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Stroke Jun 2022
Topics: Cerebral Hemorrhage; Humans; Magnetic Resonance Imaging; Microaneurysm
PubMed: 35450437
DOI: 10.1161/STROKEAHA.122.038785 -
Ophthalmology. Retina Feb 2020In diabetic retinopathy (DR), OCT angiography (OCTA) could not image all fluorescein angiography (FA)-detected microaneurysms. We investigated whether multiple image... (Observational Study)
Observational Study
PURPOSE
In diabetic retinopathy (DR), OCT angiography (OCTA) could not image all fluorescein angiography (FA)-detected microaneurysms. We investigated whether multiple image averaging could enhance the microaneurysm detection capability of OCTA in patients with DR.
DESIGN
Prospective and cross-sectional observational study.
PARTICIPANTS
Consecutive 31 patients (n = 62 eyes) with DR.
METHODS
All eyes underwent FA and 3 × 3 mm fovea-centered OCTA images were obtained using 2 devices: RTVue XR Avanti (Optovue Inc, Fremont, CA) and OCT HS-100 (Canon Inc, Toyko, Japan). OCTA imaging (HS-100) was performed 10 consecutive times. Microaneurysm detection capability was compared among 5 OCTA images (single image, ×3, ×5, and ×10 averaged images and single scan image with the RTVue XR Avanti device).
MAIN OUTCOME MEASURES
Microaneurysm detection capability and the correlation between microaneurysm clinical characteristics or morphology and the extent of image averaging required for OCTA detection.
RESULTS
A total of 415 microaneurysms could be analyzed in 31 eyes from 25 patients. Microaneurysms detected on single image, ×3, ×5, and ×10 averaged OCTA images were 144 (34.7%), 227 (54.7%), 285 (68.7%), and 306 (73.7%), respectively. Microaneurysm detection capability was significantly increased with increased image averaging. Microaneurysm detection with OCTA was not correlated with retinal thickness, FA leakiness, and indocyanine green angiogram detection or the number of averaged images, whereas there was significant correlation between microaneurysm morphology and microaneurysm visibility by the image-averaging process for 4 morphologies, particular the focal bulge types (P < 0.01).
CONCLUSIONS
In DR, multiple image averaging is useful for increasing the microaneurysm detection capability of OCTA, especially for focal bulge-type microaneurysms.
Topics: Cross-Sectional Studies; Female; Fluorescein Angiography; Fovea Centralis; Fundus Oculi; Humans; Male; Microaneurysm; Middle Aged; Prospective Studies; Retinal Vessels; Tomography, Optical Coherence
PubMed: 31753811
DOI: 10.1016/j.oret.2019.09.010 -
Eye (London, England) Jan 2021Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus. Optical coherence tomography angiography (OCTA) has been developed to visualize... (Review)
Review
Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus. Optical coherence tomography angiography (OCTA) has been developed to visualize the retinal microvasculature and choriocapillaris based on the motion contrast of circulating blood cells. Depth-resolved ability and non-invasive nature of OCTA allow for repeated examinations and visualization of microvasculature at the retinal capillary plexuses and choriocapillaris. OCTA enables quantification of microvascular alterations in the retinal capillary network, in addition to the detection of classical features associated with DR, including microaneurysms, intraretinal microvascular abnormalities, and neovascularization. OCTA has a promising role as an objective tool for quantifying extent of microvascular damage and identify eyes with diabetic macular ischaemia contributed to visual loss. Furthermore, OCTA can identify preclinical microvascular abnormalities preceding the onset of clinically detectable DR. In this review, we focused on the applications of OCTA derived quantitative metrics that are relevant to early detection, staging and progression of DR. Advancement of OCTA technology in clinical research will ultimately lead to enhancement of individualised management of DR and prevention of visual impairment in patients with diabetes.
