Areas Of Nonperfusion Research Articles

Blue light reflectance imaging in non-perfusion areas detection: insights from multimodal analysis

DesignA retrospective, cross-sectional image analysis using a convenience sample.SubjectsFive cases selected based on the availability of comprehensive imaging data.MethodsThis study involved a retrospective review of images from five cases, focusing on the use of retinal monochromatic blue light reflectance (BLR) imaging to detect non-perfusion areas. Two cases of sickle-cell retinopathy demonstrated peripheral retinal non-perfusion identified through widefield fluorescein angiography. Three other cases—one with branch retinal vein occlusion, one with branch retinal artery occlusion, and one presenting paracentral acute middle maculopathy showed focal macular non-perfusion detected by structural OCT and OCTA. The areas of nonperfused retinal tissue, confirmed by fluorescein angiography, OCT, and OCTA, were then correlated with findings from the BLR image. This correlation aimed to identify any potential associations between these imaging modalities.Main outcome measuresEnhance understanding of the utilization of retinal monochromatic BLR images as a non-perfusion biomarker.ResultsThe perfusion defects identified through fluorescein angiography were qualitatively correlated with hypo-reflective regions observed in the BLR images. A notable correlation was also observed between the OCTA deep capillary plexus findings and the BLR images. Additionally, areas of retinal thinning identified on structural OCT thickness maps corresponded with the hypo-reflective regions in the BLR images. This indicates the potential of BLR in identifying non-perfused retinal areas.ConclusionsThis study reinforces the evidence, through OCT, OCTA, and angiographic correlation, that the BLR can effectively identify areas of retinal non-perfusion in a non-invasive manner. Further research is warranted to assess the method’s sensitivity, specificity, and limitations. While the interaction of blue light with the retina, leading to specular reflections and scattering, is established, this research represents a pioneering effort in suggesting which specific retinal structures may be implicated in this phenomenon. This novel insight opens avenues for deeper exploration into the underlying mechanisms and potential clinical applications of utilizing the BLR imaging technique for assessing retinal vascular abnormalities.

Role of angiopoietin-like 4 in neovascularization associated with retinopathy of prematurity

To elucidate the mechanisms of angiopoietin-like 4 (ANGTPL4) in neovascularization (NV) in retinopathy of prematurity (ROP). We compared ANGPTL4 expression levels of aqueous humor and vitreous fluid samples in infants with acute-phase ROP and control group. ANGPTL4-/- mice and WT mice were used to constructed oxygen-induced retinopathy (OIR) mouse models, with retinal tissues collected on postnatal days 12 (P12), 15 (P15) and 17 (P17). Analysis of retinal vessels and transcriptomics were performed to explore the role of ANGTPL4 in NV. The results showed ANGPTL4 level was significantly higher in the aqueous humour and vitreous fluid of children with ROP than that of control group. At P15 and P17, the vascular indices in the ANGPTL4-/--CON group were lower than those in the WT-CON group. The central non-perfused area of the retina and number of neovascular nuclei were also smaller in the ANGPTL4-/--OIR group than in the WT-OIR group. Immunofluorescence results showed the overexpression of ANGPTL4 protein in the WT-OIR group than in the WT-CON group, especially at P17. Furthermore, extracellular matrix (ECM) organisation was one of the key involved pathways based on gene ontology (GO) enrichment analyses. ANGPTL4 was one of the core genes involved in ECM organization, and neuralized E3 ubiquitin protein ligase 1B (NEURL1B), cd36 Molecule (CD36), matrix metallopeptidase 3 (MMP3) and collagen type III alpha 1 chain (COL3A1) were the first nodes interacting with ANGPTL4.In conclusion, ANGPTL4 is involved in the pathological NV by regulating NEURL1B, CD36, MMP3, and COL3A1. Thus, ANGPTL4 is a potential therapeutic target for ROP.

IDIOPATHIC RETINAL VASCULITIS, ANEURYSMS, AND NEURORETINITIS COMPLICATED BY CILIORETINAL ARTERY OCCLUSION: MULTIMODAL IMAGING AND 5-YEAR FOLLOW-UP.

