Retinal status analysis method based on feature extraction and quantitative grading in OCT images

Background: Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. Methods: This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. Results: This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. Conclusions: This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosi

Vascular Adhesion Protein-1 Blockade Suppresses Ocular Inflammation After Retinal Laser Photocoagulation in Mice

PURPOSE. To investigate the effect of the vascular adhesion protein-1 (VAP-1) inhibitor RTU-1096 on retinal morphologic changes and ocular inflammation after retinal laser photocoagulation in mice. METHODS. C57BL/6JJcl mice were fed a diet containing RTU-1096, a specific inhibitor for VAP-1, or a control diet ad libitum for 7 days. Laser photocoagulation was performed on the peripheral retina of the animals. The semicarbazide sensitive amine oxidase (SSAO) activities in plasma and chorioretinal tissues were measured. Optical coherence tomography (OCT) images were acquired before and at 1, 3, and 7 days after laser photocoagulation, and thickness of the individual retinal layers was measured. Intravitreal leukocyte infiltration was assessed by histologic analysis. The expression level of intercellular adhesion molecule-1 (ICAM-1) in retinal tissues were examined by quantitative real-time PCR. RESULTS. One day after laser photocoagulation, the thickness of the outer nuclear layer (ONL) increased in the laser group compared with in the control group, and RTU-1096 administration abrogated the ONL thickening. Histologic analysis and OCT observation revealed that laser photocoagulation caused infiltration of inflammatory cells and the appearance of hyperreflective foci at the vitreoretinal surface, both of which were suppressed by RTU-1096 administration. In addition, systemic administration of RTU-1096 reduced upregulation of the leukocyte adhesion molecules ICAM-1 in the retina. CONCLUSIONS. The current data indicate that VAP-1/SSAO inhibition may be a potential therapeutic strategy for the prevention of macular edema secondary to scatter laser photocoagulation in patients with ischemic retinal diseases such as diabetic retinopathy

The APOSTEL recommendations for reporting quantitative optical coherence tomography studies

OBJECTIVE: To develop consensus recommendations for reporting of quantitative optical coherence tomography (OCT) study results. METHODS: A panel of experienced OCT researchers (including 11 neurologists, 2 ophthalmologists, and 2 neuroscientists) discussed requirements for performing and reporting quantitative analyses of retinal morphology and developed a list of initial recommendations based on experience and previous studies. The list of recommendations was subsequently revised during several meetings of the coordinating group. RESULTS: We provide a 9-point checklist encompassing aspects deemed relevant when reporting quantitative OCT studies. The areas covered are study protocol, acquisition device, acquisition settings, scanning protocol, funduscopic imaging, postacquisition data selection, postacquisition data analysis, recommended nomenclature, and statistical analysis. CONCLUSIONS: The Advised Protocol for OCT Study Terminology and Elements recommendations include core items to standardize and improve quality of reporting in quantitative OCT studies. The recommendations will make reporting of quantitative OCT studies more consistent and in line with existing standards for reporting research in other biomedical areas. The recommendations originated from expert consensus and thus represent Class IV evidence. They will need to be regularly adjusted according to new insights and practices

Less is more: Ensemble Learning for Retinal Disease Recognition Under Limited Resources

Retinal optical coherence tomography (OCT) images provide crucial insights into the health of the posterior ocular segment. Therefore, the advancement of automated image analysis methods is imperative to equip clinicians and researchers with quantitative data, thereby facilitating informed decision-making. The application of deep learning (DL)-based approaches has gained extensive traction for executing these analysis tasks, demonstrating remarkable performance compared to labor-intensive manual analyses. However, the acquisition of Retinal OCT images often presents challenges stemming from privacy concerns and the resource-intensive labeling procedures, which contradicts the prevailing notion that DL models necessitate substantial data volumes for achieving superior performance. Moreover, limitations in available computational resources constrain the progress of high-performance medical artificial intelligence, particularly in less developed regions and countries. This paper introduces a novel ensemble learning mechanism designed for recognizing retinal diseases under limited resources (e.g., data, computation). The mechanism leverages insights from multiple pre-trained models, facilitating the transfer and adaptation of their knowledge to Retinal OCT images. This approach establishes a robust model even when confronted with limited labeled data, eliminating the need for an extensive array of parameters, as required in learning from scratch. Comprehensive experimentation on real-world datasets demonstrates that the proposed approach can achieve superior performance in recognizing Retinal OCT images, even when dealing with exceedingly restricted labeled datasets. Furthermore, this method obviates the necessity of learning extensive-scale parameters, making it well-suited for deployment in low-resource scenarios.Comment: Ongoing wor

