Ultra-widefield Imaging Research Articles

Non-invasive biomarkers for close activity monitoring in birdshot chorioretinitis: Optical coherence tomography angiography and beyond.

The purpose of the study was to identify non-invasive imaging biomarkers potentially useful for close activity monitoring in birdshot chorioretinitis (BSCR). Cross-sectional study of BSCR eyes included as per Levinson's and/or SUN criteria. Eyes were blindly classified into active or inactive groups per clinical inflammatory parameters, ultra-widefield (UWF) pseudocolour images, UWF fluorescein angiography (FA) and macular optical coherence tomography (OCT) cube. Qualitative and quantitative OCT and OCT-angiography (OCT-A) parameters at the fundus, superonasal and inferonasal fields were compared between active and inactive eyes. Thirty consecutive BSCR patients (60 eyes) were analysed. 28 eyes (46.66%) were from women and the overall mean age was 59.7 ± 12.3 years. Active eyes showed an abnormal retinal thickening at inferonasal field (nasal retinal thickness) and a higher averaged thickened retinal index (ATRI) (72.36 active vs. 20.12 inactive, p < 0.0001). A significant moderate correlation was observed between ATRI and FA scores (r = 0.259, p = 0.022). Macular vascular loops were more frequent in the superficial vascular plexus of OCT-A in the active eyes (p = 0.028). The vascular perfusion index tended to be higher in all subfields of active eyes but did not reach statistical significance. Multimodal imaging could be key to discerning activity in BSCR eyes. Higher ATRI and the presence of vascular loops in the superficial plexus are potential non-invasive activity biomarkers for the close monitoring of BSCR.

Distribution of leakage index using ultra-widefield fluorescein angiography in patients with non-ischemic branch retinal vein occlusion and its association with macular edema

BackgroundTo investigate the distribution of leakage index in patients with non-ischemic branch retinal vein occlusion (BRVO) and its correlation with the severity of macular edema. MethodsRetrospective observational study. Forty-five eyes of 45 patients with BRVO were included. Late ultra-widefield fluorescein angiography images of the affected eyes were processed and analyzed for their leakage index using Fiji software. The visible panretinal area was further divided into the peri‑macular area (PMA), near-peripheral area (NPA), midperipheral area (MPA), and far-peripheral area (FPA). The relationship between the leakage index and central retinal thickness (CMT) was analyzed for the panretina and each subregion. ResultsThe median (interquartile range) leakage indexes of the panretina, PMA, NPA, MPA, and FPA were 5.532% (7.667%), 23.127% (26.073%), 8.303% (16.807%), 1.588% (6.204%), and 0.408% (2.215%), respectively, with a mean CMT of 552.800 ± 183.335 μm. The CMT was positively correlated with the leakage index in the panretina, PMA, NPA, MPA and FPA (r = 0.468, 0.426, 0.463, 0.447, 0.320, respectively; all p < 0.05). ConclusionsThe leakage index in non-ischemic BRVO patients is associated with macular edema severity. The leakage index has the potential to be a useful indicator for monitoring and guiding treatment of macular edema in BRVO patients.

Spotlight on Lattice Degeneration Imaging Techniques.

Lattice degeneration (LD), routinely diagnosed with indirect ophthalmoscopy, is one of the most common and clinically significant peripheral retinal findings. In this review, we have summarized the data on currently available imaging techniques which help to improve diagnosis and our understanding of LD pathogenesis. Ultra-wide field imaging provides reliable color fundus capturing for the primary diagnosis of LD and may also be used as a screening tool. Wide-field imaging can be used for targeted documentation of LD lesions using true colors and with minimal optical distortions. Information on the status of the vitreoretinal interface, including detection of retinal holes, detachments, and vitreous tractions, can be obtained with peripheral structural optical coherence tomography (OCT) or scanning laser ophthalmoscopy in retro-mode. These techniques clarify the associated risks of rhegmatogenous retinal detachment. Fundus autofluorescence can provide details on atrophic changes. However, the risk of retinal detachment by means of this technique requires further investigation. OCT angiography may be successfully performed for some lesions. Taken together, OCT and OCT angiography demonstrate thinning of the choroid, alteration of local choroidal microcirculation, and, in severe lesions, involvement of the sclera. OCT angiography confirms loss of retinal microcirculation within LD lesion, which was previously shown with fluorescein angiography. In conclusion, despite relatively simple primary diagnosis, imaging of LD lesions remains challenging due to their peripheral localization. However, several new strategies, including ultra-wide field imaging, peripheral OCT, and scanning laser ophthalmoscopy, make LD imaging possible on a routine basis, improving diagnosis and understanding of LD pathogenesis.