To describe a multimodal imaging and a 5-year follow-up of a case of cilioretinal artery occlusion (CLRAO) in a 40-year-old woman with idiopathic retinal vasculitis, aneurysms, and neuroretinitis (IRVAN) syndrome. Fundus photography, indocyanine green and fluorescein angiography, optical coherence tomography (OCT), OCT angiography (OCTA), and a literature review of retinal artery occlusions associated with IRVAN syndrome were performed. Fundus examination revealed bilateral blurred margins of the discs and peri-vascular hard exudates. Fluorescein angiography (FA) demonstrated peripheral capillary nonperfusion areas in both eyes (OU). It also revealed an aberrant cilioretinal artery in the right eye (OD). OCT showed attenuation of the inner retinal layers and disruption of the outer retinal layers secondary to CLRAO in OD. OCTA allowed a clear identification of macular hypoperfusion in OU. Laser photocoagulation, along with anti-VEGF and corticosteroid intravitreal injections, was administered in OU. Best-corrected visual acuity remained stable, with no evidence of progression or development of neovascularization after a 5-year follow-up. IRVAN syndrome may be complicated by CLRAO, resulting in poor final visual acuity despite reperfusion of the occluded artery. In such cases, multimodal imaging allows the identification of complications such as macular atrophy on OCT and hypoperfusion areas that may not be detected on FA on OCTA.

Automated grading of diabetic retinopathy and Radiomics analysis on ultra-wide optical coherence tomography angiography scans

Diabetic retinopathy (DR), a progressive condition due to diabetes that can lead to blindness, is typically characterized by a number of stages, including non-proliferative (mild, moderate and severe) and proliferative DR. These stages are marked by various vascular abnormalities, such as intraretinal microvascular abnormalities (IRMA), neovascularization (NV), and non-perfusion areas (NPA). Automated detection of these abnormalities and grading the severity of DR are crucial for computer-aided diagnosis. Ultra-wide optical coherence tomography angiography (UW-OCTA) images, a type of retinal imaging, are particularly well-suited for analyzing vascular abnormalities due to their prominence on these images. However, accurate detection of abnormalities and subsequent grading of DR is quite challenging due to noisy data, presence of artifacts, poor contrast and subtle nature of abnormalities. In this work, we aim to develop an automated method for accurate grading of DR severity on UW-OCTA images. Our method consists of various components such as UW-OCTA scan quality assessment, segmentation of vascular abnormalities and grading the scans for DR severity. Applied on publicly available data from Diabetic retinopathy analysis challenge (DRAC 2022), our method shows promising results with a Dice overlap metric and recall values of 0.88 for abnormality segmentation, and the coefficient-of-agreement (κ) value of 0.873 for DR grading. We also performed a radiomics analysis, and observed that the radiomics features are significantly different for increasing levels of DR severity. This suggests that radiomics could be used for multimodal grading and further analysis of DR, indicating its potential scope in this area.

Eales’ disease with secondary coats’-like reaction: a case report

BackgroundEales’ disease is an idiopathic, inflammatory condition characterized by peripheral retinal phlebitis, distal non-perfusion, and neovascularization. Coats’ disease, on the other hand, is an idiopathic, retinal vasculopathy characterized by telangiectasia and yellowish exudation. Both diseases commonly affect males. Here, we report an atypical case of unilateral Eales’ disease with co-existing, secondary Coats’-like reaction in a 25-year-old male exhibiting unilateral retinal telangiectasia accompanied by subtle macular edema, extensive peripheral vascular sheathing, and distal non-perfusion in the absence of clinically visible exudation.MethodsCase report.ResultsA 25-year-old male presented with painless blurring of vision in the right eye for two months. Best-corrected Snellen visual acuity was 3/60 in the affected eye, with relative afferent pupillary defect observed, and 6/9 contralaterally. Anterior segment examination was unremarkable. Right eye fundoscopy showed aneurysmal telangiectasia at the macula, 360 degrees perivascular sheathing and telangiectasia of peripheral retinal vessels. There was no exudation, neovascularization, tractional membranes, vitritis, retinitis, and choroiditis. Left eye fundus was unremarkable. Optical coherence tomography of the macula revealed disorganization and thinning of the inner retinal layers with minimal intraretinal fluid. Fundus fluorescein angiography showed leakage from the aneurysms but not from the sheathed vessels, and an enlarged foveolar avascular zone. A well-defined zone of non-perfusion and retinal vascular telangiectasia with shunts was observed. Blood investigations ruled out metabolic, infectious, haematological, and autoimmune causes. Carotid Doppler showed no stenosis, and CT angiography of the brain did not show any vascular abnormalities. In view that no cause was identified, a diagnosis of Eales’ disease with secondary Coats’-like reaction was made. Treatment consisted of FFA-guided laser photocoagulation to the areas of non-perfusion. Intavitreal anti-vascular endothelial growth factor injection was not done in view of poor visual prognosis. The condition and visual acuity remained stable during 18 months of follow-up.ConclusionThis report highlights an atypical case of Eales’ disease with co-existing, secondary Coats’-like reaction.

