Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease.

Understanding the mechanics of blood flow is necessary for developing insights into mechanisms of physiology and vascular diseases in microcirculation. Given the limitations of technologies available for assessing in vivo flow fields, in vitro methods based on traditional microfluidic platforms have been developed to mimic physiological conditions. However, existing methods lack the capability to provide accurate assessment of these flow fields, particularly in vessels with complex geometries. Conventional approaches to quantify flow fields rely either on analyzing only visual images or on enforcing underlying physics without considering visualization data, which could compromise accuracy of predictions. Here, we present artificial-intelligence velocimetry (AIV) to quantify velocity and stress fields of blood flow by integrating the imaging data with underlying physics using physics-informed neural networks. We demonstrate the capability of AIV by quantifying hemodynamics in microchannels designed to mimic saccular-shaped microaneurysms (microaneurysm-on-a-chip, or MAOAC), which signify common manifestations of diabetic retinopathy, a leading cause of vision loss from blood-vessel damage in the retina in diabetic patients. We show that AIV can, without any a priori knowledge of the inlet and outlet boundary conditions, infer the two-dimensional (2D) flow fields from a sequence of 2D images of blood flow in MAOAC, but also can infer three-dimensional (3D) flow fields using only 2D images, thanks to the encoded physics laws. AIV provides a unique paradigm that seamlessly integrates images, experimental data, and underlying physics using neural networks to automatically analyze experimental data and infer key hemodynamic indicators that assess vascular injury.

Resilient back-propagation machine learning-based classification on fundus images for retinal microaneurysm detection.

BACKGROUND: The timely diagnosis of medical conditions, particularly diabetic retinopathy, relies on the identification of retinal microaneurysms. However, the commonly used retinography method poses a challenge due to the diminutive dimensions and limited differentiation of microaneurysms in images. PROBLEM STATEMENT: Automated identification of microaneurysms becomes crucial, necessitating the use of comprehensive ad-hoc processing techniques. Although fluorescein angiography enhances detectability, its invasiveness limits its suitability for routine preventative screening. OBJECTIVE: This study proposes a novel approach for detecting retinal microaneurysms using a fundus scan, leveraging circular reference-based shape features (CR-SF) and radial gradient-based texture features (RG-TF). METHODOLOGY: The proposed technique involves extracting CR-SF and RG-TF for each candidate microaneurysm, employing a robust back-propagation machine learning method for training. During testing, extracted features from test images are compared with training features to categorize microaneurysm presence. RESULTS: The experimental assessment utilized four datasets (MESSIDOR, Diaretdb1, e-ophtha-MA, and ROC), employing various measures. The proposed approach demonstrated high accuracy (98.01%), sensitivity (98.74%), specificity (97.12%), and area under the curve (91.72%). CONCLUSION: The presented approach showcases a successful method for detecting retinal microaneurysms using a fundus scan, providing promising accuracy and sensitivity. This non-invasive technique holds potential for effective screening in diabetic retinopathy and other related medical conditions.

An optimized framework for prediagnosis of diabetic retinopathy using HHO-CBL model.

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).

Computational investigation of blood cell transport in retinal microaneurysms.

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.

Predictive factors for microvascular recovery after treatments for diabetic retinopathy.

BACKGROUND: To identify factors associated with microvascular recovery after intravitreal bevacizumab or panretinal photocoagulation (PRP) in diabetic retinopathy (DR). METHODS: We retrospectively reviewed 320 eyes/patients with DR treated with intravitreal bevacizumab and/or PRP. Two consecutive fluorescein angiographies (FAs) of each eye were compared. The number of microaneurysms and the area of capillary non-perfusion were calculated automatically using ImageJ software. Microvascular recovery was defined as a marked reduction in the numbers of microaneurysms (< 20%) or a marked reduction in the area of capillary non-perfusion (< 50%) in 45-degree fields or a complete regression of new vessels in ETDRS 7 standard fields. Baseline FA findings and changes in the ocular and systemic factors were analyzed. RESULTS: Twenty-eight (8.8%) of the 320 total eyes were found to meet the criteria of microvascular recovery after the treatments. Multivariate analysis revealed the presence of diffuse capillary telangiectasis (P = .003) and late disc leaking (P = .007) on baseline FA and a reduction of glycated hemoglobin (P = .005) during the follow-up period were predictive factors of microvascular recovery after the treatments. Although the microvascular recovery group presented with a significant improvement of BCVA after the treatments, the baseline BCVA could not predict the microvascular recovery after the treatments. CONCLUSIONS: Diffuse capillary telangiectasis or late disc leaking on baseline FA and improved glycemic control positively predicted the microvascular recovery after treatments for DR.

