Functional OCT reveals anisotropic changes of retinal flicker-evoked vasodilation.

The purpose of this study is to verify the effect of anisotropic property of retinal biomechanics on vasodilation measurement. A custom-built optical coherence tomography (OCT) was used for time-lapse imaging of flicker stimulation-evoked vessel lumen changes in mouse retinas. A comparative analysis revealed significantly larger (18.21%) lumen dilation in the axial direction compared to the lateral (10.77%) direction. The axial lumen dilation predominantly resulted from the top vessel wall movement toward the vitreous direction, whereas the bottom vessel wall remained stable. This observation indicates that the traditional vasodilation measurement in the lateral direction may result in an underestimated value.

Imaging Assessment of Peripapillary Vessel Diameters in Postmortem Eyes.

PURPOSE: Proof of concept of ex vivo retinal vessel diameter measurements in human postmortem eyes. METHODS: En face near-infrared (IR) images and optical coherence tomography (OCT) of the optic nerve head (ONH) were captured ex vivo with a Heidelberg Engineering Spectralis (Spectralis, version 7.0.4, Image Capture Module, version 1.2.4, Heidelberg Heidelberg, Germany) device, using a custom-made eye chamber holding and positioning the eyes during the image process. Thirty-two formaldehyde-fixated eyes of 16 patients were imaged. In the IR images, two independent graders measured retinal vessel diameters at the intersection of a drawn circle centered on the ONH with diameters of 2.0 mm and 3.4 mm, respectively. The anatomically corresponding measurements between both graders were statistically analyzed using a Wilcoxon signed-rank test. RESULTS: A total of 246 matched measurements of both graders were analyzed across all 32 imaged eyes. Statistically significant differences between the graders were found for arterioles at 2 mm from the ONH. The other measurements did not show statistically significant intergrader differences. The mean values for arteriole diameters were 72.2 µm at 2.0 mm and 61.5 µm at 3.4 mm for grader 1, and 66.4 µm at 2.0 mm and 63.2 µm at 3.4 mm for grader 2. The mean diameter for venules were 75.5 µm at 2.0 mm and 79.3 µm at 3.4 mm for grader 1, and 67.4 µm at 2 mm and 79.1 µm at 3.4 mm for grader 2. CONCLUSION: To the best of our knowledge, this is the first study to present IR image-based retinal vessel diameters in ex vivo postmortem eyes. Retinal IR/OCT imaging is possible, and measurements are reproducible in formaldehyde-fixated human eyes. Fixation artefacts result in lower image quality, and this can impose challenges in correctly detecting, classifying, and measuring retinal vessels.

Hemoglobin levels are associated with retinal vascular caliber in a middle-aged birth cohort.

Vascular and neural structures of the retina can be visualized non-invasively and used to predict ocular and systemic pathologies. We set out to evaluate the association of hemoglobin (Hb) levels within the national reference interval with retinal vascular caliber, optical coherence tomography (OCT) and visual field (VF) parameters in the Northern Finland 1966 Birth Cohort (n = 2319, 42.1% male, average age 47 years). The studied parameters were evaluated in Hb quintiles and multivariable linear regression models. The lowest Hb quintile of both sexes presented the narrowest central retinal vein equivalent (CRVE) and the healthiest cardiometabolic profile compared to the other Hb quintiles. In the regression models, CRVE associated positively with Hb levels in both sexes, (Bmales = 0.068 [0.001; 0.135], Bfemales = 0.087 [0.033; 0.140]), after being adjusted for key cardiometabolic and inflammatory parameters, smoking status, and fellow vessel caliber. No statistically significant associations of Hb levels with central retinal artery equivalent, OCT or VF parameters were detected. In conclusion, Hb levels were positively and specifically associated with CRVE, indicating that Hb levels are an independent factor affecting CRVE and the effect is in parallel with established risk factors for cardiometabolic diseases.

Automated diagnosis of plus disease in retinopathy of prematurity using quantification of vessels characteristics.

