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Chinese Medical Journal Jun 2024
PubMed: 38879807
DOI: 10.1097/CM9.0000000000003166 -
Biomedical Engineering Online May 2019Diabetic retinopathy (DR) is the leading cause of blindness worldwide, and therefore its early detection is important in order to reduce disease-related eye injuries. DR...
BACKGROUND AND OBJECTIVES
Diabetic retinopathy (DR) is the leading cause of blindness worldwide, and therefore its early detection is important in order to reduce disease-related eye injuries. DR is diagnosed by inspecting fundus images. Since microaneurysms (MA) are one of the main symptoms of the disease, distinguishing this complication within the fundus images facilitates early DR detection. In this paper, an automatic analysis of retinal images using convolutional neural network (CNN) is presented.
METHODS
Our method incorporates a novel technique utilizing a two-stage process with two online datasets which results in accurate detection while solving the imbalance data problem and decreasing training time in comparison with previous studies. We have implemented our proposed CNNs using the Keras library.
RESULTS
In order to evaluate our proposed method, an experiment was conducted on two standard publicly available datasets, i.e., Retinopathy Online Challenge dataset and E-Ophtha-MA dataset. Our results demonstrated a promising sensitivity value of about 0.8 for an average of >6 false positives per image, which is competitive with state of the art approaches.
CONCLUSION
Our method indicates significant improvement in MA-detection using retinal fundus images for monitoring diabetic retinopathy.
Topics: Deep Learning; Fundus Oculi; Image Processing, Computer-Assisted; Microaneurysm; Tomography, X-Ray Computed
PubMed: 31142335
DOI: 10.1186/s12938-019-0675-9 -
Acta Ophthalmologica Sep 2021To investigate the relationship between microaneurysm (MA) density and residual oedema after intravitreal injection of an anti-vascular endothelial growth factor agent... (Comparative Study)
Comparative Study
PURPOSE
To investigate the relationship between microaneurysm (MA) density and residual oedema after intravitreal injection of an anti-vascular endothelial growth factor agent for the treatment of diabetic macular oedema (DMO).
METHODS
Patients with DMO were divided into those with residual oedema (RO) and those with no residual oedema (NRO) by the presence and absence of oedema at 1 month after intravitreal injection of either aflibercept or ranibizumab. We then compared MA density, best corrected visual acuity (BCVA), central retinal thickness (CRT) and size of the severely thickened area, as indicated by a white area (WA) on optical coherence tomography.
RESULTS
We examined 48 eyes in the RO group and 25 eyes in the NRO group (n = 73). In both groups, the CRT and WA size significantly decreased and BCVA improved at 1 month and thereafter. CRT was significantly higher and BCVA was poor in the RO group at 1 and 3 months, while WA size was larger at 1, 3 and 6 months compared with the NRO group (p < 0.05). The number of injections in the RO group (3.62 ± 1.75) was larger than the NRO group (1.89 ± 0.97; p < 0.0001). At 1 and 6 months, the MA density in the area with persistent oedema was significantly higher than in the area with improved oedema (1 month: p = 0.0001, 6 months: p = 0.029).
CONCLUSION
High MA density and extensive swelling may be characteristic of RO following treatment for DMO with intravitreal injection of either aflibercept or ranibizumab.
Topics: Aged; Angiogenesis Inhibitors; Diabetic Retinopathy; Female; Follow-Up Studies; Humans; Intravitreal Injections; Macula Lutea; Macular Edema; Male; Microaneurysm; Microvascular Density; Middle Aged; Ranibizumab; Receptors, Vascular Endothelial Growth Factor; Recombinant Fusion Proteins; Retinal Artery; Retrospective Studies; Tomography, Optical Coherence; Treatment Outcome
PubMed: 33326191
DOI: 10.1111/aos.14706 -
Clinical Practice and Cases in... Aug 2022We present the case of an older male with point-of-care-ultrasound (POCUS) imaging consistent with retinal detachment who was instead found by ophthalmology to have a...