Retinopathy is associated with impaired cognition in patients undergoing peritoneal dialysis.

Objective: Previous studies have shown a relationship between retinopathy and cognition including population with and without chronic kidney disease (CKD) but data regarding peritoneal dialysis (PD) are limited. This study aims to investigate the relationship between retinopathy and cognitive impairment in patients undergoing peritoneal dialysis (PD). Methods: In this observational study, we recruited a total of 107 participants undergoing PD, consisting of 48 men and 59 women, ages ranging from 21 to 78 years. The study followed a cross-sectional design. Retinal microvascular characteristics, such as geometric changes in retinal vascular including tortuosity, fractal dimension (FD), and calibers, were assessed. Retinopathy (such as retinal hemorrhage or microaneurysms) was evaluated using digitized photographs. The Modified Mini-Mental State Examination (3MS) was performed to assess global cognitive function. Results: The prevalence rates of retinal hemorrhage, microaneurysms, and retinopathy were 25%, 30%, and 43%, respectively. The mean arteriolar and venular calibers were 63.2 and 78.5 µm, respectively, and the corresponding mean tortuosity was 37.7 ± 3.6 and 37.2 ± 3.0 mm-1. The mean FD was 1.49. After adjusting for age, sex, education, mean arterial pressure, and Charlson index, a negative association was revealed between retinopathy and 3MS scores (regression coefficient: -3.71, 95% confidence interval: -7.09 to -0.33, p = 0.03). Conclusions: Retinopathy, a condition common in patients undergoing PD, was associated with global cognitive impairment. These findings highlight retinopathy, can serve as a valuable primary screening tool for assessing the risk of cognitive decline.

Peripheral microcirculation alteration as cause of posterosuperior rotator cuff tear: the possible indirect contribution of nailfold capillaroscopy.

BACKGROUND: Most of the recent literature regarding rotator cuff tear etiology identifies in peripheral microcirculation disorders the probable main cause of tissue degeneration, and consequently of tendon rupture. Nailfold capillaroscopy is a practical and inexpensive diagnostic technique used to evaluate the health status of peripheral microcirculation, and recently, its use has found other indications in addition to that of diagnosing connective tissue diseases and Raynaud phenomenon. We verified the possible indirect contribution of nailfold capillaroscopy in the identification of peripheral microcirculation disturbances in a group of patients with rotator cuff tear and whether these possible alterations could be related to rotator cuff tear size. MATERIALS AND METHODS: A case-control study was performed. One hundred patients (56 male, 44 female; mean age ± standard deviation [SD]: 60.46 ± 5.46 years) with different-sized posterosuperior cuff tears and 100 healthy controls (38 male, 62 female; mean age ± SD: 60.40 ± 6.34 years) were submitted to capillaroscopic examination. The following parameters were examined: capillary morphology and density, avascular areas, visibility of the subpapillary venous plexus, enlarged and giant capillaries, ectasias and microaneurysms, neoangiogenesis, hemosiderin deposits, pericapillary edema, and capillary blood flow. Severe exclusion criteria were applied. Statistical analysis was performed. RESULTS: Visibility of subpapillary venous plexus (P < .001), pericapillary edema (P < .001), capillary blood flow (P < .001), ectasias and microaneurysms (P < .001), and neoangiogenesis (P = .04) were significantly associated with presence of a rotator cuff tear. CONCLUSIONS: Our results support the hypothesis that microcirculation disorder has a relevant role in the genesis of cuff degeneration and, consequently, of tendon rupture. However, these alterations do not seem to be related to rotator cuff tear size.

Automatic Detection of Microaneurysms in Fundus Images Using an Ensemble-Based Segmentation Method.