The condition known as Plus disease is distinguished by atypical alterations in the retinal vasculature of neonates born prematurely. It has been demonstrated that the diagnosis of Plus disease is subjective and qualitative in nature. The utilization of quantitative methods and computer-based image analysis to enhance the objectivity of Plus disease diagnosis has been extensively established in the literature. This study presents the development of a computer-based image analysis method aimed at automatically distinguishing Plus images from non-Plus images. The proposed methodology conducts a quantitative analysis of the vascular characteristics linked to Plus disease, thereby aiding physicians in making informed judgments. A collection of 76 posterior retinal images from a diverse group of infants who underwent screening for Retinopathy of Prematurity (ROP) was obtained. A reference standard diagnosis was established as the majority of the labeling performed by three experts in ROP during two separate sessions. The process of segmenting retinal vessels was carried out using a semi-automatic methodology. Computer algorithms were developed to compute the tortuosity, dilation, and density of vessels in various retinal regions as potential discriminative characteristics. A classifier was provided with a set of selected features in order to distinguish between Plus images and non-Plus images. This study included 76 infants (49 [64.5%] boys) with mean birth weight of 1305 ± 427 g and mean gestational age of 29.3 ± 3 weeks. The average level of agreement among experts for the diagnosis of plus disease was found to be 79% with a standard deviation of 5.3%. In terms of intra-expert agreement, the average was 85% with a standard deviation of 3%. Furthermore, the average tortuosity of the five most tortuous vessels was significantly higher in Plus images compared to non-Plus images (p ≤ 0.0001). The curvature values based on points were found to be significantly higher in Plus images compared to non-Plus images (p ≤ 0.0001). The maximum diameter of vessels within a region extending 5-disc diameters away from the border of the optic disc (referred to as 5DD) exhibited a statistically significant increase in Plus images compared to non-Plus images (p ≤ 0.0001). The density of vessels in Plus images was found to be significantly higher compared to non-Plus images (p ≤ 0.0001). The classifier's accuracy in distinguishing between Plus and non-Plus images, as determined through tenfold cross-validation, was found to be 0.86 ± 0.01. This accuracy was observed to be higher than the diagnostic accuracy of one out of three experts when compared to the reference standard. The implemented algorithm in the current study demonstrated a commendable level of accuracy in detecting Plus disease in cases of retinopathy of prematurity, exhibiting comparable performance to that of expert diagnoses. By engaging in an objective analysis of the characteristics of vessels, there exists the possibility of conducting a quantitative assessment of the disease progression's features. The utilization of this automated system has the potential to enhance physicians' ability to diagnose Plus disease, thereby offering valuable contributions to the management of ROP through the integration of traditional ophthalmoscopy and image-based telemedicine methodologies.

Potential ocular indicators to distinguish posterior cortical atrophy and typical Alzheimer's disease: a cross-section study using optical coherence tomography angiography.

BACKGROUND: Posterior cortical atrophy (PCA) is a form of dementia that frequently displays significant visual dysfunction and relatively preserved cognitive and executive functions, thus hindering early diagnosis and treatment. This study aimed to investigate possible fundus markers in PCA patients and compare them with those of typical Alzheimer's disease (AD) patients to seek potential diagnostic patterns. METHODS: Age-matched PCA and AD patients and healthy controls (HC) completed optometry, intraocular pressure measurement, neuropsychologic assessments, optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA) examination in one visit. Overall, six outcomes of thicknesses of various retinal layers and seven outcomes of the retinal microvascular network were calculated. After adjusting for age, sex, and years of education, the OCT and OCTA results were analyzed using analysis of covariance and generalized linear models. Correlation analyses were performed using Spearman correlation, and ROC curves were plotted. RESULTS: Twelve PCA patients, nineteen AD patients, and thirty HC, aged 45-80 years were included. Fifty HC, thirty AD, and twenty PCA eyes were available for foveal avascular zone (FAZ) area analysis; forty-nine HC, thirty-four AD, and eighteen PCA eyes were available for OCT and OCTA assessments. PCA patients had thinner retinal nerve fiber layer and ganglion cell layer + inner plexiform layer than HC in the 0-3 mm circle and 1-3 mm ring. Few structural differences were observed between the AD group and the other two groups. The flow area of the superficial capillary plexus and the intermediate capillary plexus was smaller in the PCA group than in the HC group in the 0-1 mm circle, 0-3 mm circle. MMSE performed better than any combination of optical parameters in identifying AD and PCA from HC (AUC = 1), while the combination of MoCA, retinal thickness and vascular density of ICP in the 1-3 mm ring, with flow area of ICP in the 0-1 mm circle showed the strongest ability to distinguish PCA from AD (AUC = 0.944). CONCLUSIONS: PCA patients exhibited similar impairment patterns to AD patients in the fundus structure and microvascular network. OCTA may aid in the non-invasive detection of AD and PCA, but still remains to be substantiated.