Framework Nucleic Acids Loaded with Quercetin: Protecting Retinal Neurovascular Unit via the Protein Kinase B/Heme Oxygenase-1 Pathway.

Retinal neovascular disease is a leading cause of vision loss and blindness globally. It occurs when abnormal new blood vessels form in the retina. In this study, we utilized tetrahedral framework nucleic acids (tFNAs) as vehicles to load quercetin (QUE), a small-molecule flavonoid, forming a deoxyribonucleic acid (DNA) nanocomplex, tFNAs-QUE. Our data show this nanocomplex inhibits pathological neovascularization, reduces the area of retinal nonperfusion area, protects retinal neurons, and preserves the visual function. Further, we discovered that tFNAs-QUE selectively upregulates the AKT/Nrf2/HO-1 signaling pathway, which can suppress pathological vascular growth and exert antioxidative effects. Therefore, this study presents a promising small-molecule-loading mechanism for the treatment of ischemic retinal diseases.

Development and evaluation of a deep learning model for automatic segmentation of non-perfusion area in fundus fluorescein angiography

Diabetic retinopathy (DR) is the most prevalent cause of preventable vision loss worldwide, imposing a significant economic and medical burden on society today, of which early identification is the cornerstones of the management. The diagnosis and severity grading of DR rely on scales based on clinical visualized features, but lack detailed quantitative parameters. Retinal non-perfusion area (NPA) is a pathogenic characteristic of DR that symbolizes retinal hypoxia conditions, and was found to be intimately associated with disease progression, prognosis, and management. However, the practical value of NPA is constrained since it appears on fundus fluorescein angiography (FFA) as distributed, irregularly shaped, darker plaques that are challenging to measure manually. In this study, we propose a deep learning-based method, NPA-Net, for accurate and automatic segmentation of NPAs from FFA images acquired in clinical practice. NPA-Net uses the U-net structure as the basic backbone, which has an encoder-decoder model structure. To enhance the recognition performance of the model for NPA, we adaptively incorporate multi-scale features and contextual information in feature learning and design three modules: Adaptive Encoder Feature Fusion (AEFF) module, Multilayer Deep Supervised Loss, and Atrous Spatial Pyramid Pooling (ASPP) module, which enhance the recognition ability of the model for NPAs of different sizes from different perspectives. We conducted extensive experiments on a clinical dataset with 163 eyes with NPAs manually annotated by ophthalmologists, and NPA-Net achieved better segmentation performance compared to other existing methods with an area under the receiver operating characteristic curve (AUC) of 0.9752, accuracy of 0.9431, sensitivity of 0.8794, specificity of 0.9459, IOU of 0.3876 and Dice of 0.5686. This new automatic segmentation model is useful for identifying NPA in clinical practice, generating quantitative parameters that can be useful for further research as well as guiding DR detection, grading severity, treatment planning, and prognosis.

Severity Scale of Diabetic Macular Ischemia Based on the Distribution of Capillary Nonperfusion in OCT Angiography

To evaluate the severity scales of diabetic macular ischemia (DMI) by analyzing the quantity and distribution of capillary nonperfusion using OCT angiography (OCTA) images. A single-center, prospective case series. Three hundred one eyes from 301 patients with diabetic retinopathy. We acquired 3× 3-mm swept-source OCTA images and created en face images within a central 2.5-mm circle. The circle was divided into 15× 15-pixel squares and nonperfusion squares (NPSs) were defined as those without retinal vessels. Eyes with high-dimensional spatial data were arranged on a 2-dimensional space using the uniform manifold approximation and projection (UMAP) algorithm and classified by clustering into 5 groups: Initial, Mild, Superficial, Moderate, and Severe. Development of a severity scale for DMI. Eyes arranged on a 2-dimensional UMAP space were divided into 5 clusters, based on the similarity of nonperfusion area distribution. Nonperfusion square counts in the deep layer increased in eyes of the Initial, Mild, Moderate, and Severe groups in a stepwise manner. In contrast, there were no significant changes in superficial NPS counts between eyes of the Initial and Mild groups. In the intermediate stage, eyes of the Superficial group exhibited higher NPS counts in the central sector of the superficial layer compared with those of the Moderate group. The foveal avascular zone extended into the temporal subfield of the deep layer in eyes of the Moderate group. Eyes of the Severe group had significantly poorer visual acuity that was more frequently accompanied with proliferative diabetic retinopathy. The application of dimensionality reduction and clustering has facilitated the development of a novel severity scale for DMI based on the distribution of capillary nonperfusion in OCTA images. The authors have no proprietary or commercial interest in any materials discussed in this article.

