-
Acta Neurochirurgica May 2024A 40-year-old female with a history of ischemic moyamoya disease treated with indirect revascularization at ages 12 and 25 years presented with a sudden severe...
A 40-year-old female with a history of ischemic moyamoya disease treated with indirect revascularization at ages 12 and 25 years presented with a sudden severe headache. Imaging studies revealed focal parenchymal hemorrhage and acute subdural hematoma, confirming a microaneurysm formed on the postoperative transosseous vascular network as the source of bleeding. Conservative management was performed, and no hemorrhage recurred during the 6-month follow-up period. Interestingly, follow-up imaging revealed spontaneous occlusion of the microaneurysm. However, due to the rarity of this presentation, the efficacy of conservative treatment remains unclear. Further research on similar cases is warranted.
Topics: Humans; Moyamoya Disease; Female; Adult; Cerebral Revascularization; Aneurysm, Ruptured; Postoperative Complications; Intracranial Aneurysm; Anastomosis, Surgical
PubMed: 38719974
DOI: 10.1007/s00701-024-06102-1 -
Medical & Biological Engineering &... May 2024Most diabetes patients are liable to have diabetic retinopathy (DR); however, the majority of them might not be even aware of the ailment. Therefore, early detection and...
Most diabetes patients are liable to have diabetic retinopathy (DR); however, the majority of them might not be even aware of the ailment. Therefore, early detection and treatment of DR are necessary to prevent vision loss. But, avoiding DR is not a simple process. An ophthalmologist can typically identify DR through an optical evaluation of the fundus and through the evaluation of color pictures. However, due to the increased count of DR patients, this could not be possible as it consumes more time. To rectify this problem, a novel deep ensemble-based DR classification technique is developed in this work. Initially, a Wiener filter (WF) is applied for preprocessing the image. Then, the enhanced U-Net-based segmentation process is done. Subsequent to the segmentation process, features are extracted that include statistical features, inferior superior nasal temporal (ISNT), cup to disc ratio (CDR), and improved LGBP as well. Further, deep ensemble classifiers (DEC) like CNN, Bi-GRU, and DMN are used to recognize the disease. The outcomes from DMN, CNN, and Bi-GRU are then subjected to improved SLF. Additionally, the weights of DMN, CNN, and Bi-GRU are adjusted via pelican updated Tasmanian devil optimization (PU-TDO). Finally, outputs on DR (microaneurysms, hemorrhages, hard exudates, and soft exudates) are obtained. The performance of DEC + PU-TDO for diabetic retinopathy is computed over extant models with regard to different measures for four datasets. The results on accuracy using the DEC + PU-TDO scheme for the IDRID dataset is maximum around 0.975 at 90th LP while other models have less accuracy. The FPR of DEC + PU-TDO is less around 0.039 at the 90th LP for the SUSTech-SYSU dataset, while other extant models have maximum FPR.
PubMed: 38713340
DOI: 10.1007/s11517-024-03076-1 -
PeerJ. Computer Science 2024Diabetic retinopathy (DR) is the leading cause of visual impairment globally. It occurs due to long-term diabetes with fluctuating blood glucose levels. It has become a...
Diabetic retinopathy (DR) is the leading cause of visual impairment globally. It occurs due to long-term diabetes with fluctuating blood glucose levels. It has become a significant concern for people in the working age group as it can lead to vision loss in the future. Manual examination of fundus images is time-consuming and requires much effort and expertise to determine the severity of the retinopathy. To diagnose and evaluate the disease, deep learning-based technologies have been used, which analyze blood vessels, microaneurysms, exudates, macula, optic discs, and hemorrhages also used for initial detection and grading of DR. This study examines the fundamentals of diabetes, its prevalence, complications, and treatment strategies that use artificial intelligence methods such as machine learning (ML), deep learning (DL), and federated learning (FL). The research covers future studies, performance assessments, biomarkers, screening methods, and current datasets. Various neural network designs, including recurrent neural networks (RNNs), generative adversarial networks (GANs), and applications of ML, DL, and FL in the processing of fundus images, such as convolutional neural networks (CNNs) and their variations, are thoroughly examined. The potential research methods, such as developing DL models and incorporating heterogeneous data sources, are also outlined. Finally, the challenges and future directions of this research are discussed.
