Retinal Optical Coherence Tomography Angiography Research Articles

SFNet: Spatial and Frequency Domain Networks for Wide-Field OCT Angiography Retinal Vessel Segmentation.

Automatic segmentation of blood vessels in fundus images is important to assist ophthalmologists in diagnosis. However, automatic segmentation for Optical Coherence Tomography Angiography (OCTA) blood vessels has not been fully investigated due to various difficulties, such as vessel complexity. In addition, there are only a few publicly available OCTA image data sets for training and validating segmentation algorithms. To address these issues, we constructed a wild-field retinal OCTA segmentation data set, the Retinal Vessels Images in OCTA (REVIO) dataset. Second, we propose a new retinal vessel segmentation network based on spatial and frequency domain networks (SFNet). The proposed model are tested on three benchmark data sets including REVIO, ROSE and OCTA-500. The experimental results show superior performance on segmentation tasks compared to the representative methods.

A pilot study : retinal sensitivity change in neovascular age-related macular degeneration patients with better baseline visual acuity

This study evaluated changes in retinal sensitivity (RS) during aflibercept treatment in neovascular age-related macular degeneration (nAMD) patients with good vision. Treatment-naive nAMD patients with visual acuity better than 20/40 were treated with an aflibercept loading regiment, and RS was measured using the MAIA microperimetry device. The study examined RS differences based on visit, region, adjacent local pathology, outer retinal changes and optical coherence tomography angiography (OCTA) data were investigated. Twelve patients completed the protocol. Mean RS improved from 17.9 (3.9) µm at baseline to 20.4 (4.7) µm at final visit, while best-corrected visual acuity (BCVA) did not change. (P = 0.041) RS at baseline is worst in the presence of intraretinal fluid (IRF) and improved after treatment for all retinal pathologies except IRF. RS improvement occurred even with initial outer retinal damage. A Linear mixed model showed subretinal hyperreflective material, baseline IRF height, outer retinal integrity, fibrovascular pigment epithelial detachment height, and local choroidal vascular index as factors associated with RS. In conclusion, RS improved with aflibercept treatment in nAMD eyes with good initial visual acuity, despite no change in BCVA, except when IRF was present.

Artificial intelligence-based prediction of neurocardiovascular risk score from retinal swept-source optical coherence tomography–angiography

The recent rise of artificial intelligence represents a revolutionary way of improving current medical practices, including cardiovascular (CV) assessment scores. Retinal vascular alterations may reflect systemic processes such as the presence of CV risk factors. The value of swept-source retinal optical coherence tomography–angiography (SS OCT-A) imaging is significantly enhanced by image analysis tools that provide rapid and accurate quantification of vascular features. We report on the interest of using machine-learning (ML) and deep-learning (DL) models for CV assessment from SS OCT-A microvasculature imaging. We assessed the accuracy of ML and DL algorithms in predicting the CHA2DS2-VASc neurocardiovascular score based on SS OCT-A retinal images of patients from the open-source RASTA dataset. The ML and DL models were trained on data from 491 patients. The ML models tested here achieved good performance with area under the curve (AUC) values ranging from 0.71 to 0.96. According to a classification into two neurocardiovascular risk groups, the EfficientNetV2-B3, a well suited DL model for retinal OCT-A images, predicted risk correctly in 68% of cases, with a mean absolute error (MAE) of approximately 0.697. Our models enable a confident prediction of the CHA2DS2-VASc score from SS OCT-A imaging, which could be a useful tool contributing to the assessment of neurocardiovascular profiles in the future.

Associations of Retinal Vessel Geometry and Optical Coherence Tomography Angiography Metrics With Choroidal Metrics in Diabetic Retinopathy.

