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Bratislavske Lekarske Listy 2024Diabetic Retinopathy (DR) is a widespread intense stage of diabetes mellitus that causes vision-effecting anomalies in the retina. It is a medical health condition on...
BACKGROUND
Diabetic Retinopathy (DR) is a widespread intense stage of diabetes mellitus that causes vision-effecting anomalies in the retina. It is a medical health condition on the strength of fluctuating glucose level in the blood that can result in vision loss in case of severity.
OBJECTIVE
As a result, early detection and treatment with DR is the most significant task which will tremendously reduce the likelihood of vision impairment and is still a difficult challenge. Many conventional methods fail to detect primary causes of formation of Microaneurysms, that are used to determine the Prediagnosis of DR.
METHOD
To overcome this challenge, the proposed model incorporates Harris Hawk Optimization with CNN-Bi-LSTM (HHO-CBL) to extract the features. The Prediagnosis of DR has been achieved through this model by spotting saccular dilations, hyaline like material in the capillary aneurysm wall, kinking of vessels since these are the indications for the creation of microaneurysms that are spotted in the blood vessel of the retina. The recommended model is also used to automatically detect DR and its progression in many phases. Furthermore, in order to identify the severity of DR retina, we used a benchmark Kaggle APTOS dataset to train the HHO-CBL model.
RESULTS
Experimental results reveal that this model obtains the best classification accuracy of 96.4 % for an early diagnosis and 98.8 % for a five-degree classification. In addition to those results, a comparison with previously carried out studies has also shown that this model provides a promising solution for a successful Prediagnosis of DR and its staging.
CONCLUSIONS
In the current research, an innovative HHO-CBL was developed for identifying the primary causes that lead to the formation of microaneurysms and diagnosing all five grades of DR. According to the acquired results presented through the evaluation performance metrics indicates that the pre-early diagnosis and five grade classification using feature embedding technique outperformed the other prevailing approaches (Tab. 4, Fig. 10, Ref. 31).
Topics: Humans; Diabetic Retinopathy; Microaneurysm; Algorithms; Retina; Diabetes Mellitus; Early Diagnosis
PubMed: 38385547
DOI: 10.4149/BLL_2024_24 -
Indian Journal of Ophthalmology Aug 2023To characterize the relationship between diabetic macular ischemia (DMI) delineated by optical coherence tomography angiography (OCTA) and microaneurysms (MAs)...
PURPOSE
To characterize the relationship between diabetic macular ischemia (DMI) delineated by optical coherence tomography angiography (OCTA) and microaneurysms (MAs) identified by fundus fluorescein angiography (FFA).
METHODS
Patients with diabetic retinopathy (DR) who underwent OCTA and FFA were retrospectively identified. FFA images were cropped and aligned with their respective OCTA images using i2k Align Retina software (Dual-Align, Clifton Park, NY, USA). Foveal avascular zone (FAZ) and ischemic areas were manually delineated on OCTA images, and MAs were marked on the corresponding FFA images before overlaying paired scans for analysis (ImageJ; National Institutes of Health, Bethesda, MD, USA).
RESULTS
Twenty-eight eyes of 20 patients were included. The average number of MAs identified in cropped FFA images was 127 ± 42. More DMI was noted in the superficial capillary plexus (SCP; 36 ± 13%) compared to the deep capillary plexus (DCP; 28 ± 14%, P < 0.001). Similarly, more MAs were associated with ischemic areas in SCP compared to DCP (92.0 ± 35.0 vs. 76.8 ± 36.5, P < 0.001). Most MAs bordered ischemic areas; fewer than 10% localized inside these regions. As DMI area increased, so did associated MAs (SCP: r = 0.695, P < 0.001; DCP: r = 0.726, P < 0.001). Density of MAs surrounding FAZ (7.7 ± 6.0 MAs/mm) was similar to other DMI areas (SCP: 7.0 ± 4.0 MAs/mm, P = 0.478; DCP: 9.2 ± 10.9 MAs/mm, P = 0.394).
