Normal Optical Coherence Tomography Research Articles

Importance of optical coherence tomography before cataract surgery

PurposeTo determine the importance of optical coherence tomography (OCT) in patients scheduled for cataract surgery who present with no pathologies in biomicroscopic fundus examination.DesignRetrospective study.MethodsIn this study, the routine ophthalmologic examination of patients who were recommended cataract surgery was performed.Occult retinal pathologies were evaluated using OCT in patients without any pathologies in biomicroscopic fundus examination.According to whether retinal pathologies were detected on OCT, the patients were divided into two groups: normal and abnormal OCT.The findings of patients with retinal pathologies on OCT and their distribution according to age were also evaluated.ResultsA total of 271 eyes from 271 patients were evaluated.The number of patients with retinal pathologies on OCT despite normal fundoscopic examination findings was 38(14.0%).Of these patients,15(39.4%) had an epiretinal membrane,10(26.3%) had age-related macular degeneration, eight(21%) had vitreomacular traction, two(5.2%) had a lamellar hole, and 1(2.6%) patient each had a full-thickness macular hole, an intraretinal cyst, and photoreceptor layer damage.The age distribution of the patients with retinal pathologies was as follows: two patients,<60 years; six patients,60–70 years;14 patients,70–80 years; and 16 patients,>80 years.The rate of patients aged > 70 years and above was 78.9%.There was no statistically significant difference between the normal and abnormal OCT groups in terms of age, gender, the presence of systemic diseases, visual acuity, central macular thickness, and cataract type or density(p > 0.05 for all).ConclusionIn one of seven patients evaluated, retinal pathologies were detected on OCT despite normal fundoscopic examination findings.OCT can be used to detect occult retinal pathologies that cannot be detected by biomicroscopic fundus examination before cataract surgery.

Boundary-Repairing Dual-Path Network for Retinal Layer Segmentation in OCT Image with Pigment Epithelial Detachment.

Automatic retinal layer segmentation in optical coherence tomography (OCT) images is crucial for the diagnosis of ocular diseases. Currently, automatic retinal layer segmentation works well with normal OCT images. However, pigment epithelial detachment (PED) dramatically alters the retinal structure, causing blurred boundaries and partial disappearance of the Bruch's Membrane (BM), thus posing challenges to the segmentation. To tackle these problems, we propose a novel dual-path U-shaped network for simultaneous layer segmentation and boundary regression. This network first designs a feature interaction fusion (FIF) module to strengthen the boundary shape constraints in the layer path. To address the challenge posed by partial BM disappearance and boundary-blurring, we propose a layer boundary repair (LBR) module. This module aims to use contrastive loss to enhance the confidence of blurred boundary regions and refine the segmentation of layer boundaries through the re-prediction head. In addition, we introduce a novel bilateral threshold distance map (BTDM) designed for the boundary path. The BTDM serves to emphasize information within boundary regions. This map, combined with the updated probability map, culminates in topology-guaranteed segmentation results achieved through a topology correction (TC) module. We investigated the proposed network on two severely deformed datasets (i.e., OCTA-500 and Aier-PED) and one slightly deformed dataset (i.e., DUKE). The proposed method achieves an average Dice score of 94.26% on the OCTA-500 dataset, which was 1.5% higher than BAU-Net and outperformed other methods. In the DUKE and Aier-PED datasets, the proposed method achieved average Dice scores of 91.65% and 95.75%, respectively.

Multimodal in-vivo maps as a tool to characterize retinal structural biomarkers for progression in adult-onset Stargardt disease.