Investigating neuroinflammatory disease through retinal imaging and biomarkers

Neuroinflammatory diseases, in particular multiple sclerosis (MS) and neuromyelitis optica spectrum disorder, often affect the anterior visual pathways. This can occur through direct inflammatory insult in the form of optic neuritis or through retrograde degeneration, but progressive neurodegenerative processes related to axonal loss and atrophy also play a role. Energy failure has been postulated as an important factor mediating factor in these neurodegenerative processes, but its exact role is poorly understood. The advent of optical coherence tomography (OCT) enables high resolution imaging of the retina with relative ease. In neurology research, OCT has mostly been used to quantify retinal layer thicknesses. This thesis focuses on the largely unexplored potential of OCT as a functional biomarker. The primary aim is to develop indirect non-invasive in-vivo biomarkers informing on metabolic function, taking into account the high energy demand of the retina, particularly during dark-adaptation. First, two novel functional OCT measures are presented; the dynamic dark-adaptation related thickening of the outer retinal layers and the relative reflectivity of the ellipsoid zone (EZ), which comprises the majority of retinal mitochondria. Both measures appeared to be reduced in acute optic neuritis, and also in chronic neuroinflammatory disease in the case of EZ reflectivity. Furthermore, pilot OCT-angiography (OCTA) data indicated that vascular density was reduced in acute optic neuritis. As reduced EZ reflectivity and lower vascular density were present to a similar degree in both eyes of acute optic neuritis patients suggest that a background level of mitochondrial dysfunction and hypoperfusion may occur in neuroinflammatory disease, independent from acute inflammatory activity. The work presented in this thesis illustrates that OCT has the potential to provide valuable information on retinal function in neuroinflammatory disease. In the future, artificial intelligence and big data analysis may enable the development of a holistic analysis method for raw OCT data, providing a summary report on both qualitative, such as presence of microcystic macular oedema (MMO), and quantitative scan features, such as layer thickness, vascular density and reflectivity. Comprehensive analysis of both functional and structural OCT data may facilitate diagnosis, inform on prognosis and provide important insight into the role of metabolic failure in the pathophysiology of neuroinflammatory disease

Total flow intensity, active flow intensity and volume related flow intensity as new quantitative metrics in optical coherence tomography angiography

Optical coherence tomography (OCT) angiography (OCTA) is a non-invasive tool for the in-vivo study of the intraretinal vascular network. It is based on the analysis of motion particles within the retina to reconstruct the paths followed by the erythrocytes, i.e. retinal capillaries. To date, qualitative and quantitative information are based on the morphological features disclosed by retinal capillaries. In the present study, we proposed new quantitative functional metrics, named Total Flow Intensity (TFI), Active Flow Intensity (AFI), and Volume-related Flow Intensity (VFI), based on the processing of the blood flow signal detected by OCTA. We studied these metrics in a cohort of healthy subjects, and we assessed their clinical utility by including a cohort of age-matched patients affected by Stargardt disease. Moreover, we compared TFI, AFI, and VFI to the widely used vessel density (VD) parameter. TFI, AFI, and VFI were able to describe in detail the different properties of the retinal vascular compartment. In particular, TFI was intended as the overall amount of volumetric retinal blood flow. AFI represented a selective measure of voxels disclosing blood flow signal. VFI was developed to put in relationship the volumetric blood flow information with the not vascularized retinal volume. In conclusion, TFI, AFI, and VFI were proposed as feasible functional OCTA biomarkers based on the analysis of retinal blood flow signal

Analysis of Peripapillary Atrophy Using Spectral Domain Optical Coherence Tomography

