Detection Of Neovascularization Research Articles

Detection of macular neovascularization in eyes presenting with macular edema using optical coherence tomography angiography and a deep-learning model

PurposeTo test the diagnostic performance of an artificial intelligence algorithm for detecting and segmenting macular neovascularization (MNV) with optical coherence tomography (OCT) and OCT angiography(OCTA) in eyes with macular edema from various diagnoses. DesignProspective cross-sectional study. ParticipantsStudy participants with macular edema due to either treatment-naïve exudative age-related macular degeneration (AMD), diabetic macular edema (DME), or retinal vein occlusion (RVO). MethodsStudy participants were imaged with macular 3x3-mm and 6x6-mm spectral-domain OCTA. Eyes with exudative AMD were required to have MNV in the central 3x3-mm area. A previously developed hybrid multi-task convolutional neural network for MNV detection (aiMNV) and segmentation was applied to all images, regardless of image quality. Main Outcome MeasuresSensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of detecting MNV; and intersection over union(IoU) score and F1 score for segmentation. ResultsOf 114 eyes from 112 study participants, 56 eyes had MNV due to exudative AMD and 58 eyes with macular edema due to either DME or RVO. 3x3-mm OCTA scans with aiMNV detected MNV with 96.4% sensitivity, 98.3% specificity, 98.2% PPV, and 96.6% NPV. For segmentation, the average IoU score was 0.947 and the F1 score was 0.973. 6x6-mm scans performed well; however, sensitivity for MNV detection was lower than 3x3-mm scans due to lower scan sampling density. ConclusionThis novel aiMNV algorithm can accurately detect and segment MNV in eyes with exudative AMD from a control group of eyes that present with macular edema from either DME or RVO. Higher scan sampling density improved the aiMNV sensitivity for MNV detection.

Comparison of the diagnostic performance of contrast-enhanced ultrasound and high-resolution magnetic resonance imaging in the evaluation of histologically defined vulnerable carotid plaque: a systematic review and meta-analysis.

Vulnerable carotid plaque is closely associated with ischemic stroke. Contrast-enhanced ultrasound (CEUS) and high-resolution magnetic resonance imaging (HR-MRI) are two imaging modalities capable of assessing the vulnerability of carotid plaques. This systematic review aimed to compare the diagnostic performance of CEUS and HR-MRI in the evaluation of histologically defined vulnerable carotid plaques. A systematic literature search with predefined search terms was performed on PubMed, the Cochrane library, Embase, and Web of Science from January 2001 to December 2023. Studies that evaluated the diagnostic accuracy of vulnerable carotid plaques confirmed by histology with CEUS and/or HR-MRI were included. The pooled values were calculated using a random-effects meta-analysis to determine diagnostic power. This analysis included a total of 839 patients from 20 studies comprising 1,357 HR-MRI plaques and CEUS 504 plaques. With the reference to histological results, all nine CEUS studies focused on the detection of intraplaque neovascularization (IPN), and three studies also examined morphological changes or ulcerated plaques; meanwhile, among the HR-MRI studies, seven predominantly focused on identifying intraplaque hemorrhage (IPH) and three mainly examined lipid-rich necrotic cores (LRNCs). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the area under the curve (AUC) for CEUS studies were 0.85 [95% confidence interval (CI): 0.81-0.89], 0.76 (95% CI: 0.69-0.83), 3.41 (95% CI: 1.68-6.94), 0.14 (95% CI: 0.05-0.38), 27.68 (95% CI: 5.78-132.62), and 0.89 [standard error (SE) 0.06], respectively; for HR-MRI, these values were 0.88 (95% CI: 0.85-0.90), 0.89 (95% CI: 0.86-0.92), 7.49 (95% CI: 3.28-17.09), 0.17 (95% CI: 0.12-0.24), 49.13 (95% CI: 23.87-101.11), and 0.94 (SE 0.01), respectively. The difference in AUC between the two modalities was not statistically significant (Z=0.82; P=0.68). CEUS and HR-MRI are valuable noninvasive diagnostic tools for identifying histologically confirmed vulnerable carotid plaques and demonstrate similar diagnostic performance. CEUS is more capable of detecting IPN and morphological changes, while HR-MRI is more suited to classifying IPH and LRNCs.