To elucidate the mechanism underlying changes in choroidal metrics (choroidal thickness [CT], choroidal vascularity index [CVI], and choriocapillaris [CC] flow deficit [FD]) observed in diabetic retinopathy (DR) and examine the association of choroidal metrics with both retinal vessel geometry and optical coherence tomography angiography (OCTA) metrics. Overall, 133 eyes of 133 patients were analyzed retrospectively. Retinal vessel geometry parameters were assessed using semiautomated software. The OCTA metrics and CT were calculated using automated algorithms provided by the manufacturer, whereas the CVI and CC-FD were calculated using ImageJ software from the binarized choroid B-scan image and the CC slab provided by the manufacturer, respectively. To assess the associations among choroidal metrics, retinal vessel geometry, and OCTA metrics, multivariable regression analyses were performed while controlling for clinical features and DR severity. In the multivariable linear regression analysis, CT (β = -399.84; P = 0.014) and CVI (β = -2.34; P = 0.021) showed significant associations with the arteriole-venule ratio, which is a ratio of central retinal arteriolar equivalent caliber with respect to central retinal venular equivalent caliber. The CC-FD showed a significant association with the fractal dimension of retinal arteriolar network (β = -2.90; P = 0.040). In contrast, the OCTA metrics showed no significant association with the choroidal metrics. The CT, CVI, and CC-FD in patients with DR were associated with retinal arteriolar geometry parameters rather than OCTA metrics, which indicates an association between choroidal changes and hemodynamic alterations in retinal arterioles and venules.

Association of Retinal Biomarkers With the Subtypes of Ischemic Stroke and an Automated Classification Model.

Retinal microvascular changes are associated with ischemic stroke, and optical coherence tomography angiography (OCTA) is a potential tool to reveal the retinal microvasculature. We investigated the feasibility of using the OCTA image to automatically identify ischemic stroke and its subtypes (i.e. lacunar and non-lacunar stroke), and exploited the association of retinal biomarkers with the subtypes of ischemic stroke. Two cohorts were included in this study and a total of 1730 eyes from 865 participants were studied. A deep learning model was developed to discriminate the subjects with ischemic stroke from healthy controls and to distinguish the subtypes of ischemic stroke. We also extracted geometric parameters of the retinal microvasculature at different retinal layers to investigate the correlations. Superficial vascular plexus (SVP) yielded the highest areas under the receiver operating characteristic curve (AUCs) of 0.922 and 0.871 for the ischemic stroke detection and stroke subtypes classification, respectively. For external data validation, our model achieved an AUC of 0.822 and 0.766 for the ischemic stroke detection and stroke subtypes classification, respectively. When parameterizing the OCTA images, we showed individuals with ischemic strokes had increased SVP tortuosity (B = 0.085, 95% confidence interval [CI] = 0.005-0.166, P = 0.038) and reduced FAZ circularity (B = -0.212, 95% CI = -0.42 to -0.005, P = 0.045); non-lacunar stroke had reduced SVP FAZ circularity (P = 0.027) compared to lacunar stroke. Our study demonstrates the applicability of artificial intelligence (AI)-enhanced OCTA image analysis for ischemic stroke detection and its subtypes classification. Biomarkers from retinal OCTA images can provide useful information for clinical decision-making and diagnosis of ischemic stroke and its subtypes.

Advanced OCTA imaging segmentation: Unsupervised, non-linear retinal vessel detection using modified self-organizing maps and joint MGRF modeling