In this study, a novel method for automatic microaneurysm detection in color fundus images is presented. The proposed method is based on three main steps: (1) image breakdown to smaller image patches, (2) inference to segmentation models, and (3) reconstruction of the predicted segmentation map from output patches. The proposed segmentation method is based on an ensemble of three individual deep networks, such as U-Net, ResNet34-UNet and UNet++. The performance evaluation is based on the calculation of the Dice score and IoU values. The ensemble-based model achieved higher Dice score (0.95) and IoU (0.91) values compared to other network architectures. The proposed ensemble-based model demonstrates the high practical application potential for detection of early-stage diabetic retinopathy in color fundus images.

Role of Microaneurysms in the Pathogenesis and Therapy of Diabetic Macular Edema: A Descriptive Review.

Background and Objectives: This study aims to elucidate the role of microaneurysms (MAs) in the pathogenesis and treatment of diabetic retinopathy (DR) and diabetic macular edema (DME), the major causes of acquired visual impairment. Materials and Methods: We synthesized the relevance of findings on the clinical characteristics, pathogenesis, and etiology of MAs in DR and DME and their role in anti-vascular endothelial growth factor (VEGF) therapy. Results: MAs, a characteristic feature in DR and DME, can be detected by fluorescein angiography, optical coherence tomography (OCT) and OCT angiography. These instrumental analyses demonstrated a geographic and functional association between MA and ischemic areas. MA turnover, the production and loss of MA, reflects the activity of DME and DR. Several cytokines are involved in the pathogenesis of MAs, which is characterized by pericyte loss and endothelial cell proliferation in a VEGF-dependent or -independent manner. Ischemia and MAs localized in the deep retinal layers are characteristic of refractory DME cases. Even in the current anti-VEGF era, laser photocoagulation targeting MAs in the focal residual edema is still an effective therapeutic tool, but it is necessary to be creative in accurately identifying the location of MAs and performing highly precise and minimally invasive coagulation. Conclusions: MAs play a distinctive and important role in the pathogenesis of the onset, progression of DR and DME, and response to anti-VEGF treatment. Further research on MA is significant not only for understanding the pathogenesis of DME but also for improving the effectiveness of treatment.

The Role of Laser Photocoagulation in Treating Diabetic Macular Edema in the Era of Intravitreal Drug Administration: A Descriptive Review.

Background and Objectives: This study aimed to elucidate the role of laser photocoagulation therapy in the treatment of diabetic macular edema (DME) as an alternative to, or in conjunction with, the first-line treatment, anti-vascular endothelial growth factor (VEGF). Materials and Methods: A comprehensive literature search to identify studies that evaluated the efficacy of laser photocoagulation therapy in the management of DME was performed. The relevant findings of the efficacy of focal/grid laser therapy from data in randomized, controlled trials were synthesized, and the potential of new laser technologies, such as navigated laser systems, pattern scan lasers, and subthreshold lasers, was explored. The usefulness of multimodal imaging-guided laser therapy was also evaluated, with a focus on the potential contribution to anti-VEGF therapy. Results: Focal laser photocoagulation targeting microaneurysms remains an effective therapeutic approach to chronic refractory edema, despite the widespread use of anti-VEGF therapy. To achieve the best possible treatment outcomes, precise identification of microaneurysms is essential. This requires the use of multimodal imaging-guided, highly accurate, minimally invasive coagulation techniques. Subthreshold laser therapy can also reduce the frequency of anti-VEGF injections and minimize treatment burden. Conclusions: Further studies are needed to determine the optimal timing and settings for laser photocoagulation therapy and the potential of new laser technologies in the management of DME. Nevertheless, laser photocoagulation therapy plays an important role in the management of DME, in conjunction with anti-VEGF therapy.

Morphology and fluorescein leakage in diabetic retinal microaneurysms: a study using multiple en face OCT angiography image averaging.

