SLOctolyzer: Fully Automatic Analysis Toolkit for Segmentation and Feature Extracting in Scanning Laser Ophthalmoscopy Images.

Purpose: The purpose of this study was to introduce SLOctolyzer: an open-source analysis toolkit for en face retinal vessels in infrared reflectance scanning laser ophthalmoscopy (SLO) images.

Methods: SLOctolyzer includes two main modules: segmentation and measurement. The segmentation module uses deep learning methods to delineate retinal anatomy, and detects the fovea and optic disc, whereas the measurement module quantifies the complexity, density, tortuosity, and caliber of the segmented retinal vessels.

Choroidalyzer: An Open-Source, End-to-End Pipeline for Choroidal Analysis in Optical Coherence Tomography.

Purpose: To develop Choroidalyzer, an open-source, end-to-end pipeline for segmenting the choroid region, vessels, and fovea, and deriving choroidal thickness, area, and vascular index.

Methods: We used 5600 OCT B-scans (233 subjects, six systemic disease cohorts, three device types, two manufacturers). To generate region and vessel ground-truths, we used state-of-the-art automatic methods following manual correction of inaccurate segmentations, with foveal positions manually annotated.

PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness.

Purpose: We sough to develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fiber layer (pRNFL) thickness.

Methods: We used deep learning to segment the optic disc, fovea, and vessels in fundus photographs, and measured pallor. We assessed the relationship between pallor and pRNFL thickness derived from optical coherence tomography scans in 118 participants.

An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.

Purpose: To develop an open-source, fully automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data.

Methods: We used a dataset of 715 OCT B-scans (82 subjects, 115 eyes) from three clinical studies related to systemic disease. Ground-truth segmentations were generated using a clinically validated, semiautomatic choroid segmentation method, Gaussian Process Edge Tracing (GPET).

Evaluation of an Automated Choroid Segmentation Algorithm in a Longitudinal Kidney Donor and Recipient Cohort.

Purpose: To evaluate the performance of an automated choroid segmentation algorithm in optical coherence tomography (OCT) data using a longitudinal kidney donor and recipient cohort.

Methods: We assessed 22 donors and 23 patients requiring renal transplantation over up to 1 year posttransplant. We measured choroidal thickness (CT) and area and compared our automated CT measurements to manual ones at the same locations.

Guardians and research staff experiences and views about the consent process in hospital-based paediatric research studies in urban Malawi: A qualitative study.

Background: Obtaining consent has become a standard way of respecting the patient's rights and autonomy in clinical research. Ethical guidelines recommend that the child's parent/s or authorised legal guardian provides informed consent for their child's participation. However, obtaining informed consent in paediatric research is challenging.

Histological Identification of Sequestered Parasitized Red Cells.

The performance of complete post-mortem examinations of children with severe malaria has helped to explain the cause of death in cerebral malaria as well as show the global phenomenon of sequestration in tissues throughout the body, beyond the brain and eye. The pathology of the brain and other organs has been well described and shows a systemic disease with the most catastrophic features found in the brain (i.e.

Ocular Pathology of Cerebral Malaria.

Investigation of post-mortem eyes from children with malarial retinopathy has helped to explain the retinal pathology of cerebral malaria, and also demonstrated histological associations between evolving retinal pathogenesis-visible clinically-and similar cerebral features which can only be examined at autopsy. The pathology of malarial retinopathy has been well-described and correlates with brain pathology. Some clinical and pathological features are associated with outcome.

Measuring the Impact of Malaria on the Living Human Retina.

Retinal examination and imaging are relatively simple methods for studying the dynamic impact of cerebral malaria on the microcirculation of the central nervous system. Retina and brain are affected similarly by Plasmodium falciparum. Unlike the brain, the human retina can be directly observed using commercially available clinical instruments in the setting of a critical care unit, and this can be done repeatedly and non-invasively.

Bridging and Clumping: Investigating Platelet Interactions with P. falciparum-Infected Red Blood Cells and Endothelial Cells in Cerebral Malaria.

The methods presented in this chapter describe how to perform ex vivo clumping and in vitro bridging assays in the context of cerebral malaria. Both the protocols are detailed, and emphasis is made on how to prepare platelet suspensions suitable to each technique, including description of specific buffers and reagents to minimize the risk of aggregation while maintaining the platelet properties.

A proposed theoretical framework for retinal biomarkers.

Objective: Propose a theoretical framework for retinal biomarkers of Alzheimer's disease (AD).