The Role of Widefield Optical Coherence Tomography Angiography in Assessing the Severity of Diabetic Retinopathy.

Physicians need an accurate understanding of diabetic retinopathy (DR) severity to optimally manage patients. The aim of this prospective study is to correlate the severity of macular and peripheral retinal vascular abnormalities seen on widefield (WF) optical coherence tomography angiography (OCTA) with DR grading based on WF fundus photography. The study included 150 eyes from 82 patients with treatment-naïve DR. All patients were imaged with WF fundus photography and swept-source WF OCTA. Quantitative and qualitative analyses of the foveal avascular zone (FAZ) size and shape, and measurement of capillary nonperfusion (CNP) areas, were performed from the OCTA images. The mixed-effects model was used to compare the DR grading from WF photography with the vascular changes seen on WF-OCTA, and Bonferroni correction was applied to the gradings. The mean [± standard deviation (SD)] age of patients was 55.5 (± 9.4) years. The WF-OCTA showed that an increasing size of the FAZ (from 0.442 (± 0.059) µm to 0.933 (± 0.086) µm) correlated with increasing severity of the DR (as determined with WF photography). The deep capillary plexus, FAZ size, and CNP areas in eyes with proliferative diabetic retinopathy (PDR) differed from those with mild nonproliferative diabetic retinopathy (NPDR) (p < 0.001). Most eyes with severe nonproliferative DR were found to have CNP in four quadrants [superficial capillary plexus (SCP) 60%, deep capillary plexus (DCP) 50%]. The WF-OCTA detected subtle neovascularization of the disc (NVD) in 7 eyes (10%) and neovascularization elsewhere (NVE) in 13 eyes (18%) that had been diagnosed with only moderate NPDR on WF photography. FAZ and CNP areas as measured by WF-OCTA correlate with DR severity. WF-OCTA can also detect subtle NVE and NVD that cannot be seen with fundus photography.

Association of microaneurysms with retinal vascular alterations in patients with retinal vein occlusion

ObjectiveTo investigate the localization, distribution, and type of central microaneurysms (MAs) and their relationship with retinal vascular alterations in patients with retinal vein occlusion (RVO). MethodsIn this cross-sectional study, ultra-widefield color fundus photography (UWF-CF), standard and single-capture 65° widefield (WF) optical coherence tomography angiography (OCTA) were performed in consecutive patients with RVO treated at the Department of Ophthalmology and Optometry, Medical University of Vienna. UWF-CF, en face and B-Scans in 6 mm × 6 mm OCTA were examined for detection of MAs. Nonperfusion areas (NPA) and collateral vessels (CV) were evaluated on WF-OCTA, ghost vessels (GV), and tortuous vessels (TV) on UWF-CF. ResultsOne-hundred-and-twelve patients were included in the study, and data from 59 eyes of 59 patients with disease duration longer than 3 months, good image quality, and without relevant ocular comorbidities were eligible for statistical analysis. Fifty-six of 59 (94.9%) patients were previously treated with anti-vascular endothelial growth factor agents for macular edema, 31 of 59 (52.5%) patients presented with MAs in the central 6 mm and 60 MAs were found in total using multimodal imaging. There was no statistically significant difference in the greatest diameter of fluid-associated versus non-fluid-associated MAs (p = 0.53). Eyes with MAs were associated with CV, TV, and GV (χ2-test; p < 0.001, p = 0.0498, and p = 0.001). Median NPA was 27.3 mm2 (quartiles 1.3–62.8 mm2) in eyes with MAs and 0 mm2 (quartiles 0–36.2 mm2) in eyes without MAs (Mann-Whitney-U-test; p = 0.018). ConclusionMAs were associated with extensive NPA, the presence of CV, GV, and TV. There was no correlation between the diameter of the MA and the adjacent intraretinal fluid in our predominantly pretreated RVO study patients.

Pachychoroid neovascular membrane in a patient with sickle cell disease trait.

