1,721,134 research outputs found
Systematic Comparison of Heatmapping Techniques in Deep Learning in the Context of Diabetic Retinopathy Lesion Detection
No full textPurpose: Heatmapping techniques can support explainability of deep learning (DL) predictions inmedical image analysis. However, individual techniques have been mainly applied in a descriptive way without an objective and systematic evaluation. We investigated comparative performances using diabetic retinopathy lesion detection as a benchmark task. Methods: The Indian Diabetic Retinopathy Image Dataset (IDRiD) publicly available database contains fundus images of diabetes patients with pixel level annotations of diabetic retinopathy (DR) lesions, the ground truth for this study. Three in advance trained DL models (ResNet50, VGG16 or InceptionV3) were used for DR detection in these images. Next, explainability was visualized with each of the 10 most used heatmapping techniques. The quantitative correspondence between the output of a heatmap and the ground truth was evaluated with the Explainability Consistency Score (ECS), a metric between 0 and 1, developed for this comparative task. Results: In case of the overall DR lesions detection, the ECS ranged from 0.21 to 0.51 for all model/heatmapping combinations. The highest score was for VGG16+Grad-CAM (ECS= 0.51; 95% confidence interval [CI]: [0.46; 0.55]). For individual lesions, VGG16+Grad-CAM performed best on hemorrhages and hard exudates. ResNet50+SmoothGrad performed best for soft exudates and ResNet50+Guided Backpropagation performed best for microaneurysms. Conclusions: Our empirical evaluation on the IDRiD database demonstrated that the combination DL model/heatmapping affects explainability when considering common DR lesions. Our approach found considerable disagreement between regions highlighted by heatmaps and expert annotations.Supported by intramural funding from VITO.De Boever, P (corresponding author), Univ Antwerp, Dept Biol, Univ Pl 1, B-2610 Antwerp, Belgium.
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Pathological myopia classification with simultaneous lesion segmentation using deep learning
No full textBACKGROUND AND OBJECTIVES: Pathological myopia (PM) is the seventh leading cause of blindness, with a reported global prevalence up to 3%. Early and automated PM detection from fundus images could aid to prevent blindness in a world population that is characterized by a rising myopia prevalence. We aim to assess the use of convolutional neural networks (CNNs) for the detection of PM and semantic segmentation of myopia-induced lesions from fundus images on a recently introduced reference data set. METHODS: This investigation reports on the results of CNNs developed for the recently introduced Pathological Myopia (PALM) dataset, which consists of 1200 images. Our CNN bundles lesion segmentation and PM classification, as the two tasks are heavily intertwined. Domain knowledge is also inserted through the introduction of a new Optic Nerve Head (ONH)-based prediction enhancement for the segmentation of atrophy and fovea localization. Finally, we are the first to approach fovea localization using segmentation instead of detection or regression models. Evaluation metrics include area under the receiver operating characteristic curve (AUC) for PM detection, Euclidean distance for fovea localization, and Dice and F1 metrics for the semantic segmentation tasks (optic disc, retinal atrophy and retinal detachment). RESULTS: Models trained with 400 available training images achieved an AUC of 0.9867 for PM detection, and a Euclidean distance of 58.27 pixels on the fovea localization task, evaluated on a test set of 400 images. Dice and F1 metrics for semantic segmentation of lesions scored 0.9303 and 0.9869 on optic disc, 0.8001 and 0.9135 on retinal atrophy, and 0.8073 and 0.7059 on retinal detachment, respectively. CONCLUSIONS: We report a successful approach for a simultaneous classification of pathological myopia and segmentation of associated lesions. Our work was acknowledged with an award in the context of the "Pathological Myopia detection from retinal images" challenge held during the IEEE International Symposium on Biomedical Imaging (April 2019). Considering that (pathological) myopia cases are often identified as false positives and negatives in glaucoma deep learning models, we envisage that the current work could aid in future research to discriminate between glaucomatous and highly-myopic eyes, complemented by the localization and segmentation of landmarks such as fovea, optic disc and atrophy.sponsorship: The first author is jointly supported by the Research Group Ophthalmology, KU Leuven and VITO NV. This research received funding from the Flemish Government under the "Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen" programme. No outside entities have been involved in the study design, in the collection, analysis and interpretation of data, in the writing of the manuscript, nor in the decision to submit the manuscript for publication. Thus, the authors declare that there are no conflicts of interest in this work. (Research Group Ophthalmology, VITO NV, Flemish Government, KU Leuven)status: Published onlin
A smartphone-based solution to monitor daily physical activity in a care home
