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. We trained a U-Net deep learning model to detect the region, vessels, and fovea to calculate choroid thickness, area, and vascular index in a fovea-centered region of interest. We analyzed segmentation agreement (AUC, Dice) and choroid metrics agreement (Pearson, Spearman, mean absolute error [MAE]) in internal and external test sets. We compared Choroidalyzer to two manual graders on a small subset of external test images and examined cases of high error. Results: Choroidalyzer took 0.299 seconds per image on a standard laptop and achieved excellent region (Dice: internal 0.9789, external 0.9749), very good vessel segmentation performance (Dice: internal 0.8817, external 0.8703), and excellent fovea location prediction (MAE: internal 3.9 pixels, external 3.4 pixels). For thickness, area, and vascular index, Pearson correlations were 0.9754, 0.9815, and 0.8285 (internal)/0.9831, 0.9779, 0.7948 (external), respectively (all P < 0.0001). Choroidalyzer's agreement with graders was comparable to the intergrader agreement across all metrics. Conclusions: Choroidalyzer is an open-source, end-to-end pipeline that accurately segments the choroid and reliably extracts thickness, area, and vascular index. Especially choroidal vessel segmentation is a difficult and subjective task, and fully automatic methods like Choroidalyzer could provide objectivity and standardization.

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. Separately, we used images diagnosed by clinical inspection as pale (n = 45) and assessed how measurements compared with healthy controls (n = 46). We also developed automatic rejection thresholds and tested the software for robustness to camera type, image format, and resolution. Results: We developed software that automatically quantified disc pallor across several zones in fundus photographs. Pallor was associated with pRNFL thickness globally (ß = -9.81; standard error [SE] = 3.16; P < 0.05), in the temporal inferior zone (ß = -29.78; SE = 8.32; P < 0.01), with the nasal/temporal ratio (ß = 0.88; SE = 0.34; P < 0.05), and in the whole disc (ß = -8.22; SE = 2.92; P < 0.05). Furthermore, pallor was significantly higher in the patient group. Last, we demonstrate the analysis to be robust to camera type, image format, and resolution. Conclusions: We developed software that automatically locates and quantifies disc pallor in fundus photographs and found associations between pallor measurements and pRNFL thickness. Translational Relevance: We think our method will be useful for the identification, monitoring, and progression of diseases characterized by disc pallor and optic atrophy, including glaucoma, compression, and potentially in neurodegenerative disorders.

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. We estimated associations between choroidal measurements and markers of renal function (estimated glomerular filtration rate [eGFR], serum creatinine, and urea) using correlation and linear mixed-effects (LME) modeling. Results: There was good agreement between manual and automated CT. Automated measures were more precise because of smaller measurement error over time. External adjudication of major discrepancies was in favor of automated measures. Significant differences were observed in the choroid pre- and posttransplant in both cohorts, and LME modeling revealed significant linear associations observed between choroidal measures and renal function in recipients. Significant associations were mostly stronger with automated CT (eGFR, P < 0.001; creatinine, P = 0.004; urea, P = 0.04) compared to manual CT (eGFR, P = 0.002; creatinine, P = 0.01; urea, P = 0.03). Conclusions: Our automated approach has greater precision than human-performed manual measurements, which may explain stronger associations with renal function compared to manual measurements. To improve detection of meaningful associations with clinical endpoints in longitudinal studies of OCT, reducing measurement error should be a priority, and automated measurements help achieve this. Translational Relevance: We introduce a novel choroid segmentation algorithm that can replace manual grading for studying the choroid in renal disease and other clinical conditions.

