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Clinical Ophthalmology (Auckland, N.Z.) 2020To analyze the subclinical intraocular involvement using multimodal imaging approach in patients affected by Erdheim-Chester disease (ECD) without ocular symptoms.
PURPOSE
To analyze the subclinical intraocular involvement using multimodal imaging approach in patients affected by Erdheim-Chester disease (ECD) without ocular symptoms.
PATIENTS AND METHODS
In this prospective cross-sectional study, 18 eyes of 9 consecutive patients with ECD were enrolled. Each patient underwent comprehensive ocular examination and extensive multimodal chorioretinal imaging.
RESULTS
None of the patients presented any evidence of chorioretinal localization of disease using multimodal imaging. One patient exhibited a choroidal nevus complicated by active polypoidal choroidal neovascularization. Subretinal hyperreflective material was seen in three eyes, mainly resembling acquired vitelliform lesion. One patient had an isolated intraretinal hemorrhage. Most patients exhibited peripheral vascular abnormalities (ie, microaneurysms, peripheral vascular leakage). Fundus autofluorescence showed faint hyperautofluorescence in eleven eyes.
CONCLUSION
Intraocular involvement is an extremely rare event of an extremely rare disease. In patients affected by ECD without ocular symptoms, advance multimodal imaging examinations did not show signs of subclinical chorioretinal involvement related to the disease.
PubMed: 32184546
DOI: 10.2147/OPTH.S224672 -
The British Journal of Ophthalmology Oct 2022This study investigates the association of intraocular cytokine expression and ultrawide-field fluorescein angiography (UWFA) quantitative imaging biomarkers and their...
BACKGROUND
This study investigates the association of intraocular cytokine expression and ultrawide-field fluorescein angiography (UWFA) quantitative imaging biomarkers and their association with angiographical feature response after antivascular endothelial growth factor (VEGF) therapy in diabetic macular oedema (DME).
METHODS
The IMAGINE DME study is a post hoc imaging biomarker and intraocular cytokine assessment from the DAVE study, a prospective DME clinical trial that included aqueous humour sampling and UWFA imaging. Fifty-four cytokines associated with inflammation and angiogenesis were evaluated through multiplex arrays. UWFA parameters were assessed using an automated feature analysis platform to determine ischaemic and leakage indices and microaneurysm (MA) count. Eyes were classified into UWFA responder or non-responder groups based on longitudinal quantitative UWFA parameter improvement. Cytokine expression was correlated with UWFA metrics and evaluated in the context of therapeutic response.
RESULTS
Twenty-one eyes were included with a mean age of 55±10 years. Increased panretinal leakage index correlated with VEGF (r=0.70, p=0.0005), angiopoietin-like 4 (r=0.77, p=4.6E-5) and interleukin (IL)-6 (r=0.64, p=0.002). Panretinal ischaemic index was associated with tissue inhibitor of metalloproteinases 1 (TIMP-1, r=0.49, p=0.03) and peripheral ischaemia correlated with VEGF (r=0.45, p=0.05). MA count correlated with increased monocyte chemotactic protein-4 (MCP-4, r=0.60, p=0.004) and platelet and endothelial cell adhesion molecule 1 (PECAM-1, r=0.58, p=0.005). Longitudinal MA reduction was associated with decreased baseline VEGF and urokinase receptor (uPAR) (p<0.05). High baseline VEGF and IL-6 were associated with dramatic reduction in macular leakage (p<0.05).
CONCLUSIONS
Baseline and longitudinal quantitative UWFA imaging parameters correlated with multiple aqueous humour cytokine concentrations, including VEGF and IL-6. Further research is needed to assess the possible implications of using these findings for evaluating treatment response.