The use of optical coherence tomography (OCT) and OCT angiography in borderline personality disorder compared to health control subjects.

BACKGROUND: Optical coherence tomography (OCT) or OCT angiography (OCTA) has been investigated in few research studies of psychiatric disorders. No research has been done using OCT or OCTA in patients with borderline personality disorder (BPD). METHODS: OCTA measured foveal avascular zone (FAZ), macular vessel density (MVD), and peripapillary vessel density (PVD). OCT measured the peripapillary retinal fiber layer (RNFL) and central retinal thickness (CRT). The study utilized the Ottawa Self-Injury Inventory, Hamilton Anxiety Rating Scale (HAMA), and Global Assessment of Functioning (GAF) to assess the symptom characteristics of individuals with BPD. RESULTS: Fifty-nine eyes of BPD patients and 58 eyes of normal subjects were analyzed, MVD of the superficial retinal capillary plexus declined noticeably in most subfields (p < 0.05). Significant differences were observed in the whole inner ring and outer ring index between BPD and HC groups (p < 0.05). The patients with BPD exhibited lower RNFL and CRT, the difference was significant (p < 0.05). CRT indicated a significant negative correlation with the Ottawa Self-Injury Inventory (p < 0.05). In addition, we observed that there was a negative correlation identified between the MVD of the inner ring and HAMA (p < 0.05). Meanwhile, the MVD of the outer ring was positively correlated with GAF (p < 0.05). The areas under the receiver operating characteristic curves (AUROCs) for distinguishing BPD and HC eyes in OCTA were the highest for fovea MVD (0.679), followed by outer ring MVD (0.669), inner ring MVD (0.641), FAZ (0.579). In OCT, CRT was highest for BPD (0.711), followed by RNFL (0.625). CONCLUSION: The OCT and OCTA can non-invasively detect microvascular and morphology changes of the retina in BPD patients compared to healthy control subjects.

Macular perfusion changes in people administered two types of COVID-19 vaccines: optical coherence tomography angiography study.

PURPOSE: To evaluate macular chorioretinal flow changes on optical coherence tomography angiography, in participants who received inactivated and messenger RNA (mRNA) vaccines to prevent Coronavirus disease 2019 (COVID-19). METHODS: In this prospective cohort study, healthy participants who received two doses of an inactivated COVID-19 vaccine (CoronaVac) and then one dose of an mRNA vaccine (BNT162b2) were examined before and after each vaccination. Ophthalmologic examination and imaging with optical coherence tomography angiography were performed during each visit. We evaluated vascular densities in the superficial and deep capillary plexuses in foveal, parafoveal, and perifoveal areas; the foveal avascular zone; and choriocapillaris flows (in 1- and 6-mm-diameter areas). RESULTS: One eye in each of the 24 participants was assessed. Superficial capillary plexus vascular densities in the parafoveal area were significantly lower after the second dose of the CoronaVac vaccine than after the first dose. In the deep capillary plexus, vascular attenuation was observed only in the parafoveal region after the first CoronaVac dose. However, in all regions, the deep capillary plexus vascular densities and subfoveal choriocapillaris flow were significantly decreased after the second CoronaVac dose. After the BNT162b2 dose, the superficial capillary plexus vascular densities, the deep capillary plexus vascular densities, and subfoveal choriocapillaris flow of most regions were significantly lower than those before vaccinations. CONCLUSION: Vascular attenuation, observed particularly after the second dose of the CoronaVac vaccine, may explain the pathogenesis of postvaccine ocular ischemic disorders reported in the literature. However, these disorders are extremely rare, and the incidence of thrombotic events caused by COVID-19 itself is higher.