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). We finetuned a U-Net with the MobileNetV3 backbone pretrained on ImageNet. Standard segmentation agreement metrics, as well as derived measures of choroidal thickness and area, were used to evaluate DeepGPET, alongside qualitative evaluation from a clinical ophthalmologist. Results: DeepGPET achieved excellent agreement with GPET on data from three clinical studies (AUC = 0.9994, Dice = 0.9664; Pearson correlation = 0.8908 for choroidal thickness and 0.9082 for choroidal area), while reducing the mean processing time per image on a standard laptop CPU from 34.49 ± 15.09 seconds using GPET to 1.25 ± 0.10 seconds using DeepGPET. Both methods performed similarly according to a clinical ophthalmologist who qualitatively judged a subset of segmentations by GPET and DeepGPET, based on smoothness and accuracy of segmentations. Conclusions: DeepGPET, a fully automatic, open-source algorithm for choroidal segmentation, will enable researchers to efficiently extract choroidal measurements, even for large datasets. As no manual interventions are required, DeepGPET is less subjective than semiautomatic methods and could be deployed in clinical practice without requiring a trained operator. Translational Relevance: DeepGPET addresses the lack of open-source, fully automatic, and clinically relevant choroid segmentation algorithms, and its subsequent public release will facilitate future choroidal research in both ophthalmology and wider systemic health.

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. Parents become vulnerable because of stress related to their child's illness. Understanding the views held by guardians and researchers about the consent process in Malawi, where there are limitations in health care access and research literacy will assist in developing appropriate consent guidelines. METHODS: We conducted 20 in-depth interviews with guardians of children and research staff who had participated in paediatric clinical trial and observational studies in acute and non-acute settings in the Southern Region of Malawi. Interviews were audio-recorded, transcribed verbatim, and thematically analysed. Interviews were compared across studies and settings to identify differences and similarities in participants' views about informed consent processes. Data analysis was facilitated by NVIVO 11 software. RESULTS: All participants across study types and settings reported that they associated participating in research with therapeutic benefits. Substantial differences were noted in the decision-making process across study settings. Guardians from acute studies felt that the role of their spouses was neglected during consenting, while staff reported that they had problems obtaining consent from guardians when their partners were not present. Across all study types and settings, research staff reported that they emphasised the benefits more than the risks of the study to participants, due to pressure to recruit. Participants from non-acute settings were more likely to recall information shared during the consent process than participants in the acute setting. CONCLUSION: The health care context, culture and research process influenced participants' understanding of study information across study types and settings. We advise research managers or principal investigators to define minimum requirements that would not compromise the consent process and conduct study specific training for staff. The use of one size fits all consent process may not be ideal. More guidance is needed on how these differences can be incorporated during the consent process to improve understanding and delivery of consent. Trial registration Not applicable.

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.

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. Additional information about blood-tissue barriers can be gained from fluorescein angiography. Non-ophthalmologist clinician scientists are usually unfamiliar with ophthalmoscopy and retinal imaging, and some readers may feel that these techniques are beyond them. This chapter aims to quell these fears by providing a step-by-step description of how to examine and photograph the human retina in children with cerebral malaria.

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. This chapter describes the materials and methods needed to study the pathological features of malarial retinopathy. Some are common to histopathology in general, but accurate spatial correlation between retinal features observed in life and their associated pathology in post-mortem specimens requires special techniques.

Investigating Interactions Between Endothelial Cells and Parasitized Red Blood Cells in Skin and Subcutaneous Tissue.

In this chapter we present the methods for using biopsies of skin or subcutaneous tissue to examine the interactions between parasitized red blood cells and endothelial cells in patients with malaria infection. Punch biopsy can be used to obtain all skin layers and needle biopsy to obtain subcutaneous tissue. Smears are useful for spreading vessels on a slide for immunofluorescence staining. Specimens can be fixed and embedded for sectioning and traditional histological or immunostaining techniques or confocal microscopy with three-dimensional reconstruction. Finally, endothelium can be dissociated, allowing individual cells to be isolated for culture and ex vivo assays or used for immunophenotyping.

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., fatal cerebral edema).This chapter describes the materials and methods needed to study the pathological features of tissues outside of the eye, including the brain and other organs. The bulk of these techniques are standard to pathology including gross examination, histology, special stains, and immunohistochemistry.