PURPOSE: To investigate the relevance of microaneurysm morphology in optical coherence tomography angiography (OCTA) image averaging and fluorescein leakage in diabetic retinopathy (DR). METHODS: In 38 consecutive patients with DR, ten consecutive 3- × 3-mm fovea-centered OCTA (HS100, Canon Inc., Tokyo, Japan) and fluorescein angiography (FA) were performed, and averaged OCTA images were created based on the 10 images. After detecting all microaneurysms in FA images, the morphology was classified into four types (focal bulge, saccular/pedunculated, fusiform, and mixed) using averaged OCTA images. The correlation between microaneurysm leakage in FA, retinopathy stage, and microaneurysm morphology was estimated. RESULTS: Thirty-eight eyes (50.0%) of the 33 patients were available for analysis, and 370 (63.5%) of the 583 FA-detected microaneurysms were morphologically classifiable (focal bulge, 46; saccular/pedunculated, 143; fusiform, 29; and mixed, 152) in OCTA. There was a significant correlation between stage and percentage of microaneurysm morphology and between morphology and the presence of leakage (P < 0.0001 and P < 0.01, respectively). The proportion of focal bulges decreased with stage progression, while the other three types increased with stage progression. The percentage of FA leakage for focal bulge, saccular/pedunculated, fusiform, and mixed was 41.3%, 66.4%, 82.8%, and 66.4%, respectively, and the fusiform type showed significant FA leakage. CONCLUSION: Microaneurysm morphology is correlated with the DR stage and FA leakage. Microaneurysm morphology recognition using OCTA image averaging may be useful for the clinical evaluation of DR.

Optical coherence tomography angiography analysis of microvascular abnormalities and vessel density in treatment-naïve eyes with diabetic macular edema.

BACKGROUND: The aim of this study was to evaluate the structural retinal vascular integrity using optical coherence tomography angiography (OCTA) in treatment-naïve eyes with diabetic macular edema (DME) and to compare it with findings in diabetic eyes without DME. METHODS: In this prospective study, 70 eyes with diabetic retinopathy were included (37 eyes with DME and 33 eyes without DME). The medical records, including swept-source optical coherence tomography and 9 × 9 mm swept-source OCTA images were reviewed and compared between DME and non-DME groups. Microaneurysms, intraretinal microvascular abnormalities (IRMA), areas of capillary non perfusion, foveal avascular zone (FAZ), and capillary vascular density (CVD) were analyzed in the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). RESULTS: Compared to the non-DME eyes, DME eyes had more microaneurysms in the SCP and the DCP (p = 0,039 and p = 0,024 respectively), more IRMA in the SCP (p = 0,005), larger areas of capillary non perfusion in the SCP and the DCP (p = 0,026 and p = 0,02 respectively) and larger FAZ in both plexuses (p = 0,048 in the SCP and p = 0,012 in the DCP). The CVD in the DCP was lower in DME eyes compared to non-DME eyes (p = 0,007). The severity of DME was significantly correlated to the number of microaneurysms and to the FAZ surface. Central macular thickness was significantly correlated with the number of microaneurysms in the DCP, the surface of capillary non perfusion areas and the FAZ area in both plexuses. CONCLUSIONS: OCTA with a 9 × 9 mm field of view showed that the retinal vascular integrity regarding the number of microaneurysms, the number of IRMA, the surface of capillary non perfusion areas, the FAZ area and the CVD, was significantly more impaired in DME eyes compared to diabetic eyes without DME. The DCP seemed to be more affected in diabetic eyes with and without DME than the SCP.

Deep Learning Approach for Automatic Microaneurysms Detection.

In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness. In the proposed method, early detection of MAs is performed using a hybrid feature embedding approach of pre-trained CNN models, named as VGG-19 and Inception-v3. The performance of the proposed approach was evaluated using publicly available datasets, namely "E-Ophtha" and "DIARETDB1", and achieved 96% and 94% classification accuracy, respectively. Furthermore, the developed approach outperformed the state-of-the-art approaches in terms of sensitivity and specificity for microaneurysms detection.

[Detection of microaneurysms in fundus images based on improved YOLOv4 with SENet embedded].