Background: The retina and brain share important biological features that are relevant to AD. Developing retinal biomarkers of AD is a strategic priority but as yet none have been validated for clinical use.

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based polygon regression methods, we build a novel graph neural network (GNN) based deep learning framework with multiple graph reasoning modules to explicitly leverage both region and boundary features in an end-to-end manner. The mechanism extracts discriminative region and boundary features, referred to as initialized region and boundary node embeddings, using a proposed Attention Enhancement Module (AEM).

How Does Blood-Retinal Barrier Breakdown Relate to Death and Disability in Pediatric Cerebral Malaria?

Background: In cerebral malaria, the retina can be used to understand disease pathogenesis. The mechanisms linking sequestration, brain swelling, and death remain poorly understood. We hypothesized that retinal vascular leakage would be associated with brain swelling.

Correction: Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile.

[This corrects the article DOI: 10.1371/journal.pone.

Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile.

Background: Glaucoma is the leading cause of irreversible blindness worldwide. It is a heterogeneous group of conditions with a common optic neuropathy and associated loss of peripheral vision. Both over and under-diagnosis carry high costs in terms of healthcare spending and preventable blindness.

Neurovascular sequestration in paediatric malaria is visible clinically in the retina.

Retinal vessel changes and retinal whitening, distinctive features of malarial retinopathy, can be directly observed during routine eye examination in children with cerebral malaria. We investigated their clinical significance and underlying mechanisms through linked clinical, clinicopathological and image analysis studies. Orange vessels and severe foveal whitening (clinical examination, n = 817, OR, 95% CI: 2.

Spatial statistical modelling of capillary non-perfusion in the retina.

Manual grading of lesions in retinal images is relevant to clinical management and clinical trials, but it is time-consuming and expensive. Furthermore, it collects only limited information - such as lesion size or frequency. The spatial distribution of lesions is ignored, even though it may contribute to the overall clinical assessment of disease severity, and correspond to microvascular and physiological topography.

Linking EPCR-Binding PfEMP1 to Brain Swelling in Pediatric Cerebral Malaria.

Brain swelling is a major predictor of mortality in pediatric cerebral malaria (CM). However, the mechanisms leading to swelling remain poorly defined. Here, we combined neuroimaging, parasite transcript profiling, and laboratory blood profiles to develop machine-learning models of malarial retinopathy and brain swelling.

Decreased Rate of Plasma Arginine Appearance in Murine Malaria May Explain Hypoargininemia in Children With Cerebral Malaria.

Background:  Plasmodium infection depletes arginine, the substrate for nitric oxide synthesis, and impairs endothelium-dependent vasodilation. Increased conversion of arginine to ornithine by parasites or host arginase is a proposed mechanism of arginine depletion.

Methods:  We used high-performance liquid chromatography to measure plasma arginine, ornithine, and citrulline levels in Malawian children with cerebral malaria and in mice infected with Plasmodium berghei ANKA with or without the arginase gene.

Longitudinal Visuomotor Development in a Malaria Endemic Area: Cerebral Malaria and Beyond.

Paediatric cerebral malaria is the most serious complication of Plasmodium falciparum infection. While the majority recover, long-term cognitive impairment has been highlighted as a significant and neglected problem. Persistent or serious deficits in processes such as attention or behavioural inhibition should be manifest in changes to performance on oculomotor tasks.

Grading fluorescein angiograms in malarial retinopathy.

Background: Malarial retinopathy is an important finding in Plasmodium falciparum cerebral malaria, since it strengthens diagnostic accuracy, predicts clinical outcome and appears to parallel cerebral disease processes. Several angiographic features of malarial retinopathy have been described, but observations in different populations can only be reliably compared if consistent methodology is used to capture and grade retinal images. Currently no grading scheme exists for fluorescein angiographic features of malarial retinopathy.

Developing retinal biomarkers of neurological disease: an analytical perspective.

The inaccessibility of the brain poses a problem for neuroscience. Scientists have traditionally responded by developing biomarkers for brain physiology and disease. The retina is an attractive source of biomarkers since it shares many features with the brain.

Automated Detection of Vessel Abnormalities on Fluorescein Angiogram in Malarial Retinopathy.

The detection and assessment of intravascular filling defects is important, because they may represent a process central to cerebral malaria pathogenesis: neurovascular sequestration. We have developed and validated a framework that can automatically detect intravascular filling defects in fluorescein angiogram images. It first employs a state-of-the-art segmentation approach to extract the vessels from images and then divide them into individual segments by geometrical analysis.