Topics: Angiogenesis Inhibitors; Angiopoietins; Biological Products; Biomarkers; Cell Adhesion Molecule-1; Cytokines; Diabetic Retinopathy; Endothelial Growth Factors; Fluorescein Angiography; Humans; Interleukin-6; Intravitreal Injections; Microaneurysm; Monocyte Chemoattractant Proteins; Phenotype; Platelet Endothelial Cell Adhesion Molecule-1; Prospective Studies; Tissue Inhibitor of Metalloproteinase-1; Urokinase-Type Plasminogen Activator; Vascular Endothelial Growth Factor A; Visual Acuity
PubMed: 34099465
DOI: 10.1136/bjophthalmol-2020-318726 -
The Cochrane Database of Systematic... Dec 2018Diabetic retinopathy is one of the major causes of blindness and the number of cases has risen in recent years. Herbal medicine has been used to treat diabetes and its... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Diabetic retinopathy is one of the major causes of blindness and the number of cases has risen in recent years. Herbal medicine has been used to treat diabetes and its complications including diabetic retinopathy for thousands of years around the world. However, common practice is not always evidence-based. Evidence is needed to help people with diabetic retinopathy or doctors to make judicious judgements about using herbal medicine as treatment.
OBJECTIVES
To evaluate the effectiveness and harm of single herbal medicine for diabetic retinopathy.
SEARCH METHODS
We searched CENTRAL, which contains the Cochrane Eyes and Vision Trials Register, MEDLINE, Embase, OpenGrey, the ISRCTN registry, ClinicalTrials.gov and the ICTRP. The date of the search was 12 June 2018. We also searched the following Chinese databases in June 2013: Chinese BioMedical Literature Database (CBM), Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS), Wanfang China Dissertation Database (CDDB), Wanfang China Conference Paper Database (CCPD) and the Index to Chinese Periodical Literature.
SELECTION CRITERIA
We included randomised controlled trials (RCTs) and quasi-RCTs that investigated the effects of any single herb (or extracts from a single herb) as a treatment for people with diabetic retinopathy. We considered the following comparators: placebo, no treatment, non-herbal (conventional) medicine or surgical treatment.
DATA COLLECTION AND ANALYSIS
Two review authors independently extracted data and assessed the risk of bias in the studies. Our prespecified outcomes were: progression of diabetic retinopathy, visual acuity, microaneurysms and haemorrhages in the retina, blood glycated haemoglobin A1c (HbA1c) (%) and adverse effects. We performed meta-analyses using risk ratios (RR) for dichotomous outcomes and mean differences (MD) for continuous outcomes, with 95% confidence intervals (CI). We assessed the certainty of the evidence using GRADE.
MAIN RESULTS
We included 10 studies involving 754 participants, of which nine were conducted in China and one in Poland. In all studies, participants in both groups received conventional treatment for diabetic retinopathy which included maintaining blood glucose and lipids using medicines and keeping a stable diabetic diet. In three studies, the comparator group also received an additional potentially active comparator in the form of a vasoprotective drug. The single herbs or extracts included Ruscus extract tablet, Sanqi Tongshu capsule, tetramethylpyrazine injection, Xueshuantong injection, Puerarin injection and Xuesaitong injection. The Sanqi Tongshu capsule, Xueshuantong injection and Xuesaitong injection were all made from the extract of Radix Notoginseng (San qi) and the main ingredient was sanchinoside. The risk of bias was high in all included studies mainly due to lack of masking (blinding). None of the studies reported the primary outcome of this review, progression of retinopathy.Combined analysis of herbal interventions suggested that people who took these herbs in combination with conventional treatment may have been more likely to gain 2 or more lines of visual acuity compared to people who did not take these herbs when compared to conventional intervention alone at the end of treatment (RR 1.26, 95% CI 1.08 to 1.48; 5 trials, 541 participants; low-certainty evidence). Subgroup analyses based on the different single herbs found no evidence for different effects of different herbs, but the power of this analysis was low. One study reported Sanqi Tongshu capsule might be associated with a greater reduction in microaneurysms and haemorrhages in the retina (very low-certainty evidence). The pooled analysis of two studies on tetramethylpyrazine or Xueshuantong injection showed such herbs may have had little effect on lowering HbA1c (MD 0.00, 95% CI -0.58 to 0.58; 215 participants; low-certainty evidence).There was very low-certainty evidence on adverse events. Two studies reported minor adverse events such as uncomfortable stomach, urticaria, dizziness and headache. There was no report of observation on adverse events in the other studies.