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. Part of the reason may be that fundamental inferential assumptions have been overlooked. Failing to recognize these assumptions will disadvantage biomarker discovery and validation, but incorporating them into analyses could facilitate translation. New theory: The biological assumption that a disease causes analogous effects in the brain and retina can be expressed within a Bayesian network. This allows inferences about abstract theory and individual events, and provides an opportunity to falsify the foundational hypothesis of retina-brain analogy. Graphical representation of the relationships between variables simplifies comparison between studies and facilitates judgements about whether key assumptions are valid given the current state of knowledge. Major challenges: The framework provides a visual approach to retinal biomarkers and may help to rationalize analysis of future studies. It suggests possible reasons for inconsistent results in existing literature on AD biomarkers. Linkage to other theories: The framework can be modified to describe alternative theories of retinal biomarker biology, such as retrograde degeneration resulting from brain disease, and can incorporate confounding factors such as co-existent glaucoma or macular degeneration. Parallels with analogue confirmation theory and surrogate marker validation suggest strengths and weaknesses of the framework that can be anticipated when developing analysis plans. Highlights: Retinal biomarkers hold great promise for Alzheimer's disease (AD), but none are currently used clinically.Assumptions about the cause of retinal and brain changes are often overlooked, and this may disadvantage biomarker discovery and validation.We present a new approach to retinal biomarkers that describes cause and effect graphically in a Bayesian network.We show how this allows a more complete assessment of how well a biomarker might reflect the brain, and how data from right and left eyes can be used to rule out poor biomarker candidates.

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. The Quality in Prognosis Studies (QUIPS) tool was used for quality assessment, followed by narrative synthesis of included studies. RESULTS: Eight cohort studies were identified. Three showed significant positive associations between DR and poor COVID-19 outcomes. The highest quality study, McGurnaghan, found increased risk of the combined outcome fatal or critical care unit (CCU)-treated COVID-19 with referable-grade DR (OR 1.672, 95% CI 1.38-2.03). Indirectly, four studies reported positive associations with microvascular disease and poorer prognosis. Variability between studies limited comparability. CONCLUSIONS: The current literature suggests an independent association between DR and poorer COVID-19 prognosis in patients with DM after controlling for key variables such as age. The use of standardised methodology in future studies would establish the predictive value of DR with greater confidence. Researchers should consider comparing the predictive value of DR and its severity, to other microvascular complications of DM.

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. METHODS: We used retinal angiography to study blood-retinal barrier integrity. We analyzed retinal leakage, histopathology, brain magnatic resonance imaging (MRI), and associations with death and neurological disability in prospective cohorts of Malawian children with cerebral malaria. RESULTS: Three types of retinal leakage were seen: large focal leak (LFL), punctate leak (PL), and vessel leak. The LFL and PL were associated with death (odds ratio [OR] = 13.20, 95% confidence interval [CI] = 5.21-33.78 and OR = 8.58, 95% CI = 2.56-29.08, respectively) and brain swelling (P < .05). Vessel leak and macular nonperfusion were associated with neurological disability (OR = 3.71, 95% CI = 1.26-11.02 and OR = 9.06, 95% CI = 1.79-45.90). Large focal leak was observed as an evolving retinal hemorrhage. A core of fibrinogen and monocytes was found in 39 (93%) white-centered hemorrhages. CONCLUSIONS: Blood-retina barrier breakdown occurs in 3 patterns in cerebral malaria. Associations between LFL, brain swelling, and death suggest that the rapid accumulation of cerebral hemorrhages, with accompanying fluid egress, may cause fatal brain swelling. Vessel leak, from barrier dysfunction, and nonperfusion were not associated with severe brain swelling but with neurological deficits, suggesting hypoxic injury in survivors.

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). The weighted links between cross-domain nodes (region and boundary feature domains) in each graph are defined in a data-dependent way, which retains both global and local cross-node relationships. The iterative message aggregation and node update mechanism can enhance the interaction between each graph reasoning module's global semantic information and local spatial characteristics. Our model, in particular, is capable of concurrently addressing region and boundary feature reasoning and aggregation at several different feature levels due to the proposed multi-level feature node embeddings in different parallel graph reasoning modules. Experiments on two types of challenging datasets demonstrate that our method outperforms state-of-the-art approaches for segmentation of polyps in colonoscopy images and of the optic disc and optic cup in colour fundus images. The trained models will be made available at: https://github.com/smallmax00/Graph_Region_Boudnary.

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.0209409.].

