Quantitative Optical Coherence Tomography Angiography of Choroidal Neovascularization in Age-Related Macular Degeneration

Purpose To detect and quantify choroidal neovascularization (CNV) in patients with age-related macular degeneration (AMD) using optical coherence tomography (OCT) angiography. Design Observational, cross-sectional study. Participants A total of 5 normal subjects and 5 subjects with neovascular AMD were included. Methods A total of 5 eyes with neovascular AMD and 5 normal age-matched controls were scanned by a high-speed (100 000 A-scans/seconds) 1050-nm wavelength swept-source OCT. The macular angiography scan covered a 3×3-mm area and comprised 200×200×8 A-scans acquired in 3.5 seconds. Flow was detected using the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm. Motion artifacts were removed by 3-dimensional (3D) orthogonal registration and merging of 4 scans. The 3D angiography was segmented into 3 layers: inner retina (to show retinal vasculature), outer retina (to identify CNV), and choroid. En face maximum projection was used to obtain 2-dimensional angiograms from the 3 layers. The CNV area and flow index were computed from the en face OCT angiogram of the outer retinal layer. Flow (decorrelation) and structural data were combined in composite color angiograms for both en face and cross-sectional views. Main Outcome Measures The CNV angiogram, CNV area, and CNV flow index. Results En face OCT angiograms of CNV showed sizes and locations that were confirmed by fluorescein angiography (FA). Optical coherence tomography angiography provided more distinct vascular network patterns that were less obscured by subretinal hemorrhage. The en face angiograms also showed areas of reduced choroidal flow adjacent to the CNV in all cases and significantly reduced retinal flow in 1 case. Cross-sectional angiograms were used to visualize CNV location relative to the retinal pigment epithelium and Bruch's layer and classify type I and type II CNV. A feeder vessel could be identified in 1 case. Higher flow indexes were associated with larger CNV and type II CNV. Conclusions Optical coherence tomography angiography provides depth-resolved information and detailed images of CNV in neovascular AMD. Quantitative information regarding CNV flow and area can be obtained. Further studies are needed to assess the role of quantitative OCT angiography in the evaluation and treatment of neovascular AMD.National Institutes of Health (U.S.) (Grant 1R01 EY023285-01)National Institutes of Health (U.S.) (Grant R01 EY013516)Rosenbaum's P30EY010572National Institutes of Health (U.S.) (Clinical and Translational Science Award Grant UL1TR000128)Research to Prevent Blindness, Inc. (United States) (Grant R01-EY11289-26)United States. Air Force Office of Scientific Research (FA9550-10-1-0551)German Research Foundation (DFG-HO-1791/11-1)German Research Foundation (DFG-GSC80-SAOT

CAD system for early diagnosis of diabetic retinopathy based on 3D extracted imaging markers.

This dissertation makes significant contributions to the field of ophthalmology, addressing the segmentation of retinal layers and the diagnosis of diabetic retinopathy (DR). The first contribution is a novel 3D segmentation approach that leverages the patientspecific anatomy of retinal layers. This approach demonstrates superior accuracy in segmenting all retinal layers from a 3D retinal image compared to current state-of-the-art methods. It also offers enhanced speed, enabling potential clinical applications. The proposed segmentation approach holds great potential for supporting surgical planning and guidance in retinal procedures such as retinal detachment repair or macular hole closure. Surgeons can benefit from the accurate delineation of retinal layers, enabling better understanding of the anatomical structure and more effective surgical interventions. Moreover, real-time guidance systems can be developed to assist surgeons during procedures, improving overall patient outcomes. The second contribution of this dissertation is the introduction of a novel computeraided diagnosis (CAD) system for precise identification of diabetic retinopathy. The CAD system utilizes 3D-OCT imaging and employs an innovative approach that extracts two distinct features: first-order reflectivity and 3D thickness. These features are then fused and used to train and test a neural network classifier. The proposed CAD system exhibits promising results, surpassing other machine learning and deep learning algorithms commonly employed in DR detection. This demonstrates the effectiveness of the comprehensive analysis approach employed by the CAD system, which considers both low-level and high-level data from the 3D retinal layers. The CAD system presents a groundbreaking contribution to the field, as it goes beyond conventional methods, optimizing backpropagated neural networks to integrate multiple levels of information effectively. By achieving superior performance, the proposed CAD system showcases its potential in accurately diagnosing DR and aiding in the prevention of vision loss. In conclusion, this dissertation presents novel approaches for the segmentation of retinal layers and the diagnosis of diabetic retinopathy. The proposed methods exhibit significant improvements in accuracy, speed, and performance compared to existing techniques, opening new avenues for clinical applications and advancements in the field of ophthalmology. By addressing future research directions, such as testing on larger datasets, exploring alternative algorithms, and incorporating user feedback, the proposed methods can be further refined and developed into robust, accurate, and clinically valuable tools for diagnosing and monitoring retinal diseases