Background and Objective:This paper proposes a fully automated and unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs Random Field (MGRF) to detect the vascular system from retinal Optical Coherence Tomography Angiography (OCTA) images, which is a critical step in developing Computer-Aided Diagnosis (CAD) systems for detecting retinal diseases. Methods:Using a new probabilistic model based on a Linear Combination of Discrete Gaussian (LCDG), the first level models the appearance of OCTA images and their spatially smoothed images. The parameters of the LCDG model are estimated using a modified Expectation Maximization (EM) algorithm. The second level models the maps of OCTA images, including the vascular system and other retina tissues, using MGRF with analytically estimated parameters from the input images. The proposed segmentation approach employs modified self-organizing maps as a MAP-based optimizer maximizing the joint likelihood and handles the Joint MGRF model in a new, unsupervised way. This approach deviates from traditional stochastic optimization approaches and leverages non-linear optimization to achieve more accurate segmentation results. Results:The proposed segmentation framework is evaluated quantitatively on a dataset of 204 subjects. Achieving 0.92 ± 0.03 Dice similarity coefficient, 0.69 ± 0.25 95-percentile bidirectional Hausdorff distance, and 0.93 ± 0.03 accuracy, confirms the superior performance of the proposed approach. Conclusions:The conclusions drawn from the study highlight the superior performance of the proposed unsupervised and fully automated segmentation approach in detecting the vascular system from OCTA images. This approach not only deviates from traditional methods but also achieves more accurate segmentation results, demonstrating its potential in aiding the development of CAD systems for detecting retinal diseases.

Repeatability of retinal and choroidal optical coherence tomography angiography indices in healthy children and young adults.

To evaluate the repeatability of retinal and choroidal optical coherence tomography angiography (OCT-A) indices among healthy children and compare it to healthy young adults. This prospective study captured 3 mm × 3 mm and 6 mm × 6 mm macular OCT-A scans including superficial and deep retinal layers, choriocapillaris and deep choroid over two visits, 1 week apart at approximately the same time of day, for 22 healthy adults (18-30 years) and 21 children (6-15 years). Magnification and projection-artefact corrected indices extracted using a custom image analysis program and individual biometry were compared between visits using Bland-Altman analysis and intraclass correlation (ICC). Retinal indices included foveal avascular zone metrics, perfusion and vessel density and choroidal indices included choriocapillaris flow deficit metrics and deep choroid perfusion density, in the foveal, parafoveal and perifoveal regions. Repeatability between adults and children was compared with F-test. Bland-Altman analysis showed that the mean differences between repeated OCT-A indices were not significantly different from zero for either of the zones, layers and scan sizes in the two age groups (p > 0.05) except for foveal vessel density and foveal avascular zone perimeter (p = 0.04 for both) of 6-mm-deep retinal layer scans. The ICC ranged between 0.67 and 0.99. Significantly higher variability between visits (p < 0.05) in the indices was noted among adults than children, especially for choroidal indices of larger scan size. The retinal and choroidal OCT-A indices in the foveal, parafoveal and perifoveal zones were repeatable in healthy children except for the foveal vessel density and foveal avascular zone perimeter of the 6-mm-deep retinal layer, which exhibited statistically borderline differences between visits. The adult group showed more variability between visits compared to children, especially in the larger scan size for choroidal OCT-A indices.

Towards standardising retinal OCT angiography image analysis with open-source toolbox OCTAVA

Quantitative assessment of retinal microvasculature in optical coherence tomography angiography (OCTA) images is important for studying, diagnosing, monitoring, and guiding the treatment of ocular and systemic diseases. However, the OCTA user community lacks universal and transparent image analysis tools that can be applied to images from a range of OCTA instruments and provide reliable and consistent microvascular metrics from diverse datasets. We present a retinal extension to the OCTA Vascular Analyser (OCTAVA) that addresses the challenges of providing robust, easy-to-use, and transparent analysis of retinal OCTA images. OCTAVA is a user-friendly, open-source toolbox that can analyse retinal OCTA images from various instruments. The toolbox delivers seven microvascular metrics for the whole image or subregions and six metrics characterising the foveal avascular zone. We validate OCTAVA using images collected by four commercial OCTA instruments demonstrating robust performance across datasets from different instruments acquired at different sites from different study cohorts. We show that OCTAVA delivers values for retinal microvascular metrics comparable to the literature and reduces their variation between studies compared to their commercial equivalents. By making OCTAVA publicly available, we aim to expand standardised research and thereby improve the reproducibility of quantitative analysis of retinal microvascular imaging. Such improvements will help to better identify more reliable and sensitive biomarkers of ocular and systemic diseases.