Objective To study retinal morphologic changes around the optic disc in patients with peripapillary atrophy (PPA) with high-resolution spectral domain optical coherence tomography (SD OCT). Design Cross-sectional, retrospective analysis. Participants A total of 103 eyes of 73 patients with PPA and 21 eyes of 12 normal patients seen at the New England Eye Center, Tufts Medical Center, between January 2007 and August 2009. Methods Spectral domain optical coherence tomography images taken through the region of PPA were quantitatively and qualitatively analyzed. Inclusion criteria included eyes with at least 300 μm of temporal PPA as detected on color fundus photographs. The study population was divided into subgroups according to the following clinical diagnoses: glaucoma (n=13), age-related macular degeneration (n=11), high myopia (n=11), glaucoma and high myopia (n=3), and optic neuropathy (n=11). Fifty-four patients were classified with other diagnoses. By using OCT software, retinal thickness and retinal nerve fiber layer (RNFL) thickness were both manually measured perpendicular to the internal limiting membrane and retinal pigment epithelium (RPE) 300 μm temporal to the optic disc, within the region of PPA. Qualitative analysis for morphologic changes in the atrophic area was also performed. Main Outcome Measures Qualitative assessment and quantitative measures of retinal and RNFL thickness in PPA. Results The study group was categorized by 6 characteristics demonstrated in the area of PPA by SD OCT: RPE loss with accompanying photoreceptor loss, RPE disruption, RNFL thickening with plaque-like formation, intraretinal cystic changes, inner and outer retinal thinning, and abnormal retinal sloping. Statistical analysis of measurements revealed a statistically significant difference in the total retinal thickness between normal eyes and eyes with PPA (P=0.0005), with normal eyes 15% thicker than the eyes with PPA; however, the RNFL thickness was not significantly different between the normal eyes and the eyes with PPA (P=0.05). Conclusions Eyes with PPA manifest characteristic retinal changes that can be described via SD OCT.National Institutes of Health (U.S.) (Contract R01-EY11289-24)National Institutes of Health (U.S.) (Contract R01-EY13178-10)National Institutes of Health (U.S.) (Contract R01-EY013516-07)United States. Air Force Office of Scientific Research (FA9550-07-1-0101)United States. Air Force Office of Scientific Research (FA9550-07-1-0014)Massachusetts Lions Eye Research Fund, Inc

Distinctive Mechanisms and Patterns of Exudative Versus Tractional Intraretinal Cystoid Spaces as Seen With Multimodal Imaging.

PurposeTo determine clear-cut distinctions between tractional and exudative intraretinal cystoid spaces subtypes.DesignRetrospective, multicenter, observational case series.MethodsA cohort of patients diagnosed with intraretinal cystoid spaces and imaged with optical coherence tomography (OCT), fluorescein angiography (FA), blue fundus autofluorescence (BFAF), en face OCT, and OCT angiography (OCT-A) was included in the study. All images were qualitatively and quantitatively evaluated.ResultsIn this study were included 72 eyes of 69 patients. Exudative intraretinal cystoid spaces (36/72 eyes, 50%) displayed a "petaloid" morphology as seen with en face OCT, FA, and BFAF. Tractional intraretinal cystoid spaces (24/72 eyes, 33.3%), displayed a radial "spoke-wheel" en face OCT pattern. There was no leakage with FA and BFAF did not reveal specific patterns. Eyes with full-thickness macular hole (FTMH, 12/72 eyes, 16.7%) displayed a "sunflower" en face OCT appearance. FTMH showed OCT, OCT-A, and BFAF features of both exudative and tractional cystoid spaces, but without any FA leakage. Inner nuclear layer (INL) thickness was significantly lower in tractional cystoid spaces (P < .001). There were a greater number of INL cystoid spaces in both the exudative and FTMH subgroups (P = .001). The surface area of INL cystoid spaces was significantly lower in the tractional subgroup (P < .001). There was a significant reduction of the microvascular density in eyes with exudative vs tractional (P = .002) and FTMH (P < .001) subgroups.ConclusionsExudative and tractional intraretinal cystoid spaces displayed characteristic multimodal imaging features and they may represent 2 different pathologic conditions with equally different clinical implications