CONCLUSION
MAs identified in FFA strongly associate with, and border areas of, DMI delineated by OCTA. Although more MAs are localized to SCP ischemia, the concentration of MAs associated with DCP ischemia is greater. By contrast, few MAs are present inside low-flow regions, likely because capillary loss is associated with their regression.
Topics: Humans; Fluorescein Angiography; Retinal Vessels; Retrospective Studies; Tomography, Optical Coherence; Microaneurysm; Fundus Oculi; Visual Acuity; Diabetic Retinopathy; Diabetes Mellitus
PubMed: 37530285
DOI: 10.4103/IJO.IJO_3155_22 -
Frontiers in Endocrinology 2023This study aimed to observe and compare retinal vein diameter changes and other essential indicators in patients with high-risk proliferative diabetic retinopathy (PDR)...
OBJECTIVE
This study aimed to observe and compare retinal vein diameter changes and other essential indicators in patients with high-risk proliferative diabetic retinopathy (PDR) treated with intravitreal injection of conbercept (IVC) combined with panretinal photocoagulation (PRP) versus PRP monotherapy.
METHODS
A retrospective analysis was conducted on data from patients with high-risk PDR who received specific treatment and were followed up for 24 months. Among 82 patients with high-risk PDR, 50 eyes received PRP combined with IVC, whereas 32 eyes received PRP alone. During the 24-month follow-up period, changes in best-corrected visual acuity (BCVA), central foveal thickness (CFT), retinal vein diameter, number of microaneurysms (MA), neovascularization (NV) area, hard exudate (HE) area, size of the foveal avascular zone (FAZ), superficial capillary plexus (SCP) blood flow density, and adverse effects were recorded and compared between the two groups at baseline and at 6, 12, 18, and 24 months after treatment. The relationship between each observation index and vein diameter was also analyzed.
RESULTS
During the 24-month follow up, significant improvements in the BCVA, CFT, retinal vein diameter, number of MAs, NV area, HE area, FAZ, and SCP were observed in the IVC+PRP group after treatment. The PRP group only showed significant reductions in NV and HE areas. The IVC+PRP group showed significant superiority over the PRP group in improving the vein diameter, number of MA, and HE area. However, no statistically significant difference in NV area reduction was found between the groups.
CONCLUSION
In the treatment of high-risk PDR, IVC+PRP therapy has a significant advantage over PRP monotherapy. IVC+PRP therapy may reverse diabetes-induced retinal vein changes, restoring morphology and function.
Topics: Humans; Diabetic Retinopathy; Cohort Studies; Retinal Vein; Retrospective Studies; Macula Lutea; Light Coagulation; Diabetes Mellitus
PubMed: 37693359
DOI: 10.3389/fendo.2023.1218442 -
American Journal of Ophthalmology Case... Mar 2024In this study, we report a patient who presented with both chronic myelocytic leukemia (CML) and Susac syndrome (SS).
PURPOSE
In this study, we report a patient who presented with both chronic myelocytic leukemia (CML) and Susac syndrome (SS).
OBSERVATIONS
A 45-year-old male diagnosed with CML in the blast phase sought consultation due to a deterioration in vision in his right eye. He also had hearing loss and severe migraneous headaches. Best corrected visual acuity was light perception and 20/20 in the right and left eyes, respectively. The slit lamp examination and intraocular pressure were within normal ranges for both eyes. Upon dilated fundoscopy, organized vitreous hemorrhage was observed in the right eye, while the left eye exhibited extensive sclerotic vessels with retinal neovascularization in the periphery. Ultrasound of the right eye showed tractional retinal detachment. Optical coherence tomography of the left retina showed thinning of the retina in temporal macula. Fluorescein angiography revealed a substantial nonperfused region in the peripheral left retina, accompanied by arterioarterial and arteriovenous collaterals, along with microaneurysms. MRI showed scattered foci of hyperintensity within the supratentorial white matter, mostly subcortical on T2-weighted and fluid-attenuated inversion-recovery. The patient received a diagnosis of SS and was subsequently referred to the neurology service for further assessment and potential treatment.
CONCLUSION AND IMPORTANCE
SS may manifest as a presentation of CML. It is advisable to conduct investigations for SS in CML patients experiencing neurological, ophthalmological, or otological symptoms.