EAMR-Net: A multiscale effective spatial and cross-channel attention network for retinal vessel segmentation.

Delineation of retinal vessels in fundus images is essential for detecting a range of eye disorders. An automated technique for vessel segmentation can assist clinicians and enhance the efficiency of the diagnostic process. Traditional methods fail to extract multiscale information, discard unnecessary information, and delineate thin vessels. In this paper, a novel residual U-Net architecture that incorporates multi-scale feature learning and effective attention is proposed to delineate the retinal vessels precisely. Since drop block regularization performs better than drop out in preventing overfitting, drop block was used in this study. A multi-scale feature learning module was added instead of a skip connection to learn multi-scale features. A novel effective attention block was proposed and integrated with the decoder block to obtain precise spatial and channel information. Experimental findings indicated that the proposed model exhibited outstanding performance in retinal vessel delineation. The sensitivities achieved for DRIVE, STARE, and CHASE_DB datasets were 0.8293, 0.8151 and 0.8084, respectively.

HRD-Net: High resolution segmentation network with adaptive learning ability of retinal vessel features.

Retinal segmentation is a crucial step in the early warning of human health conditions. However, retinal blood vessels possess complex curvature, irregular distribution, and contain multi-scale fine structures, which make the limited receptive field of regular convolution challenging to process their vascular details efficiently. Additionally, the encoder-decoder based network leads to irreversible spatial information loss because of multiple downsampling, resulting in over-segmentation and missed segmentation of the vessels. For this reason, we develop a high-resolution network based on Deformable Convolution v3, called HRD-Net. By constructing a high-resolution representation, the network allows special attention to be paid to the details of tiny blood vessels. The proposed feature enhancement cascade module based on Deformable Convolution v3 can flexibly adapt and capture the ever-changing morphology and intricate connections of retinal blood vessels, ensuring the continuity of vessel segmentation. In the output phase of the network, the proposed global aggregation module integrates full-resolution feature maps while suppressing redundant features, achieving an effective fusion of high-level semantic information and spatial detail information. In addition, we have re-examined the selection criteria for activation and normalization methods, and also refine the network architectures from a spatial domain perspective to release redundant computational loads. Testing on the DRIVE, STARE, and CHASE_DB1 datasets indicates that HRD-Net, with fewer parameters, outperforms existing segmentation methods on several evaluation metrics such as F1, ACC, SE, SP, AUC, and IOU.

Association between obstructive coronary disease and diabetic retinopathy: Cross-sectional study of coronary angiotomography and multimodal retinal imaging.

AIMS: To investigate the association between diabetic retinopathy (DR) and coronary artery disease (CAD) using coronary angiotomography (CCTA) and multimodal retinal imaging (MMRI) with ultra-widefield retinography and optical coherence tomography angiography and structural domain. METHODS: Single-center, cross-sectional, single-blind. Patients with diabetes who had undergone CCTA underwent MMRI. Uni and multivariate analysis were used to assess the association between CAD and DR and to identify variables independently associated with DR. RESULTS: We included 171 patients, 87 CAD and 84 non-CAD. Most CAD patients were males (74 % vs 38 %, P < 0.01), insulin users (52 % vs 38 %, p < 0.01) and revascularized (64 %). They had a higher prevalence of DR (48 % vs 22 %, p = 0.01), microaneurysms (25 % vs 13 %, p = 0.04), intraretinal cysts (22 % vs 8 %, p = 0.01) and areas of reduced capillary density (46 % vs 20 %, p < 0.01). CAD patients also had lower mean vascular density (MVD) (15.7 % vs 16.5,%, p = 0.049) and foveal avascular zone (FAZ) circularity (0.64 ± 0.1 vs 0.69 ± 0.1, p = 0.04). There were significant and negative correlations between Duke coronary score and MVD (r = -0.189; p = 0.03) and FAZ circularity (r = -0,206; p = 0.02). CAD, DM duration and insulin use independently associated with DR. CONCLUSIONS: CAD patients had higher prevalence of DR and lower MVD. CAD, DM duration and insulin use were independently associated with DR.