Added Clinical Value of Intraplaque Neovascularization Detection to Color Doppler Ultrasound for Assessing Ischemic Stroke Risk.

Intraplaque neovascularization, assessed using contrast-enhanced ultrasound (CEUS), is associated with ischemic stroke. It remains unclear whether detection of intraplaque neovascularization combined with color Doppler ultrasound (CDUS) provides additional value compared with CDUS alone in assessing ischemic stroke risk. Therefore, we investigated the clinical value of combined CEUS, CDUS, and clinical features for ischemic stroke risk stratification. We recruited 360 patients with ≥50% carotid stenosis between January 2019 and September 2022. Patients were examined using CDUS and CEUS. Covariates associated with ischemic stroke were identified using multivariate logistic regression analysis. The discrimination and calibration were verified using the C-statistic and Hosmer-Lemeshow test. The incremental value of intraplaque neovascularization in the assessment of ischemic stroke was analyzed using the Delong test. We analyzed the data of 162 symptomatic and 159 asymptomatic patients who satisfied the inclusion and exclusion criteria, respectively. Based on multivariate logistic regression analysis, we constructed a nomogram using intraplaque neovascularization, degree of carotid stenosis, plaque hypoechoicity, and smoking status, with a C-statistic of 0.719 (95% confidence interval [CI]: 0.666-0.768) and a Hosmer-Lemeshow test p value of 0.261. The net reclassification index of the nomogram was 0.249 (95% CI: 0.138-0.359), and the integrated discrimination improvement was 0.053 (95% CI: 0.029-0.079). Adding intraplaque neovascularization to the combination of CDUS and clinical features (0.672; 95% CI: 0.617-0.723) increased the C-statistics (p=0.028). Further assessment of intraplaque neovascularization after CDUS may help more accurately identify patients at risk of ischemic stroke. Combining multiparametric carotid ultrasound and clinical features may help improve the risk stratification of patients with ischemic stroke with ≥50% carotid stenosis.

OCT angiography 2023 update: focus on diabetic retinopathy.

Optical coherence tomography angiography (OCTA) has become part of the clinical practice and its growing applications are in continuous development. Coherently with the growing concern about the human and economic cost of diabetes, diabetic retinopathy (DR) was the most popular topic for OCTA studies in the past year. The analysis of the literature reveals that applications of OCTA in DR are in continuous growth. In particular, ultrawide field (UWF) OCTA and artificial intelligence (AI) based on OCTA images are affirming as the new frontiers of scientific research in the field. Diagnostic accuracy of AI methods based on OCTA is equal or superior to the one based on OCT methods and also bears potential to detect systemic associations. UWF OCTA is noninvasive method that is reaching similar accuracy of FA in detection of neovascularization and intraretinal microvascular abnormalities (IRMAs) and has allowed better characterization of microvascular peripherical changes in DR. Lastly, deep capillary plexus (DCP) characteristics seem to play a pivotal role in the development of diabetic macular edema (DME) and refinement of biomarkers for different phenotypes of DME and diabetic macular ischemia (DMI) is currently on its way.

Peranan Sekuen Susceptibility Weight Imaging (SWI) Pada Pemeriksaan MRI Brain Pada Kasus Tumor

