Correction to: Lack of netrin-4 alters vascular remodeling in the retina.

The article "Lack of netrin-4 alters vascular remodeling in the retina".

Lack of netrin-4 alters vascular remodeling in the retina.

PURPOSE: Netrin-4 (NTN4) is a protein that plays an important role in the regulation of angiogenesis in the pathological retina. Some evidences show that it can also have a role in inflammation and vascular stability. We will explore these questions in vivo in the mature mouse retina. METHODS: We created a NTN4 knockout that expresses EGFP in mononuclear phagocytes (CSFR1-positive cells) to track inflammation in vivo in the retina by scanning laser ophthalmoscopy (SLO). Fundus angiography permitted to study blood vessels. Retinal function was assessed with electroretinography (ERG). RESULTS: Lack of NTN4 leads to an increased amount of amoeboid mononuclear phagocytes in the adult retina, and blood vessels displayed increased tortuosity when compared with the wildtype. Inner retina function also seemed affected in NTN4 null. Lack of NTN4 resulted in a higher persistence of hyaloid artery and spontaneous leakage in the adult retina. No differences were found regarding vessel bifurcation, vessel width, or vein/artery ratio. CONCLUSIONS: These in vivo data show for the first time that lack of NTN4 induces changes in the retinal vascular phenotype in a non-pathological scenario. This evidence widens the role of NTN4 as a guidance cue in vascular remodeling.

A Fast and Efficient Technique for the Automatic Tracing of Corneal Nerves in Confocal Microscopy.

PURPOSE: We describe a novel fully automatic method capable of tracing the subbasal plexus nerves from human corneal confocal images. METHODS: Following an increasing interest in the automatic analysis of corneal nerves, a few approaches have been proposed. These, however, cannot cope with large images, such as mosaics, in due time. The rationale of the proposed method is to minimize required computing time while still providing accurate results. Our method consists of two sequential steps - a thresholding step followed by a supervised classification. For the classification we use a support vector machines (SVM) approach. Initially, a large set of features is computed, which is later reduced using a backward-elimination based on segmentation accuracy. To validate the obtained tracings, we evaluated the tracing accuracy and reliability of extracted clinical parameters (corneal nerves density and tortuosity). RESULTS: The proposed algorithm proved capable to correctly trace 0.89 ± 0.07 of the corneal nerves. The obtained performance level was comparable to a second human grader. Furthermore, the proposed approach compares favorably to other methods. For both evaluated clinical parameters the proposed approach performed well. An execution time of 0.61 ± 0.07 seconds per image was achieved. The proposed algorithm was applied successfully to mosaic images, with run times of the order of tens of seconds. CONCLUSIONS: The achieved quality and processing time of the proposed method appear adequate for the application of this technique to clinical practice. TRANSLATIONAL RELEVANCE: The automatic tracing of corneal nerves is an important step for the quantitative analysis of corneal nerves in daily clinical practice. The proposed fast technique allows features, such as corneal nerve density and tortuosity, to be computed in a few seconds. The application of nerve tracing to mosaics covering a large area can be a key component in clinical studies aimed at investigating neuropathy influence in various ocular or systemic diseases.

Automatic Gunn and Salus sign quantification in retinal images.

Prolonged hypertension can lead to abnormal changes in the retinal vasculature, including sclerosis and thickening of the arteriole walls. These changes can cause compression (Gunn's sign) and deflection (Salus's sign) of the veins at arteriovenous crossings. In retinal images, Gunn's sign appears as a tapering of the vein at a crossing point, while Salus's sign presents as an S-shaped curving. This paper presents a method for the automatic quantification of these two signs once a crossover has been detected; combining segmentation, artery vein classification, and morphological feature extraction techniques to calculate vein widths and angles entering and exiting the crossover. The method was tested on a small set of crossings, graded by a set of 3 doctors who were in agreement as having or not having Gunn/Salus sign. Results show separation between the two classes and that we can reliably detect and quantify these sign under the right conditions.