PubMed: 38699206
DOI: 10.7717/peerj-cs.1947 -
Scientific Reports May 2024The impact of aging on diabetic retinopathy (DR) remains underestimated. The current study aimed to investigate the association between biological aging and DR, in...
The impact of aging on diabetic retinopathy (DR) remains underestimated. The current study aimed to investigate the association between biological aging and DR, in contrast to chronological age (CA). Using the National Health and Nutrition Survey data from 2005 to 2008. Biological aging was evaluated through the biological age (BA) and phenotypic age (PA), which were calculated from clinical markers. DR was identified in participants with diabetes mellitus (DM) when they exhibited one or more retinal microaneurysms or retinal blot hemorrhages under retinal imaging, with or without the presence of more severe lesions. Survey-weighted multivariable logistic regression was performed, and the regression model was further fitted using restricted cubic splines. The discriminatory capability and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Based on weighted analyses, of the 3100 participants included in this study, of which 162 had DR. In the adjusted model, BA (odds ratio [OR] = 1.12, 95% CI, 1.06-1.18) and PA (OR = 1.11, 95% CI, 1.07-1.14) were associated with DR, while CA was not significantly (OR = 1.01, 95% CI, 0.99-1.03). Narrowing the analysis to DM participants and adjusting for factors like insulin showed similar results. ROC and DCA analyses indicate that BA/PA predicted DR better than CA and offer greater clinical utility. The positive association between BA/PA and DR was consistent across subgroups despite potential interactions. Biological aging heightens DR risk, with BA/PA showing a stronger association than CA. Our findings underscored the importance of timely anti-aging interventions for preventing DR.
Topics: Humans; Diabetic Retinopathy; Male; Female; Aging; Middle Aged; Aged; Risk Factors; ROC Curve; Adult; Nutrition Surveys
PubMed: 38698194
DOI: 10.1038/s41598-024-60913-x -
Current Vascular Pharmacology Apr 2024Studies on the early retinal changes in Diabetic Retinopathy (DR) have demonstrated that neurodegeneration precedes vascular abnormalities like microaneurysms or...
BACKGROUND
Studies on the early retinal changes in Diabetic Retinopathy (DR) have demonstrated that neurodegeneration precedes vascular abnormalities like microaneurysms or intraretinal hemorrhages. Therefore, there is a growing field of study to analyze the cellular and molecular pathways involved to allow for the development of novel therapeutics to prevent the onset or delay the progression of DR. Molecular Mechanisms: Oxidative stress and mitochondrial dysfunction contribute to neurodegeneration through pathways involving polyol, hexosamine, advanced glycation end products, and protein kinase C. Potential interventions targeting these pathways include aldose reductase inhibitors and protein kinase C inhibitors. Neurotrophic factor imbalances, notably brain-derived neurotrophic factor and nerve growth factor, also play a role in early neurodegeneration, and supplementation of these neurotrophic factors show promise in mitigating neurodegeneration. Cellular Mechanisms: Major cellular mechanisms of neurodegeneration include caspase-mediated apoptosis, glial cell reactivity, and glutamate excitotoxicity. Therefore, inhibitors of these pathways are potential therapeutic avenues. Vascular Component: The nitric oxide pathway, critical for neurovascular coupling, is disrupted in DR due to increased reactive oxygen species. Vascular Endothelial Growth Factor (VEGF), a long-known angiogenic factor, has demonstrated both damaging and neuroprotective effects, prompting a careful consideration of long-term anti-VEGF therapy.