The aim of the research is to find out the role of the transverse suspectibility weighted imaging (SWI) sequence in brain MRI examination techniques in tumor cases. The research method used in this research is a qualitative descriptive study that uses a literature study approach to explore, analyze and identify information about how the Susceptibility Weighted Imaging (SWI) sequence plays a role in the Brain MRI examination process in patients who have tumors. The results and discussion of the literature review show: 1) Susceptibility-Weighted Imaging (SWI) on MRI brain has an important role in detecting blood degradation products, calcification and iron accumulation in glioblastoma. SWI allows visualization of small blood vessels, detection of iron, as well as identification of areas of calcification within the tumor, providing a more detailed picture of the nature and malignancy of glioblastoma. The Intratumoral Susceptibility Signal (ITSS) on SWI images is a visual marker associated with microhemorrhage, neoangiogenesis, and calcification, enabling tumor grading based on the frequency and distribution of these signals. In addition, Intralesional Susceptibility Signal (ILSS) also has an important role in differentiating glioblastoma from abscesses and metastases, with high levels of ILSS tending to be associated with tumor severity. Thus, the integration of SWI and ITSS and ILSS analysis can make a significant contribution to the characterization and assessment of the level of malignancy. 2) Susceptibility-Weighted Imaging (SWI) in the diagnosis of glioblastoma has the advantage of providing internal visualization of the tumor with high resolution. SWI is highly sensitive to differences in tissue susceptibility, allows the detection of neovascularization, hemorrhage, and calcification within glioblastoma, and provides detailed information about cerebral vascular anatomy. The advantages of SWI include its ability to image the Intratumoral Susceptibility Signal (ITSS) and Intralesional Susceptibility Signal (ILSS) and increase the visibility of low signal intensity structures. However, its shortcomings, namely sensitivity to artifacts, dependence on susceptibility phenomena, and subjective interpretation are aspects that need to be considered.

A Complete Review of Automatic Detection, Segmentation, and Quantification of Neovascularization in Optical Coherence Tomography Angiography Images.

Optical coherence tomography (OCT) is revolutionizing the way we assess eye complications such as diabetic retinopathy (DR) and age-related macular degeneration (AMD). With its ability to provide layer-by-layer information on the retina, OCT enables the early detection of abnormalities emerging underneath the retinal surface. The latest advancement in this field, OCT angiography (OCTA), takes this to the next level by providing detailed vascular information without requiring dye injections. One of the most significant indicators of DR and AMD is neovascularization, the abnormal growth of unhealthy vessels. In this work, the techniques and algorithms used for the automatic detection, classification, and segmentation of neovascularization in OCTA images are explored. From image processing to machine learning and deep learning, works related to automated image analysis of neovascularization are summarized from different points of view. The problems and future work of each method are also discussed.

Three-Year Follow-Up Detecting Choroidal Neovascularization with Swept Source Optical Coherence Tomography Angiography (SS-OCTA) after Successful Half-Fluence Photodynamic Therapy for Chronic Central Serous Chorioretinopathy.

Purpose: To assess the clinical course, structural changes, and choroidal neovascularization detection by SS-OCTA in long-standing and resolved patients with chronic central serous chorioretinopathy (cCSC) after successful half-fluence photodynamic therapy (hf-PDT) treatment. Methods: Twenty-four eyes presenting with cCSC were examined with SS-OCTA and were classified as choroidal neovascular (CNV) or non-choroidal neovascular (non-CNV) cCSC depending on the vascular pattern detected by SS-OCTA after one, two, and three years after hf-PDT. Two groups were compared based on the following clinical findings: demographic characteristics, time of clinical signs, best corrected visual acuity (BCVA), central retinal thickness (CRT), central choroidal thickness (CFT), subretinal fluid (SRF), flat, irregular pigment epithelial detachment (FIPED), and features of fluorescein angiography (FA) and vascular pattern by SS-OCTA. Results: All patients showed resolved cCSC during follow-up after hf-PDT. A total of 5 of 24 (20.8%) eyes showed a neovascular pattern by SS-OCTA. No differences between BCVA, CRT, SRF, FIPED, or FA features were found between both groups (p > 0.05). However, CFT and older age were associated with a neovascular pattern by SS-OCTA (p < 0.05) in follow-up. No signs of neovascular activity were detected by SS-OCT during follow-up in CNV cCSC patients, and no antiVEGF treatment was required for three-year follow-ups. Conclusions: Despite patients with cCSC showing a favorable clinical response after hf-PDT, lower foveal thickness and older age were associated with CNV patterns by SS-OCTA during follow-up.