AUTHORS' CONCLUSIONS
No conclusions could be drawn about the effect of any single herb or herbal extract on diabetic retinopathy from the current available evidence. It was difficult to exclude the placebo effect as a possible explanation for observed differences due to the lack of placebo control in the included studies. Further adequately designed trials are needed to establish the evidence.
Topics: China; Diabetic Retinopathy; Drugs, Chinese Herbal; Ginsenosides; Humans; Isoflavones; Microaneurysm; Phytotherapy; Plants, Medicinal; Pyrazines; Randomized Controlled Trials as Topic; Retinal Hemorrhage; Ruscus; Saponins; Vasodilator Agents; Visual Acuity
PubMed: 30566763
DOI: 10.1002/14651858.CD007939.pub2 -
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 -
Sensors (Basel, Switzerland) Apr 2022Fundus is the only structure that can be observed without trauma to the human body. By analyzing color fundus images, the diagnosis basis for various diseases can be...
Fundus is the only structure that can be observed without trauma to the human body. By analyzing color fundus images, the diagnosis basis for various diseases can be obtained. Recently, fundus image segmentation has witnessed vast progress with the development of deep learning. However, the improvement of segmentation accuracy comes with the complexity of deep models. As a result, these models show low inference speeds and high memory usages when deploying to mobile edges. To promote the deployment of deep fundus segmentation models to mobile devices, we aim to design a lightweight fundus segmentation network. Our observation comes from the fact that high-resolution representations could boost the segmentation of tiny fundus structures, and the classification of small fundus structures depends more on local features. To this end, we propose a lightweight segmentation model called LightEyes. We first design a high-resolution backbone network to learn high-resolution representations, so that the spatial relationship between feature maps can be always retained. Meanwhile, considering high-resolution features means high memory usage; for each layer, we use at most 16 convolutional filters to reduce memory usage and decrease training difficulty. LightEyes has been verified on three kinds of fundus segmentation tasks, including the hard exudate, the microaneurysm, and the vessel, on five publicly available datasets. Experimental results show that LightEyes achieves highly competitive segmentation accuracy and segmentation speed compared with state-of-the-art fundus segmentation models, while running at 1.6 images/s Cambricon-1A speed and 51.3 images/s GPU speed with only 36k parameters.
Topics: Humans; Exudates and Transudates; Fundus Oculi; Image Processing, Computer-Assisted; Neural Networks, Computer; Retinal Vessels
PubMed: 35590802
DOI: 10.3390/s22093112 -
PLoS Computational Biology Jan 2022Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). MA leakage or rupture may precipitate local pathology in the...
Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). MA leakage or rupture may precipitate local pathology in the surrounding neural retina that impacts visual function. Thrombosis in MAs may affect their turnover time, an indicator associated with visual and anatomic outcomes in the diabetic eyes. In this work, we perform computational modeling of blood flow in microchannels containing various MAs to investigate the pathologies of MAs in DR. The particle-based model employed in this study can explicitly represent red blood cells (RBCs) and platelets as well as their interaction in the blood flow, a process that is very difficult to observe in vivo. Our simulations illustrate that while the main blood flow from the parent vessels can perfuse the entire lumen of MAs with small body-to-neck ratio (BNR), it can only perfuse part of the lumen in MAs with large BNR, particularly at a low hematocrit level, leading to possible hypoxic conditions inside MAs. We also quantify the impacts of the size of MAs, blood flow velocity, hematocrit and RBC stiffness and adhesion on the likelihood of platelets entering MAs as well as their residence time inside, two factors that are thought to be associated with thrombus formation in MAs. Our results show that enlarged MA size, increased blood velocity and hematocrit in the parent vessel of MAs as well as the RBC-RBC adhesion promote the migration of platelets into MAs and also prolong their residence time, thereby increasing the propensity of thrombosis within MAs. Overall, our work suggests that computational simulations using particle-based models can help to understand the microvascular pathology pertaining to MAs in DR and provide insights to stimulate and steer new experimental and computational studies in this area.
