyperreflectivity of inner retinal layers in 12 out of 46 eyes in Group 1 versus 30 out of 34 eyes in Group 2 (p value 0.002). None of the eyes in Group 1 showed choroidal thinning at posterior pole as compared to 14 out of 34 eyes in Group 2 (p value 0.001). Intraretinal hypo reflective Cystic changes at fovea were seen in 16 out of 46 eyes in Group 1 and 2 out of 34 eyes in Group 2 (p value 0.012). Pre-injection swept source OCT biomarkers could predict the treatment outcomes of anti-VEGF (Bevacizumab) monotherapy in A-ROP eyes. Hyperreflectivity of inner retinal layers and choroidal thinning had poorer and unpredictable response to anti-VEGF injection whereas, cystic changes at fovea predicted favourable response.

Deep Learning Performance of Ultra-Widefield Fundus Imaging for Screening Retinal Lesions in Rural Locales

Retinal diseases are the leading cause of irreversible blindness worldwide, and timely detection contributes to prevention of permanent vision loss, especially for patients in rural areas with limited medical resources. Deep learning systems (DLSs) based on fundus images with a 45° field of view have been extensively applied in population screening, while the feasibility of using ultra-widefield (UWF) fundus image-based DLSs to detect retinal lesions in patients in rural areas warrants exploration. To explore the performance of a DLS for multiple retinal lesion screening using UWF fundus images from patients in rural areas. In this diagnostic study, a previously developed DLS based on UWF fundus images was used to screen for 5 retinal lesions (retinal exudates or drusen, glaucomatous optic neuropathy, retinal hemorrhage, lattice degeneration or retinal breaks, and retinal detachment) in 24 villages of Yangxi County, China, between November 17, 2020, and March 30, 2021. The captured images were analyzed by the DLS and ophthalmologists. The performance of the DLS in rural screening was compared with that of the internal validation in the previous model development stage. The image quality, lesion proportion, and complexity of lesion composition were compared between the model development stage and the rural screening stage. A total of 6222 eyes in 3149 participants (1685 women [53.5%]; mean [SD] age, 70.9 [9.1] years) were screened. The DLS achieved a mean (SD) area under the receiver operating characteristic curve (AUC) of 0.918 (0.021) (95% CI, 0.892-0.944) for detecting 5 retinal lesions in the entire data set when applied for patients in rural areas, which was lower than that reported at the model development stage (AUC, 0.998 [0.002] [95% CI, 0.995-1.000]; P < .001). Compared with the fundus images in the model development stage, the fundus images in this rural screening study had an increased frequency of poor quality (13.8% [860 of 6222] vs 0%), increased variation in lesion proportions (0.1% [6 of 6222]-36.5% [2271 of 6222] vs 14.0% [2793 of 19 891]-21.3% [3433 of 16 138]), and an increased complexity of lesion composition. This diagnostic study suggests that the DLS exhibited excellent performance using UWF fundus images as a screening tool for 5 retinal lesions in patients in a rural setting. However, poor image quality, diverse lesion proportions, and a complex set of lesions may have reduced the performance of the DLS; these factors in targeted screening scenarios should be taken into consideration in the model development stage to ensure good performance.

Assessment of early diabetic retinopathy severity using ultra-widefield Clarus versus conventional five-field and ultra-widefield Optos fundus imaging