Comparison of widefield swept-source optical coherence tomographic angiography and fluorescein fundus angiography for detection of retinal neovascularization with diabetic retinopathy

BackgroundTo compare vitreous angiomosaic images (VAMIs), obtained by widefield swept-source optical coherence tomographic angiography (wfSS-OCTA) and the image of fluorescein fundus angiography (FFA) in the identification of retinal neovascularization (NV) in patients with diabetic retinopathy (DR).MethodsIn this prospective observational study, severe non-proliferative diabetic retinopathy (NPDR) or proliferative DR (PDR) patients were included. All patients underwent FFA and wfSS-OCTA. The number of NVs identified by wfSS-OCTA VAMIs using five fixations 12 × 12 mm montage scans and the resembling FFA images were compared.ResultsFifty-three eyes of 29 patients were enrolled. NVs were detected in 25 eyes by using FFA, including 9 NVs of the disc (NVDs) and 72 NVs elsewhere (NVEs), and in 29 eyes by OCTA, including 11 NVDs and 90 NVEs. The detection rate of NV and NVD of OCTA was comparable to that of FFA (p > 0.05), and the level of agreement was excellent (κ = 0.850, κ = 0.754). Using FFA as the gold standard, the sensitivity for detection of NV by OCTA was 100.0%, specificity was 85.7%, the positive-predictive value was 86.2%, and the negative-predictive value was 100.0%. Compared with FFA, OCTA was superior in terms of the number of NVEs identified (p = 0.024). When we excluded images of patients treated with anti-vascular endothelial growth factor (VEGF) intravitreal therapy for < 3 months, OCTA was comparable to FFA in terms of the number of NVEs discovered (p = 0.203), with excellent agreement (intraclass correlation coefficient = 0.941).ConclusionsWfSS-OCTA is an independent non-invasive alternative to FFA for NV discovery, NVD detection, and individual NVE identification, particularly in patients with PDR who have a history of prior treatment with anti-VEGF.

Inter-Rater Reliability of Proliferative Diabetic Retinopathy Assessment on Wide-Field OCT-Angiography and Fluorescein Angiography.

To assess inter-rater reliability in the detection of proliferative diabetic retinopathy (PDR) changes using wide-field optical coherence tomography angiography (WF-OCTA) versus fluorescein angiography (FA). This retrospective, cross-sectional study included patients with severe nonproliferative and PDR. Images were acquired with 12 × 12 mm WF-OCTA and FA with a 55° lens. Images were cropped to represent the exact same field of view. Qualitative (detection of neovascularization at the disc [NVD] and elsewhere [NVE], enlarged foveal avascular zone [FAZ], vitreous hemorrhage [VH]) and quantitative analyses (FAZ area, horizontal, vertical, and maximum FAZ diameter) were performed by 2 masked graders using ImageJ. Inter-rater reliability was calculated using unweighted Cohen's kappa coefficient (κ) for qualitative analyses and intraclass correlation coefficients (ICC) for quantitative analyses. Twenty-three eyes of 17 patients were included. Inter-rater reliability was higher for FA than for WF-OCTA in qualitative analyses: κ values were 0.65 and 0.78 for detection of extended FAZ, 0.83 and 1.0 for NVD, 0.78 and 1.0 for NVE, and 0.19 and 1 for VH for WF-OCTA and FA, respectively. In contrast, inter-rater reliability was higher for WF-OCTA than for FA in the quantitative analyses: ICC values were 0.94 and 0.76 for FAZ size, 0.92 and 0.79 for horizontal FAZ diameter, 0.82 and 0.72 for vertical FAZ diameter, and 0.88 and 0.82 for maximum FAZ diameter on WF-OCTA and FA, respectively. Inter-rater reliability of FA is superior to WF-OCTA for qualitative analyses whereas inter-rater reliability of WF-OCTA is superior to FA for quantitative analyses. The study highlights the specific merits of both imaging modalities in terms of reliability. FA should be preferred for qualitative parameters, whereas WF-OCTA should be preferred for quantitative parameters.

