232 research outputs found

    Autonomous virulence adaptation improves coevolutionary optimization

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    The European Network for Translational Research in Atrial Fibrillation (EUTRAF): objectives and initial results.

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    Atrial fibrillation (AF) is the most common sustained arrhythmia in the general population. As an age-related arrhythmia AF is becoming a huge socio-economic burden for European healthcare systems. Despite significant progress in our understanding of the pathophysiology of AF, therapeutic strategies for AF have not changed substantially and the major challenges in the management of AF are still unmet. This lack of progress may be related to the multifactorial pathogenesis of atrial remodelling and AF that hampers the identification of causative pathophysiological alterations in individual patients. Also, again new mechanisms have been identified and the relative contribution of these mechanisms still has to be established. In November 2010, the European Union launched the large collaborative project EUTRAF (European Network of Translational Research in Atrial Fibrillation) to address these challenges. The main aims of EUTRAF are to study the main mechanisms of initiation and perpetuation of AF, to identify the molecular alterations underlying atrial remodelling, to develop markers allowing to monitor this processes, and suggest strategies to treat AF based on insights in newly defined disease mechanisms. This article reports on the objectives, the structure, and initial results of this network

    Artificial intelligence in digital pathology: a diagnostic test accuracy systematic review and meta-analysis

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    Ensuring diagnostic performance of AI models before clinical use is key to the safe and successful adoption of these technologies. Studies reporting AI applied to digital pathology images for diagnostic purposes have rapidly increased in number in recent years. The aim of this work is to provide an overview of the diagnostic accuracy of AI in digital pathology images from all areas of pathology. This systematic review and meta-analysis included diagnostic accuracy studies using any type of artificial intelligence applied to whole slide images (WSIs) in any disease type. The reference standard was diagnosis through histopathological assessment and / or immunohistochemistry. Searches were conducted in PubMed, EMBASE and CENTRAL in June 2022. We identified 2976 studies, of which 100 were included in the review and 48 in the full meta-analysis. Risk of bias and concerns of applicability were assessed using the QUADAS-2 tool. Data extraction was conducted by two investigators and meta-analysis was performed using a bivariate random effects model. 100 studies were identified for inclusion, equating to over 152,000 whole slide images (WSIs) and representing many disease types. Of these, 48 studies were included in the meta-analysis. These studies reported a mean sensitivity of 96.3% (CI 94.1-97.7) and mean specificity of 93.3% (CI 90.5-95.4) for AI. There was substantial heterogeneity in study design and all 100 studies identified for inclusion had at least one area at high or unclear risk of bias. This review provides a broad overview of AI performance across applications in whole slide imaging. However, there is huge variability in study design and available performance data, with details around the conduct of the study and make up of the datasets frequently missing. Overall, AI offers good accuracy when applied to WSIs but requires more rigorous evaluation of its performance.Comment: 26 pages, 5 figures, 8 tables + Supplementary material

    Complementary role of cardiac CT in the assessment of aortic valve replacement dysfunction

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    Aortic valve replacement is the second most common cardiothoracic procedure in the UK. With an ageing population, there are an increasing number of patients with prosthetic valves that require follow-up. Imaging of prosthetic valves is challenging with conventional echocardiographic techniques making early detection of valve dysfunction or complications difficult. CT has recently emerged as a complementary approach offering excellent spatial resolution and the ability to identify a range of aortic valve replacement complications including structural valve dysfunction, thrombus development, pannus formation and prosthetic valve infective endocarditis. This review discusses each and how CT might be incorporated into a multimodal cardiovascular imaging pathway for the assessment of aortic valve replacements and in guiding clinical management

    Contrast-enhanced computed tomography assessment of aortic stenosis

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    Objectives Non-contrast CT aortic valve calcium scoring ignores the contribution of valvular fibrosis in aortic stenosis. We assessed aortic valve calcific and non-calcific disease using contrast-enhanced CT. Methods This was a post hoc analysis of 164 patients (median age 71 (IQR 66-77) years, 78% male) with aortic stenosis (41 mild, 89 moderate, 34 severe; 7% bicuspid) who underwent echocardiography and contrast-enhanced CT as part of imaging studies. Calcific and non-calcific (fibrosis) valve tissue volumes were quantified and indexed to annulus area, using Hounsfield unit thresholds calibrated against blood pool radiodensity. The fibrocalcific ratio assessed the relative contributions of valve fibrosis and calcification. The fibrocalcific volume (sum of indexed non-calcific and calcific volumes) was compared with aortic valve peak velocity and, in a subgroup, histology and valve weight. Results Contrast-enhanced CT calcium volumes correlated with CT calcium score (r=0.80, p<0.001) and peak aortic jet velocity (r=0.55, p<0.001). The fibrocalcific ratio decreased with increasing aortic stenosis severity (mild: 1.29 (0.98-2.38), moderate: 0.87 (1.48-1.72), severe: 0.47 (0.33-0.78), p<0.001) while the fibrocalcific volume increased (mild: 109 (75-150), moderate: 191 (117-253), severe: 274 (213-344) mm 3 /cm 2). Fibrocalcific volume correlated with ex vivo valve weight (r=0.72, p<0.001). Compared with the Agatston score, fibrocalcific volume demonstrated a better correlation with peak aortic jet velocity (r=0.59 and r=0.67, respectively), particularly in females (r=0.38 and r=0.72, respectively). Conclusions Contrast-enhanced CT assessment of aortic valve calcific and non-calcific volumes correlates with aortic stenosis severity and may be preferable to non-contrast CT when fibrosis is a significant contributor to valve obstruction

    Contrast-enhanced computed tomography assessment of aortic stenosis

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    Abstract Objectives Non-contrast CT aortic valve calcium scoring ignores the contribution of valvular fibrosis in aortic stenosis. We assessed aortic valve calcific and non-calcific disease using contrast-enhanced CT. Methods This was a post hoc analysis of 164 patients (median age 71 (IQR 66–77) years, 78% male) with aortic stenosis (41 mild, 89 moderate, 34 severe; 7% bicuspid) who underwent echocardiography and contrast-enhanced CT as part of imaging studies. Calcific and non-calcific (fibrosis) valve tissue volumes were quantified and indexed to annulus area, using Hounsfield unit thresholds calibrated against blood pool radiodensity. The fibrocalcific ratio assessed the relative contributions of valve fibrosis and calcification. The fibrocalcific volume (sum of indexed non-calcific and calcific volumes) was compared with aortic valve peak velocity and, in a subgroup, histology and valve weight. Results Contrast-enhanced CT calcium volumes correlated with CT calcium score (r=0.80, p<0.001) and peak aortic jet velocity (r=0.55, p<0.001). The fibrocalcific ratio decreased with increasing aortic stenosis severity (mild: 1.29 (0.98–2.38), moderate: 0.87 (1.48–1.72), severe: 0.47 (0.33–0.78), p<0.001) while the fibrocalcific volume increased (mild: 109 (75–150), moderate: 191 (117–253), severe: 274 (213–344) mm3/cm2). Fibrocalcific volume correlated with ex vivo valve weight (r=0.72, p<0.001). Compared with the Agatston score, fibrocalcific volume demonstrated a better correlation with peak aortic jet velocity (r=0.59 and r=0.67, respectively), particularly in females (r=0.38 and r=0.72, respectively). Conclusions Contrast-enhanced CT assessment of aortic valve calcific and non-calcific volumes correlates with aortic stenosis severity and may be preferable to non-contrast CT when fibrosis is a significant contributor to valve obstruction
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