No full textINTRODUCTION: In an ageing population, increasing chronic disease prevalence puts a high economic burden on society. Physical activity plays an important role in disease prevention and should therefore be promoted in the elderly. METHODS: In this study, a mobile health (mHealth) system was implemented in a care home setting to monitor and promote elderly peoples' daily activity. The physical activity of 20 elderly people (8 female and 12 male, aged 81 ± 9 years old) was monitored over 10 weeks using the mHealth system, consisting of a smartphone and heart rate belt. Feedback on physical activity was provided weekly. A reference performance test battery derived from the Senior Fitness Test determined the participants' physical fitness. RESULTS: Activity levels increased from week 1 onwards, peaking at week 5, and decreasing slightly until week 10. This illustrates that the use of mHealth and feedback on physical activity can motivate the elderly to become more active, but that the effect is transient without other incentives. Bio-data from the mHealth system were translated into a fitness score explaining 65% of the test battery's variance. After separating the elderly into three groups depending on physical fitness determined from the test battery, classification based on the fitness score resulted in a correct classification rate of 67.3%. DISCUSSION: This study demonstrates that an mHealth system can be implemented in a care home setting to motivate activity of the elderly, and that the bio-data can be translated in a fitness score predicting the outcome of labour-intensive tests.sponsorship: The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The project Fit-4-Life 65+ received financial support from the province Flemish Brabant in the context of action domain Lifetech Sensing 'technological solutions for prevention and diagnostics in healthcare'. (province Flemish Brabant)status: Publishe
Vascular health assessment with flow-mediated dilatation and retinal image analysis : a pilot study in an adult population from Cape Town
No full textAbstract: Aim: Flow-mediated dilatation (FMD) and retinal vascular analysis (RVA) may assist in predicting cardiovascular disease (CVD) but are poorly characterised in South Africa. We recorded baseline FMD and retinal vascular widths in healthy participants, and investigated associations with cardiovascular risk factors. Methods: Endothelial function (measured with FMD), microvascular structure (evaluated via fundus image analysis) and major CVD risk factors were assessed in 66 participants from Cape Town. Results: Median FMD% was 9.6%, with higher values in females. Mean retinal arteriolar and venular widths were similar to 156 and similar to 250 mu m, respectively. FMD was not associated with CVD risk factors. Hypertension was associated with narrower retinal arterioles and venules. Conclusions: We report novel baseline FMD data in healthy South African adults from the Western Cape, and show that retinal microvascular calibres are associated with blood pressure. Our baseline FMD and RVA data could serve as a reference for future studies in South Africa
Editorial: The Effects of Climate Change and Environmental Factors on Exercising Children and Youth
Full text linkEditorial on the Research TopicThe Effects of Climate Change and Environmental Factors on Exercising Children and YouthThe effects of climate change will exert both indirect (e.g., ecosystem disruption, air pollution, and changing disease-vector patterns) and direct (e.g., droughts, floods, wildfires, temperature increases) impacts on human health (Figure 1), especially in vulnerable populations like children (Helldén et al., 2021). How these factors affect physical activity (PA) in children is less frequently investigated. Indeed, child health is not prioritized in policy-making to the level required to reduce harm (Pegram and Colon, 2019). A recent scoping review concluded that children will experience high morbidity and mortality burden in the coming years because of climate change (Helldén et al., 2021)
Analysis of retinal blood vessel diameters in patients with COPD undergoing a pulmonary rehabilitation program
No full textBackground: Regular exercise positively affects cardiovascular physiology, translating into the adequate capacity of microvascular blood vessels to dilate in response to acute bouts of exercise. However, this remains unstudied in patients with chronic obstructive pulmonary disease (COPD), who often suffer from cardiovascular comorbidity. Therefore, we studied acute changes in retinal blood vessel diameters in response to high-intensity exercise in patients with COPD. The effect of an exercise-based 8-week pulmonary rehabilitation (PR) program was evaluated. We consider changes in these retinal metrics as an indicator of microvascular reactivity. Methods: Demographics and clinical characteristics of 41 patients were collected at the start and end of the PR program. Patients performed a high-intensity exercise test on a cycle ergometer at the start and end of the PR program, during which we collected retinal images. Fundus images were taken immediately before and 0, 5, 10, 15, and 30 min after the ergometer test. Widths of retinal blood vessels, represented as Central Retinal Arteriolar and Venular Equivalents (CRAE and CRVE), were calculated. Results: Thirty patients with COPD completed the study protocol (57% males; mean age: 64 +/- 7 years; mean FEV1: 45 +/- 17%pred). We did not observe a change in retinal vessel widths following the ergometer test at the start of the PR program. This null result remained at the end of the 8-week PR program. Our observations did not alter when considering responders and non-responders to PR. Conclusion: Retinal blood vessel diameters of patients with COPD did not change following an exercise test on an ergometer. The exercise-based PR program of eight weeks did not counteract the blunted retinal microvascular response
Making the invisible visible - retinal microvascular reactivity in ischemic cardiac patients and healthy individuals.