CASE PRESENTATION
We present the case of an older male with point-of-care-ultrasound (POCUS) imaging consistent with retinal detachment who was instead found by ophthalmology to have a ruptured arterial microaneurysm with vitreous and preretinal hemorrhage. The patient later had complete resolution of his symptoms. We discuss this retinal detachment "mimic."
DISCUSSION
Preretinal hemorrhage is an uncommon condition that can be mistaken for ophthalmologic emergencies such as retinal detachment. The images and videos shown here add to the body of evidence that POCUS is useful in diagnosing pre-retinal hemorrhage but must be differ-entiated from retinal detachment. These images also emphasize the need for further research and application of POCUS for the identification of preretinal hemorrhage.
PubMed: 36049192
DOI: 10.5811/cpcem2022.4.55301 -
Investigative Ophthalmology & Visual... Oct 2023Microaneurysm (MA) plays an important role in the pathogenesis of diabetic macular edema (DME) progression and response to anti-vascular endothelial growth factor (VEGF)...
PURPOSE
Microaneurysm (MA) plays an important role in the pathogenesis of diabetic macular edema (DME) progression and response to anti-vascular endothelial growth factor (VEGF) therapy. This study aimed to investigate the effect of faricimab, a bispecific antibody against angiopoietin-2 and VEGF, on the number of MAs and their turnover in the treatment of DME.
METHODS
We included that patients with DME who underwent three monthly injections of faricimab in one eye, with the other eye as control. We examined central retinal thickness (CRT) based on optical coherence tomography (OCT) and best-corrected visual acuity. Turnover, including loss and newly formed MAs, and the total number of MAs were counted based on merged images of the OCT map and fluorescein angiography.
RESULTS
We enrolled 28 patients with DME. After 3 monthly injections of faricimab, CRT significantly improved, 66.0 ± 16.2% of MAs disappeared, and 6.71 ± 5.6% of new MAs were generated, resulting in total reduction to 40.7 ± 15.2%. In the treated eyes, MA disappearance (P < 0.0001) and turnover (P = 0.007) were significantly greater, and new formation was smaller (P < 0.0001) than in non-treated eyes. The size of the retained MAs decreased after treatment. Microaneurysm turnover was not significantly different between areas with and without edema before treatment.
CONCLUSIONS
In the process of improving edema in DME with faricimab, MAs shrink and disappear, and formation of MAs are inhibited, resulting in decreased total number of MAs. Intravitreal administration of faricimab suppresses vascular permeability and improves vascular structure.
Topics: Humans; Macular Edema; Diabetic Retinopathy; Vascular Endothelial Growth Factor A; Angiogenesis Inhibitors; Microaneurysm; Intravitreal Injections; Edema; Tomography, Optical Coherence; Diabetes Mellitus
PubMed: 37856112
DOI: 10.1167/iovs.64.13.31 -
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 -
Journal of Clinical Medicine May 2021Analysis of retinal microaneurysm turnover (MAT) has been previously shown to contribute to the identification of eyes at risk of developing clinically significant...
Microaneurysm Turnover in Mild Non-Proliferative Diabetic Retinopathy is Associated with Progression and Development of Vision-Threatening Complications: A 5-Year Longitudinal Study.
BACKGROUND
Analysis of retinal microaneurysm turnover (MAT) has been previously shown to contribute to the identification of eyes at risk of developing clinically significant complications associated with diabetic retinopathy (DR). We propose to further characterize MAT as a predictive biomarker of DR progression and development of vision-threatening complications.
METHODS
212 individuals with type 2 diabetes (T2D; ETDRS grades 20 and 35) were evaluated annually in a 5-year prospective, longitudinal study, by color fundus photography and optical coherence tomography. Endpoints were diabetic macular edema (DME) or proliferative retinopathy (PDR). MAT analysis included determination of MA formation and disappearance rates, automatically assessed using the RetMarkerDR. Retinopathy severity progression was evaluated using step increases in ETDRS severity levels.