Ultra-widefield multimodal imaging of whitish outer retinal spots in rhegmatogenous retinal detachment

Ultra-widefield multimodal imaging of whitish outer retinal spots in rhegmatogenous retinal detachment

ASSESSMENT OF QUALITY AND ADEQUACY OF PANRETINAL PHOTOCOAGULATION IN PROLIFERATIVE DIABETIC RETINOPATHY USING ULTRA-WIDEFIELD IMAGING.

To assess the characteristics of completed panretinal photocoagulation (PRP), using ultra-widefield imaging in proliferative diabetic retinopathy. Quantitative assessment of ultra-widefield imaging images of 133 patients with proliferative diabetic retinopathy with completed PRP was made using ImageJ software. The parameters assessed included distance of laser spots from the optic disk, foveal center, superior and inferior arcades, and extent of the maximum width of laser. Areas assessed were total area of the image, area of the inner limit within which laser spots are restricted, minimum areas of unlasered patches, total area lasered, and ideal area to be covered by PRP. Two hundred one images were assessed for the final analysis. The mean distance of laser spots was 4.2 ± 2.4 mm from the optic disk (nasal) and 6.6 ± 2.5 mm from the foveal center (temporal). The mean distance of laser spots from the superior arcade vessel was 3.2 ± 1.9 mm and 6.2 ± 4.4 mm from the inferior arcade. The mean area of the retina that should have been ideally lasered was found to be 900 ± 267 mm 2 , and the actual area lasered was found to be 681 ± 254.4 mm 2 . Approximately one-quarter area of the retina continues to remain ischemic because of the lack of inadequate coverage of PRP. Further longitudinal studies are recommended, using ultra-widefield imaging to objectively assess the adequacy of PRP and its role in modulating the course of progression of the retinopathy.

The Sensitivity of Ultra-Widefield Fundus Photography Versus Scleral Depressed Examination for Detection of Retinal Horseshoe Tears

Ultra-widefield (UWF) imaging is commonly used in ophthalmology in tandem with scleral depressed examinations (SDE) to evaluate peripheral retinal disease. Because of the increased reliance on this technology in tele-ophthalmology, it is critical to evaluate its efficacy for detecting the peripheral retina when performed in isolation. Therefore, we sought to evaluate UWF imaging sensitivity in detecting retinal horseshoe tears (HSTs). Retrospective clinical validity and reliability study. A single-institutional retrospective analysis was performed on patients at the Shiley Eye Institute, University of California, San Diego. Patients with HSTs seen on SDE who underwent treatment with laser were included in the study. A total of 140 patients with HSTs in the right and/or left eyes met the inclusion criteria. Those with concomitant ruptured globes, retinal detachments, and vitreous hemorrhages were excluded. A total of 123 patients with 135 HSTs were included in the final analysis. The primary outcome was the number of HSTs detected by UWF imaging. A secondary outcome was HST location. Sensitivity was measured with respect to HST location, and statistical significance was calculated by Fisher exact testing. A total of 69 (51.1%) HSTs were visualized on UWF images and 66 (48.9%) were not visualized. The sensitivity of UWF imaging in capturing HSTs was 7 of 41 (17.1%), 8 of 25 (32.0%), 7 of 14 (50.0%), and 47 of 55 (85.5%) for the superior, inferior, nasal, and temporal quadrants, respectively. Sensitivities between HST visibility and location were statistically significant (P < .001). Nearly half of HSTs were missed by UWF imaging. This study demonstrates that UWF imaging alone is not sufficiently sensitive to exclude the presence of HSTs.