To describe a rare presentation of pachychoroid neovascular membrane in a patient with sickle cell trait and the accuracy of ruling out hemoglobinopathies in the presentation of pachychoroid spectrum. The patient was subjected to physical examinations, multimodal images (fluorescein angiography, optical coherence tomography), hemoglobin electrophoresis, and peripheral blood smear, documenting sickle cell trait. The management included laser treatment to target non-perfusion areas, along with a single dose of anti-VEGF. A 45-year-old male patient with diagnosis of pachychoroid neovascularization treated for 6 years with multiple anti VEGF injections in the left eye. A detailed clinical evaluation included hypochromic conjunctiva, peripheral vascular occlusion with non-perfusion areas led us to suspect sickle cell disease retinopathy. The images of fluorescein angiography showed peripheral arteriovenous anastomosis with non-perfusion areas; the optical coherence tomography revealed a thinner neuroepithelium with a thicker choroid; also, hemoglobin electrophoresis and peripheral blood smear documenting sickle cell trait. The chosen management was photocoagulation of the peripheral retina on the non-perfusion areas and anti VEGF without neovascular activity recurrence in the follow up period. Although sickle cell trait is considered a mild form of this pathology without serious retinal manifestations, it has to be noted that in the context of pachychoroid spectrum diseases is a trigger that could perpetuate retinal ischemia and neovascular activity.

The effect of long-term hemodialysis on diabetic retinopathy observed by swept-source optical coherence tomography angiography

BackgroundDiabetes can cause chronic microvascular complications such as diabetic retinopathy (DR) and diabetic nephropathy (DN). DR and DN can lead to or exacerbate diabetic macular edema (DME). Hemodialysis (HD) is the main treatment method for patients with end-stage kidney disease (ESKD) secondary to DN.PurposeThe aim of this prospective cohort study was to determine the immediate effect of single HD session on retinal and choroidal thickness in DR patients with ESKD and the features of DR and the prevalence of DME in these patients who have received long-term HD.MethodsEighty-five eyes of 44 DR patients with ESKD who underwent long-term HD were examined by swept-source optical coherence tomography angiography (SS-OCTA). Based on OCTA images, the characteristics of DR and the prevalence of DME in these patients were analyzed. Changes in central retinal thickness (CRT), central retinal volume (CRV), subfoveal choroidal thickness (SFCT) and subfoveal choroidal volume (SFCV) within 30 min before and after single HD session were compared. CRT, CRV, SFCT and SFCV were compared before single HD session and before the next single HD session.ResultsThere was no significant difference in the average CRT (251.69 ± 39.21 μm vs. 251.46 ± 39.38 μm, P = 0.286) or CRV (0.15 ± 0.62 μm vs. 0.15 ± 0.63 μm, P = 0.324) between before and after single HD session. After single HD session, SFCT (243.11 ± 77.15 μm vs. 219.20 ± 72.84 μm, P < 0.001) and SFCV (0.15 ± 0.10 μm vs. 0.13 ± 0.90 μm, P < 0.001) significantly decreased. There was no statistically significant difference in CRT (251.69 ± 39.21 μm vs. 251.11 ± 38.47 μm, P = 0.206), CRV (0.15 ± 0.62 μm vs. 0.15 ± 0.61 μm, P = 0.154), SFCT (243.11 ± 77.15 μm vs. 245.41 ± 76.23 μm, P = 0.108), or SFCV (0.15 ± 0.10 μm vs. 0.16 ± 0.10 μm, P = 0.174) before HD and before the next single HD session. On en face OCTA images, eighty-five eyes (100%) had retinal nonperfusion areas, foveal avascular zone (FAZ) enlargement, and abnormal retinal microvasculature. Based on cross-sectional OCTA images, retinal neovascularization (RNV) was confirmed in 42 eyes (49.41%), and intraretinal microvascular abnormalities (IRMAs) were detected in 85 eyes (100%). Seventeen eyes (20%) still had DME, all of which were cystoid macular edema (CME). Among eyes with DME, the epiretinal membrane (ERM) was present in 7 eyes (8.24%).ConclusionsFor DR patients with ESKD who have undergone long-term HD, the choroidal thickness still changes significantly before and after single HD session, which may be related to short-term effects such as reduced blood volume and plasma osmotic pressure caused by single HD session. Although macular features seem to have stabilized in DR patients undergoing long-term dialysis, the DR of patients with ESKD should still be given attention.

VMseg: Using spatial variance to automatically segment retinal non-perfusion on OCT-angiography.