Correlations between Retinal Microvascular Parameters and Clinical Parameters in Young Patients with Type 1 Diabetes Mellitus: An Optical Coherence Tomography Angiography Study

Objectives: In the current study, we investigated the correlations between retinal microvascular parameters using optical coherence tomography angiography (OCTA) and clinical parameters for a group of 69 young patients with type 1 diabetes mellitus (T1DM). Materials and Methods: This retrospective, exploratory study enrolled 69 patients between 5 years old and 30 years old who met the inclusion criteria. All the study participants underwent a comprehensive ophthalmic examination and OCTA scans for the evaluation of the retinal microcirculation. The retinal OCTA parameters were correlated with the following clinical parameters: the patient’s age at the onset of the disease, the duration of T1DM, the BMI at the time of enrollment in the study, the HbA1C values at onset, the mean values of HbA1C over the period of monitoring the disease and the degree of DKA at onset. Results: For the study group, the foveal avascular zone (FAZ) area and perimeter correlated positively with the mean value of HbA1C (Pearson correlation, Sig.2-Tailed Area: 0.044; perimeter: 0.049). The total vessel density in the superficial capillary plexus (SCP) correlated negatively with the duration of T1DM, based on the superior and inferior analyzed areas (Spearman correlation, Sig.2-Tailed SCP in total region: 0.002; SCP in the superior region: 0.024; SCP in the inferior region: 0.050). The foveal thickness also correlated negatively with the levels of diabetic ketoacidosis (DKA) at onset (Spearman correlation, Sig.2-Tailed: 0.034) and the levels of HbA1C at onset (Spearman correlation, Sig.2-Tailed: 0.047). Further on, the study patients were distributed into two groups according to the duration of the disease: group 1 included 32 patients with a duration of T1DM of less than 5 years, and group 2 included 37 patients with a duration of T1DM of more than 5 years. Independent t-tests were used to compare the OCTA retinal parameters for the two subgroups. While the FAZ-related parameters did not show significant statistical differences between the two groups, the vessel densities in both the SCP and DCP were significantly lower in group 2. Conclusions: Our data suggest that specific alterations in OCTA imaging biomarkers correlate with various clinical parameters: the FAZ area and perimeter increase with higher mean values of HbA1C, leading to poor metabolic control. Moreover, the SCP total vessel density decreases as the duration of T1DM increases. Regarding the vessel densities in the SCP and the DCP, they decrease with a duration of the disease of more than 5 years.

Assessment of Retinal Microangiopathy in Patients with Balkan Endemic Nephropathy Using Optical Coherence Tomography Angiography-A Pilot Study.

Background and Objectives: It is well known that alterations in microvascular structure and function contribute to the development of ocular, renal, and cardiovascular diseases. Accordingly, the presence of fundus vascular changes in patients suffering from chronic kidney disease (CKD) and Balkan endemic nephropathy (BEN) may provide information of prognostic value regarding the progression of renal disease. This study aimed to examine the associations between clinical characteristics and retinal optical coherence tomography angiography (OCTA) parameters in patients with BEN and compare them with those in CKD. Materials and Methods: This pilot study, conducted from March 2021 to April 2022, included 63 patients who were divided into two groups: the first group consisted of 29 patients suffering from BEN, and the second was a control group of 34 patients with CKD. Demographic, laboratory, clinical, and medication data were noted for all the patients included in this study. Each eye underwent OCT angiography, and the results were interpreted in accordance with the practical guide for the interpretation of OCTA findings. Results: Statistically significantly higher levels of total serum protein and triglycerides were recorded in the BEN group than in the CKD group, while the level of HDL cholesterol was lower. Based on the performed urinalysis, statistically significantly higher values of total protein and creatinine were detected in patients with CKD compared to the BEN group. It was demonstrated that the OCTA vascular plexus density of certain parts of the retina was in significant association with systolic and diastolic blood pressure, creatinine clearance, urinary creatinine, total cholesterol, diabetes mellitus type 2, age, body mass index, total serum and urinary protein, sCRP, and diuretic and antihypertensive treatment. Conclusions: In comparison with CKD, BEN leads to more significant disturbances in retinal vasculature density.