To compare early diabetic retinopathy (DR) severity level and the abilities in detecting early DR lesions among conventional five-field, ultrawide-field (UWF) Optos, and UWF Clarus fundus imaging methods. This was a single-center, prospective, clinic-based, and comparative study. In total, 157 consecutive patients with diabetes mellitus were enrolled in this study. All patients underwent comprehensive ophthalmological examinations. Following mydriasis, each eye was examined with conventional five-field, UWF Optos, and UWF Clarus fundus imaging methods. The initial UWF images were overlaid with a template mask that obscured the retina, which created a five-field view from UWF images (covered UWF images). The covered UWF images were then graded, after which the template mask was removed, and the original UWF images were also evaluated. All images were graded using the International Clinical DR severity scale. DR grades were compared and analyzed by weighted kappa statistics among the three fundus imaging methods. In total, 157 consecutive patients with diabetes (302 eyes) were enrolled in this study. Weighted kappa statistics for agreement were 0.471 (five-field vs. covered Optos), 0.809 (five-field vs. covered Clarus), 0.396 (covered Optos vs. covered Clarus), 0.463 (five-field vs. Optos), 0.521 (five-field vs. Clarus 133°), 0.500 (five-field vs. Clarus 200°), 0.323 (Optos vs. Clarus 133°), and 0.349 (Optos vs. Clarus 200°). The area under curve of covered Clarus images was higher than that of conventional five-field images at three different thresholds. Compared with conventional five-field and Optos fundus imaging methods, Clarus fundus imaging methods exhibited excellent performance in assessing early DR severity. Thus, Clarus fundus imaging methods were superior for early detection of DR.

X-Linked Retinoschisis Masquerading Uveitis.

X-linked retinoschisis (XLRS) shows features also seen in patients with uveitis and is recognized as an uveitis masquerade syndrome. This retrospective study aimed to describe characteristics of XLRS patients with an initial uveitis diagnosis and to contrast these to patients with an initial XLRS diagnosis. Patients referred to a uveitis clinic, which turned out to have XLRS (n = 4), and patients referred to a clinic for inherited retinal diseases (n = 18) were included. All patients underwent comprehensive ophthalmic examinations, including retinal imaging with fundus photography, ultra-widefield fundus imaging, and optical coherence tomography (OCT). In patients with an initial diagnosis of uveitis, a macular cystoid schisis was always interpreted as an inflammatory macular edema; vitreous hemorrhages were commonly interpreted as intraocular inflammation. Patients with an initial diagnosis of XLRS rarely (2/18; p = 0.02) showed vitreous hemorrhages. No additional demographic, anamnestic, and anatomical differences were found. An increased awareness of XLRS as a uveitis masquerade syndrome may facilitate early diagnosis and may prevent unnecessary therapies.

SPONTANEOUS REATTACHMENT OF RHEGMATOGENOUS RETINAL DETACHMENT

To describe the clinical characteristics and posterior vitreous findings of spontaneous reattachment of rhegmatogenous retinal detachment (SRRRD). Eighty-six eyes from 80 patients who were diagnosed with SRRRD (SRRRD group) and 92 eyes from 92 patients who had undergone successful scleral buckling for rhegmatogenous retinal detachment ( group for comparison) were included. Ultrawide field fundus imaging and spectral domain optical coherence tomography were performed to evaluate fundus characteristics and vitreoretinal interface. A significant difference was found in the proportion of complete posterior vitreous attachment between the SRRRD and rhegmatogenous retinal detachment groups (44.2% vs. 19.6%, P < 0.001). The incidence of atypical epiretinal tissue (AET) in the SRRRD group was 14% (12 of 86 eyes), whereas none of the eyes in the rhegmatogenous retinal detachment group exhibited AET. In SRRRD eyes with AET, the visual acuity was lower (logarithm of the minimum angle of resolution, 0.51 ± 0.57 vs. 0.14 ± 0.15, P < 0.001), the mean age was higher (years, 61.7 vs. 39.4, P < 0.001), and the SRRRD lesion extent was wider (clock hours, 5.67 vs. 3.70, P = 0.004) than in SRRRD eyes without AET. Compared with the rhegmatogenous retinal detachment group, the SRRRD group had a higher incidence of posterior vitreous attachment. Furthermore, AET was a significant comorbidity in the eyes with SRRRD, particularly in the elderly and the area of presumed reattachment over two quadrants and was related to worse functional outcomes.