INTEGRATING MACULAR OPTICAL COHERENCE TOMOGRAPHY WITH ULTRAWIDE-FIELD IMAGING IN A DIABETIC RETINOPATHY TELEMEDICINE PROGRAM USING A SINGLE DEVICE.

To determine the effect of combined macular spectral-domain optical coherence tomography (SD-OCT) and ultrawide field retinal imaging (UWFI) within a telemedicine program. Comparative cohort study of consecutive patients with both UWFI and SD-OCT. Ultrawide field retinal imaging and SD-OOCT were independently evaluated for diabetic macular edema (DME) and nondiabetic macular abnormality. Sensitivity and specificity were calculated with SD-OCT as the gold standard. Four hundred twenty-two eyes from 211 diabetic patients were evaluated. Diabetic macular edema severity by UWFI was as follows: no DME 93.4%, noncenter involved DME (nonciDME) 5.1%, ciDME 0.7%, ungradable DME 0.7%. SD-OCT was ungradable in 0.5%. Macular abnormality was identified in 34 (8.1%) eyes by UWFI and in 44 (10.4%) eyes by SD-OCT. Diabetic macular edema represented only 38.6% of referable macular abnormality identified by SD-OCT imaging. Sensitivity/specificity of UWFI compared with SD-OCT was 59%/96% for DME and 33%/99% for ciDME. Sensitivity/specificity of UWFI compared with SDOCT was 3%/98% for epiretinal membrane. Addition of SD-OCT increased the identification of macular abnormality by 29.4%. More than 58.3% of the eyes believed to have any DME on UWF imaging alone were false-positives by SD-OCT. The integration of SD-OCT with UWFI markedly increased detection and reduced false-positive assessments of DME and macular abnormality in a teleophthalmology program.

The relationship of diabetic retinopathy severity scales with frequency and surface area of diabetic retinopathy lesions

PurposeTo assess the relationship between qualitative diabetic retinopathy (DR) scales with the precise numbers and surface area of DR lesions within the Early Treatment Diabetic Retinopathy Study (ETDRS) standard seven field (S7F) region on ultrawide-field (UWF) color fundus images.MethodsIn this study, we collected UWF images from adult patients with diabetes. Poor-quality images and eyes with any pathology precluding assessment of DR severity were excluded. The DR lesions were manually segmented. DR severity was graded according to the International Clinical Diabetic Retinopathy (ICDR) and AA protocol by two masked graders within the ETDRS S7F. These lesions’ numbers and surface area were computed and correlated against the DR scores using the Kruskal–Wallis H test. Cohen’s Kappa was performed to determine the agreement between two graders.ResultsOne thousand five hundred and twenty eyes of 869 patients (294 females, 756 right eyes) with a mean age of 58.7 years were included. 47.4% were graded as no DR, 2.2% as mild non-proliferative DR (NPDR), 24.0% as moderate NPDR, 6.3% as severe NPDR, and 20.1% as proliferative DR (PDR). The area and number of DR lesions generally increased as the ICDR level increased up to severe NPDR, but decreased from severe NPDR to PDR. There was perfect intergrader agreement on the DR severity.ConclusionA quantitative approach reveals that DR lesions’ number and area generally correlate with ICDR-based categorical DR severity levels with an increasing trend in the number and area of DR lesions from mild to severe NPDR and a decrease from severe NPDR to PDR.