To develop and test VMseg, a new image processing algorithm performing automatic segmentation of retinal non-perfusion in widefield OCT-Angiography images, in order to estimate the non-perfusion index in diabetic patients. We included diabetic patients with severe non-proliferative or proliferative diabetic retinopathy. We acquired images using the PlexElite 9000 OCT-A device with a photomontage of 5 images of size 12 x 12 mm. We then developed VMseg, a Python algorithm for non-perfusion detection, which binarizes a variance map calculated through convolution and morphological operations. We used 70% of our data set (development set) to fine-tune the algorithm parameters (convolution and morphological parameters, binarization thresholds) and evaluated the algorithm performance on the remaining 30% (test set). The obtained automatic segmentations were compared to a ground truth corresponding to manual segmentation from a retina expert and the inference processing time was estimated. We included 51 eyes of 30 patients (27 severe non-proliferative, 24 proliferative diabetic retinopathy). Using the optimal parameters found on the development set to tune the algorithm, the mean dice for the test set was 0.683 (sd = 0.175). We found a higher dice coefficient for images with a higher area of retinal non-perfusion (rs = 0.722, p < 10-4). There was a strong correlation (rs = 0.877, p < 10-4) between VMseg estimated non-perfusion indexes and indexes estimated using the ground truth segmentation. The Bland-Altman plot revealed that 3 eyes (5.9%) were significantly under-segmented by VMseg. We developed VMseg, an automatic algorithm for retinal non-perfusion segmentation on 12 x 12 mm OCT-A widefield photomontages. This simple algorithm was fast at inference time, segmented images in full-resolution and for the OCT-A format, was accurate enough for automatic estimation of retinal non-perfusion index in diabetic patients with diabetic retinopathy.

Quantitative Volumetric Analysis of Retinal Ischemia with an Oxygen Diffusion Model and OCT Angiography

PurposeRetinal ischemia is a major feature of diabetic retinopathy (DR). Traditional nonperfused areas measured by optical coherence tomography angiography (OCTA) measure blood supply but not ischemia. We propose a novel 3-dimensional (3D) quantitative method to derive ischemia measurements from OCTA data. DesignCross-sectional study. ParticipantsWe acquired 223 macular OCTA volumes from 33 healthy eyes, 33 diabetic eyes without retinopathy, 7 eyes with non-referable DR, 17 eyes with referable but non-vision-threatening DR, and 133 eyes with vision-threatening DR. MethodsEach eye was scanned using a spectral-domain OCTA system (Avanti RTVue-XR, Visionix/Optovue, Inc) with 1.6 mm scan depth in a 3 × 3-mm region (640 × 304 × 304 voxels) centered on the fovea. For each scanned OCTA volume, a custom algorithm removed flow projection artifacts. We then enhanced, binarized, and skeletonized the vasculature in each OCTA volume and generated a 3D oxygen tension map using a zero-order kinetics oxygen diffusion model. Each volume was scaled to the average retina thickness in healthy controls after foveal registration and flattening of the Bruch membrane. Finally, we extracted 3D ischemia maps by comparison with a reference map established from scans of healthy eyes using the same processing. To assess the ability of the ischemia maps to grade DR severity, we constructed receiver-operating characteristic (ROC) curves for diagnosing diabetes, referable DR, and vision-threatening DR. Main outcome measuresSpearman correlation coefficient and area under ROC curve (AUC) were used to quantify the ability of the ischemia maps to DR. ResultsThe ischemia maps showed that the ischemic tissues were at or near pathologically non-perfused areas, but not the normally non-vascular tissue, such as the foveal avascular zone. We found multiple novel metrics, including inferred 3D-oxygen tension, ischemia index, and ischemic volume ratio, were strongly correlated with DR severity. The AUCs of ischemia index measured were 0.95 for diabetes, 0.89 for DR, 0.88 for referable DR, and 0.85 for vision threatening DR. ConclusionsA quantitative method to infer 3D oxygen tension and ischemia using OCTA in diabetic eyes can identify ischemic tissue that are more specific to pathologic changes in DR.

Multi-Plexus Nonperfusion Area Segmentation in Widefield OCT Angiography Using a Deep Convolutional Neural Network.