PKSEA-Net: A prior knowledge supervised edge-aware multi-task network for retinal arteriolar morphometry.

Retinal fundus images serve as a non-invasive modality to obtain information pertaining to retinal vessels through fundus photography, thereby offering insights into cardiovascular and cerebrovascular diseases. Retinal arteriolar morphometry has emerged as the most convenient and fundamental clinical methodology in the realm of patient screening and diagnosis. Nevertheless, the analysis of retinal arterioles is challenging attributable to imaging noise, stochastic fuzzy characteristics, and blurred boundaries proximal to blood vessels. In response to these limitations, we introduce an innovative methodology, named PKSEA-Net, which aims to improve segmentation accuracy by enhancing the perception of edge information in retinal fundus images. PKSEA-Net employs the universal architecture PVT-v2 as the encoder, complemented by a novel decoder architecture consisting of an Edge-Aware Block (EAB) and a Pyramid Feature Fusion Module (PFFM). The EAB block incorporates prior knowledge for supervision and multi-query for multi-task learning, with supervision information derived from an enhanced Full Width at Half Maximum (FWHM) algorithm and gradient map. Moreover, PFFM efficiently integrates multi-scale features through a novel attention fusion method. Additionally, we have collected a Retinal Cross-Sectional Vessel (RCSV) dataset derived from approximately 200 patients in Quzhou People's Hospital to serve as the benchmark dataset. Comparative evaluations with several state-of-the-art (SOTA) networks confirm that PKSEA-Net achieves exceptional experimental performance, thereby establishing its status as a SOTA approach for precise boundary delineation and retinal vessel segmentation.

A retinal vessel segmentation network with multiple-dimension attention and adaptive feature fusion.

The incidence of blinding eye diseases is highly correlated with changes in retinal morphology, and is clinically detected by segmenting retinal structures in fundus images. However, some existing methods have limitations in accurately segmenting thin vessels. In recent years, deep learning has made a splash in the medical image segmentation, but the lack of edge information representation due to repetitive convolution and pooling, limits the final segmentation accuracy. To this end, this paper proposes a pixel-level retinal vessel segmentation network with multiple-dimension attention and adaptive feature fusion. Here, a multiple dimension attention enhancement (MDAE) block is proposed to acquire more local edge information. Meanwhile, a deep guidance fusion (DGF) block and a cross-pooling semantic enhancement (CPSE) block are proposed simultaneously to acquire more global contexts. Further, the predictions of different decoding stages are learned and aggregated by an adaptive weight learner (AWL) unit to obtain the best weights for effective feature fusion. The experimental results on three public fundus image datasets show that proposed network could effectively enhance the segmentation performance on retinal blood vessels. In particular, the proposed method achieves AUC of 98.30%, 98.75%, and 98.71% on the DRIVE, CHASE_DB1, and STARE datasets, respectively, while the F1 score on all three datasets exceeded 83%. The source code of the proposed model is available at https://github.com/gegao310/VesselSeg-Pytorch-master.

Evaluation of Optic Nerve Head Microcirculation in Open-Angle Glaucoma Patients with Unilateral Visual Field Defect.