Proliferative Diabetic Retinopathy Diagnosis Using Varying-Scales Filter Banks and Double-Layered Thresholding

Diabetic retinopathy is one of the abnormalities of the retina in which a diabetic patient suffers from severe vision loss due to an affected retina. Proliferative diabetic retinopathy (PDR) is the final and most critical stage of diabetic retinopathy. Abnormal and fragile blood vessels start to grow on the surface of the retina at this stage. It causes retinal detachment, which may lead to complete blindness in severe cases. In this paper, a novel method is proposed for the detection and grading of neovascularization. The proposed system first performs pre-processing on input retinal images to enhance the vascular pattern, followed by blood vessel segmentation and optic disc localization. Then various features are tested on the candidate regions with different thresholds. In this way, positive and negative advanced diabetic retinopathy cases are separated. Optic disc coordinates are applied for the grading of neovascularization as NVD or NVE. The proposed algorithm improves the quality of automated diagnostic systems by eliminating normal blood vessels and exudates that might cause hindrances in accurate disease detection, thus resulting in more accurate detection of abnormal blood vessels. The evaluation of the proposed system has been carried out using performance parameters such as sensitivity, specificity, accuracy, and positive predictive value (PPV) on a publicly available standard retinal image database and one of the locally available databases. The proposed algorithm gives an accuracy of 98.5% and PPV of 99.8% on MESSIDOR and an accuracy of 96.5% and PPV of 100% on the local database.

Clinical application of super sensitive microflow ultrasound on the detection of intraplaque neovascularization in patients with atheromatous carotid artery plaque.

Contrast-enhanced ultrasound (CEUS) is a routine technique for detecting intraplaque neovascularization (IPN). However, the invasiveness and complexity of CEUS severely limit its clinical application. This article aims to investigate the application value of AngioPLUS (AP) technique in assessing IPN formation in patients with atheromatous (AS) carotid artery plaque. Patients diagnosed with carotid artery atherosclerosis combined plaque formation were recruited and their demographic characteristics including serum fasting blood glucose (FBG), triglyceride (TG), and low-density lipoprotein (LDL) were collected. AP was used to scoring intraplaque microvascular flow (IMVF), measuring the thickness and length of the plaque and determining the number of IPN of the plaque. IMVF score evaluated by AP was positively correlated with plaque length, thickness, IPN number, serum TG, LDL and FBG levels in patients with carotid atherosclerosis with plaque. The evaluation results of CEUS score and IMVF classification detected by AP of plaques were consistent in patients with carotid atherosclerosis. IMVF scoring by AP is a promising approach to assess IPN and plaque status in patients with atheromatous carotid artery plaque.

LATE CHOROIDAL NEOVASCULAR COMPLICATIONS IN A PATIENT TREATED FOR RETINOBLASTOMA. A CASE REPORT.

Case report of choroidal neovascularization (CNV) detection in patient who was treated for bilateral retinoblastoma in early childhood. Patient at 1.5 years of age treated for endophytic retinoblastoma stage 4 (according to the Reese-Ellsworth classification) bilaterally, with a positive mutation in the Rb1 gene. After undergoing bilateral retinal laser treatment and 6 cycles of systemic chemotherapy, the tumor remained inactive without other complications. At the age of 14, the boy developed visual impairment in his left eye with metamorphosis. Based on a local finding and other auxiliary examinations, he was diagnosed with CNV in the macular area at the interface of the tumor scar and the healthy retina of the left eye. After three applications of anti-VEGF (antibodies blocking vascular endothelial growth factor) substance intravitreally (bevacizumab 1.2 mg), there was a reduction in CNV and also an improvement in visual function.