To characterize retinal structural biomarkers for progression in adult-onset Stargardt disease from multimodal retinal imaging in-vivo maps. Seven adult patients (29-69 years; 3 males) with genetically-confirmed and clinically diagnosed adult-onset Stargardt disease and age-matched healthy controls were imaged with confocal and non-confocal Adaptive Optics Scanning Light Ophthalmoscopy (AOSLO), optical coherence tomography (OCT), fundus infrared (FIR), short wavelength-autofluorescence (FAF) and color fundus photography (CFP). Images from each modality were scaled for differences in lateral magnification before montages of AOSLO images were aligned with en-face FIR, FAF and OCT scans to explore changes in retinal structure across imaging modalities. Photoreceptors, retinal pigment epithelium (RPE) cells, flecks, and other retinal alterations in macular regions were identified, delineated, and correlated across imaging modalities. Retinal layer-thicknesses were extracted from segmented OCT images in areas of normal appearance on clinical imaging and intact outer retinal structure on OCT. Eccentricity dependency in cell density was compared with retinal thickness and outer retinal layer thickness, evaluated across patients, and compared with data from healthy controls. In patients with Stargardt disease, alterations in retinal structure were visible in different image modalities depending on layer location and structural properties. The patients had highly variable foveal structure, associated with equally variable visual acuity (-0.02 to 0.98 logMAR). Cone and rod photoreceptors, as well as RPE-like structures in some areas, could be quantified on non-confocal split-detection AOSLO images. RPE cells were also visible on dark field AOSLO images close to the foveal center. Hypo-reflective gaps of non-waveguiding cones (dark cones) were seen on confocal AOSLO in regions with clinically normal CFP, FIR, FAF and OCT appearance and an intact cone inner segment mosaic in three patients. Dark cones were identified as a possible first sign of retinal disease progression in adult-onset Stargardt disease as these are observed in retinal locations with otherwise normal appearance and outer retinal thickness. This corroborates a previous report where dark cones were proposed as a first sign of progression in childhood-onset Stargardt disease. This also supports the hypothesis that, in Stargardt disease, photoreceptor degeneration occurs before RPE cell death.

A new intelligent system based deep learning to detect DME and AMD in OCT images.

Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular retinal diseases, playing a crucial role in diagnosing retinopathy while maintaining a non-invasive modality. The increasing volume of OCT images underscores the growing importance of automating image analysis. Age-related diabetic Macular Degeneration (AMD) and Diabetic Macular Edema (DME) are the most common cause of visual impairment. Early detection and timely intervention for diabetes-related conditions are essential for preventing optical complications and reducing the risk of blindness. This study introduces a novel Computer-Aided Diagnosis (CAD) system based on a Convolutional Neural Network (CNN) model, aiming to identify and classify OCT retinal images into AMD, DME, and Normal classes. Leveraging CNN efficiency, including feature learning and classification, various CNN, including pre-trained VGG16, VGG19, Inception_V3, a custom from scratch model, BCNN (VGG16) , BCNN (VGG19) , and BCNN (Inception_V3) , are developed for the classification of AMD, DME, and Normal OCT images. The proposed approach has been evaluated on two datasets, including a DUKE public dataset and a Tunisian private dataset. The combination of the Inception_V3 model and the extracted feature from the proposed custom CNN achieved the highest accuracy value of 99.53% in the DUKE dataset. The obtained results on DUKE public and Tunisian datasets demonstrate the proposed approach as a significant tool for efficient and automatic retinal OCT image classification.

Linear multifractional stable motion for modeling of fluid-filled regions in retinal optical coherence tomography images

Fluid appears in several retinal disorders can be visualized by optical coherence tomography (OCT) images. Since manual survey of OCT images is challenging, automatic fluid detection is desirable. This paper develops a generalized multifractal framework to model the local scale-invariant property of retinal OCT signals and accordingly proposes a simple methodology for automatic localization of fluid-filled regions. The proposed framework comprises both local self-similarity and heavy tailed distribution of OCT signals by generalization of fractional Levy stable motion (fLsm) to the Riemann-Liouville multifractional Levy stable motion (RL-mLsm). In order to measure the multifractality appears in RL-mLsm, the scaling properties of Levy flights and stochastic differential equations (SDEs) are used to develop a fractional momentbased algorithm namely, multi-fractional Levy fluctuation analysis (MLFA) algorithm. Here, we apply MLFA to model OCT images. Modeling results indicate the significant difference between the multifractal bandwidth in non-fluid and fluid regions. In addition, by utilizing various surrogate series of the signals, we discover the source of multifractality of OCT signals. As an application of the proposed multifractal modeling, we propose a new method, based on simple clustering of estimated local scaling exponent of modeled OCT signals, to localize fluid regions in OCT images. The localization method is validated, and the experimental results reveal the superiority of proposed method. Overall, the proposed multifractal framework has full advantages on excellent improvement of fluid localization, which promises the proposed model is suitable for effective description of self-similar nature of normal and abnormal OCT images independent of capturing device.