INTRODUCTION: Microcirculation of optic nerve head (ONH) in open-angle glaucoma (OAG) patients with unilateral visual field (VF) loss has yet to be fully investigated, especially the perimetrically unaffected fellow eyes. METHODS: Thirty-eight OAG patients with VF defect in one eye and normal VF in the other eye, and thirty-one healthy participants were analyzed. All participants underwent laser speckle flowgraphy (LSFG), spectral-domain optical coherence tomography (SD-OCT) imaging, and VF test for further analyses. LSFG measurements included mean blur rate in all area of ONH (MA), big vessel area of ONH (MV), and tissue area of ONH (MT). SD-OCT parameters included circumpapillary retinal nerve fiber layer (cpRNFL) thickness and macula thicknesses. The difference of LSFG and SD-OCT indices between glaucoma patients and healthy controls were compared. The diagnostic accuracy was analyzed with the areas under the receiver operating characteristic curves (AROCs). RESULTS: Global cpRNFL thickness and macular thickness in unaffected eyes of OAG patients were higher than their fellow eyes and lower than healthy eyes. MA and MV in healthy eyes and unaffected eyes were significantly higher than in affected eyes. MT in unaffected eyes of OAG patients was higher than in their fellow affected eyes but lower than in healthy eyes. The AROCs were highest for cpRNFL (0.925), followed by macular thickness (0.838), and MT (0.834). CONCLUSIONS: ONH microcirculation in perimetrically unaffected fellow eyes was decreased in OAG patients with unilateral VF loss. LSFG can detect changes of ONH in high-risk eyes before detectable VF damage, which may reflect the vascular pathophysiology for glaucoma.

Comparison of Changes in Retinal Vascular Parameters and Density in Patients with Moyamoya Disease: A Retrospective Study.

INTRODUCTION: This study aimed to compare retinal vascular parameters and density in patients with moyamoya disease using the optical coherence tomography angiography. METHODS: This clinical trial totally enrolls 78 eyes from 39 participants, and all these patients with moyamoya disease (N = 13) are set as experimental group and participants with health who matched with age and gender are considered as the control group (N = 26). Then all these participants receive optical coherence tomography angiography detection. Participants' general data are collected and analyzed. Skeleton density (SD) value, vessel density (VD) value, fractal dimension (FD) value, vessel diameter index (VDI) value, foveal avascular zone (FAZ) value are analyzed. RESULTS: A total of 39 participants are included in this study. The SD value in the experimental group was significantly lower than that in control group (0.175 [0.166, 0.181] vs. 0.184 [0.175, 0.188], p = 0.017). Similarly, the VD value in the experimental group was significantly lower than that in the control group (0.333 [0.320, 0.350] vs. 0.354 [0.337, 0.364], p = 0.024). Additionally, the FD value in the experimental group was significantly lower than that in the control group (2.088 [2.083, 2.094] vs. 2.096 [2.090, 2.101], p = 0.022). As for the VDI and FAZ, VDI and FAZ values in the experimental group were lower than those in the control group, there was no significant difference in VDI and FAZ values between the two groups. CONCLUSIONS: Our study, using non-invasive and rapid OCTA imaging, confirmed decreased retinal vascular parameters and density in patients with moyamoya disease.

MAG-Net : Multi-fusion network with grouped attention for retinal vessel segmentation.

Retinal vessel segmentation plays a vital role in the clinical diagnosis of ophthalmic diseases. Despite convolutional neural networks (CNNs) excelling in this task, challenges persist, such as restricted receptive fields and information loss from downsampling. To address these issues, we propose a new multi-fusion network with grouped attention (MAG-Net). First, we introduce a hybrid convolutional fusion module instead of the original encoding block to learn more feature information by expanding the receptive field. Additionally, the grouped attention enhancement module uses high-level features to guide low-level features and facilitates detailed information transmission through skip connections. Finally, the multi-scale feature fusion module aggregates features at different scales, effectively reducing information loss during decoder upsampling. To evaluate the performance of the MAG-Net, we conducted experiments on three widely used retinal datasets: DRIVE, CHASE and STARE. The results demonstrate remarkable segmentation accuracy, specificity and Dice coefficients. Specifically, the MAG-Net achieved segmentation accuracy values of 0.9708, 0.9773 and 0.9743, specificity values of 0.9836, 0.9875 and 0.9906 and Dice coefficients of 0.8576, 0.8069 and 0.8228, respectively. The experimental results demonstrate that our method outperforms existing segmentation methods exhibiting superior performance and segmentation outcomes.

Retinal vascular density as a potential biomarker of diabetic cerebral small vessel disease.