The Value of Superb Microvascular Imaging and Contrast-enhanced Ultrasound for the Evaluation of Neovascularization in Carotid Artery Plaques

To compare the consistency between superb microvascular imaging (SMI) and contrast-enhanced ultrasound (CEUS) for the detection of neovascularization in carotid plaques of different thicknesses and to evaluate the applied value of these two methods for detecting neovascularization in carotid plaques in the clinic. A total of 45 patients with carotid artery plaques who were diagnosed in our hospital involving 76 hypoechoic plaques with a thickness ≥2.0 mm were selected. According to thickness, the plaques were divided into three groups: 2.0-2.5 mm, 2.5-3.0 mm and ≥3.0 mm. Each group underwent both SMI and CEUS, and two experienced sonographers (A and B) analyzed the ultrasound images to evaluate the neovascularization of carotid plaques. The amount of the neovascular signal was assessed using a semi-quantitative grading scale (vascularity grade: grade 0-3). SMI and CEUS were graded respectively according to the visual methods as follows: grade 0: no blood flow signal/enhancement within plaques; grade 1: a few blood flow signals/enhancement within plaques; grade 2: medium blood flow signals/enhancement within plaques; and grade 3: extensive blood flow signals/enhancement within plaques. Kappa consistency test was used to analyze the consistency of the grade of neovascularization in plaques between SMI with CEUS. Gamma rank correlation analysis was used to examine the correlation between neovascularization grade by SMI and CEUS in plaque and plaque thickness. Of these patients, 14 had unilateral plaques and 31 had bilateral plaques. The two sonographers were highly consistent in terms of applying SMI and CEUS methods for diagnosing neovascularization in carotid plaques (Kappa values were 0.736 and 0.680>0). Consistency was found between SMI and CEUS by sonographers (sonographer A: Kappa=0.823; sonographer B: Kappa=0.842) in evaluating the neovascular grade in the carotid plaques. SMI and CEUS grades were positively correlated with plaque thickness (sonographer A: γ=0.735 and 0.772; sonographer B: γ=0.805 and 0.798). Neovascularization in carotid plaques was successfully detected by SMI in a manner that concurred well with CEUS results. Our data indicate that both CEUS and SMI have high diagnostic value for assessing the neovascularization of plaques.

Volume-based, layer-independent, disease-agnostic detection of abnormal retinal reflectivity, nonperfusion, and neovascularization using structural and angiographic OCT.

Optical coherence tomography (OCT) is widely used in ophthalmic practice because it can visualize retinal structure and vasculature in vivo and 3-dimensionally (3D). Even though OCT procedures yield data volumes, clinicians typically interpret the 3D images using two-dimensional (2D) data subsets, such as cross-sectional scans or en face projections. Since a single OCT volume can contain hundreds of cross-sections (each of which must be processed with retinal layer segmentation to produce en face images), a thorough manual analysis of the complete OCT volume can be prohibitively time-consuming. Furthermore, 2D reductions of the full OCT volume may obscure relationships between disease progression and the (volumetric) location of pathology within the retina and can be prone to mis-segmentation artifacts. In this work, we propose a novel framework that can detect several retinal pathologies in three dimensions using structural and angiographic OCT. Our framework operates by detecting deviations in reflectance, angiography, and simulated perfusion from a percent depth normalized standard retina created by merging and averaging scans from healthy subjects. We show that these deviations from the standard retina can highlight multiple key features, while the depth normalization obviates the need to segment several retinal layers. We also construct a composite pathology index that measures average deviation from the standard retina in several categories (hypo- and hyper-reflectance, nonperfusion, presence of choroidal neovascularization, and thickness change) and show that this index correlates with DR severity. Requiring minimal retinal layer segmentation and being fully automated, this 3D framework has a strong potential to be integrated into commercial OCT systems and to benefit ophthalmology research and clinical care.

Detection of Retinal Neovascularization Using Optimized Deep Convolutional Neural Networks

The most common disease that is found among people across the world is Diabetes and it is predicted to increase more in the upcoming years by The World Health Organization (WHO). People who are diabetic for a longer period are more likely to have Diabetic Retinopathy (DR), an eye disease which can lead to blindness and this cannot be reversed. One of the severe stage problems of DR is Retinal Neovascularization (RN), i.e., outburst of retinal blood vessels. Residual Network (ResNet) has an effective technique called Skip or Residual Connections which solves the problem of vanishing gradient during backpropagation. ResNet50 has 50 layers which is a deep network that omits signal representations and learns from residual representations leading to predict RN with 88.97% accuracy.