Optimizing criterion to reduce the variability between observers in the delimitation of the foveal avascular zone in diabetic patients

Aims/Purpose: To reduce the variability when performing manual segmentation of the foveal avascular zone (FAZ) on retinal optical coherence tomography angiography (OCTA) images, and to find a new accurate FAZ delimitation criterion.Methods: Seventy‐three eyes from healthy subjects, 40 eyes from Type 1 diabetes mellitus (DM1) patients without diabetic retinopathy (DR) and 54 eyes from Type 2 diabetes mellitus (DM2) patients with moderate DR and without diabetic macular oedema (DME) were evaluated using OCTA. A manual FAZ segmentation was performed by different observers of each OCTA image of the superficial (SCP) and deep capillary plexuses (DCP). After comparing the results, a new criterion was established to reduce the variability in the segmentations. The FAZ area and circularity were also studied.Results: The novel criterion produces smaller areas (closer to the real FAZ), as well as a diminution of the standard deviation values, with a factor of 0.5, with lower variability than the different criteria of the explorers in both plexuses for the three groups. This was particularly notorious for the DM2 group with damaged retinas, where it was very difficult to define the FAZ limits. The acircularity values were also slightly reduced with the final criterion in all groups. In the DM2 group a significant reduction in the acircularity mean value of both plexuses was obtained. Looking for a relationship between the FAZ area and the acircularity, we found slightly higher values of acircularity for smaller FAZ areas. The number of extremal values was much higher for the initial method, and when the DCP was evaluated.Conclusions: The implementation of a new criterion for FAZ segmentation produced more consistent results with less variability among observers.

Bilateral, Simultaneous Central Serous Chorioretinopathy in Association With Oral Contraception Use.

This report describes a case of bilateral, simultaneous central serous chorioretinopathy (CSCR) in a young woman on oral contraceptive pills (OCP). A 21-year-old woman with a negative past medical history presented with sudden onset of bilateral decreased vision shortly after starting OCP. Comprehensive ocular examination revealed bilateral central serous chorioretinopathy (CSCR), confirmed on retinal optical coherence tomography (OCT) and intravenous fluorescein angiography. The patient was instructed to discontinue OCP, and three weeks later, there was complete resolution of the visual symptoms and of the bilateral serous retinal detachments, documented on OCT. [Ophthalmic Surg Lasers Imaging Retina 2024;55:96-99.].

MR2-Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance.

Optical coherence tomography angiography (OCTA) plays a crucial role in quantifying and analyzing retinal vascular diseases. However, the limited field of view (FOV) inherent in most commercial OCTA imaging systems poses a significant challenge for clinicians, restricting the possibility to analyze larger retinal regions of high resolution. Automatic stitching of OCTA scans in adjacent regions may provide a promising solution to extend the region of interest. However, commonly-used stitching algorithms face difficulties in achieving effective alignment due to noise, artifacts and dense vasculature present in OCTA images. To address these challenges, we propose a novel retinal OCTA image stitching network, named MR2-Net, which integrates multi-scale representation learning and dynamic location guidance. In the first stage, an image registration network with a progressive multi-resolution feature fusion is proposed to derive deep semantic information effectively. Additionally, we introduce a dynamic guidance strategy to locate the foveal avascular zone (FAZ) and constrain registration errors in overlapping vascular regions. In the second stage, an image fusion network based on multiple mask constraints and adjacent image aggregation (AIA) strategies is developed to further eliminate the artifacts in the overlapping areas of stitched images, thereby achieving precise vessel alignment. To validate the effectiveness of our method, we conduct a series of experiments on two delicately constructed datasets, i.e., OPTOVUE-OCTA and SVision-OCTA. Experimental results demonstrate that our method outperforms other image stitching methods and effectively generates high-quality wide-field OCTA images, achieving a structural similarity index (SSIM) score of 0.8264 and 0.8014 on the two datasets, respectively.