26-LB: Identifying the Risk of Diabetic Retinopathy Progression Using Machine Learning on Ultrawide Field Retinal Images

Estimating the risk of diabetic retinopathy (DR) progression is one of the most important and difficult tasks when caring for individuals with diabetic eye disease. Current DR severity scales have informed clinicians on the progression risk and provided recommendations for follow-up and treatment. The use of artificial intelligence (AI) algorithms may improve in this process. In this study, we developed and validated machine learning (ML) models for DR progression from ultrawide field (UWF) retinal images, which were labeled for baseline DR severity and progression based on clinician review of the images and 3-year longitudinal follow-up using the Early Treatment Diabetic Retinopathy Study (ETDRS) severity scale. This dataset has 8 classes: no DR nonprogression (14.62%), Mild nonproliferative DR (NPDR) progression (10.16%) /nonprogression (10.73%), Moderate NPDR progression (10.1%) /nonprogression (15.85%), Severe NPDR progression (11.27%) /nonprogression (10.68%), and proliferative DR (16.55%). A total of 9970 unique images were split into the train, the validation, and the test datasets based on 60-20-20 proportions. The class imbalance was addressed during model building through data augmentation. The ResNet model fine-tuned on this dataset has a classification test accuracy of 81% and an AUC of 0.967 on the test dataset. The objective of the model is to reduce false negatives, which refers to predicting a class that is less progressive than the true label. The predicted labels for 91% of the images were either correct labels or were the labels with greater progression than the original labels. These findings demonstrate the accuracy and feasibility of using machine learning models for identifying DR progression developed using UWF images. Potentially, the use of machine learning algorithms may further refine the risk of disease progression and personalize screening intervals that may reduce costs and improve vision-related outcomes. Disclosure A. Nigam: None. J. Sun: None. V. Subhash: None. P. S. Silva: Research Support; Optos plc., Optomed, Speaker's Bureau; Novartis, Roche Pharmaceuticals, Bayer Inc.

Deep learning for automated detection of neovascular leakage on ultra-widefield fluorescein angiography in diabetic retinopathy

Diabetic retinopathy is a leading cause of blindness in working-age adults worldwide. Neovascular leakage on fluorescein angiography indicates progression to the proliferative stage of diabetic retinopathy, which is an important distinction that requires timely ophthalmic intervention with laser or intravitreal injection treatment to reduce the risk of severe, permanent vision loss. In this study, we developed a deep learning algorithm to detect neovascular leakage on ultra-widefield fluorescein angiography images obtained from patients with diabetic retinopathy. The algorithm, an ensemble of three convolutional neural networks, was able to accurately classify neovascular leakage and distinguish this disease marker from other angiographic disease features. With additional real-world validation and testing, our algorithm could facilitate identification of neovascular leakage in the clinical setting, allowing timely intervention to reduce the burden of blinding diabetic eye disease.

ULTRA-WIDEFIELD OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IN MILD FAMILIAL EXUDATIVE VITREORETINOPATHY.

To investigate ultra-widefield optical coherence tomography angiography (UWF-OCTA) to detect and evaluate mild familial exudative vitreoretinopathy and compare the detective ratio of UWF-OCTA with ultra-widefield scanning laser ophthalmoscopy and ultra-widefield fluorescein angiography. The patients with familial exudative vitreoretinopathy were included in this study. UWF-OCTA, using a 24- × 20-mm montage, was performed for all patients. All images were independently tested for the presence of familial exudative vitreoretinopathy-associated lesions. Statistical analysis was performed with SPSS V.24.0. Forty-six eyes of 26 participants were included in the study. Ultra-widefield optical coherence tomography angiography was found to be greatly superior to ultra-widefield scanning laser ophthalmoscopy in detecting peripheral retinal vascular abnormality ( P < 0.001) and peripheral retinal avascular zone ( P < 0.001). The detection rates of peripheral retinal vascular abnormality, peripheral retinal avascular zone, retinal neovascularization, macular ectopia, and temporal midperipheral vitreoretinal interface abnormality were comparable with ultra-widefield fluorescein angiography images ( P > 0.05). Furthermore, vitreoretinal traction (17/46, 37%) and small foveal avascular zone (17/46, 37%) were detected effectively on UWF-OCTA. Ultra-widefield optical coherence tomography angiography is a reliable noninvasive tool to detect familial exudative vitreoretinopathy lesions, especially in mild patients or asymptomatic family members. The unique manifestation of UWF-OCTA offers an alternative to ultra-widefield fluorescein angiography for the screening and diagnosis of FEVR.