Multimodal Imaging of Macular Telangiectasia Type 2: Focus on Vascular Changes Using Optical Coherence Tomography Angiography

PURPOSE. To report morphologic features of idiopathic macular telangiectasia (MacTel) type 2 by means of optical coherence tomography angiography (OCTA) and to compare these findings to fundus fluorescein angiography (FFA), fundus autofluorescence (FAF), confocal blue reflectance (CBR), and spectral-domain OCT (SD-OCT). In addition, foveal vessel density and parafoveal vascular density (PFVD), and foveal retinal thickness and parafoveal retinal thickness (PFRT) were compared between MacTel 2 patients and normal aged-matched controls. METHODS. Eight patients (15 eyes) with MacTel 2 and 17 normal controls (17 eyes) underwent retinal multimodal imaging assessment and grading. Results from different imaging techniques were used to compare interimaging modalities. Objective quantification of retinal vessel density and macular thickness was evaluated in MacTel 2 patients (15 eyes). RESULTS. In MacTel 2 eyes a comparison of OCTA to the other imaging techniques showed that the strongest correlations were present with SD-OCT, early FFA, and late FFA. Moderate correlations were found between OCTA and CBR and FAF. Foveal vessel density was significantly lower in MacTel 2 eyes than control eyes both in the superficial plexus (23.74% vs. 33.14%; P = 0.003) and in the deep plexus (24.63% vs. 34.21%; P = 0.005). Superficial PFVD was significantly different in the two groups (47.06% vs. 51.40%; P = 0.005) but not the deep PFVD. Foveal retinal thickness was 214.13 mu m in MacTel 2 eyes and 258.18 mu m in normal controls, and PFRT was 279.60 and 323.29 mu m, respectively (P CONCLUSIONS. Optical coherence tomography angiography is useful for retinal vasculature characterization in MacTel type 2 patients and showed a high correlation with well-established imaging techniques

Clinical outcomes of ranibizumab treatment in diabetic eye disease

Background: The vascular endothelial growth factor (VEGF) inhibitor ranibizumab is emerging as an efficacious treatment for diabetic macular oedema. Large clinical trials have shown improvements in visual acuity and reduced central retinal thickness. Details of its effect on other retinal functional parameters are lacking. There is a concern that repeated ranibizumab treatment could exacerbate macular ischaemia or lead to global retinal dysfunction by inhibiting physiological isoforms of VEGF. Outcomes of surgery for advanced proliferative retinopathy remain variable and post-operative complications including recurrent haemorrhage can limit visual recovery. VEGF is strongly implicated in the pathogenesis of advanced retinopathy, so VEGF inhibition prior to surgery may improve outcomes. Trials have failed to demonstrate a clear benefit for bevacizumab, so investigation of the licensed intraocular agent ranibizumab represents a logical next step. Aims: To investigate the effects of ranibizumab and laser treatment in diabetic macular oedema on the following parameters: visual acuity, protan and tritan colour contrast sensitivity, 4° and 12° macular sensitivity by microperimetry, electrophysiological indices from pattern and full field electroretinograms. To report structural retinal changes following ranibizumab and laser treatment in terms of qualitative and quantitative optical coherence tomography outcomes, and to quantify macular ischaemia by fluorescein angiography. To investigate the effect on visual acuity at three months post-surgery of ranibizumab pre-treatment in patients undergoing vitrectomy for advanced proliferative diabetic retinopathy. Methods: Randomised clinical trial of intravitreal ranibizumab vs. laser in 36 subjects with centre-involving diabetic macular oedema (The LUCIDATE study). Randomised clinical trial of pre-operative intravitreal ranibizumab vs. subconjunctival saline injection in 30 subjects undergoing vitrectomy-delamination for advanced proliferative diabetic retinopathy (The RaDiVit study). Results: Thirty six subjects with diabetic macular oedema were recruited and 33 completed the trial. Ranibizumab treated subjects gained a mean of 6 letters compared with 0.9 letter loss for laser at 48 weeks. Retinal sensitivity improved in the central macular 4° and 12° in both groups but to a greater extent with ranibizumab. There was no evidence of worsening global retinal dysfunction by electroretinograms in either group. Retinal thickness decreased in both groups: there was a 132 µm reduction in central macular thickness with ranibizumab compared with 103 µm for laser. Fluorescein angiography showed no evidence of significantly increased macular ischaemia in either group. Thirty subjects with advanced proliferative diabetic retinopathy were recruited, underwent surgery, and completed the study. At three months post-surgery, visual acuity in the ranibizumab group was 53 letters compared with 47 letters in the control group. Conclusion: In diabetic macular oedema, there is evidence that ranibizumab leads to greater improvements in visual acuity and retinal sensitivity than laser, with a corresponding greater reduction in retinal thickness. There is no evidence that it worsens macular ischaemia or indices of global retinal electrophysiological function, but larger trials designed to address each of the outcomes investigated here would be required to confirm these findings. In proliferative diabetic retinopathy, there is evidence from this small pilot study that ranibizumab treatment leads to better visual acuity at 3 months post-surgery. An appropriately powered trial would be required to confirm this