Опыт применения новых технологий оптической когерентной томографии в диагностике заболеваний роговицы у собак и кошек

In the article we present the results of the clinical study of cornea optical coherence tomography (OCT) in cats and dogs, performed by the authors during complex diagnostics of various keratophathies, such as: endothelial corneal dystrophy, pigmentary keratitis, chronic keratoconjunctivitis, chronic herpetic keratitis, ulcerative keratitis, corneal injuries, cats’ corneal sequestration, chronic keratitis complications of glaucoma. Normal cornea OCT scans characteristics for cats and dogs are given. OCT scans of various corneal pathologies in cats and dogs are presented and the identified pathological changes are described. Corneal OCT scan results of animals after keratoplasty operations with the use of various grafts forms have a great clinical interest. The results of the current clinical study suggest that corneal OCT in cats and dogs is highly informative and promising method of additional diagnosis of severe keratopathies, especially in cases of weak effectiveness of traditional drug therapy regimens, as well as before performing keratoplasty and in its postoperative period.

Hemoglobin Genotype, Hemolytic Activity, Fetal Hemoglobin and Retinal Changes on Optic Coherence Tomography in Children with Sickle Cell Disease

Introduction: Sickle cell disease (SCD) affects multiple organs, including the eye. Optical coherence tomography (OCT) is a quick, noncontact test that provides high-resolution images of distinctive retinal layers. OCT has revolutionized ophthalmology examination and offers valuable new information on retinal damage in SCD. Our earlier studies show that OCT has a higher detection rate for retinal changes in SCD, offering earlier diagnosis than fundoscopy alone. Additionally, abnormal retinal OCT correlates with cerebrovascular disease (CVD) strongly suggesting that retinal OCT may aid in detecting and monitoring SCD related brain injury. One of the characteristics of SCD is the marked variability in patients' clinical manifestations. SCD genotype impacts the presentation of sickle cell retinopathy (SCR). Though OCT has revealed a higher frequency of SCR and more extensive retinal changes associated with the more severe SCD genotypes SS and Sβ0 as compared to SC, significant heterogeneity remains even among patients with the same genotype. Early identification of factors predictive of organ damage, such as SCR and CVD, will allow initiation of individualized disease-modifying treatment before organ systems suffer repeated hypoxic-ischemic events, thus improving long-term outcomes. Degree of hemolysis and fetal hemoglobin (FHb) are among the most important factors affecting SCD severity. There have been limited studies on their effect on ocular health in children with SCD. Methods: The Delaware Comprehensive Sickle Cell Research Center performed a prospective longitudinal cohort study in which all participants underwent complete ophthalmologic examination and OCT imaging. Posterior pole volume scans centered at approximately 3 mm temporal to the foveal were obtained. Areas of retinal thinning were identified using the thickness map. Medical history, brain imaging and laboratory data were collected. All available FHb values were recorded to examine the changing trend with age. Retinal findings were correlated with brain imaging and clinical data. Analysis was performed using IBM SPSS Statistics 27 (IBM, Armonk, NY). The Chi-square test was used for categorical data, and the nonparametric test for continuous variable analysis. The relationship between FHb, age at FHb testing and OCT was examined using multiple regression analysis. Results: From July 2015 to April 2023, 181 (88 males) patients aged 5.35 - 20.39 (12.72 ± 4.29) years with SCD (108 SS, 56 SC, 10 Sβ+ thalassemia, 5 Sβ0 thalassemia and 2 other) enrolled in the study. Visual acuity ranged 20/20 - 20/40. On funduscopic exams, 23 of 181 (12.71%) showed signs of SCR, whereas 107 (59.12%) had retinal injuries on OCT. Seventy-six patients with SS/Sβ0 genotype had brain MRI, and 28 had abnormal findings (Table). Twenty-four of the 28 patients (85.71%) also had abnormal OCT (p = 0.021). Children with SC and SS/Sβ0 disease with normal retinal OCT had FHb values significantly higher than those with abnormal OCT (Z =-2.61 and -4.16, p = 0.009 and 0.000). Children with SS/Sβ0 disease, abnormal OCT had more elevated reticulocyte counts than those with normal OCT (Z = -2.848, p = 0.004). SS genotype were evaluated for FHb values. As expected, FHb levels decline with age, and the rate of descent diminishes (i.e., more rapid fall at an early age). Interestingly, the decrease in FHb is significantly more profound before age 15 for patients with abnormal OCT than those with normal OCT (Figure). The effect of hydroxyurea (HU) in preventing SCR is inconclusive. Children with normal OCT had similar FHb levels without and with HU. However, HU raises FHb levels among those with abnormal OCT. Conclusions: 1) Retinal and brain injury correlates in SS/Sβ0, and OCT may help to select patients for MRI. 2) Abnormal OCT is associated with increased reticulocyte count, indicating heightened hemolysis. While AST and indirect bilirubin levels are not significantly different between normal and abnormal OCT groups in the current dataset, we will repeat the analysis of these hemolytic markers with a larger sample. 3) Early serial measurement of FHb levels throughout childhood can identify patients at high risk for subsequent severe complications such as SCR and CVD who might benefit from early disease modifying treatments. These important findings and the impact of hydroxyurea require further study in a larger patient population undergoing serial exams.