AIM: The retina and brain share similar anatomical and physiological features. Thus, retinal imaging by optical coherence tomography angiography (OCTA) might be a potential tool for the early diagnosis of diabetic cerebral small vessel disease (CSVD). In this study, we aimed to evaluate retinal vascular density (VD) in diabetic CSVD by OCTA imaging and explore the associations between retinal VD and cerebral magnetic resonance imaging (MRI) markers and cognitive function. METHODS: In total, 131 patients were enrolled, including CSVD (n = 43) and non-CSVD groups (n = 88). The VD and foveal avascular zone of the retinal capillary plexus were measured with OCTA. A brain MRI was performed. RESULTS: MRI imaging showed that in the diabetic CSVD group, white matter hyperintensities (WMHs), particularly deep WMHs (58.82%), are the most common MRI marker, followed by cerebral microbleeds in the subtentorial and cortical areas (34.78%). The CSVD group showed increases in the prevalence of cognitive dysfunction (p = .034) and depression (p = .033) and decreases in visuospatial/executive ability and delayed recall ability. In the CSVD group, VDs of the macular superficial vascular plexus (32.93 ± 7.15% vs. 36.97 ± 6.59%, p = .002), intermediate capillary plexus (20.87 ± 4.30% vs. 23.08 ± 4.30%, p = .005) and deep capillary plexus (23.54 ± 5.00% vs. 26.05 ± 4.20%, p = .003) were lower than those of the non-CSVD group. Multiple linear regression analysis showed that VD of the macular superficial vascular plexus was independently associated with cerebral microbleeds. Meanwhile, VD of the macular intermediate capillary plexus was associated with white matter lacunar infarcts after adjustment. CONCLUSIONS: Diabetic CSVDs are characterized by MRI markers, including deep WMHs and cerebral microbleeds, and showed impaired cognition with decreased visuospatial/executive ability and delayed recall ability. OCTA imaging revealed a significant decrease in retinal microvascular perfusion in diabetic CSVD, which was related to MRI markers and cognitive function. OCTA might be a valuable potential measurement for the early diagnosis of CSVD.

Effect of mydriasis on macular and peripapillary metrics in swept-source optical coherence tomography angiography.

Introduction: The study aimed to evaluate the effect of mydriasis on macular and peripapillary metrics with swept-source optical coherence tomography angiography (SS-OCTA) in healthy subjects. Methods: Thirty-five healthy subjects were included. The macular region was scanned by the 3×3mm mode and 6×6mm mode, and the peripapillary region was scanned by the 4.5×4.5mm mode on both eyes with SS-OCTA before and after mydriasis. Macular and peripapillary metrics, including retinal vessel density (VD) and fundus thickness were measured by the built-in program. Data of the right eye were analyzed. Results: The signal strength of the scans was comparable before and after mydriasis (all P>0.05). There were no significant differences in foveal avascular zone (FAZ) parameters and retinal VD of most sectors in both macular and peripapillary areas (all P>0.05). Choroidal thickness was decreased, outer and whole retinal thickness was increased in most of the macular sectors after mydriasis (all P<0.05). Choroidal thickness was decreased in all the peripapillary sectors, but whole retinal thickness and GCC thickness were increased in some peripapillary sectors after mydriasis (all P<0.05). Conclusions: FAZ parameters and retinal VD in the most macular and peripapillary regions are not affected by mydriasis. The thickness of the choroid is decreased after mydriasis, while the thickness of retinal layers in some sectors may be increased after mydriasis.

Remnant cholesterol is correlated with retinal vascular morphology and diabetic retinopathy in type 2 diabetes mellitus: a cross-sectional study.