PubMed: 38318442
DOI: 10.1016/j.ajoc.2024.101996 -
Computers in Biology and Medicine Feb 2024Diabetic retinopathy is the main cause of blindness, and lesion segmentation is an important basic work for the diagnosis of this disease. The main lesions include soft...
Diabetic retinopathy is the main cause of blindness, and lesion segmentation is an important basic work for the diagnosis of this disease. The main lesions include soft and hard exudates, microaneurysms, and hemorrhages. However, the segmentation of these four types of lesions is difficult because of their variability in size and contrast, and high intertype similarity. Currently, many network models have problems, such as a large number of parameters and complex calculations, and most segmentation models for diabetic retinopathy focus only on one type of lesion. In this study, a lightweight algorithm based on BiSeNet V2 was proposed for the segmentation of multiple lesions in diabetic retinopathy fundus. First, a hybrid attention module was embedded in the semantic branch of BiSeNet V2 for 8- and 16-fold downsampling, which helped reassign deep feature-map weights and enhanced the ability to extract local key features. Second, a ghost feature-mapping unit was used to optimize the traditional convolution layers and further reduce the computational cost. Third, a new loss function based on the dynamic threshold loss function was applied to supervise the training by adjusting the training weights of the high-loss difficult samples, which enhanced the model's attention to small goals. In experiments on the IDRiD dataset, we conducted an ablation study to verify the effectiveness of each component and compared the proposed model, BiSeNet V2-Pro, with several state-of-the-art models. In comparison with the baseline BiSeNet V2, the segmentation performance of BiSeNet V2-Pro improved by 12.17 %, 11.44 %, and 8.49 % in terms of Sensitivity (SEN), Intersection over Union (IoU), and Dice coefficient (DICE), respectively. Specifically, IoU of MA reaches 0.5716. Compared with other methods, the segmentation speed was significantly improved while ensuring segmentation accuracy, and the number of model parameters was lower. These results demonstrate the superiority of BiSeNet V2-Pro in the multi-lesion segmentation of diabetic retinopathy.
Topics: Humans; Diabetic Retinopathy; Algorithms; Fundus Oculi; Semantics; Image Processing, Computer-Assisted; Diabetes Mellitus
PubMed: 38109836
DOI: 10.1016/j.compbiomed.2023.107854 -
European Journal of Ophthalmology Nov 2023To report successful treatment of a hypofluorescent perifoveal exudative vascular anomalous complex (PEVAC)/capillary macroaneurysm.
PURPOSE
To report successful treatment of a hypofluorescent perifoveal exudative vascular anomalous complex (PEVAC)/capillary macroaneurysm.
CASE DESCRIPTION
A 63 year old healthy gentleman had a perifoveal isolated aneurysmal lesion with white rim. Optical coherence tomography (OCT) showed cystoid macular edema (CME) with neurosensory detachment. The aneurysmal lesion was seen in the inner retina as a hyperreflective intraretinal structure with a heterogenous lumen suggestive of PEVAC/capillary macroaneurysm. OCT angiography showed a capillary loop and a slightly hyperreflective lesion at the tip of the loop in the superficial capillary plexus slab. Minimal reduction in edema was noted following one dose of intravitreal triamcinolone (2 mg). Fundus fluorescein angiography performed at 6 weeks demonstrated the capillary loop, but the aneurysmal lesion remained hypofluorescent with no definite leak in the late phase. Few perifoveal microaneurysms were seen in both the eyes. Six weeks later, focal laser photocoagulation of the aneurysmal lesion was performed, which resulted in complete resolution of macular edema at 1 month. There was no recurrence of macular edema till his recent follow up, which is 4 month post laser.
DISCUSSION
PEVAC is typically described as unifocal lesion and is not associated with other retinal vascular abnormalities. But in this case, in addition to the lesion, perifoveal microaneurysms were seen in both the eyes. Despite the absence of leak on fundus fluorescein angiography, targeted focal laser photocoagulation resulted in complete resolution of macular edema at 1 month.
CONCLUSION
Laser photocoagulation would be helpful even in hypofluorescent PEVAC/capillary macroaneurysms.