Optical coherence tomography angiography for the detection and evaluation of ptic disc neovascularization: a retrospective, observational study

BackgroundTo assess and characterize neovascularization of the optic disc (NVD) using optical coherence tomography angiography (OCTA) and different OCTA-based methods.MethodsThis retrospective, observational study included patients who were suspected of having early PDR with no presence of clinically apparent neovascularization (NV) bur were clinically diagnosed with proliferative diabetic retinopathy (PDR), or severe NPDR. Patients underwent standard clinical examinations and OCTA imaging using a 6 × 6 montage scan. Two trained graders identified NVD using different imaging systems (ultra-widefield-colour fundus photography (UWF-CFP), OCT, OCTA and fluorescein angiography (FA)). Moreover, morphological classification of NVD was performed. The detection and morphological classification of NVD by different OCTA-based methods (B-scan OCTA, En-face OCTA, VRI Angio and VRI Structure) were compared.ResultsA total of 169 eyes (126 eyes with PDR and 43 eyes with severe NPDR) of 123 participants were included in this study. The detection rate of NVD was 34.91% by UWF-CFP compared with 59.76% by OCT, 59.76% by OCTA, and 62.72% by FA. After excluding 2 cases with epiretinal membranes, the NVD diagnosis detected by OCT was used as the standard. Among 99 eyes diagnosed with NVD by OCT, B-scan OCTA detected NVD with a sensitivity of 97.98%, which was higher than that by en face OCTA (80.81%), VRI Angio (65.66%), and VRI Structure (61.62%) (all P < 0.05). According to its characteristics on OCTA, NVD was divided into four types (12 cases of type I, 6 cases of type II, 39 cases of type III, and 42 cases of type IV). For type I, B-scan OCTA exhibited a higher diagnostic sensitivity than other methods (P < 0.05). For types II and IV, there were no statistically significant differences in the sensitivity of various methods between the two groups (P > 0.05).ConclusionOCTA and different OCTA-based methods are significant to the diagnosis of NVD, and the diagnostic accuracy of different detection methods may be related to different types of NVD.

Comparison of Ultra-Wide Field Photography to Ultra-Wide Field Angiography for the Staging of Sickle Cell Retinopathy.

Sickle cell retinopathy (SCR) is classified by Goldberg based on peripheral vascular changes. Ultra-wide field (UWF) imaging has enhanced visualization of the peripheral retina. However, there is no consensus on the optimal imaging technique for the screening of SCR. We performed a monocentric observational cross-sectional study to compare UWF fundus photography (UWF-FP) with UWF angiography (UWF-FA). All patients who underwent UWF-imaging (Optos, PLC, Scotland, UK) for screening of sickle cell retinopathy between January 2016 and December 2019 were retrospectively included. Eyes with previous laser treatment or concomitant retinal disease were excluded. UWF-FP images were graded based on the Goldberg classification by four graders with various degrees of experience. UWF-FA pictures were reviewed by an independent retina specialist. Differences in Goldberg staging across UWF-FP and UWF-FA were assessed. A total of 84 eyes of 44 patients were included. Based on UWF-FA, most eyes were stage 2 (77.4%) and 19 were stage 3 (22.6%). The pre-retinal neovascularization detection sensitivity on UWF-FP was 52.6 to 78.9%, depending on the graders. UWF-FA led to a later Goldberg stage of retinopathy, in most cases from stage 1 to stage 2. Neovascularization (stage 3) was not detected by our graders on UWF-FP in 21.1 to 57.9% of eyes. UWP-FP tends to underestimate Goldberg stages of retinopathy compared with UWF-FA and is less accurate when detecting neovascularization in sickle cell retinopathy, which has a direct impact on therapeutic management and prognosis.

NIR-II Ratiometric Lanthanide-Dye Hybrid Nanoprobes Doped Bioscaffolds for In Situ Bone Repair Monitoring.