BACKGROUND: The association between remnant cholesterol (RC) and diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) remains unclear. Morphological changes in retinal vessels have been reported to predict vascular complications of diabetes, including DR. METHODS: This cross-sectional study included 6535 individuals with T2DM. The RC value was calculated using the recognized formula. The retinal vascular parameters were measured using fundus photography. The independent relationship between RC and DR was analyzed using binary logistic regression models. Multiple linear regression and subgroup analyses were employed to investigate the link between RC and vascular parameters, including the retinal arteriolar diameter (CRAE), venular diameter (CRVE), and fractal dimension (Df). Mediation analysis was performed to assess whether the vascular morphology could explain the association between RC and DR. RESULTS: RC was independently associated with DR in patients with a longer duration of T2DM (> 7 years). Patients with the highest quartile RC levels had larger CRAE (5.559 [4.093, 7.025] µm), CRVE (7.620 [5.298, 9.941] µm) and Df (0.013 [0.009, 0.017]) compared with patients with the lowest quartile RC levels. Results were robust across different subgroups. The association between RC and DR was mediated by CRVE (0.020 ± 0.005; 95% confidence interval: 0.012-0.032). CONCLUSIONS: RC may be a risk factor for DR among those who have had T2DM for a longer period of time. Higher RC levels were correlated with wider retinal arterioles and venules as well as higher Df, and it may contribute to DR through the dilation of retinal venules.

DISCOVER: 2-D multiview summarization of Optical Coherence Tomography Angiography for automatic diabetic retinopathy diagnosis.

Diabetic Retinopathy (DR), an ocular complication of diabetes, is a leading cause of blindness worldwide. Traditionally, DR is monitored using Color Fundus Photography (CFP), a widespread 2-D imaging modality. However, DR classifications based on CFP have poor predictive power, resulting in suboptimal DR management. Optical Coherence Tomography Angiography (OCTA) is a recent 3-D imaging modality offering enhanced structural and functional information (blood flow) with a wider field of view. This paper investigates automatic DR severity assessment using 3-D OCTA. A straightforward solution to this task is a 3-D neural network classifier. However, 3-D architectures have numerous parameters and typically require many training samples. A lighter solution consists in using 2-D neural network classifiers processing 2-D en-face (or frontal) projections and/or 2-D cross-sectional slices. Such an approach mimics the way ophthalmologists analyze OCTA acquisitions: (1) en-face flow maps are often used to detect avascular zones and neovascularization, and (2) cross-sectional slices are commonly analyzed to detect macular edemas, for instance. However, arbitrary data reduction or selection might result in information loss. Two complementary strategies are thus proposed to optimally summarize OCTA volumes with 2-D images: (1) a parametric en-face projection optimized through deep learning and (2) a cross-sectional slice selection process controlled through gradient-based attribution. The full summarization and DR classification pipeline is trained from end to end. The automatic 2-D summary can be displayed in a viewer or printed in a report to support the decision. We show that the proposed 2-D summarization and classification pipeline outperforms direct 3-D classification with the advantage of improved interpretability.

Decreased retinal capillary density as a beneficial response to 24-week high-speed circuit resistant training in healthy older adults.

PURPOSE: To determine the changes in retinal microvascular density after a 24-week high-speed circuit resistance training program (HSCT) in healthy older adults. METHODS: Thirty healthy older adults were recruited and randomly assigned to either a training group (HSCT) or a non-training (CON) group. Fifteen subjects (age 73.3 ± 7.76 yrs) in the HSCT group exercised three times per week on non-consecutive days for 24 weeks. Fifteen subjects in the CON group (age 72.2 ± 6.04 yrs) did not have formal physical training. Both eyes of each subject were imaged using optical coherence tomography angiography (OCTA) at baseline and at the 24-week follow-up. The vessel densities of the retinal vascular network (RVN), superficial vascular plexus (SVP), and deep vascular plexus (DVP) were measured. RESULTS: There were no demographic differences between the study groups. There were significant decreases in the retinal vessel densities of RVN, SVP and DVP in the HSCT group (P < 0.05). However, there were no significant changes in all three vascular measurements in the CON group (P > 0.05), although the changes showed a decreasing trend. The decreased vessel densities were doubled in the HSCT group in comparison to the CON group. However, the differences between groups did not reach a significant level (P > 0.05). CONCLUSIONS: This is the first study to reveal the decreased retinal vessel densities as a possible imaging marker for the beneficial effects of the 24-week HSCT program in older adults.