PubMed: 36567497
DOI: 10.1177/11206721221149064 -
Kidney International Jun 2024
Topics: Humans; Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis; Renal Artery; Microaneurysm; Male; Female; Middle Aged
PubMed: 38777408
DOI: 10.1016/j.kint.2023.12.019 -
Retinal Cases & Brief Reports Nov 2023Retinal racemose hemangioma is a rare, unilateral, nonhereditary, arteriovenous malformation characterized by the appearance of dilated and tortuous retinal vessels....
PURPOSE
Retinal racemose hemangioma is a rare, unilateral, nonhereditary, arteriovenous malformation characterized by the appearance of dilated and tortuous retinal vessels. Retinal racemose hemangioma can develop complications associated with retinal ischemia, such as vitreous hemorrhage, retinal vein occlusion, and neovascular glaucoma. Here, a case of retinal racemose hemangioma with retinal hypoperfusion detected by wide-field swept-source optical coherence tomographic angiography was reported, which was not unambiguously illustrated by fluorescein angiography.
METHODS
Case report.
RESULTS
A 57-year-old woman was referred to our hospital for the evaluation of severe retinal vascular tortuosity, dilation, and retinal hemorrhages in the left eye. Fundus examination revealed arteriovenous communications temporal to the fovea and multiple microaneurysms surrounded by retinal hemorrhages at the midperipheral temporal fundus. In fluorescein angiography, multiple hyperfluorescent lesions with leakage corresponding to microaneurysms were observed in the temporal and lower midperipheral areas; however, nonperfused areas were apparently absent. By contrast, wide-field optical coherence tomographic angiography clearly showed low-density retinal capillaries in the superotemporal quadrant in comparison with those in the inferotemporal quadrant.
CONCLUSION
Wide-field optical coherence tomographic angiography detected sparse retinal capillaries, which were not well illustrated by fluorescein angiography, in a patient with retinal racemose hemangioma. This indicates the presence of low-grade retinal hypoperfusion caused by altered retinal hemodynamics, potentially leading to ischemia-related retinal disorders during a prolonged course, in patients with clinically quiescent retinal racemose hemangioma.
Topics: Female; Humans; Middle Aged; Retinal Hemorrhage; Microaneurysm; Hemangioma; Fluorescein Angiography; Eye Neoplasms; Tomography, Optical Coherence; Ischemia; Retinal Vessels
PubMed: 35385436
DOI: 10.1097/ICB.0000000000001271 -
Artificial Intelligence in Medicine Mar 2024Diabetic retinopathy (DR) is the most prevalent cause of visual impairment in adults worldwide. Typically, patients with DR do not show symptoms until later stages, by...
Diabetic retinopathy (DR) is the most prevalent cause of visual impairment in adults worldwide. Typically, patients with DR do not show symptoms until later stages, by which time it may be too late to receive effective treatment. DR Grading is challenging because of the small size and variation in lesion patterns. The key to fine-grained DR grading is to discover more discriminating elements such as cotton wool, hard exudates, hemorrhages, microaneurysms etc. Although deep learning models like convolutional neural networks (CNN) seem ideal for the automated detection of abnormalities in advanced clinical imaging, small-size lesions are very hard to distinguish by using traditional networks. This work proposes a bi-directional spatial and channel-wise parallel attention based network to learn discriminative features for diabetic retinopathy grading. The proposed attention block plugged with a backbone network helps to extract features specific to fine-grained DR-grading. This scheme boosts classification performance along with the detection of small-sized lesion parts. Extensive experiments are performed on four widely used benchmark datasets for DR grading, and performance is evaluated on different quality metrics. Also, for model interpretability, activation maps are generated using the LIME method to visualize the predicted lesion parts. In comparison with state-of-the-art methods, the proposed IDANet exhibits better performance for DR grading and lesion detection.
Topics: Adult; Humans; Diabetic Retinopathy; Neural Networks, Computer; Image Interpretation, Computer-Assisted; Diabetes Mellitus
PubMed: 38462283
DOI: 10.1016/j.artmed.2024.102782 -
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