Topics: Blood Flow Velocity; Computer Simulation; Diabetic Retinopathy; Erythrocytes; Hematocrit; Humans; Microaneurysm; Retinal Vessels; Thrombosis
PubMed: 34986147
DOI: 10.1371/journal.pcbi.1009728 -
Acta Diabetologica Feb 2021To characterize the progression in retinopathy severity of different phenotypes of mild nonproliferative diabetic retinopathy (NPDR) in patients with type 2 diabetes.
PURPOSE
To characterize the progression in retinopathy severity of different phenotypes of mild nonproliferative diabetic retinopathy (NPDR) in patients with type 2 diabetes.
DESIGN AND METHODS
Patients with type 2 diabetes and mild NPDR (ETDRS 20 or 35) were followed in a 5-year longitudinal study. Examinations, including color fundus photography (CFP) and optical coherence tomography (OCT and OCTA), were performed at baseline, 6 months and then annually. Phenotype classification was performed based on microaneurysm turnover (MAT, on CFP) and central retinal thickness (CRT, on OCT). Phenotype A is characterized by low MAT (< 6) and normal CRT; Phenotype B by low MAT (< 6) and increased CRT; and Phenotype C by higher MAT (≥ 6) with or without increased CRT. ETDRS grading of seven fields CFP was performed at the initial and last visits.
RESULTS
Analysis of ETDRS grade step changes showed significant differences in diabetic retinopathy (DR) progression between the different phenotypes (p < 0.001). Of the 66 participants with phenotype A only 2 eyes (3%) presented 2-or-more-step worsening. None of the 50 participants characterized as phenotype B developed 2-step worsening, whereas 13 eyes (23.2%) characterized as phenotype C had 2-or-more-steps worsening. Phenotype C presents the higher risk for 2-or-more step worsening (OR: 15.94 95% CI: 3.45-73.71; p < 0.001) and higher sensitivity, correctly identifying 86.7% of cases at risk (AUC: 0.84 95% CI: 0.72-0.96; p < 0.001). Diabetic retinopathy severity progression was associated with HbA (p = 0.019), LDL levels (p = 0.043), and ocular factors as MAT (p = 0.010), MA formation rate (p = 0.014) and MA disappearance rate (p = 0.005). Capillary closure at 5-year follow-up, identified by lower vessel density (VD) on OCTA, was also associated with diabetic DR severity progression (p = 0.035).
CONCLUSIONS
Different DR phenotypes in type 2 diabetes show different risks of retinopathy progression. Phenotype C is associated with increased HbA values and presents a higher risk of a 2-or-more-step worsening of the ETDRS severity score.
Topics: Aged; Capillaries; Cohort Studies; Diabetes Mellitus, Type 2; Diabetic Retinopathy; Disease Progression; Female; Fundus Oculi; Humans; Longitudinal Studies; Male; Microaneurysm; Middle Aged; Phenotype; Photography; Prognosis; Retina; Retinal Artery; Tomography, Optical Coherence
PubMed: 33025221
DOI: 10.1007/s00592-020-01602-9 -
Scientific Reports Jan 2022Diabetic retinopathy (DR) is a frequent vascular complication of diabetes mellitus and remains a leading cause of vision loss worldwide. Microaneurysm (MA) is usually...