Evaluation of geometric features as biomarkers of diabetic retinopathy for characterizing the retinal vascular changes during the progression of diabetes.

Diabetic retinopathy (DR) has been widely studied and characterized. However, until now, it is unclear how different features, extracted from the retinal vasculature, can be associated with the progression of diabetes and therefore become biomarkers of DR. In this study, a comprehensive analysis is presented, in which four groups were created, using eighty fundus images from twenty patients, who have progressed to DR and they had no history of any other diseases (e.g. hypertension or glaucoma). The significance of the following features was evaluated: widths, angles, branching coefficient (BC), angle-to-BC ratio, standard deviations, means and medians of widths and angles, fractal dimension (FD), lacunarity and FD-to-lacunarity ratio, using a mixed model analysis of variance (ANOVA) design. All the features were measured from the same junctions of each patient, using an automated tool. The discriminative power of these features was evaluated, using decision trees and random forests classifiers. Cross validation and out-of-bag error were used to evaluate the classifiers' performance, calculating the area under the ROC curve (AUC) and the classification error. Widths, FD and FD-to-Lacunarity ratio were found to differ significantly. Random forests had a superior performance of 0.768 and 0.737 in the AUC for the two cases of classification, namely three-years-pre-DR/post-DR and two-years-pre-DR/post-DR respectively.

Measuring blood flow velocity from intravital video recordings.

There is an obvious scientific interest in computing blood flow velocity from intravital microscopy using digital video cameras attached to microscopes. Therefore, software capable of measuring blood flow velocity from videos is of major importance. In this work, a novel software tool is presented. The software tackles three main issues in velocity measurement from videos, the registration, segmentation, and finally the measuring itself. The software was tested in chick chorioallantoic membrane (CAM) videos captured with different resolutions, frame rates, and even cameras. The obtained results show the robustness achieved.

A multiscale optimization approach to detect exudates in the macula.

Pathologies that occur on or near the fovea, such as clinically significant macular edema (CSME), represent high risk for vision loss. The presence of exudates, lipid residues of serous leakage from damaged capillaries, has been associated with CSME, in particular if they are located one optic disc-diameter away from the fovea. In this paper, we present an automatic system to detect exudates in the macula. Our approach uses optimal thresholding of instantaneous amplitude (IA) components that are extracted from multiple frequency scales to generate candidate exudate regions. For each candidate region, we extract color, shape, and texture features that are used for classification. Classification is performed using partial least squares (PLS). We tested the performance of the system on two different databases of 652 and 400 images. The system achieved an area under the receiver operator characteristic curve (AUC) of 0.96 for the combination of both databases and an AUC of 0.97 for each of them when they were evaluated independently.

Automatic detection of microdots in the stromal layer of corneal images.

Microdots are bright, 1-2um features of the cornea. It has not been proven what these dots represent, but they are thought to be remnants of apoptotic cell death, such as lipofuscin granules. Their presence has been shown to correlate with corneal aging and extended contact use, both of which are linked to oxygen deprivation in the cornea. Confocal images of the stroma show these microdots mixed with larger keratocyte cells. This paper presents a method for detecting microdots using a two-step filtering scheme that separates the keratocyte cells and the microdots. Keratocyte cell locations are then used to eliminate falsely detected microdots. Results are compared to ground truth based on a grading scale from 0-5. Two graders were given a set of 50 images to grade using a GUI that included sample images for each of the six grades. The two graders had a correlation of .88 with each other. The algorithm had a correlation of .88 with the average of graders and .85 with each of the graders individually.

Automatic montaging of corneal sub-basal nerve images for the composition of a wide-range mosaic.

We present and discuss a computerized system able to provide a wide-range mosaic of the sub-basal nerve layer of central cornea, built from several images acquired in-vivo with confocal microscopy. The montage is performed by a fast, reliable and fully automatic computerized system that does not require any expedient or manual adjustment during the acquisition process. The resulting mosaic provides a large high quality image, which should significantly aid clinicians in evaluating and assessing in a more reliable way the pathologic signs of interest.