Microaneurysm is the initial symptom of diabetic retinopathy. Eliminating this lesion can effectively prevent diabetic retinopathy in the early stage. However, due to the complex retinal structure and the different brightness and contrast of fundus image because of different factors such as patients, environment and acquisition equipment, the existing detection algorithms are difficult to achieve the accurate detection and location of the lesion. Therefore, an improved detection algorithm of you only look once (YOLO) v4 with Squeeze-and-Excitation networks (SENet) embedded was proposed. Firstly, an improved and fast fuzzy c-means clustering algorithm was used to optimize the anchor parameters of the target samples to improve the matching degree between the anchors and the feature graphs; Then, the SENet attention module was embedded in the backbone network to enhance the key information of the image and suppress the background information of the image, so as to improve the confidence of microaneurysms; In addition, an spatial pyramid pooling was added to the network neck to enhance the acceptance domain of the output characteristics of the backbone network, so as to help separate important context information; Finally, the model was verified on the Kaggle diabetic retinopathy dataset and compared with other methods. The experimental results showed that compared with other YOLOv4 network models with various structures, the improved YOLOv4 network model could significantly improve the automatic detection results such as F-score which increased by 12.68%; Compared with other network models and methods, the automatic detection accuracy of the improved YOLOv4 network model with SENet embedded was obviously better, and accurate positioning could be realized. Therefore, the proposed YOLOv4 algorithm with SENet embedded has better performance, and can accurately and effectively detect and locate microaneurysms in fundus images.

Charcot-Bouchard aneurysms revisited: clinicopathologic correlations.

Intracerebral hemorrhage (ICH) is a significant cause of morbidity and mortality worldwide. Hypertension and cerebral amyloid angiopathy (CAA) are the most common causes of primary ICH, but the mechanism of hemorrhage in both conditions is unclear. Although fibrinoid necrosis and Charcot-Bouchard aneurysms (CBAs) have been postulated to underlie vessel rupture in ICH, the role and significance of CBAs in ICH has been controversial. First described as the source of bleeding in hypertensive hemorrhage, they are also one of the CAA-associated microangiopathies along with fibrinoid necrosis, fibrosis and "lumen within a lumen appearance." We describe clinicopathologic findings of CBAs found in 12 patients out of over 2700 routine autopsies at a tertiary academic medical center. CBAs were rare and predominantly seen in elderly individuals, many of whom had multiple systemic and cerebrovascular comorbidities including hypertension, myocardial and cerebral infarcts, and CAA. Only one of the 12 subjects with CBAs had a large ICH, and the etiology underlying the hemorrhage was likely multifactorial. Two CBAs in the basal ganglia demonstrated associated microhemorrhages, while three demonstrated infarcts in the vicinity. CBAs may not be a significant cause of ICH but are a manifestation of severe cerebral small vessel disease including both hypertensive arteriopathy and CAA.

Visualization of microaneurysms in macular telangiectasia type 1 on optical coherence tomography angiography before and after photocoagulation.

PURPOSE: To evaluate changes in the visualization of microaneurysms (MAs) in cases of macular telangiectasia (Mac Tel) type 1 on optical coherence tomography angiography (OCTA) before and after treatment with direct photocoagulation and to evaluate their relationship with treatment efficacy. METHODS: The study included 12 eyes from 12 patients (8 men, 4 women; mean age 72.1 years) with Mac Tel type 1 accompanied by cystoid macular edema. OCTA for the evaluation of MAs was performed before and 15 min and 6, 12, and 24 weeks after photocoagulation. The best-corrected visual acuity (BCVA) and central retinal thickness (CRT) were also evaluated. RESULTS: A total of 73 MAs were detected within the areas of macular edema on OCTA, and 39 of these underwent photocoagulation. At 15 min after treatment, 17 MAs were no longer visible on OCTA. At 6 weeks, two MAs had reappeared, whereas five additional MAs were no longer visible. The CRT in eyes with resolved MA was significantly less than that in eyes with persistent MAs (p = 0.016). At 24 weeks, seven eyes had no visible MAs, and the BCVA was not significantly different from baseline. CONCLUSION: OCTA can monitor changes in the visualization of MAs associated with Mac Tel type 1 after direct photocoagulation. Eyes in which MAs disappeared after treatment could recover from cystoid macular edema.