Early optical coherence tomography evaluation of donor-transmitted atherosclerosis and cardiac allograft vasculopathy: insights from a prospective, single-center study

The impact of donor transmitted atherosclerosis as assessed by intravascular ultrasound on development and progression of cardiac allograft vasculopathy (CAV) after heart transplantation (HT) remains poorly defined in contemporary practice. In this exploratory analysis, we sought to assess the prognostic role of early qualitative assessment of donor artery morphology using optical coherence tomography (OCT) as a more sensitive imaging modality. HT recipients were prospectively enrolled for baseline OCT imaging of the left anterior descending coronary artery. OCT findings were classified as normal, homogeneous intimal thickening, and advanced plaque characteristics. The endpoint was a composite of cardiac death, myocardial infarction, or new angiographically detectable CAV stratified by the International Society of Heart and Lung Transplantation criteria up to 4 years of follow-up. A total of 35 patients underwent baseline OCT of whom 51.4% had normal OCT, 14.3% had homogenous plaque, and 34.3% had advanced characteristics. There were no significant differences in baseline demographics between patients with and without normal morphology. During a mean follow-up of 3.3±0.4 years, the endpoint occurred in 11 patients including 1 death, 7 CAV1, 3 CAV2, and 1 CAV3. Kaplan-Meier analysis revealed a significantly higher event rate in patients with advanced characteristics (log-rank p=0.010). In multivariate analysis, OCT-based plaque morphology was an independent predictor of clinical events (adjusted hazard ratio 4.57, 95% confidence interval 1.50-13.92, p=0.008) while maximal intimal thickness ≥0.5mm was not. Early qualitative OCT assessment of donor coronary artery morphology appears to be a reliable marker for predicting future cardiovascular events in HT recipients. Our findings warrant more careful study in a larger cohort.

Optical Coherence Tomography Retinal Nerve Fibre Layer and Ganglion Cell Complex Measurements in Normal Southern Nigerian Eyes.

Introduction Glaucoma is the leading cause of irreversible blindness worldwide. It is more severe in people with African heritage, and intraocular pressure remains the only modifiable risk factor in managing glaucoma. Attempts to improve the diagnosis and monitoring of glaucoma are ongoing. One of those attempts is the development of optical coherence tomography (OCT). However, there is a theoretical possibility of a delayed or wrong diagnosis of glaucoma using the OCT because of racial, age, and sex differences in the RNFL (retina nerve fibre layer), GCL (ganglion cell layer), and GCL+IPL (ganglion cell layer and inner plexiform layer) thickness. Objective This study aims to provide the measurements of RNFL, GCL, and GCL+IPL in normal eyes of southern Nigerian patients and specifically to evaluate the relationship of these measurements to gender, age, intra-eye variability, and the Topcon SD-OCT normative database. Method Three hundred and four eyes of 152 patients who had normal OCT scans using the 6x6 RNFL (four sectors) and Macula scans of the Topcon OCT-1 3D Maestro OCT machine were included for analysis. Parametric tests were used to interrogate the relationship between normally distributed parameters and gender, age, and the Topcon reference database. Non-parametric tests were used for non-normally distributed data. Results The male-to-female ratio was 1:1, and ages ranged between 18 and 71 for both genders. The average RNFL values were 111.49 ± 10.44 (right eye - RE) and 111.96 ± 9.66 (left eye - LE). For the GCL, average values were 66.23 ± 4.4 (RE) and 66.34 ± 4.19 (LE). GCL+IPL values were 104.02 ± 6.71 (RE) and 103.89 ± 6.66 (LE). There was no difference between genders (X2 = 56.467; df = 46; p = 0.160), and RNFL, GCL, and GCL+IPL values showed a significant reduction as the age of the respondents increased. There was a significant difference between RNFL, GCL, and GCL+IPL values and the Topcon reference database, p < 0.001. Conclusion Significant differences exist between the Southern Nigerian eyes' RNFL, GCL, and GCL+ IPL values and the Topcon OCT-1 3D Maestro reference database. While randomised control trials and extensive multi-centre studies have not been conducted to determine the possible effects of these differences between measured values and reference databases of the OCTs, they need to be considered while diagnosing and managing glaucoma with the OCT.