CONCLUSION
Current DR treatments primarily address vascular symptoms but fall short of preventing or halting the disease. Insights into the mechanisms of retinal neurodegeneration in the setting of diabetes mellitus not only enhance our understanding of DR but also pave the way for future therapeutic interventions aimed at preventing disease progression and preserving vision.
PubMed: 38693745
DOI: 10.2174/0115701611272737240426050930 -
Cureus Mar 2024Behçet's disease is a rare autoimmune condition characterized by systemic vasculitis, an inflammation of blood vessels, with an unknown etiology. It has varied clinical...
Behçet's disease is a rare autoimmune condition characterized by systemic vasculitis, an inflammation of blood vessels, with an unknown etiology. It has varied clinical presentations. Herein, we present the case of a 31-year-old male patient with neuro-Behçet disease who presented with subarachnoid hemorrhage and microaneurysms.
PubMed: 38686277
DOI: 10.7759/cureus.57275 -
Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.Medical & Biological Engineering &... Apr 2024Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level...
Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level poses a challenge as each pixel does not reflect any semantic entities. Furthermore, the computational cost of inspecting each pixel is expensive because the number of pixels is high even at low resolution. In this work, we propose a hybrid image processing method. Simple Linear Iterative Clustering with Gaussian Filter (SLIC-G) for the purpose of overcoming pixel constraints. The SLIC-G image processing method is divided into two stages: (1) simple linear iterative clustering superpixel segmentation and (2) Gaussian smoothing operation. In such a way, a large number of new transformed datasets are generated and then used for model training. Finally, two performance evaluation metrics that are suitable for imbalanced diabetic retinopathy datasets were used to validate the effectiveness of the proposed SLIC-G. The results indicate that, in comparison to prior published works' results, the proposed SLIC-G shows better performance on image classification of class imbalanced diabetic retinopathy datasets. This research reveals the importance of image processing and how it influences the performance of deep learning networks. The proposed SLIC-G enhances pre-trained network performance by eliminating the local redundancy of an image, which preserves local structures, but avoids over-segmented, noisy clips. It closes the research gap by introducing the use of superpixel segmentation and Gaussian smoothing operation as image processing methods in diabetic retinopathy-related tasks.
PubMed: 38649629
DOI: 10.1007/s11517-024-03093-0 -
International Journal of Ophthalmology 2024To propose an algorithm for automatic detection of diabetic retinopathy (DR) lesions based on ultra-widefield scanning laser ophthalmoscopy (SLO).
AIM
To propose an algorithm for automatic detection of diabetic retinopathy (DR) lesions based on ultra-widefield scanning laser ophthalmoscopy (SLO).
METHODS
The algorithm utilized the FasterRCNN (Faster Regions with CNN features)+ResNet50 (Residua Network 50)+FPN (Feature Pyramid Networks) method for detecting hemorrhagic spots, cotton wool spots, exudates, and microaneurysms in DR ultra-widefield SLO. Subimage segmentation combined with a deeper residual network FasterRCNN+ResNet50 was employed for feature extraction to enhance intelligent learning rate. Feature fusion was carried out by the feature pyramid network FPN, which significantly improved lesion detection rates in SLO fundus images.
RESULTS
By analyzing 1076 ultra-widefield SLO images provided by our hospital, with a resolution of 2600×2048 dpi, the accuracy rates for hemorrhagic spots, cotton wool spots, exudates, and microaneurysms were found to be 87.23%, 83.57%, 86.75%, and 54.94%, respectively.
CONCLUSION
The proposed algorithm demonstrates intelligent detection of DR lesions in ultra-widefield SLO, providing significant advantages over traditional fundus color imaging intelligent diagnosis algorithms.
PubMed: 38638262
DOI: 10.18240/ijo.2024.04.02 -
Cornea Apr 2024The diagnosis of conjunctival squamous intraepithelial neoplasia (CSIN) can be difficult because of the heterogeneous appearance. Despite established risk factors and...