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.

REFINING THE RETINAL PHENOTYPE OF PATIENTS WITH SUSPECTED PENTOSAN POLYSULFATE SODIUM RETINOPATHY.

To refine the retinal phenotypes of suspected pentosan polysulfate sodium toxicity using ultra-widefield imaging. Patients with complete dosing profiles who visited the ophthalmology department and with ultra-widefield and optical coherence tomography imaging records were identified using electronic health records at a large academic center. Retinal toxicity was initially identified using previously published imaging criteria, while grading was categorized using both previously reported and new classification systems. One hundred and four patients were included in this study. Twenty-six (25%) were identified as having toxicity from PPS. The mean duration of exposure and cumulative dose between the retinopathy group (162.7 months, 1,803.2 g) were longer and higher compared with the nonretinopathy group (69.7 months, 972.6 g) (both P < 0.001). There was variability of extramacular phenotype in the retinopathy group, with four eyes having only peripapillary involvement and six eyes having far peripheral extension. Retinal toxicity in the setting of prolonged exposure and increased cumulative dosing from PPS therapy produces phenotypic variability. Providers should be aware of the extramacular component of toxicity when screening patients. Understanding the different retinal phenotypes may prevent continued exposure and reduce the risk of vision-threatening foveal-involving disease.

Peripheral retinal vessel whitening in patients with diabetes mellitus

This study aimed to identify retinal vessel whitening outside the standard Early Treatment Diabetic Retinopathy Study (ETDRS) fields and to correlate the findings with vision and severity of diabetic retinopathy. Patients with diabetes mellitus who were seen in the retinal clinic to assess diabetic retinopathy status were included. Retinal vessel whitening was identified using ultra-widefield imaging. Four hundred and forty-five eyes of 260 patients were included. Thirty-five eyes in 24 patients (7.9%) were noted to have peripheral retinal vessel whitening. Thirty-one eyes with peripheral retinal vessel whitening did not have vessel whitening within the standard 7 ETDRS fields (p < 0.001). The proportion of whitening increased as DR severity increased, from 4.0% for patients with no DR (OR 0.249) to 33.3% for those with severe NPDR and PDR (OR 6.430 and 7.232, respectively). In addition, patients with peripheral retinal vessel whitening had worse visual acuity (logMAR = 0.34) compared to those without (logMAR = 0.15) (p < 0.001). In conclusion, we found an association between peripheral retinal vessel whitening in diabetic patients which correlated with diabetic retinopathy severity. Additionally, we found an association between vessel whitening and reduced vision, suggesting that vessel whitening identified using ultra-widefield imaging may be a prognostic indicator of vision in diabetic retinopathy.

MSHF: A Multi-Source Heterogeneous Fundus (MSHF) Dataset for Image Quality Assessment

Image quality assessment (IQA) is significant for current techniques of image-based computer-aided diagnosis, and fundus imaging is the chief modality for screening and diagnosing ophthalmic diseases. However, most of the existing IQA datasets are single-center datasets, disregarding the type of imaging device, eye condition, and imaging environment. In this paper, we collected a multi-source heterogeneous fundus (MSHF) database. The MSHF dataset consisted of 1302 high-resolution normal and pathologic images from color fundus photography (CFP), images of healthy volunteers taken with a portable camera, and ultrawide-field (UWF) images of diabetic retinopathy patients. Dataset diversity was visualized with a spatial scatter plot. Image quality was determined by three ophthalmologists according to its illumination, clarity, contrast and overall quality. To the best of our knowledge, this is one of the largest fundus IQA datasets and we believe this work will be beneficial to the construction of a standardized medical image database.