Analysis of Retinal Structure and Electrophysiological Function in Visual Snow Syndrome: An Exploratory Case Series.

Visual snow (VS) is a rare but distressing phenomenon of persistent granular or pixelated visual distortions that may occur in isolation or as a component of visual snow syndrome (VSS). The current understanding of VS pathogenesis, including the role of retinal involvement structurally and functionally, is limited. The objective of this study is to investigate retinal structural and electrophysiological abnormalities in VS. This retrospective case series included 8 subjects (7 with VSS and 1 with isolated VS). Patients with other ocular and neurologic diseases were excluded. Data were assessed from automated perimetry, optical coherence tomography (OCT), visual evoked potential (VEP), and full-field electroretinography (ffERG) testing. The VEP and ffERG data of visual snow subjects were compared with age- and sex-matched control subjects for statistical significance. The mean age of the cohort was 29.4 years (SD = ±5.3) with 50% gender split. The mean age of VS onset was 24.2 years (SD = ±3.8). All subjects had normal visual acuity, color vision, brain MRI, automated perimetry, OCT parameters (peripapillary retinal nerve fiber layer and macular ganglion cell layer thickness), and P100 and N135 wave pattern on VEP. Compared with controls, VS subjects had a greater mean b-wave amplitude in response to light-adapted 3.0 stimuli ( t test; P = 0.035 right eye and P = 0.072 left eye), greater mean light-adapted 3.0 flicker amplitude ( t test; P = 0.028 right eye P = 0.166 left eye) and greater b-wave amplitude in response to dark-adapted 10.0 stimuli ( t test; P = 0.102 right eye; P = 0.017 left eye) on ERG. Patients with VS and VSS have normal retinal structure, but abnormal electrophysiology compared with control subjects. The increased b-wave and flicker amplitudes observed with ffERG suggest increased responsiveness of the rod and cone photoreceptors and may contribute to VS pathophysiology.

D-DAGNet: AN IMPROVED HYBRID DEEP NETWORK FOR AUTOMATED CLASSIFICATION OF GLAUCOMA FROM OCT IMAGES

The introduction of Optical Coherence Tomography (OCT) in ophthalmology has resulted in significant progress in the early detection of glaucoma. Traditional approaches to identifying retinal diseases comprise an analysis of medical history and manual assessment of retinal images. Manual diagnosis is time-consuming and requires considerable human expertise, without which, errors could be costly to human sight. The use of artificial intelligence such as machine learning techniques in image analysis has been gaining ground in recent years for accurate, fast and cost-effective diagnosis from retinal images. This work proposes a Directed Acyclic Graph (DAG) network that combines Depthwise Convolution (DC) to decisively recognize early-stage retinal glaucoma from OCT images. The proposed method leverages the benefits of both depthwise convolution and DAG. The Convolutional Neural Network (CNN) information obtained in the proposed architecture is processed as per the partial order over the nodes. The Grad-CAM method is adopted to quantify and visualize normal and glaucomatous OCT heatmaps to improve diagnostic interpretability. The experiments were performed on LFH_Glaucoma dataset composed of 1105 glaucoma and 1049 healthy OCT scans. The proposed faster hybrid Depthwise-Directed Acyclic Graph Network (D-DAGNet) achieved an accuracy of 0.9995, precision of 0.9989, recall of 1.0, F1-score of 0.9994 and AUC of 0.9995 with only 0.0047 M learnable parameters. Hybrid D-DAGNet enhances network training efficacy and significantly reduces learnable parameters required for identification of the features of interest. The proposed network overcomes the problems of overfitting and performance degradation due to accretion of layers in the deep network, and is thus useful for real-time identification of glaucoma features from retinal OCT images.