RESULTS
Of the 212 individuals, 172 completed the 5-year follow-up study or developed an endpoint (n = 27). MAT calculated at 1 year showed a significant difference between groups of endpoint developments ( = 0.018), particularly MA disappearance rate ( = 0.007). MAT also showed a significant difference between eyes with different ETDRS severity progression in the 5-year period ( = 0.035).
CONCLUSIONS
MAT is an indicator of the development of DME and/or PDR as well as of DR severity progression in T2D individuals with mild retinopathy.
PubMed: 34063514
DOI: 10.3390/jcm10102142 -
Journal of Digital Imaging Apr 2018Automated microaneurysm (MA) detection is still an open challenge due to its small size and similarity with blood vessels. In this paper, we present a novel method which...
Automated microaneurysm (MA) detection is still an open challenge due to its small size and similarity with blood vessels. In this paper, we present a novel method which is simple, efficient, and real-time for segmenting and detecting MA in color fundus images (CFI). To do this, a novel set of features based on statistics of geometrical properties of connected regions, that can easily discriminate lesion and non-lesion pixels are used. For large-scale evaluation proposed method is validated on DIARETDB1, ROC, STARE, and MESSIDOR dataset. It proves robust with respect to different image characteristics and camera settings. The best performance was achieved on per-image evaluation on DIARETDB1 dataset with sensitivity of 88.09 at 92.65% specificity which is quite encouraging for clinical use.
Topics: Databases, Factual; Diabetic Retinopathy; Diagnostic Techniques, Ophthalmological; Fundus Oculi; Humans; Image Interpretation, Computer-Assisted; Microaneurysm; Sensitivity and Specificity
PubMed: 28785874
DOI: 10.1007/s10278-017-0008-0 -
American Journal of Ophthalmology Case... Jun 2020A 63-year-old healthy woman was referred for a retinal examination. Dilated fundus examination of the left eye revealed small retinal hemorrhage with surrounding...
A 63-year-old healthy woman was referred for a retinal examination. Dilated fundus examination of the left eye revealed small retinal hemorrhage with surrounding exudation, most consistent with a large retinal microaneurysm, which was confirmed by fluorescein angiography and optical coherence tomography angiography (OCT-A). OCT-A has the potential to clearly delineate the anatomy of retinal aneurysms and could be used for diagnosis and surveillance, possibly replacing the current gold-standard fluorescein angiography.
PubMed: 32373757
DOI: 10.1016/j.ajoc.2020.100690 -
IEEE Transactions on Nanobioscience Jul 2018Diabetic retinopathy (DR) is an eye abnormality caused by long-term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs),...
Diabetic retinopathy (DR) is an eye abnormality caused by long-term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs), resulting from leakage from retinal blood vessels, are early indicators of DR. In this paper, we analyzed MA detectability using small 25 by 25 pixel patches extracted from fundus images in the DIAbetic RETinopathy DataBase - Calibration Level 1 (DIARETDB1). Raw pixel intensities of extracted patches served directly as inputs into the following classifiers: random forest (RF), neural network, and support vector machine. We also explored the use of two techniques (principal component analysis and RF feature importance) for reducing input dimensionality. With traditional machine learning methods and leave-10-patients-out cross validation, our method outperformed a deep learning-based MA detection method, with AUC performance improved from 0.962 to 0.985 and F-measure improved from 0.913 to 0.926, using the same DIARETDB1 database. Furthermore, we validated our method on a different dataset-retinopathy online challenge (ROC) data set. The performance of the three classifiers and the pattern with different percentage of principal components are consistent on the two data sets. Especially, we trained the RF on DIARETDB1 and applied it to ROC; the performance is very similar to that of the RF trained and tested using cross validation on ROC data set. This result indicates that our method has the potential to generalize to different datasets.
Topics: Diabetic Retinopathy; Humans; Image Interpretation, Computer-Assisted; Machine Learning; Microaneurysm; Neural Networks, Computer; Principal Component Analysis; Support Vector Machine
PubMed: 29994317
DOI: 10.1109/TNB.2018.2840084