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. The characteristic clinical feature of glaucoma is asymmetrical optic nerve rim narrowing, which is difficult for humans to quantify reliably. Strategies to improve and automate optic disc assessment are therefore needed to prevent sight loss. METHODS: We developed a novel glaucoma detection algorithm that segments and analyses colour photographs to quantify optic nerve rim consistency around the whole disc at 15-degree intervals. This provides a profile of the cup/disc ratio, in contrast to the vertical cup/disc ratio in common use. We introduce a spatial probabilistic model, to account for the optic nerve shape, we then use this model to derive a disc deformation index and a decision rule for glaucoma. We tested our algorithm on two separate image datasets (ORIGA and RIM-ONE). RESULTS: The spatial algorithm accurately distinguished glaucomatous and healthy discs on internal and external validation (AUROC 99.6% and 91.0% respectively). It achieves this using a dataset 100-times smaller than that required for deep learning algorithms, is flexible to the type of cup and disc segmentation (automated or semi-automated), utilises images with missing data, and is correlated with the disc size (p = 0.02) and the rim-to-disc at the narrowest rim (p<0.001, in external validation). DISCUSSION: The spatial probabilistic algorithm is highly accurate, highly data efficient and it extends to any imaging hardware in which the boundaries of cup and disc can be segmented, thus making the algorithm particularly applicable to research into disease mechanisms, and also glaucoma screening in low resource settings.

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. The detection of MR can reduce the false positive diagnosis of CM and alert physicians to investigate for other possible causes of the clinical symptoms and apply a more appropriate clinical intervention of underlying diseases. In order to facilitate easily accessible and affordable means of MR detection, we have developed an automated software system that detects the retinal lesions specific to MR, whitening and hemorrhages, using retinal color fundus images. The individual lesion detection algorithms were combined into an MR detection model using partial least square classifier. The classifier model was trained and tested on retinal image dataset obtained from 64 patients presenting with clinical signs of CM (44 with MR, 20 without MR). The MR detection model yielded specificity of 92% and sensitivity of 68%, with an AUC of 0.82. The proposed MR detection system demonstrates potential for broad screening of MR and can be integrated with a low-cost and portable retinal camera, to provide a bed-side tool for confirming CM diagnosis.

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. Enzyme-linked immunosorbent assay was used to determine plasma and CSF PfHRP-2 levels. Wilcoxon rank-sum tests and multivariable logistic regression analysis assessed the association of clinical and radiographic characteristics with the primary outcome of death during hospitalization. RESULTS: In this cohort of 94 patients, median age was 44 (interquartile range 29-62) months, 53 (56.4%) patients were male, 6 (7%) were HIV-infected, and 10 (11%) died during hospitalization. Elevated concentrations of plasma lactate (p = 0.005) and CSF PfHRP-2 (p = 0.04) were significantly associated with death. On multivariable analysis, higher PfHRP-2 in the CSF was associated with death (odds ratio 9.00, 95% confidence interval 1.44-56.42) while plasma PfHRP-2 was not (odds ratio 2.05, 95% confidence interval 0.45-9.35). CONCLUSIONS: Elevation of CSF, but not plasma PfHRP-2, is associated with death in this paediatric CM cohort. PfHRP-2 egress into the CSF may represent alteration of blood brain barrier permeability related to the sequestration of parasitized erythrocytes in the cerebral microvasculature.

Neurovascular sequestration in paediatric P. falciparum 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 P. falciparum 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: 2.90, 1.96-4.30; 3.4, 1.8-6.3, both p<0.001), and arteriolar involvement by intravascular filling defects (angiographic image analysis, n = 260, 2.81, 1.17-6.72, p<0.02) were strongly associated with death. Orange vessels had dense sequestration of late stage parasitised red cells (histopathology, n = 29; sensitivity 0.97, specificity 0.89) involving 360° of the lumen circumference, with altered protein expression in blood-retinal barrier cells and marked loss/disruption of pericytes. Retinal whitening was topographically associated with tissue response to hypoxia. Severe neurovascular sequestration is visible at the bedside, and is a marker of severe disease useful for diagnosis and management.