One-Shot Learning for Optical Coherence Tomography Angiography Vessel Segmentation Based on Multi-Scale U2-Net

Vessel segmentation in optical coherence tomography angiography (OCTA) is crucial for the detection and diagnosis of various eye diseases. However, it is hard to distinguish intricate vessel morphology and quantify the density of blood vessels due to the large variety of vessel sizes, significant background noise, and small datasets. To this end, a retinal angiography multi-scale segmentation network, integrated with the inception and squeeze-and-excitation modules, is proposed to address the above challenges under the one-shot learning paradigm. Specifically, the inception module extends the receptive field and extracts multi-scale features effectively to handle diverse vessel sizes. Meanwhile, the squeeze-and-excitation module modifies channel weights adaptively to improve the vessel feature extraction ability in complex noise backgrounds. Furthermore, the one-shot learning paradigm is adapted to alleviate the problem of the limited number of images in existing retinal OCTA vascular datasets. Compared with the classic U2-Net, the proposed model gains improvements in the Dice coefficient, accuracy, precision, recall, and intersection over union by 3.74%, 4.72%, 8.62%, 4.87%, and 4.32% respectively. The experimental results demonstrate that the proposed one-shot learning method is an effective solution for retinal angiography image segmentation.

Changes in retinal and choroidal optical coherence tomography angiography indices among young adults and children over 1 year

ABSTRACT Clinical relevance Optical coherence tomography angiography (OCT-A) indices are likely to change across time and optometrists should be aware of the variability expected during childhood development and in healthy adults. Background Cross-sectional studies have shown that OCT-A indices are associated with age in adults and children. The aim of this study is to investigate longitudinal changes in retinal and choroidal OCT-A indices over 1 year among healthy children and young adults. Methods This prospective longitudinal study captured macular OCT-A and OCT scans, and biometry measures at baseline and 1-year follow-up for 22 adults (18–30 years; −6.87 to +0.37 D) and 21 children (6–15 years; −5.75 to +0.25 D). Superficial and deep retinal layer, choriocapillaris and deep choroidal en face OCT-A images were analysed to extract magnification-corrected vascular indices in foveal, parafoveal and perifoveal regions. The retinal indices included foveal avascular zone metrics, perfusion, and vessel density. Flow deficit number, size, and density were extracted from choriocapillaris and perfusion density from deep choroid. Associations between annual changes in the OCT-A indices and axial length and baseline refraction were also studied. Results Among children, significant reductions were noted only in parafoveal superficial retinal and foveal and perifoveal deep retinal layer indices over 1 year (p < 0.05). Choroidal OCT-A indices in children and both retinal and choroidal OCT-A indices in adults did not show significant changes. Myopia was associated with a larger reduction in the perifoveal retinal OCT-A indices in children, and with increases in sub-foveal and sub-parafoveal choroidal indices in adults. There were associations between OCT-A indices and axial length changes but differently in adults and children. Conclusions Significant changes were noted in retinal OCT-A indices over 1 year among children but not adults. In comparison, choroidal OCT-A indices in adults and children showed a stable morphology over this period of time.

The OSCAR-MP Consensus Criteria for Quality Assessment of Retinal Optical Coherence Tomography Angiography.