Topics: Diabetes Mellitus; Diabetic Retinopathy; Fluorescein Angiography; Humans; Microaneurysm; Retinal Vessels; Tomography, Optical Coherence
PubMed: 33099579
DOI: 10.1038/s41433-020-01233-y -
The British Journal of Ophthalmology Feb 2019To analyse retinopathy phenotypes and microaneurysm (MA) turnover in mild non-proliferative diabetic retinopathy (NPDR) as predictors of progression to diabetic...
AIM
To analyse retinopathy phenotypes and microaneurysm (MA) turnover in mild non-proliferative diabetic retinopathy (NPDR) as predictors of progression to diabetic central-involved macular oedema (CIMO) in patients with type 2 diabetes mellitus (DM) in two different ethnic populations.
METHODS
205 patients with type 2 DM and mild NPDR were followed in a prospective observational study for 2 years or until development of CIMO, in two centres from different regions of the world. Ophthalmological examinations, including best-corrected visual acuity (BCVA), fundus photography with RetmarkerDR analysis, and optical coherence tomography (OCT), were performed at baseline and 6 12 and 24 months.
RESULTS
158 eyes/patients reached either the study endpoint, CIMO (24) or performed the last study visit (24-month visit) without developing CIMO (134). From the eyes/patients in analysis, 27 eyes (17.1%) progressed to more advanced ETDRS (Early Treatment Diabetic Retinopathy Study) levels: 6 progressed to mild NPDR (level 35), 15 progressed to moderate NPDR (level 43), 5 progressed to moderately severe NPDR (level 47) and 1 progressed to high risk PDR (level 71). Worsening in ETDRS level is associated with phenotype C (p=0.005). From the 130 eyes/patients with a low MA turnover, 18 (13.8%) eyes/patients had an increase in ETDRS level, and from the 19 eyes/patients with a high MA turnover, 9 (47.4%) had an increase in ETDRS level (p<0.001).
CONCLUSION
Eyes in the initial stages of diabetic retinopathy show different phenotypes with different risks for progression to CIMO. In phenotype C, MA turnover correlates with ETDRS grading worsening and development of CIMO.
Topics: Adult; Aged; Blood Glucose; Blood Pressure; Body Mass Index; Cholesterol; Diabetes Mellitus, Type 2; Diabetic Retinopathy; Disease Progression; Female; Glycated Hemoglobin; Humans; Image Processing, Computer-Assisted; Macular Edema; Male; Microaneurysm; Middle Aged; Prospective Studies; Risk Factors
PubMed: 29699981
DOI: 10.1136/bjophthalmol-2018-311887 -
Diabetes Apr 2022Microaneurysms are biomarkers of microvascular injury in diabetic retinopathy (DR). Impaired retinal capillary perfusion is a critical pathogenic mechanism in the...
Microaneurysms are biomarkers of microvascular injury in diabetic retinopathy (DR). Impaired retinal capillary perfusion is a critical pathogenic mechanism in the development of microvascular abnormalities. Targeting fundamental molecular disturbances resulting from capillary nonperfusion, such as increased vascular endothelial growth factor expression, does not always reverse the anatomic complications of DR, suggesting that other pathogenic mechanisms independent of perfusion also play a role. We stratify the effects of capillary nonperfusion, inflammation, and pericyte loss on microaneurysm size and leakage in DR through three-dimensional analysis of 636 microaneurysms using high-resolution confocal scanning laser microscopy. Capillary nonperfusion, pericyte loss, and inflammatory cells were found to be independent predictors of microaneurysm size. Nonperfusion alone without pericyte loss or inflammation was not a significant predictor of microaneurysm leakage. Microaneurysms found in regions without nonperfusion were significantly smaller than those found in regions with nonperfusion, and their size was not associated with pericyte loss or inflammation. In addition, microaneurysm size was a significant predictor of leakage in regions with nonperfusion only. This report refines our understanding of the disparate pathophysiologic mechanisms in DR and provides a histologic rationale for understanding treatment failure for microvascular complications in DR.