To train and validate a convolutional neural network to segment nonperfusion areas (NPAs) in multiple retinal vascular plexuses on widefield optical coherence tomography angiography (OCTA). This cross-sectional study included 202 participants with a full range of diabetic retinopathy (DR) severities (diabetes mellitus without retinopathy, mild to moderate non-proliferative DR, severe non-proliferative DR, and proliferative DR) and 39 healthy participants. Consecutive 6 × 6-mm OCTA scans at the central macula, optic disc, and temporal region in one eye from 202 participants in a clinical DR study were acquired with a 70-kHz OCT commercial system (RTVue-XR). Widefield OCTA en face images were generated by montaging the scans from these three regions. A projection-resolved OCTA algorithm was applied to remove projection artifacts at the voxel scale. A deep convolutional neural network with a parallel U-Net module was designed to detect NPAs and distinguish signal reduction artifacts from flow deficits in the superficial vascular complex (SVC), intermediate capillary plexus (ICP), and deep capillary plexus (DCP). Expert graders manually labeled NPAs and signal reduction artifacts for the ground truth. Sixfold cross-validation was used to evaluate the proposed algorithm on the entire dataset. The proposed algorithm showed high agreement with the manually delineated ground truth for NPA detection in three retinal vascular plexuses on widefield OCTA (mean ± SD F-score: SVC, 0.84 ± 0.05; ICP, 0.87 ± 0.04; DCP, 0.83 ± 0.07). The extrafoveal avascular area in the DCP showed the best sensitivity for differentiating eyes with diabetes but no retinopathy (77%) from healthy controls and for differentiating DR by severity: DR versus no DR, 77%; referable DR (rDR) versus non-referable DR (nrDR), 79%; vision-threatening DR (vtDR) versus non-vision-threatening DR (nvtDR), 60%. The DCP also showed the best area under the receiver operating characteristic curve for distinguishing diabetes from healthy controls (96%), DR versus no DR (95%), and rDR versus nrDR (96%). The three-plexus-combined OCTA achieved the best result in differentiating vtDR and nvtDR (81.0%). A deep learning network can accurately segment NPAs in individual retinal vascular plexuses and improve DR diagnostic accuracy. Using a deep learning method to segment nonperfusion areas in widefield OCTA can potentially improve the diagnostic accuracy of diabetic retinopathy by OCT/OCTA systems.

Quantitative Biomarkers of Diabetic Retinopathy Using Ultra-Widefield Fluorescein Angiography.

Diabetic retinopathy (DR) is a leading cause of blindness. Retinal imaging is an important tool to monitor the progression of DR. While seven-standard retinal fields are the traditional method for evaluating DR, ultra-widefield (UWF) imaging allows for improved visualization of peripheral areas of nonperfusion (NP) and neovascularization (NV), which could be used as biomarkers to monitor and predict progression of DR. A retrospective, cross-sectional study was conducted on 651 eyes from 363 patients diagnosed with type 1 or type 2 diabetes who received UWF-FA over 10 years. Fluorescein Angiography (FA) images were segmented, and surface areas of NP and NV were analyzed using multivariate regression to determine if biomarkers of DR and DR severity are associated with increasing areas of NP and NV. Each additional year with a diagnosis of DR was associated with a 10.75 mm2 increase in the total NP (95% CI, 1.94-19.56; P = 0.02) and 7.87 mm2 increase in NP far-periphery (95% CI, 1.62-14.13; P = 0.01). A one-unit change in severity as defined by the Early Treatment of Diabetic Retinopathy Study (ETDRS) classification was associated with a 25.75 mm2 increase in total NP (95% CI, 11.16-40.33; P = 0.001), a 13.15 mm2 increase in mid-periphery NP (95% CI, 6.93-19.38; P < 0.0001), and a 12.29 mm2 increase in far-periphery NP (95% CI, 3.62-20.97; P = 0.01). Biomarkers identified through UWF imaging such as total and regional areas of NP can be used to monitor and predict the progression of DR. This may provide a quantitative method for prognostication in patients with DR.

Deep learning segmentation of non-perfusion area from color fundus images and AI-generated fluorescein angiography

The non-perfusion area (NPA) of the retina is an important indicator in the visual prognosis of patients with branch retinal vein occlusion (BRVO). However, the current evaluation method of NPA, fluorescein angiography (FA), is invasive and burdensome. In this study, we examined the use of deep learning models for detecting NPA in color fundus images, bypassing the need for FA, and we also investigated the utility of synthetic FA generated from color fundus images. The models were evaluated using the Dice score and Monte Carlo dropout uncertainty. We retrospectively collected 403 sets of color fundus and FA images from 319 BRVO patients. We trained three deep learning models on FA, color fundus images, and synthetic FA. As a result, though the FA model achieved the highest score, the other two models also performed comparably. We found no statistical significance in median Dice scores between the models. However, the color fundus model showed significantly higher uncertainty than the other models (p < 0.05). In conclusion, deep learning models can detect NPAs from color fundus images with reasonable accuracy, though with somewhat less prediction stability. Synthetic FA stabilizes the prediction and reduces misleading uncertainty estimates by enhancing image quality.