No full textPublication published at 10.1080/00015385.2017.128436
Systematic Review on Fractal Dimension of the Retinal Vasculature in Neurodegeneration and Stroke: Assessment of a Potential Biomarker
No full textIntroduction: Ocular manifestations in several neurological pathologies accentuate the strong relationship between the eye and the brain. Retinal alterations in particular can serve as surrogates for cerebral changes. Offering a "window to the brain," the transparent eye enables non-invasive imaging of these changes in retinal structure and vasculature. Fractal dimension (FD) reflects the overall complexity of the retinal vasculature. Changes in FD could reflect subtle changes in the cerebral vasculature that correspond to preclinical stages of neurodegenerative diseases. In this review, the potential of this retinal vessel metric to serve as a biomarker in neurodegeneration and stroke will be explored. Methods: A literature search was conducted, following the PRISMA Statement 2009 criteria, in four large bibliographic databases (Pubmed, Embase, Web Of Science and Cochrane Library) up to 12 October 2019. Articles have been included based upon their relevance. Wherever possible, level of evidence (LOE) has been assessed by means of the Oxford Centre for Evidence-based Medicine Level of Evidence classification. Results: Twenty-one studies were included for qualitative synthesis. We performed a narrative synthesis and produced summary tables of findings of included papers because methodological heterogeneity precluded a meta-analysis. A significant association was found between decreased FD and neurodegenerative disease, mainly addressing cognitive impairment (CI) and dementia. In acute, subacute as well as chronic settings, decreased FD seems to be associated with stroke. Differences in FD between subtypes of ischemic stroke remain unclear. Conclusions: This review provides a summary of the scientific literature regarding the association between retinal FD and neurodegenerative disease and stroke. Central pathology is associated with a decreased FD, as a measure of microvascular network complexity. As retinal FD reflects the global integrity of the cerebral microvasculature, it is an attractive parameter to explore. Despite obvious concerns, mainly due to a lack of methodological standardization, retinal FD remains a promising non-invasive and low-cost diagnostic biomarker for neurodegenerative and cerebrovascular disease. Before FD can be implemented in clinic as a diagnostic biomarker, the research community should strive for uniformization and standardization.sponsorship: SL has received a Ph.D. grant from VITO to performa joint Ph.D. between VITO and UZ Leuven. (VITO)status: Publishe
Cardiovascular effects of air pollution: current evidence from animal and human studies
No full textAir pollution is a global health concern. Particulate matter (PM)(2.5), a component of ambient air pollution, has been identified by the World Health Organization as one of the pollutants that poses the greatest threat to public health. Cardiovascular health effects have been extensively documented, and these effects are still being researched to provide an overview of recent literature regarding air pollution-associated cardiovascular morbidity and mortality in humans. Additionally, potential mechanisms through which air pollutants affect the cardiovascular system are discussed based on human and additional animal studies. We used the strategy of a narrative review to summarize the scientific literature of studies that were published in the past 7 yr. Searches were carried out on PubMed and Web of Science using predefined search queries. We obtained an initial set of 800 publications that were filtered to 78 publications that were relevant to include in this review. Analysis of the literature showed significant associations between air pollution, especially PM2.5, and the risk of elevated blood pressure (BP), acute coronary syndrome, myocardial infarction (MI), cardiac arrhythmia, and heart failure (HF). Prominent mechanisms that underlie the adverse effects of air pollution include oxidative stress, systemic inflammation, endothelial dysfunction, autonomic imbalance, and thrombogenicity. The current review underscores the relevance of air pollution as a global health concern that affects cardiovascular health. More rigorous standards are needed to reduce the cardiovascular disease burden imposed by air pollution. Continued research on the health impact of air pollution is needed to provide further insight
Making the invisible visible - retinal microvascular reactivity in ischemic cardiac patients and healthy individuals.
No full textPublication published at 10.1080/00015385.2017.128436
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