PRPH2-Associated Retinopathy: Novel Variants and Genotype–Phenotype Correlations

A broad spectrum of autosomal-dominant inherited retinal diseases (IRDs), ranging from mild macular pattern dystrophy to severe cone-rod degeneration, is associated with PRPH2 variants (peripherinopathies). We present detailed clinical and molecular characterization of patients affected by peripherinopathies, aiming to expand the mutational spectrum, and propose novel genotype-phenotype correlations. Observational, retrospective case series. Patients with an IRD related to a molecularly proven PRPH2 variant. Data from ophthalmic examinations and retinal imaging were collected for each follow-up visit. The standard imaging protocol included OCT, blue-light autofluorescence, near-infrared autofluorescence, and ultra-widefield fundus imaging. Genetic analysis was performed with a genomic approach by next-generation sequencing. Results of ophthalmic examination, retinal imaging, and molecular genetic analysis. Overall, a total of 19 patients with an IRD and a (likely) pathogenic PRPH2 variant were identified. Their age at presentation had a median of 48 years, whereas the symptomatic disease onset was in their 30s or 40s in 74% of cases. The median follow-up time was 4 years. Clinically, 6 patients were diagnosed with cone-rod dystrophy and 13 with pattern dystrophy. Among the 13 PRPH2 pathogenic variants identified in our cohort, 7 were missense, 3 nonsense, 2 frame shifting, and 1 splice site. Missense variants in the D2 loop were associated with cone-rod dystrophies and poor visual prognosis, whereas predicted loss-of-function alleles with pattern dystrophies and retention of a good visual function into adulthood. Overall, the following 7 variants were novel and never associated to a clinical phenotype: c.68delT, c.290G>A, c.413T>G, c.642C>G, c.702_706dupCAGTT, c.771_772delinsGA, and c.850C>G. Here, we report the findings of a retrospective case series that provided a detailed clinical and molecular characterization of 19 patients harboring 13 different PRPH2 pathogenic variants, 7 of which were previously unreported, expanding the mutational spectrum of the PRPH2 gene. Loss-of-function variants might be preferentially associated with mild-pattern dystrophies, whereas missense dominant-negative variants might be preferentially associated with severely blinding cone-rod degenerations. Further studies are needed to better define the pathogenetic mechanisms and the functional effects of most variants to allow the development of successful gene therapy. Proprietary or commercial disclosure may be found after the references.

Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning

Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning

Ultra-wide-field fundus photography compared to ophthalmoscopy in diagnosing and classifying major retinal diseases

To analyze the performance of ultra-wide-field (UWF) fundus photography compared with ophthalmoscopy in identifying and classifying retinal diseases. Patients examined for presumed major retinal disorders were consecutively enrolled. Each patient underwent indirect ophthalmoscopic evaluation, with scleral depression and/or fundus biomicroscopy, when clinically indicated, and mydriatic UWF fundus imaging by means of CLARUS 500™ fundus camera. Each eye was classified by a clinical grader and two image graders in the following groups: normal retina, diabetic retinopathy, vascular abnormalities, macular degenerations and dystrophies, retinal and choroidal tumors, peripheral degenerative lesions and retinal detachment and myopic alterations. 7024 eyes of new patients were included. The inter-grader agreement for images classification was perfect (kappa = 0.998, 95% Confidence Interval (95%CI) = 0.997–0.999), as the two methods concordance for retinal diseases diagnosis (kappa = 0.997, 95%CI = 0.996–0.999) without statistically significant difference. UWF fundus imaging might be an alternative to ophthalmoscopy, since it allows to accurately classify major retinal diseases, widening the range of disorders possibly diagnosed with teleophthalmology. Although the clinician should be aware of the possibility that a minority of the most peripheral lesions may be not entirely visualized, it might be considered a first line diagnostic modality, in the context of a full ophthalmological examination.

Choroideremia Carriers: Dark-Adapted Perimetry and Retinal Structures.