Recent Developments in Detection of Central Serous Retinopathy through Imaging and Artificial Intelligence Techniques – A Review

Central Serous Retinopathy (CSR) or Central Serous Chorioretinopathy (CSC) is a significant disease that causes blindness and vision loss among millions of people worldwide. It transpires as a result of accumulation of watery fluids behind the retina. Therefore, detection of CSR at early stages allows preventive measures to avert any impairment to the human eye. Traditionally, several manual methods for detecting CSR have been developed in the past; however, they have shown to be imprecise and unreliable. Consequently, Artificial Intelligence (AI) services in the medical field, including automated CSR detection, are now possible to detect and cure this disease. This review assessed a variety of innovative technologies and researches that contribute to the automatic detection of CSR. In this review, various CSR disease detection techniques, broadly classified into two categories: a) CSR detection based on classical imaging technologies, and b) CSR detection based on Machine/Deep Learning methods, have been reviewed after an elaborated evaluation of 29 different relevant articles. Additionally, it also goes over the advantages, drawbacks and limitations of a variety of traditional imaging techniques, such as Optical Coherence Tomography Angiography (OCTA), Fundus Imaging and more recent approaches that utilize Artificial Intelligence techniques. Finally, it is concluded that the most recent Deep Learning (DL) classifiers deliver accurate, fast, and reliable CSR detection. However, more research needs to be conducted on publicly available datasets to improve computation complexity for the reliable detection and diagnosis of CSR disease

OCT Angiography (OCTA) in Retinal Diagnostics

Optical coherence tomography angiography (OCTA) is an imaging modality which can be applied in ophthalmology to provide detailed visualization of the perfusion of vascular networks in the eye. Compared to previous state of the art dye-based imaging, such as fluorescein angiography, OCTA is non-invasive, time-efficient, and it allows for the examination of retinal vasculature in 3D. These advantages of the technique combined with the good usability in commercial devices led to a quick adoption of the new modality in the clinical routine. However, the interpretation of OCTA data is not without problems: Commonly observed image artifacts and the quite involved algorithmic details of OCTA signal construction can make the clinical assessment of OCTA exams challenging. In this article we describe the technical background of OCTA and discuss the data acquisition process, common image visualization techniques, as well as limitations and sources of artifacts of the modality. Examples of clinical cases underline the increasing importance of the OCTA technology in ophthalmology and its relation to dye-based angiography

COMPARING FUNDUS FLUORESCEIN ANGIOGRAPHY AND SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IN THE EVALUATION OF DIABETIC MACULAR PERFUSION

PURPOSE: To compare fundus fluorescein angiography (FFA) and swept-source optical coherence tomography angiography (SS-OCTA) in the evaluation of macular perfusion in diabetic patients. METHODS: Forty-one eyes (21 diabetic patients) seen at Moorfields Eye Hospital (London) over a 1-month interval underwent color fundus photography, FFA, and SS-OCTA imaging of the capillary superficial plexus using 2 different protocols: 3 × 3 mm and 4.5 × 4.5 mm. Quantitative assessment (foveal avascular zone diameters and area), qualitative analysis (macroscopic and microscopic levels) and Early Treatment Diabetic Retinopathy Study diabetic macular ischemia grading were performed. Artifacts were recorded. Intraclass correlation coefficients and weighted kappa values were calculated. RESULTS: Mean (SD) foveal avascular zone area was 0.695 (0.52) mm on FFA, 0.627 (0.54) mm on SS-OCTA 3 × 3 and 0.701 (0.54) mm on SS-OCTA 4.5 × 4.5 protocol. Intraclass correlation coefficients showed good agreement between FFA and SS-OCTA for both vertical diameter and foveal avascular zone area measurements. The agreement between SS-OCTA 3 × 3 and 4.5 × 4.5 was good for all quantitative measurements. Weighted kappa for diabetic macular ischemia grading showed low to fair agreement between FFA and SS-OCTA, whereas the agreement was good between two different SS-OCTA protocols. CONCLUSION: Swept-source OCTA is a reproducible technique in the assessment of macular perfusion in diabetic patients with special regards to foveal avascular zone analysis. The agreement with FFA is limited especially for diabetic macular ischemia grading. Fundus fluorescein angiography is more sensitive in identifying microaneurysms