Comparison of diabetic retinopathy severity grading on ETDRS 7-field versus ultrawide-field assessment

ObjectivesTo compare the diabetic retinopathy (DR) severity level determined when considering only the ETDRS 7-field region versus the entire ultrawidefield (UWF) image.MethodsIn this retrospective, cross-sectional study, UWF pseudocolor images were graded on the Eyenuk image viewing, grading, and annotation platform for the severity of DR considering only the regions within the ETDRS 7-fields as well as the entire UWF image using two different protocols: 1) the simple International Classification of Diabetic Retinopathy (ICDR) scale and 2) the more complex DRCR.net Protocol AA grading scale.ResultsA total of 250 eyes from 157 patients were included in this analysis. Six eyes (2.4%) demonstrated a discrepancy in severity level between the ETDRS 7-field region and the entire UWF image when using the ICDR classification system. The discrepancies were due to the presence of lesions [intraretinal haemorrhage (n = 2), neovascular disease (n = 4)] in the peripheral fields which were not identified in the ETDRS 7-fields. Fourteen eyes (5.6%) had a discrepancy in severity level between the ETDRS 7-field region and the entire UWF image when using the ETDRS DRSS Protocol AA grading scale. The discrepancies were due to the presence of a higher level of disease [intraretinal haemorrhage (n = 4), neovascularization (n = 4), preretinal haemorrhage (n = 2), scatter laser scars (n = 4)] in the peripheral fields.ConclusionAlthough considering regions outside of the ETDRS 7-fields altered the DR severity level assessment in <5% of cases in this cohort, significant and potentially vision-threatening lesions including neovascularization and preretinal haemorrhage were identified in these peripheral regions. This highlights the importance of evaluating the entire UWF region when assessing patients with diabetic retinopathy.

Joint conditional generative adversarial networks for eyelash artifact removal in ultra-wide-field fundus images.

Background: Ultra-Wide-Field (UWF) fundus imaging is an essential diagnostic tool for identifying ophthalmologic diseases, as it captures detailed retinal structures within a wider field of view (FOV). However, the presence of eyelashes along the edge of the eyelids can cast shadows and obscure the view of fundus imaging, which hinders reliable interpretation and subsequent screening of fundus diseases. Despite its limitations, there are currently no effective methods or datasets available for removing eyelash artifacts from UWF fundus images. This research aims to develop an effective approach for eyelash artifact removal and thus improve the visual quality of UWF fundus images for accurate analysis and diagnosis. Methods: To address this issue, we first constructed two UWF fundus datasets: the paired synthetic eyelashes (PSE) dataset and the unpaired real eyelashes (uPRE) dataset. Then we proposed a deep learning architecture called Joint Conditional Generative Adversarial Networks (JcGAN) to remove eyelash artifacts from UWF fundus images. JcGAN employs a shared generator with two discriminators for joint learning of both real and synthetic eyelash artifacts. Furthermore, we designed a background refinement module that refines background information and is trained with the generator in an end-to-end manner. Results: Experimental results on both PSE and uPRE datasets demonstrate the superiority of the proposed JcGAN over several state-of-the-art deep learning approaches. Compared with the best existing method, JcGAN improves PSNR and SSIM by 4.82% and 0.23%, respectively. In addition, we also verified that eyelash artifact removal via JcGAN could significantly improve vessel segmentation performance in UWF fundus images. Assessment via vessel segmentation illustrates that the sensitivity, Dice coefficient and area under curve (AUC) of ResU-Net have respectively increased by 3.64%, 1.54%, and 1.43% after eyelash artifact removal using JcGAN. Conclusion: The proposed JcGAN effectively removes eyelash artifacts in UWF images, resulting in improved visibility of retinal vessels. Our method can facilitate better processing and analysis of retinal vessels and has the potential to improve diagnostic outcomes.