PURPOSE
The diagnosis of conjunctival squamous intraepithelial neoplasia (CSIN) can be difficult because of the heterogeneous appearance. Despite established risk factors and diagnostic support by high-resolution optical coherence tomography (hrOCT) and indocyanine green angiography (ICGA), the only reliable diagnostic method is a histological work-up. This case report is the first to describe corneal microaneurysms in CSIN as a vascular feature for conjunctival tumor angiogenesis.
METHODS
An 84-year-old male patient was referred with a suspected diagnosis of pterygium. Biomicroscopic examination revealed a whitish epithelial lesion of conjunctival origin with centripetal corneal growth and extension over 5 limbal hours. Intralesional vascularization showed highly altered morphology with aneurysmal changes. After imaging with hrOCT and ICGA, excision was performed in a "no-touch double-freeze and thaw" technique, followed by histological and immunohistochemical work-up.
RESULTS
hrOCT showed an epithelial, hyperreflective lesion with a maximum thickness of 272 µm and sharp central border. ICGA confirmed active perfusion and partial thrombosis of the aneurysmal terminal vascular buds dilated to 405 μm with early dye leakage within the first minute. Histological examination confirmed the clinical diagnosis of CSIN with focal high-grade dysplasia. Postoperatively, there was no recurrence during the observation period of 5 months.
CONCLUSIONS
Intralesional terminal microaneurysms are a feature of tumor angiogenesis in CSIN. The relevance and frequency of this potential new risk factor for malignancy should be investigated in further studies.
PubMed: 38635480
DOI: 10.1097/ICO.0000000000003549 -
PLoS Pathogens Apr 2024SARS-CoV-2 has been shown to cause wide-ranging ocular abnormalities and vision impairment in COVID-19 patients. However, there is limited understanding of SARS-CoV-2 in...
SARS-CoV-2 has been shown to cause wide-ranging ocular abnormalities and vision impairment in COVID-19 patients. However, there is limited understanding of SARS-CoV-2 in ocular transmission, tropism, and associated pathologies. The presence of viral RNA in corneal/conjunctival tissue and tears, along with the evidence of viral entry receptors on the ocular surface, has led to speculation that the eye may serve as a potential route of SARS-CoV-2 transmission. Here, we investigated the interaction of SARS-CoV-2 with cells lining the blood-retinal barrier (BRB) and the role of the eye in its transmission and tropism. The results from our study suggest that SARS-CoV-2 ocular exposure does not cause lung infection and moribund illness in K18-hACE2 mice despite the extended presence of viral remnants in various ocular tissues. In contrast, intranasal exposure not only resulted in SARS-CoV-2 spike (S) protein presence in different ocular tissues but also induces a hyperinflammatory immune response in the retina. Additionally, the long-term exposure to viral S-protein caused microaneurysm, retinal pigmented epithelium (RPE) mottling, retinal atrophy, and vein occlusion in mouse eyes. Notably, cells lining the BRB, the outer barrier, RPE, and the inner barrier, retinal vascular endothelium, were highly permissive to SARS-CoV-2 replication. Unexpectedly, primary human corneal epithelial cells were comparatively resistant to SARS-CoV-2 infection. The cells lining the BRB showed induced expression of viral entry receptors and increased susceptibility towards SARS-CoV-2-induced cell death. Furthermore, hyperglycemic conditions enhanced the viral entry receptor expression, infectivity, and susceptibility of SARS-CoV-2-induced cell death in the BRB cells, confirming the reported heightened pathological manifestations in comorbid populations. Collectively, our study provides the first evidence of SARS-CoV-2 ocular tropism via cells lining the BRB and that the virus can infect the retina via systemic permeation and induce retinal inflammation.
Topics: SARS-CoV-2; Animals; Blood-Retinal Barrier; COVID-19; Mice; Humans; Retina; Angiotensin-Converting Enzyme 2; Virus Internalization; Spike Glycoprotein, Coronavirus; Inflammation; Betacoronavirus; Viral Tropism; Coronavirus Infections
PubMed: 38598560
DOI: 10.1371/journal.ppat.1012156