Topics: Diabetes Mellitus; Diabetic Retinopathy; Humans; Inflammation; Microaneurysm; Pericytes; Retinal Vessels; Vascular Endothelial Growth Factor A
PubMed: 35043147
DOI: 10.2337/db21-0737 -
Computers in Biology and Medicine Nov 2020Diabetic retinopathy (DR) is a diabetes complication, which in extreme situations may lead to blindness. Since the first stages are often asymptomatic, regular eye...
Diabetic retinopathy (DR) is a diabetes complication, which in extreme situations may lead to blindness. Since the first stages are often asymptomatic, regular eye examinations are required for an early diagnosis. As microaneurysms (MAs) are one of the first signs of DR, several automated methods have been proposed for their detection in order to reduce the ophthalmologists' workload. Although local convergence filters (LCFs) have already been applied for feature extraction, their potential as MA enhancement operators was not explored yet. In this work, we propose a sliding band filter for MA enhancement aiming at obtaining a set of initial MA candidates. Then, a combination of the filter responses with color, contrast and shape information is used by an ensemble of classifiers for final candidate classification. Finally, for each eye fundus image, a score is computed from the confidence values assigned to the MAs detected in the image. The performance of the proposed methodology was evaluated in four datasets. At the lesion level, sensitivities of 64% and 81% were achieved for an average of 8 false positives per image (FPIs) in e-ophtha MA and SCREEN-DR, respectively. In the last dataset, an AUC of 0.83 was also obtained for DR detection.
Topics: Algorithms; Diabetes Mellitus; Diabetic Retinopathy; Early Diagnosis; Fundus Oculi; Humans; Microaneurysm
PubMed: 33007620
DOI: 10.1016/j.compbiomed.2020.103995 -
Bioengineering (Basel, Switzerland) Dec 2023Diabetic retinopathy (DR) is a microvascular complication of diabetes. Microaneurysms (MAs) are often observed in the retinal vessels of diabetic patients and represent...
Diabetic retinopathy (DR) is a microvascular complication of diabetes. Microaneurysms (MAs) are often observed in the retinal vessels of diabetic patients and represent one of the earliest signs of DR. Accurate and efficient detection of MAs is crucial for the diagnosis of DR. In this study, an automatic model (MA-YOLO) is proposed for MA detection in fluorescein angiography (FFA) images. To obtain detailed features and improve the discriminability of MAs in FFA images, SwinIR was utilized to reconstruct super-resolution images. To solve the problems of missed detection of small features and feature information loss, an MA detection layer was added between the neck and the head sections of YOLOv8. To enhance the generalization ability of the MA-YOLO model, transfer learning was conducted between high-resolution images and low-resolution images. To avoid excessive penalization due to geometric factors and address sample distribution imbalance, the loss function was optimized by taking the Wise-IoU loss as a bounding box regression loss. The performance of the MA-YOLO model in MA detection was compared with that of other state-of-the-art models, including SSD, RetinaNet, YOLOv5, YOLOX, and YOLOv7. The results showed that the MA-YOLO model had the best performance in MA detection, as shown by its optimal metrics, including recall, precision, F1 score, and AP, which were 88.23%, 97.98%, 92.85%, and 94.62%, respectively. Collectively, the proposed MA-YOLO model is suitable for the automatic detection of MAs in FFA images, which can assist ophthalmologists in the diagnosis of the progression of DR.
PubMed: 38135996
DOI: 10.3390/bioengineering10121405 -
Acta Ophthalmologica Dec 2023To compare detection rates of microaneurysms (MAs) on high-speed megahertz optical coherence tomography angiography (MHz-OCTA), fluorescein angiography (FA) and colour...
PURPOSE
To compare detection rates of microaneurysms (MAs) on high-speed megahertz optical coherence tomography angiography (MHz-OCTA), fluorescein angiography (FA) and colour fundus photography (CF) in patients with diabetic retinopathy (DR).
