Background/ObjectiveDespite the relevance of pancreatic fat content in the development of metabolic diseases, its association with impaired glucose metabolism, diabetes, and other adipose tissue compartments remains unclear. Thus, we determined differences in pancreatic fat content by magnetic resonance imaging (MRI) between subjects with prediabetes, diabetes, and normal controls in a cohort from the general population.MethodsSubjects without history of cardiovascular disease with established diabetes or prediabetes as well as normal controls were included and underwent whole-body MRI on a 3T scanner. Pancreatic fat content was quantified by measuring the proton-density fat fraction (PDFFpanc) using a 3D multi-echo GRE sequence (increment: 1.23 ms, 6 echoes) by placing ROIs in the pancreatic head, body, and tail by independent readers. In addition, hepatic fat content as well as abdominal subcutaneous and visceral adipose tissue (SAT and VAT) were measured by multi-echo GRE and 3D 2-point volume-interpolated DIXON MRI, respectively. Univariate and multivariate analyses were employed to determine associations.ResultsA total of 385 subjects were included in the analysis (median age: 57 years, 58.2% males), of them 53 were classified as subjects with diabetes, 95 as prediabetes, and 237 as controls (13.8%, 24.7%, and 61.6%; respectively). The median PDFFpanc was 5.2% [IQR 3.3–9.4], and significantly higher in subjects with prediabetes and diabetes as compared to controls (PDFFpanc: 6.2% [IQR: 3.5–12] vs. 8.6% [IQR: 4.3–17.5] vs. 4.9% [3.1–7.4], p<0.001, respectively). After adjusting for age, gender and BMI the association was attenuated (all p>0.12). While in univariate analysis BMI, PDFFhepatic, SAT and VAT were associated with PDFFpanc (all p<0.05), only VAT predicted PDFFpanc independently (β: 0.02, 95%-confidence interval: 0.01–0.04, p<0.001).ConclusionWhile pancreatic fat content differs significantly between subjects with prediabetes, diabetes and controls, this association may be confounded by age, gender, and the amount of VAT in this cross-sectional study.

Severe Plasmodium falciparum malaria evolves through the interplay among capillary sequestration of parasitized erythrocytes, deregulated inflammatory responses, and hemostasis dysfunction. After rupture, each parasitized erythrocyte releases not only infective merozoites, but also the digestive vacuole (DV), a membrane-bounded organelle containing the malaria pigment hemozoin. In the present study, we report that the intact organelle, but not isolated hemozoin, dually activates the alternative complement

Subjects with prediabetes and diabetes but preserved LVEF had higher LV remodelling indices, suggesting early detectable changes in the disease process, while diffuse myocardial fibrosis appears to be less relevant at this stage.

VAT and VAT/SAT ratio are associated with impaired glucose metabolism, independent of cardiovascular risk factors or MRI-based quantification technique, with a decreasing effect of VAT/SAT ratio in obese subjects. Advances in knowledge: Quantification of VAT and VAT/SAT ratio by MRI represents a reproducable biomarker associated with cardiometabolic risk factors in subjects with impaired glucose metabolism, while the association of VAT/SAT ratio with glycemic state is attenuated in obese subjects.

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MRI-derived adipose tissue measurements perform similarly in identifying prevalent hypertension compared with anthropometric markers. Especially, TAT, VAT and PAT as well as WHtR and waist circumference were highly correlated with prevalent hypertension.

Advances of computational sciences over the last decades have enabled the introduction of novel methodological approaches in biomedical research. Acquiring extensive and comprehensive data about a research subject and subsequently extracting significant information has opened new possibilities in gaining insight into biological and medical processes. This so-called big data approach has recently found entrance into medical imaging and numerous epidemiological studies have been implementing advanced imaging to identify imaging biomarkers that provide information about physiological processes, including normal development and aging but also on the development of pathological disease states. The purpose of this article is to present existing epidemiological imaging studies and to discuss opportunities, methodological and organizational aspects, and challenges that population imaging poses to the field of big data research.

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