Association between choroidal microvasculature in the eye and Alzheimer's disease risk in cognitively healthy mid-life adults: A pilot study.

Introduction: We explored associations between measurements of the ocular choroid microvasculature and Alzheimer's disease (AD) risk.

Methods: We measured the choroidal vasculature appearing in optical coherence tomography (OCT) scans of 69 healthy, mid-life individuals in the PREVENT Dementia cohort. The cohort was prospectively split into low-, medium-, and high-risk groups based on the presence of known risk factors (apolipoprotein E [] ε4 genotype and family history of dementia [FH]).

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.

Pre-existing diabetic retinopathy as a prognostic factor for COVID-19 outcomes amongst people with diabetes: A systematic review.

Aims: Certain patients with Diabetes Mellitus (DM) have high risk for complications from COVID-19. We aimed to test the hypothesis that pre-existing diabetic retinopathy (DR), a microvascular disease, is a prognostic indicator for poor COVID-19 outcome in this heterogeneous population.

Methods: Seven databases (including MEDLINE) and grey literature were searched, identifying eligible studies using predetermined selection criteria.

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.

Automated Detection of Malarial Retinopathy in Retinal Fundus Images obtained in Clinical Settings.

Cerebral malaria (CM) is a life-threatening clinical syndrome associated with 5-10% of malarial infection cases, most prevalent in Africa. About 23% of cerebral malaria cases are misdiagnosed as false positives, leading to inappropriate treatment and loss of lives. Malarial retinopathy (MR) is a retinal manifestation of CM that presents with a highly specific set of lesions.

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.

Cerebrospinal fluid Plasmodium falciparum histidine-rich protein-2 in pediatric cerebral malaria.

Background: Cerebral malaria (CM) causes a rapidly developing coma, and remains a major contributor to morbidity and mortality in malaria-endemic regions. This study sought to determine the relationship between cerebrospinal fluid (CSF) Plasmodium falciparum histidine rich protein-2 (PfHRP-2) and clinical, laboratory and radiographic features in a cohort of children with retinopathy-positive CM.

Methods: Patients included in the study were admitted (2009-2013) to the Pediatric Research Ward (Queen Elizabeth Central Hospital, Blantyre, Malawi) meeting World Health Organization criteria for CM with findings of malarial retinopathy.

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.

Evidence from a natural experiment that malaria parasitemia is pathogenic in retinopathy-negative cerebral malaria.

Cerebral malaria (CM) can be classified as retinopathy-positive or retinopathy-negative, based on the presence or absence of characteristic retinal features. While malaria parasites are considered central to the pathogenesis of retinopathy-positive CM, their contribution to retinopathy-negative CM is largely unknown. One theory is that malaria parasites are innocent bystanders in retinopathy-negative CM and the etiology of the coma is entirely non-malarial.