Optical coherence tomography in the differential diagnostics of important neuro-ophthalmological disease patterns

There are many disease patterns that are treated jointly by neurologists and ophthalmologists, for which optical coherence tomography (OCT) is of important differential diagnostic significance. In this context neurologists are mainly confronted by two patient collectives: patients with an acute ischemic event, who present with an acute but painless monocular visual deterioration (for central retinal artery occlusion) or with a monocular visual field defect (for arterial branch occlusion or anterior ischemic optic neuropathy). The second collective is patients without ophthalmological symptoms but with conspicuous optic nerve findings (papilledema or optic disc drusen). In this overview article both patient collectives are considered separately. In addition, the most important OCT findings for optic neuritis are presented. Before the disease patterns are described in detail, the normal OCT findings and the diagnostic possibilities of OCT are explained.

Noninvasive Ophthalmic Imaging Measures Retinal Degeneration and Vision Deficits in Ndufs4-/- Mouse Model of Mitochondrial Complex I Deficiency.

PurposeTo characterize postnatal ocular pathology in a Ndufs4−/− mouse model of complex I deficiency using noninvasive retinal imaging and visual testing.Methods Ndufs4−/− mice and wild-type (WT) littermates were analyzed at 3, 5, and 7 weeks postnatal. Retinal morphology was visualized by optical coherence tomography (OCT). OCT images were analyzed for changes in retinal thickness and reflectivity profiles. Visual function was assessed by electroretinogram (ERG) and optomotor reflex (OMR).Results Ndufs4−/− animals have normal OCT morphology at weaning and develop inner plexiform layer atrophy over weeks 5 to 7. Outer retinal layers show hyporeflectivity of the external limiting membrane (ELM) and photoreceptor ellipsoid zone (EZ). Retinal function is impaired at 3 weeks, with profound deficits in b-wave, a-wave, and oscillatory potential amplitudes. The b-wave and oscillatory potential implicit times are delayed, but the a-wave implicit time is unaffected. Ndufs4−/− animals have normal OMR at 3 weeks and present with increasing acuity and contrast OMR deficits at 5 and 7 weeks. Physiological thinning of inner retinal layers, attenuation of ELM reflectivity, and attenuation of ERG b- and a-wave amplitudes occur in WT C57BL/6 littermates between weeks 3 and 7.ConclusionsNoninvasive ocular imaging captures early-onset retinal degeneration in Ndufs4−/− mice and is a tractable approach for investigating retinal pathology subsequent to complex I deficiency.Translational RelevanceOphthalmic imaging captures clinically relevant measures of retinal disease in a fast-progressing mouse model of complex I deficiency consistent with human Leigh syndrome.

Mixture of Symmetric Stable Distributions for Macular Pathology Detection in Optical Coherence Tomography Scans.

Optical coherence tomography (OCT) is widely used to detect retinal disorders. In this study a new methodology is proposed for automatic detection of macular pathologies in the OCT images. Our approach is based on modeling the normal and abnormal OCT images with α-stable mixture model represented by stochastic differential equations (SDE). Parameters of the model are used to detect abnormal OCT images. The α-stable mixture model is created after applying a fractional Laplacian operator to the image and Expectation-Maximization (EM) algorithm is applied to estimate its parameters. The classification of an OCT image as normal or abnormal would be done by training SVM classifier based on estimated parameters of the mixture model. This method is examined for macular abnormality detection such as AMD, DME, and MH and achieve maximum accuracy of 97.8%. Clinical Relevance - This study establishes automatic method for anomaly detection on OCT images and provides fast and accurate OCT interpretation in clinical application.

Comparison of Non-mydriatic Fundus Photography and Optical Coherence Tomography with Dilated Fundus Examination for Detecting Diabetic Retinopathy Including Diabetic Macular Edema

Given increasing diabetes rates worldwide, better screening tools for diabetic retinopathy (DR) and macular edema (DME) are needed. The study aim was to compare reliability and predictive values between non-mydriatic fundus photography (NMFP) and spectral-domain optical coherence tomography (OCT) for detection of DR and DME with dilated fundus examination (DFE). This was a non-interventional, comparative study. Diabetics underwent both NMFP and macula OCT, followed by DFE. Images were interpreted by two masked ophthalmologists. The DFE result was considered gold standard. One hundred and fifty-four eyes of 83 patients were recruited. Sensitivity of NMFP for DR was 77.3% and 80.3% for OCT. Specificity for NMFP was 81.8% and 55.7% for OCT. Area under Receiver Operating Characteristics Curve (AROC) for DR was 0.80 for NMFP and 0.68 for OCT. The sensitivity of NMFP for DME was 63.2% and 82.5% for OCT. Specificity for DME was 90.1% by NMFP and 61.5% for OCT. Positive predictive value (PPV) of NMFP and OCT for DR was 76.1% (95% CI: 63.9-85.3%) and 57.6% (46.8-67.7%), respectively. Negative predictive value (NPV) of NMFP and OCT was 82.7% (95% CI: 72.8-89.7%) and 79.0% (66.4-87.9%) respectively. Positive predictive value of NMFP and OCT for DME was 80.0% (95% CI: 67.6- 88.5%) and 57.3% (45.9-68.0%), respectively. Negative predictive value of NMFP and OCT was 79.6% (95% CI:70.3 - 86.7%) and 84.8% (95% CI:73.4 - 92.1%), respectively. Eyes with normal OCT miss 21% of DR. In conclusion, NMFP is better than OCT for DR screening, while OCT is better than NMFP and DFE for detection of DME. Both modalities should be for better DR screening.