Diabetic retinopathy (DR) is a frequent vascular complication of diabetes mellitus and remains a leading cause of vision loss worldwide. Microaneurysm (MA) is usually the first symptom of DR that leads to blood leakage in the retina. Periodic detection of MAs will facilitate early detection of DR and reduction of vision injury. In this study, we proposed a novel model for the detection of MAs in fluorescein fundus angiography (FFA) images based on the improved FC-DenseNet, MAs-FC-DenseNet. FFA images were pre-processed by the Histogram Stretching and Gaussian Filtering algorithm to improve the quality of FFA images. Then, MA regions were detected by the improved FC-DenseNet. MAs-FC-DenseNet was compared against other FC-DenseNet models (FC-DenseNet56 and FC-DenseNet67) or the end-to-end models (DeeplabV3+ and PSPNet) to evaluate the detection performance of MAs. The result suggested that MAs-FC-DenseNet had higher values of evaluation metrics than other models, including pixel accuracy (PA), mean pixel accuracy (MPA), precision (Pre), recall (Re), F1-score (F1), and mean intersection over union (MIoU). Moreover, MA detection performance for MAs-FC-DenseNet was very close to the ground truth. Taken together, MAs-FC-DenseNet is a reliable model for rapid and accurate detection of MAs, which would be used for mass screening of DR patients.
Topics: Diabetic Retinopathy; Fluorescein Angiography; Humans; Image Processing, Computer-Assisted; Mass Screening; Microaneurysm; Models, Theoretical
PubMed: 35046432
DOI: 10.1038/s41598-021-04750-2 -
Eye (London, England) Jan 2021The introduction of optical coherence tomography angiography (OCTA) has remarkably expanded our knowledge of the ocular vascular alterations occurring in diabetes. In... (Review)
Review
The introduction of optical coherence tomography angiography (OCTA) has remarkably expanded our knowledge of the ocular vascular alterations occurring in diabetes. In this article, a review of the prominent OCTA findings in diabetes is followed by a description of salient histological and anatomical features of microaneurysms, essential for the proper interpretation of in vivo imaging of these retinal vascular abnormalities. The recent employment of a three-dimensional (3D) visualization in OCTA imaging is also discussed. The latter imaging technique has granted a detailed characterization of microaneurysms in vivo.
Topics: Diabetes Mellitus; Diabetic Retinopathy; Fluorescein Angiography; Humans; Microaneurysm; Retinal Vessels; Tomography, Optical Coherence
PubMed: 32887935
DOI: 10.1038/s41433-020-01173-7 -
Biomedical Engineering Online Apr 2020As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention....
BACKGROUND
As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention. Microaneurysms appear as the earliest symptom of DR. Accurate and reliable detection of microaneurysms in color fundus images has great importance for DR screening.
METHODS
A microaneurysms' detection method using machine learning based on directional local contrast (DLC) is proposed for the early diagnosis of DR. First, blood vessels were enhanced and segmented using improved enhancement function based on analyzing eigenvalues of Hessian matrix. Next, with blood vessels excluded, microaneurysm candidate regions were obtained using shape characteristics and connected components analysis. After image segmented to patches, the features of each microaneurysm candidate patch were extracted, and each candidate patch was classified into microaneurysm or non-microaneurysm. The main contributions of our study are (1) making use of directional local contrast in microaneurysms' detection for the first time, which does make sense for better microaneurysms' classification. (2) Applying three different machine learning techniques for classification and comparing their performance for microaneurysms' detection. The proposed algorithm was trained and tested on e-ophtha MA database, and further tested on another independent DIARETDB1 database. Results of microaneurysms' detection on the two databases were evaluated on lesion level and compared with existing algorithms.
RESULTS
The proposed method has achieved better performance compared with existing algorithms on accuracy and computation time. On e-ophtha MA and DIARETDB1 databases, the area under curve (AUC) of receiver operating characteristic (ROC) curve was 0.87 and 0.86, respectively. The free-response ROC (FROC) score on the two databases was 0.374 and 0.210, respectively. The computation time per image with resolution of 2544×1969, 1400×960 and 1500×1152 is 29 s, 3 s and 2.6 s, respectively.
CONCLUSIONS
The proposed method using machine learning based on directional local contrast of image patches can effectively detect microaneurysms in color fundus images and provide an effective scientific basis for early clinical DR diagnosis.
Topics: Area Under Curve; Fundus Oculi; Humans; Image Processing, Computer-Assisted; Machine Learning; Microaneurysm; Molecular Imaging; ROC Curve; Time Factors
PubMed: 32295576
DOI: 10.1186/s12938-020-00766-3