METHODS
For this exploratory cross-sectional study, MHz-OCTA data were acquired with a swept-source OCT prototype (A-scan rate: 1.7 MHz), and FA and CF imaging was performed using Optos® California. MA count was manually evaluated on en face MHz-OCTA/FA/CF images within an extended ETDRS grid. Detectability of MAs visible on FA images was evaluated on corresponding MHz-OCTA and CF images. MA distribution and leakage were correlated with detectability on OCTA and CF imaging.
RESULTS
47 eyes with severe DR (n = 12) and proliferative DR (n = 35) were included. MHz-OCTA and CF imaging detected on average 56% and 36% of MAs, respectively. MHz-OCTA detection rate was significantly higher than CF (p < 0.01). The combination of MHz-OCTA and CF leads to an increased detection rate of 70%. There was no statistically significant association between leakage and MA detectability on OCTA (p = 0.13). For CF, the odds of detecting leaking MAs were significantly lower than non-leaking MAs (p = 0.012). Using MHz-OCTA, detection of MAs outside the ETDRS grid was less likely than MAs located within the ETDRS grid (outer ring, p < 0.01; inner ring, p = 0.028). No statistically significant difference between rings was observed for CF measurements.
CONCLUSIONS
More MAs were detected on MHz-OCTA than on CF imaging. Detection rate was lower for MAs located outside the macular region with MHz-OCTA and for leaking MAs with CF imaging. Combining both non-invasive modalities can improve MA detection.
PubMed: 38126128
DOI: 10.1111/aos.16619 -
Biomedicines Jan 2022Retinal microaneurysm (MA) is the initial symptom of diabetic retinopathy (DR). The automatic detection of MA is helpful to assist doctors in diagnosis and treatment....
Retinal microaneurysm (MA) is the initial symptom of diabetic retinopathy (DR). The automatic detection of MA is helpful to assist doctors in diagnosis and treatment. Previous algorithms focused on the features of the target itself; however, the local structural features of the target and background are also worth exploring. To achieve MA detection, an efficient local structure awareness-based retinal MA detection with the multi-feature combination (LSAMFC) is proposed in this paper. We propose a novel local structure feature called a ring gradient descriptor (RGD) to describe the structural differences between an object and its surrounding area. Then, a combination of RGD with the salience and texture features is used by a Gradient Boosting Decision Tree (GBDT) for candidate classification. We evaluate our algorithm on two public datasets, i.e., the e-ophtha MA dataset and retinopathy online challenge (ROC) dataset. The experimental results show that the performance of the trained model significantly improved after combining traditional features with RGD, and the area under the receiver operating characteristic curve (AUC) values in the test results of the datasets e-ophtha MA and ROC increased from 0.9615 to 0.9751 and from 0.9066 to 0.9409, respectively.
PubMed: 35052803
DOI: 10.3390/biomedicines10010124 -
Computer Methods and Programs in... May 2018Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs...
BACKROUND AND OBJECTIVES
Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automatic method for detecting microaneurysms in fundus photographies.
METHODS
A novel patch-based fully convolutional neural network with batch normalization layers and Dice loss function is proposed. Compared to other methods that require up to five processing stages, it requires only three. Furthermore, to the best of the authors' knowledge, this is the first paper that shows how to successfully transfer knowledge between datasets in the microaneurysm detection domain.
RESULTS
The proposed method was evaluated using three publicly available and widely used datasets: E-Ophtha, DIARETDB1, and ROC. It achieved better results than state-of-the-art methods using the FROC metric. The proposed algorithm accomplished highest sensitivities for low false positive rates, which is particularly important for screening purposes.
CONCLUSIONS
Performance, simplicity, and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications.
Topics: Algorithms; Automation; Datasets as Topic; Diabetic Retinopathy; Diagnostic Imaging; Fundus Oculi; Humans; Microaneurysm; Neural Networks, Computer; Photography
PubMed: 29544784
DOI: 10.1016/j.cmpb.2018.02.016