Optical coherence tomography in the differential diagnostics of important neuro-ophthalmological disease patterns

There are many disease patterns that are treated jointly by neurologists and ophthalmologists, for which optical coherence tomography (OCT) is of important differential diagnostic significance. In this context neurologists are mainly confronted by two patient collectives: patients with an acute ischemic event, who present with an acute but painless monocular visual deterioration (for central retinal artery occlusion) or with a monocular visual field defect (for arterial branch occlusion or anterior ischemic optic neuropathy). The second collective is patients without ophthalmological symptoms but with conspicuous optic nerve findings (papilledema or optic disc drusen). In this overview article both patient collectives are considered separately. In addition, the most important OCT findings for optic neuritis are presented. Before the disease patterns are described in detail, the normal OCT findings and the diagnostic possibilities of OCT are explained.

Use of dominant activations obtained by processing OCT images with the CNNs and slime mold method in retinal disease detection

Retinal disease is one of the diseases that cause visual symptoms or loss of vision in humans. This disease can affect the choroid, which severely affects vision. Optical coherence tomography (OCT) images are usually used to detect retinal disease. OCT is an imaging technique that takes high-resolution slices of retinal images. It takes time for experts to examine and interpret the OCT images. Experts need to take advantage of technological capabilities to make this process faster and more accurate. Three datasets were used in this study. Dataset #1 (UCSD dataset) consists of choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal OCT image types. Dataset #2 (Duke dataset) and Dataset #3 consist of age-related macular degeneration (AMD), DME, and normal OCT image types. An artificial intelligence based hybrid approach was proposed for retinal disease detection. In the proposed approach, class-based activations were extracted for each model with nine transfer learning models using the dataset. Next, the dominant activations were selected from the model-based activations of each class using the slime mold algorithm (SMA) and the selected activations were classified using the softmax method. The overall accuracy obtained in classification is as follows: 99.60% for dataset 1, 99.89% for dataset #2 and 97.49% for dataset #3. In this study, it was found that the proposed approach contributes to the performance of transfer learning models.

A Dual-Discriminator Fourier Acquisitive GAN for Generating Retinal Optical Coherence Tomography Images

Optical coherence tomography (OCT) images are widely used for clinical examination of the retina. Automatic deep learning-based methods have been developed to classify normal and pathological OCT images. However, lack of the big enough training data reduces the performance of these models. Synthesis of data using generative adversarial networks (GANs) is already known as an efficient alternative to increase the amount of the training data. However, the recent works show that despite high structural similarity between synthetic data and the real images, a considerable distortion is observed in frequency domain. Here, we propose a dual discriminator Fourier acquisitive GAN (DDFA-GAN) to generate more realistic OCT images with considering the Fourier domain similarity in structural design of the GAN. By applying two discriminators, the proposed DDFA-GAN is jointly trained with the Fourier and spatial details of the images and is proven to be feasible with a limited number of training data. Results are compared with popular GANs, namely, DCGAN, WGAN-GP, and LS-GAN. In comparison, Fr&#x00E9;chet inception distance (FID) score of 51.30, and Multi Scale Structural Similarity Index Measure (MS-SSIM) of 0.19 indicate superiority of the proposed method in producing images resembling the same quality, discriminative features, and diversity, as the real normal and Diabetic Macular Edema (DME) OCT images. The statistical comparison illustrates this similarity in the spatial and frequency domains, as well. Overall, DDFA-GAN generates realistic OCT images to meet requirements of the training data in automatic deep learning-based methods, used for clinical examination of the retina, and to improve the accuracy of the subsequent measurements.