[Microaneurysms as a biomarker of diabetic retinopathy]. / Mikroanevrizmy kak marker diabeticheskoi retinopatii.

Diabetic retinopathy is a microvascular pathology, which is the most common complication of diabetes mellitus. Improvement of instrumental diagnostics of retinal pathologies has contributed to identification of various phenotypes of the progression of ocular fundus pathology in diabetes based on specific changes in the retina - biomarkers. In particular, microaneurysms initially described in diabetes, which are a manifestation of a wide range of systemic pathologies and retinal diseases, are an indicator of the severity of diabetic retinopathy. Dynamic changes in the number of microaneurysms are a confirmed prognostic biomarker of clinically significant macular edema. In diabetic retinopathy, microaneurysms are one of the earliest recognizable signs, and the dynamic of their formation and disappearance may serve as a predictor for the disease progression. This literature review presents the characteristics of microaneurysms based on various imaging techniques, and analyses the link between structural features and dynamic changes in microaneurysms, and progression of diabetic retinopathy.

Microaneurysms detection in color fundus images using machine learning based on directional local contrast.

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.

Characteristic distribution of microaneurysms and capillary dropouts in diabetic macular edema.

PURPOSE: To investigate the distribution pattern of microaneurysms (MAs) and capillary dropouts (CDOs) related to retinal thickness in patients with diabetic macular edema (DME). METHODS: We designed a cross-sectional observational study in which we manually merged fluorescein angiography and optical coherence tomography (OCT) map and located MAs and CDOs areas. The density of MAs, the width and the length of circumference of CDOs, and the number of MAs adjacent to CDOs were compared between highly thickened (white area (WA) in OCT map) and border areas (red area (RA)). RESULTS: We examined 115 eyes of 115 patients with DME. The density of MAs in RA (1.086 ± 0.616) was significantly higher than that in WA (0.8601 ± 1.086) (p = 0.002). The MA rates adjacent to CDOs in WA and RA were 79.1% and 80.7%, respectively. In the RA, the size of CDO adjacent to MAs was smaller (p = 0.013), but its circumference was longer (p = 0.018), and the number of MAs adjacent to CDOs was larger than those in WA (p = 0.002). The total length of circumference of CDOs was significantly correlated with the number of MAs adjacent to CDOs in WA (p = 0.011, R2 = 0.68) and RA (p = 0.008, R2 = 0.81). CONCLUSION: Smaller but more CDOs with longer circumference adjacent to MAs contribute to the higher density of MAs in the surrounding areas of DME.

Decrease in the number of microaneurysms in diabetic macular edema after anti-vascular endothelial growth factor therapy: implications for indocyanine green angiography-guided detection of refractory microaneurysms.

PURPOSE: We evaluated changes in the numbers of microaneurysms (MAs) on fluorescein angiography (FA) and indocyanine green angiography (IA) in eyes with diabetic macular edema (DME) following intravitreal injection of anti-vascular endothelial growth factor (VEGF) agents. METHODS: Twenty-one eyes of 16 patients with DME were included in this retrospective study. All patients received an initial loading dose of three monthly injections of anti-VEGF agents; thereafter, they received a pro re nata regimen for at least 12 months of follow-up. FA and IA images were obtained before and at 6 months after the initial injection. RESULTS: The median numbers of MAs significantly decreased from six (interquartile range [IQR] 3-7) MAs in early-phase FA, three (IQR 3-5) leaky MAs in late-phase FA, and two (IQR 1-4) MAs in late-phase IA at baseline to two (IQR 1-3) MAs in early-phase FA, one (IQR 0-2) leaky MA in late-phase FA, and one (IQR 0-2) MA in late-phase IA at 6 months (P < 0.0001 for all). Only the median numbers of MAs in late-phase IA at baseline and at 6 months were significantly higher in the recurrent DME group (13 eyes) than in the non-recurrent DME group (five eyes) (three [IQR 2-4] vs one [IQR 1-2], one [IQR 0.5-2] vs zero [P = 0.0185 and P = 0.009]). CONCLUSION: Intravitreal injection of anti-VEGF agents reduced the numbers of MAs in patients with DME. The numbers of MAs detected by late-phase IA might be useful predictors of DME recurrence.