Optical coherence tomography angiography (OCTA) is a noninvasive high-resolution imaging technique for assessing the retinal vasculature and is increasingly used in various ophthalmologic, neuro-ophthalmologic, and neurologic diseases. To date, there are no validated consensus criteria for quality control (QC) of OCTA. Our study aimed to develop criteria for OCTA quality assessment. To establish criteria through (1) extensive literature review on OCTA artifacts and image quality to generate standardized and easy-to-apply OCTA QC criteria, (2) application of OCTA QC criteria to evaluate interrater agreement, (3) identification of reasons for interrater disagreement, revision of OCTA QC criteria, development of OCTA QC scoring guide and training set, and (4) validation of QC criteria in an international, interdisciplinary multicenter study. We identified 7 major aspects that affect OCTA quality: (O) obvious problems, (S) signal strength, (C) centration, (A) algorithm failure, (R) retinal pathology, (M) motion artifacts, and (P) projection artifacts. Seven independent raters applied the OSCAR-MP criteria to a set of 40 OCTA scans from people with MS, Sjogren syndrome, and uveitis and healthy individuals. The interrater kappa was substantial (κ 0.67). Projection artifacts were the main reason for interrater disagreement. Because artifacts can affect only parts of OCTA images, we agreed that prior definition of a specific region of interest (ROI) is crucial for subsequent OCTA quality assessment. To enhance artifact recognition and interrater agreement on reduced image quality, we designed a scoring guide and OCTA training set. Using these educational tools, 23 raters from 14 different centers reached an almost perfect agreement (κ 0.92) for the rejection of poor-quality OCTA images using the OSCAR-MP criteria. We propose a 3-step approach for standardized quality control: (1) To define a specific ROI, (2) to assess the occurrence of OCTA artifacts according to the OSCAR-MP criteria, and (3) to evaluate OCTA quality based on the occurrence of different artifacts within the ROI. OSCAR-MP OCTA QC criteria achieved high interrater agreement in an international multicenter study and is a promising QC protocol for application in the context of future clinical trials and studies.

Retinal microvascular changes in patients with coronary artery disease and apnea.

Optical coherence tomography angiography (OCT-A) allowed visualization of capillary level of retina; however, the relationship between coronary vascular status and retinal microvascular changes in patients with apnea is not known well. Our aim was to assess the retinal OCT-A parameters in patients with ischemia and angiographically proven microvascular disease and compare them with obstructive coronary disease in patients with apnea. Our observational study included 185 eyes of 185 patients, 123 eyes of patients with apnea (72 eyes from mild OSAS, 51 eyes from moderate to severe OSAS) and 62 eyes from healthy controls. Radial scans of the macula and OCT-A scans of the central macula (superficial (SCP) and deep (DCP) capillary plexuses) were performed on all participants. All participants had documented sleep apnea disorder within 2 years prior to coronary angiography. Patients were grouped by severity of apnea and coronary atherosclerosis (50 % stenosis cut-off value for obstructive coronary artery disease). Patients presented with myocardial ischemia and without coronary artery occlusion (<50 % diameter reduction or FFR > 0.80) constitute the microvascular coronary artery (INOCA) group. Compared to healthy controls, patients with apnea showed deterioration in vascular density in all regions of the retina, regardless of obstructive or microvascular coronary artery disease on the ischemia background. This study has provided important observations of a high prevalence of INOCA in patients with OSAS and the presence of OSAS was a significant independent predictor of functional coronary artery disease. The relative decreases in vascular densities were more pronounced in the DCP layer according to SCP layer of macula. Only FAZ area values were significantly different according to the severity of OSAS (0.27 (0.11-0.62) and 0.23 (0.07-0.50) (p = 0.012)). In patients with apnea, OCT-A can be used as a noninvasive tool to define coronary artery involvement, with similar retinal microvascular changes both in obstructive and microvascular coronary artery group. In patients with OSAS, we observed a high prevalence of microvascular coronary disease, supporting pathophysiological role of OSAS in ischemia of this group of patients.

TCU-Net: Transformer Embedded in Convolutional U-Shaped Network for Retinal Vessel Segmentation.