Abstract 10785: Cardiac Magnetic Resonance Imaging and Optical Coherence Tomography in Patients with a Clinical Diagnosis of Myocardial Infarction with Non-Obstructive Coronary Arteries - A Systematic Review and Meta-Analysis

Background: Myocardial Infarction with Non-Obstructive Coronary arteries (MINOCA) is defined as acute Myocardial Infarction (MI) despite the absence of severe coronary artery stenosis on angiography (i.e., stenosis severity &lt;50%) and no specific alternative diagnosis (e.g., sepsis, pulmonary embolism). MINOCA remains a serious diagnostic and therapeutic challenge given the various possible underlying etiologies. Cardiac Magnetic Resonance Imaging (CMR) can distinguish between acute myocarditis (AM), MI, and Takotsubo cardiomyopathy (TCM) which are some of the commonest causes of MINOCA. Hence, The European Society of Cardiology (ESC) recommend CMR in all MINOCA patients with an unclear etiology. Intracoronary Optical coherence tomography (OCT) is a high-resolution imaging modality that allows for assessment of the integrity of the atheroma. We aimed to study the efficacy of CMR and OCT in detecting the etiology in MINOCA patients, which has the potential to guide medical therapy. Methods: A systematic search was made in PubMed, Medline and Cochrane database. Search terms used: Myocardial infarction, Coronary angiography, Normal coronary arteries, CMR, and OCT. Inclusion criteria was fulfilled by 18 studies. Meta-analysis and meta-regression was performed with 14 studies due to increased heterogeneity. Results: A total of 2474 patients were included in the meta-analysis. The mean age of all the patients was 51.5 and 56.4% were men. CMR was able to establish diagnosis in 74% of the patients; 30.4% had AM, 21.3% had true MI and 12% had TCM. Upon meta-regression the demographic variables, cardiovascular risk factors, troponin levels and C-reactive protein levels did not have any association with AM or MI. Incorporation of OCT with CMR was better at finding the etiology than either modalities individually. Conclusion: CMR is integral in finding the cause of MINOCA. Coupling coronary OCT and CMR is better than either techniques alone at identifying the etiology.

Microperimetry in hydroxychloroquine macular toxicity.

Objective: The aim was to evaluate the value of microperimetry (MP) in the early detection of toxic maculopathy caused by HCQ treatment in patients with normal fundoscopy, as well as normal structural optical coherence tomography (OCT).Materials and methods: Microperimetry was performed in 13 patients under hydroxychloroquine treatment, who did not present fundoscopic or structural OCT alterations compatible with maculopathy. We used Nidek MP3s equipment (Nidek, Gamagori, Japan) with a 13-point pattern centered in fovea, in mesopic mode and in scotopic mode. Results: The mean retinal sensitivity (MRS) in the study group was 27.25 +/ - 2.80 dB (95% CI 26.09 to 28.41 dB) while in the group of healthy volunteers 29.34 +/ - 2.18 dB (95% CI 28.67 to 30.1 dB). In scotopic mode, the mean sensitivity was 13.38 +/ - 1.43 dB (95% CI 12.79 to 13.97 dB) for HCQ users and 14.40 +/ - 2.1 dB (95% CI 13.76 to 15.04 dB) in the non-user group. Central retinal sensitivity (CRS) was also lower in patients using HCQ 26.52 +/ -4.0 dB (95% CI 24.8 to 28.15 dB) vs. 29.06 +/ - 2.5 dB (95% CI 28.33 to 29.87 dB) in the control group in mesopic mode. The trend was repeated in scotopic CRS (10.85 +/ -1.84 dB vs. 12.16 +/ - 2.61 dB respectively). Discussion: Our results showed that MP, especially in its mesopic mode, is a useful method to detect retinal toxicity caused by HCQ consumption in patients without funduscopic alteration and with normal macular OCT.Conclusions: In mesopic mode, MRS was significantly lower in patients with long-term hydroxychloroquine treatment compared to those who did not use it, even in cases in which no fundoscopic or structural OCT alteration was detected. Abbreviations: HCQ = hydroxychloroquine, MP = microperimetry, OCT = optical coherence tomography, BCVA = best corrected visual acuity, CRS = central retinal sensitivity, RS = retinal sensitivity, GEE = generalized estimating equations, MRS = mean retinal sensitivity, MfERG = multifocal electroretinogram, AMD = age-related macular degeneration