Glaucoma detection using non-perfused areas in OCTA

Multiple ophthalmic diseases lead to decreased capillary perfusion that can be visualized using optical coherence tomography angiography images. To quantify the decrease in perfusion, past studies have often used the vessel density, which is the percentage of vessel pixels in the image. However, this method is often not sensitive enough to detect subtle changes in early pathology. More recent methods are based on quantifying non-perfused or intercapillary areas between the vessels. These methods rely upon the accuracy of vessel segmentation, which is a challenging task and therefore a limiting factor for reliability. Intercapillary areas computed from perfusion-distance measures are less sensitive to errors in the vessel segmentation since the distance to the next vessel is only slightly changing if gaps are present in the segmentation. We present a novel method for distinguishing between glaucoma patients and healthy controls based on features computed from the probability density function of these perfusion-distance areas. The proposed approach is evaluated on different capillary plexuses and outperforms previously proposed methods that use handcrafted features for classification. Moreover the results of the proposed method are in the same range as the ones of convolutional neural networks trained on the raw input images and is therefore a computationally efficient, simple to implement and explainable alternative to deep learning-based approaches.

Intravoxel incoherent motion (IVIM)-derived perfusion fraction mapping for the visual evaluation of MR-guided high intensity focused ultrasound (MR-HIFU) ablation of uterine fibroids

Background A method for periprocedural contrast agent-free visualization of uterine fibroid perfusion could potentially shorten magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) treatment times and improve outcomes. Our goal was to test feasibility of perfusion fraction mapping by intravoxel incoherent motion (IVIM) modeling using diffusion-weighted MRI as method for visual evaluation of MR-HIFU treatment progression. Methods Conventional and T2-corrected IVIM-derived perfusion fraction maps were retrospectively calculated by applying two fitting methods to diffusion-weighted MRI data (b = 0, 50, 100, 200, 400, 600 and 800 s/mm2 at 1.5 T) from forty-four premenopausal women who underwent MR-HIFU ablation treatment of uterine fibroids. Contrast in perfusion fraction maps between areas with low perfusion fraction and surrounding tissue in the target uterine fibroid immediately following MR-HIFU treatment was evaluated. Additionally, the Dice similarity coefficient (DSC) was calculated between delineated areas with low IVIM-derived perfusion fraction and hypoperfusion based on CE-T1w. Results Average perfusion fraction ranged between 0.068 and 0.083 in areas with low perfusion fraction based on visual assessment, and between 0.256 and 0.335 in surrounding tissues (all p < 0.001). DSCs ranged from 0.714 to 0.734 between areas with low perfusion fraction and the CE-T1w derived non-perfused areas, with excellent intraobserver reliability of the delineated areas (ICC 0.97). Conclusion The MR-HIFU treatment effect in uterine fibroids can be visualized using IVIM perfusion fraction mapping, in moderate concordance with contrast enhanced MRI. IVIM perfusion fraction mapping has therefore the potential to serve as a contrast agent-free imaging method to visualize the MR-HIFU treatment progression in uterine fibroids.

The clinical evaluation of a widefield lens to expand the field of view in optical coherence tomography (OCT-A)

This study aimed to evaluate the clinical benefits of incorporating a widefield lens (WFL) in optical coherence tomography angiography (OCT-A) in patients with retinal vascular diseases in comparison to standard single-shot OCT-A scans. Sixty patients with retinal vascular diseases including diabetic retinopathy (DR) and retinal vein occlusion (RVO) were recruited. OCT-A imaging (PlexElite 9000) with and without WFL was performed in randomized order. The assessment included patient comfort, time, field of view (FoV), image quality and pathology detection. Statistical analysis included paired t-tests, Mann–Whitney U-tests and Bonferroni correction for multiple tests, with inter-grader agreement using the kappa coefficient. Using a WFL did not lead to statistically significant differences in DR and RVO group test times. Patient comfort remained high, with similar responses for WFL and non-WFL measurements. The WFL notably expanded the scan field (1.6× FoV increase), enhancing peripheral retinal visibility. However, image quality varied due to pathology and eye dominance, affecting the detection of peripheral issues in RVO and DR cases. The use of a WFL widens the scan field, aiding vascular retinal disease imaging with minor effects on comfort, time, and image quality. Further enhancements are needed for broader view angles, enabling improved quantification of non-perfused areas and more reliable peripheral proliferation detection.