Optical coherence tomography angiography (OCTA) provides a detailed visualization of the vascular system to aid in the detection and diagnosis of ophthalmic disease. However, accurately extracting microvascular details from OCTA images remains a challenging task due to the limitations of pure convolutional networks. We propose a novel end-to-end transformer-based network architecture called TCU-Net for OCTA retinal vessel segmentation tasks. To address the loss of vascular features of convolutional operations, an efficient cross-fusion transformer module is introduced to replace the original skip connection of U-Net. The transformer module interacts with the encoder's multiscale vascular features to enrich vascular information and achieve linear computational complexity. Additionally, we design an efficient channel-wise cross attention module to fuse the multiscale features and fine-grained details from the decoding stages, resolving the semantic bias between them and enhancing effective vascular information. This model has been evaluated on the dedicated Retinal OCTA Segmentation (ROSE) dataset. The accuracy values of TCU-Net tested on the ROSE-1 dataset with SVC, DVC, and SVC+DVC are 0.9230, 0.9912, and 0.9042, respectively, and the corresponding AUC values are 0.9512, 0.9823, and 0.9170. For the ROSE-2 dataset, the accuracy and AUC are 0.9454 and 0.8623, respectively. The experiments demonstrate that TCU-Net outperforms state-of-the-art approaches regarding vessel segmentation performance and robustness.

A Reliable Criterion for the Correct Delimitation of the Foveal Avascular Zone in Diabetic Patients.

Manual segmentation of the Foveal Avascular Zone (FAZ) has a high level of variability. Research into retinas needs coherent segmentation sets with low variability. Retinal optical coherence tomography angiography (OCTA) images from type-1 diabetes mellitus (DM1), type-2 diabetes mellitus (DM2) and healthy patients were included. Superficial (SCP) and deep (DCP) capillary plexus FAZs were manually segmented by different observers. After comparing the results, a new criterion was established to reduce variability in the segmentations. The FAZ area and acircularity were also studied. The new segmentation criterion produces smaller areas (closer to the real FAZ) with lower variability than the different criteria of the explorers in both plexuses for the three groups. This was particularly noticeable for the DM2 group with damaged retinas. The acircularity values were also slightly reduced with the final criterion in all groups. The FAZ areas with lower values showed slightly higher acircularity values. We also have a consistent and coherent set of segmentations with which to continue our research. Manual segmentations of FAZ are generally carried out with little attention to the consistency of the measurements. A novel criterion for segmenting the FAZ allows segmentations made by different observers to be more similar.

OCT2Former: A retinal OCT-angiography vessel segmentation transformer

Background and objectiveRetinal vessel segmentation plays an important role in the automatic retinal disease screening and diagnosis. How to segment thin vessels and maintain the connectivity of vessels are the key challenges of the retinal vessel segmentation task. Optical coherence tomography angiography (OCTA) is a noninvasive imaging technique that can reveal high-resolution retinal vessels. Aiming at make full use of its characteristic of high resolution, a new end-to-end transformer based network named as OCT2Former (OCT-a Transformer) is proposed to segment retinal vessel accurately in OCTA images. MethodsThe proposed OCT2Former is based on encoder-decoder structure, which mainly includes dynamic transformer encoder and lightweight decoder. Dynamic transformer encoder consists of dynamic token aggregation transformer and auxiliary convolution branch, in which the multi-head dynamic token aggregation attention based dynamic token aggregation transformer is designed to capture the global retinal vessel context information from the first layer throughout the network and the auxiliary convolution branch is proposed to compensate for the lack of inductive bias of the transformer and assist in the efficient feature extraction. A convolution based lightweight decoder is proposed to decode features efficiently and reduce the complexity of the proposed OCT2Former. ResultsThe proposed OCT2Former is validated on three publicly available datasets i.e. OCTA-SS, ROSE-1, OCTA-500 (subset OCTA-6M and OCTA-3M). The Jaccard indexes of the proposed OCT2Former on these datasets are 0.8344, 0.7855, 0.8099 and 0.8513, respectively, outperforming the best convolution based network 1.43, 1.32, 0.75 and 1.46%, respectively. ConclusionThe experimental results have demonstrated that the proposed OCT2Former can achieve competitive performance on retinal OCTA vessel segmentation tasks.