In situ monitoring of tissue regeneration progression is of primary importance to basic medical research and clinical transformation. Despite significant progress in the field of tissue engineering and regenerative medicine, few technologies have been established to in situ inspect the regenerative process. Here, we present an integrated second near-infrared (NIR-II, 1000-1700 nm) window in vivo imaging strategy based on 3D-printed bioactive glass scaffolds doped with NIR-II ratiometric lanthanide-dye hybrid nanoprobes, allowing for in situ monitoring of the early inflammation, angiogenesis, and implant degradation during mouse skull repair. The functional bioactive glass scaffolds contribute to more effective bone regeneration because of their excellent angiogenic and osteogenic activities. The reliability of ratiometric fluorescence imaging, coupled with low autofluoresence in the NIR-II window, facilitates the accuracy of in vivo inflammation detection and high-resolution visualization of neovascularization and implant degradation in deep tissue.

Optical coherence tomography angiography for the detection of macular neovascularization—comparison of en face versus cross-sectional view

PurposeTo evaluate sensitivity and specificity of swept source-optical coherence tomography angiography (SS-OCTA) en face images versus cross-sectional OCTA versus a combination of both for the detection of macular neovascularization (MNV).DesignProspective cohort study.ParticipantsConsecutive patients with various chorioretinal diseases and subretinal hyperreflective material (SHRM) and/or pigment epithelial detachment (PED) on OCT possibly corresponding to MNV in at least one eye.Methods102 eyes of 63 patients with fluorescein angiography (FA), OCT and SS-OCTA performed on the same day were included. FA images, the outer retina to choriocapillaris (ORCC) OCTA en face slab, a manually modified en face slab (‘custom slab’), cross-sectional OCTA and a combination of OCTA en face and cross-section were evaluated for presence of MNV.Main outcome measuresSensitivity and specificity for MNV detection, as well as the concordance was calculated using FA as the reference.ResultsOCTA en face imaging alone yielded a sensitivity of 46.3% (automated)/78.1% (custom) and specificity of 93.4% (automated)/88.5% (custom) for MNV detection. Cross-sectional OCTA (combination with en face) resulted in a sensitivity of 85.4% (82.9%) and specificity of 82.0% (85.3%). Concordance to FA was moderate for automated en face OCTA (κ = 0.43), and substantial for custom en face OCTA (κ = 0.67), cross-sectional OCTA (κ = 0.66) and the combination (κ = 0.68).ConclusionSegmentation errors result in decreased sensitivity for MNV detection on automatically generated OCTA en face images. Cross-sectional OCTA allows detection of MNV without manual modification of segmentation lines and should be used for evaluation of MNV on OCTA.

A Deep Learning Approach for the Detection of Neovascularization in Fundus Images Using Transfer Learning

Patients with diabetes are at risk of developing a retinal disorder called Proliferative Diabetic Retinopathy (PDR). One of the main characteristics of PDR is the development of neovascularization, a condition in which abnormal blood vessels are formed on the retina. This condition can cause blindness if it is not detected and treated early. Numerous studies have proposed different image processing techniques for detecting neovascularization in fundus images. However, because of its random growth pattern and small size, neovascularization remains challenging to detect. Hence, deep learning techniques are becoming more prevalent in neovascularization identification because of their ability to perform automatic feature extraction on objects with complex features. In this paper, a method of neovascularization detection based on transfer learning is proposed. The performance of the transfer learning method is investigated using four pre-trained Convolutional Neural Network (CNN) models, which include AlexNet, GoogLeNet, ResNet18, and ResNet50. In addition, an improved network based on the combination of ResNet18 and GoogLeNet is proposed. Evaluation on 1174 retinal image patches showed that the proposed network could achieve 91.57&#x0025;, 85.69&#x0025;, 97.44&#x0025;, and 97.10&#x0025; of accuracy, sensitivity, specificity, and precision, respectively. We demonstrated that the proposed method outperforms each individual CNN for neovascularization detection. It also shows better performance compared to another method that utilized deep learning models for feature extraction and Support Vector Machine (SVM) for classification.