Automatic Detection of Peripheral Retinal Lesions From Ultrawide-Field Fundus Images Using Deep Learning.

To establish a multilabel-based deep learning (DL) algorithm for automatic detection and categorization of clinically significant peripheral retinal lesions using ultrawide-field fundus images. A total of 5958 ultrawide-field fundus images from 3740 patients were randomly split into a training set, validation set, and test set. A multilabel classifier was developed to detect rhegmatogenous retinal detachment, cystic retinal tuft, lattice degeneration, and retinal breaks. Referral decision was automatically generated based on the results of each disease class. t -distributed stochastic neighbor embedding heatmaps were used to visualize the features extracted by the neural networks. Gradient-weighted class activation mapping and guided backpropagation heatmaps were generated to investigate the image locations for decision-making by the DL models. The performance of the classifier(s) was evaluated by sensitivity, specificity, accuracy, F 1 score, area under receiver operating characteristic curve (AUROC) with 95% CI, and area under the precision-recall curve. In the test set, all categories achieved a sensitivity of 0.836-0.918, a specificity of 0.858-0.989, an accuracy of 0.854-0.977, an F 1 score of 0.400-0.931, an AUROC of 0.9205-0.9882, and an area under the precision-recall curve of 0.6723-0.9745. The referral decisions achieved an AUROC of 0.9758 (95% CI= 0.9648-0.9869). The multilabel classifier had significantly better performance in cystic retinal tuft detection than the binary classifier (AUROC= 0.9781 vs 0.6112, P < 0.001). The model showed comparable performance with human experts. This new DL model of a multilabel classifier is capable of automatic, accurate, and early detection of clinically significant peripheral retinal lesions with various sample sizes. It can be applied in peripheral retinal screening in clinics.

Circumscribed Choroidal Hemangioma Simulating Choroidal Melanoma on Advanced Ultrawide-Field Pseudocolor Retinal Imaging: A Case Series

The purpose of this case series was to evaluate the features of circumscribed choroidal hemangioma on pseudocolor ultrawide-field (UWF) retinal images simulating choroidal melanoma and compare it to fundoscopic appearance. All four patients underwent full ophthalmological examination, including dilated fundus examination, ultrasonography, and UWF imaging (UWFI). All circumscribed choroidal hemangioma appeared clinically as orange-red choroidal lesions which were echodense with regular internal structure on ultrasonography. All lesions appeared green-grey in color on pseudocolor UWFI. Pseudocolor UWFI of circumscribed choroidal hemangioma represents distortion of true color appearance and may simulate choroidal melanoma. [Ophthalmic Surg Lasers Imaging Retina 2023;54:292-296.].

Novel MFRP Mutation with Nanophthalmos, Optic Disc Drusen, and Peripheral Retinoschisis Imaged with Ultra-Widefield OCT.

To describe with multimodal imaging including the use of ultra-widefield optical coherence tomography (OCT) imaging a distinct phenotype of autosomal recessive nanophthalmos associated with a novel mutation of the MFRP gene (membrane-type frizzled-related protein). Case report and review of the relevant literature. Single patient followed by the Weill Cornell Medicine Department of Ophthalmology Retina and Glaucoma Services. A patient with a novel homozygous mutation in the MFRP gene (c.472C>T) presented with nanophthalmos, optic disc drusen, foveal hypoplasia, and extensive peripheral retinoschisis, which was revealed to be multilevel retinoschisis on ultra-wide field OCT. Unlike other reported cases, the findings associated with this novel mutation did not include foveoschisis nor clinically obvious retinitis pigmentosa. The patient underwent prophylactic peripheral laser iridotomy in both eyes. Here we present a patient with nanophthalmos, optic disc drusen, and foveal hypoplasia associated with extensive peripheral retinoschisis imaged by ultra-widefield OCT, but not foveal retinoschisis or prominent retinitis pigmentosa. The findings may expand the clinical spectrum of MFRP-associated nanophthalmos.