PurposeIn choroideremia (CHM) carriers, scotopic sensitivity was assessed by dark adapted chromatic perimetry (DACP) and outer retinal structure was evaluated by multimodal imaging.MethodsNine carriers (18 eyes) and 13 healthy controls (13 eyes) underwent DACP testing with cyan and red stimuli. Analysis addressed peripapillary (4 test locations closest to the optic disc), macular (52 locations), and peripheral (60 locations outside the macula) regions. Responses were considered to be rod-mediated when cyan relative to red sensitivity was >5 dB. Fundus imaging included spectral domain optical coherence tomography (SD-OCT), short-wavelength (SW-AF), near-infrared (NIR-AF), ultrawide-field (200 degrees) pseudocolor fundus imaging, and quantitative (qAF) fundus autofluorescence.ResultsDetection of the cyan stimulus was rod mediated in essentially all test locations (99.7%). In the macular and peripheral areas, DACP sensitivity values were not significantly different from healthy eyes. In the peripapillary area, sensitivities were significantly decreased (P < 0.05). SD-OCT imaging ranged from hyper-reflective lesions and discontinuities of the outer retinal bands to hypertransmission of signal. SW-AF and NIR-AF images presented with peripapillary atrophy in seven patients (14 eyes). Mosaicism was detectable in SW-AF images in seven patients and in NIR-AF images in five patients. Frank hypo-autofluorescence was visible in eight patients with distinct chorioretinopathy in seven patients. The qAF values were below the 95% confidence interval (CI) of healthy age-matched individuals in 12 eyes.ConclusionsRod mediated scotopic sensitivity was comparable to that in control eyes in macular and peripheral areas but was decreased in the peripapillary area where changes in retinal structure were also most severe.

Comparison between Deep-Learning-Based Ultra-Wide-Field Fundus Imaging and True-Colour Confocal Scanning for Diagnosing Glaucoma.

In this retrospective, comparative study, we evaluated and compared the performance of two confocal imaging modalities in detecting glaucoma based on a deep learning (DL) classifier: ultra-wide-field (UWF) fundus imaging and true-colour confocal scanning. A total of 777 eyes, including 273 normal control eyes and 504 glaucomatous eyes, were tested. A convolutional neural network was used for each true-colour confocal scan (Eidon AF™, CenterVue, Padova, Italy) and UWF fundus image (Optomap™, Optos PLC, Dunfermline, UK) to detect glaucoma. The diagnostic model was trained using 545 training and 232 test images. The presence of glaucoma was determined, and the accuracy and area under the receiver operating characteristic curve (AUC) metrics were assessed for diagnostic power comparison. DL-based UWF fundus imaging achieved an AUC of 0.904 (95% confidence interval (CI): 0.861–0.937) and accuracy of 83.62%. In contrast, DL-based true-colour confocal scanning achieved an AUC of 0.868 (95% CI: 0.824–0.912) and accuracy of 81.46%. Both DL-based confocal imaging modalities showed no significant differences in their ability to diagnose glaucoma (p = 0.135) and were comparable to the traditional optical coherence tomography parameter-based methods (all p > 0.005). Therefore, using a DL-based algorithm on true-colour confocal scanning and UWF fundus imaging, we confirmed that both confocal fundus imaging techniques had high value in diagnosing glaucoma.

A rare finding of lamellar macular hole with lamellar hole-associated epiretinal proliferation in retinal vein occlusion

A 69-year-old female presented with right eye vision of 20/120 Snellens. Ultrawide-field fundus imaging showed old vitreous hemorrhage with superotemporal sclerosed vessels post venous occlusion. Spectral-domain optical coherence tomography revealed degenerative lamellar macular home (LMH) with lamellar hole-associated epiretinal proliferation (LHEP). The patient underwent surgery using vitrectomy with the embedding technique. Post surgery, good recovery of the foveal contour was achieved with vision improving to 20/40. LMH with LHEP can be a sequela of chronic macular edema in RVO.