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Atherosclerosis is an inflammatory disease of large and medium-sized arteries, characterized by the growth of atherosclerotic lesions (plaques). These plaques often develop at inner curvatures of arteries, branchpoints, and bifurcations, where the endothelial wall shear stress is low and oscillatory. In conjunction with other processes such as lipid deposition, biomechanical factors lead to local vascular inflammation and plaque growth. There is also evidence that low and oscillatory shear stress contribute to arterial remodeling, entailing a loss in arterial elasticity and, therefore, an increased pulse-wave velocity. Although altered shear stress profiles, elasticity and inflammation are closely intertwined and critical for plaque growth, preclinical and clinical investigations for atherosclerosis mostly focus on the investigation of one of these parameters only due to the experimental limitations. However, cardiovascular magnetic resonance imaging (MRI) has been demonstrated to be a potent tool which can be used to provide insights into a large range of biological parameters in one experimental session. It enables the evaluation of the dynamic process of atherosclerotic lesion formation without the need for harmful radiation. Flow-sensitive MRI provides the assessment of hemodynamic parameters such as wall shear stress and pulse wave velocity which may replace invasive and radiation-based techniques for imaging of the vascular
function and the characterization of early plaque development. In combination with inflammation imaging, the analyses and correlations of these parameters could not only significantly advance basic preclinical investigations of atherosclerotic lesion formation and progression, but also the diagnostic clinical evaluation for early identification of high-risk plaques, which are prone to rupture. In this review, we summarize the key applications of magnetic resonance imaging for the evaluation of plaque characteristics through flow sensitive and morphological measurements. The simultaneous measurements of functional and structural parameters will further preclinical research on atherosclerosis and has the potential to fundamentally improve the detection of inflammation and vulnerable plaques in patients.
Previous magnetic resonance imaging (MRI) studies revealed structural-functional brain reorganization 12 months after gastric-bypass surgery, encompassing cortical and subcortical regions of all brain lobes as well as the cerebellum. Changes in the mean of cluster-wise gray/white matter density (GMD/WMD) were correlated with the individual loss of body mass index (BMI), rendering the BMI a potential marker of widespread surgery-induced brain plasticity. Here, we investigated voxel-by-voxel associations between surgery-induced changes in adiposity, metabolism and inflammation and markers of functional and structural neural plasticity. We re-visited the data of patients who underwent functional and structural MRI, 6 months (n = 27) and 12 months after surgery (n = 22), and computed voxel-wise regression analyses. Only the surgery-induced weight loss was significantly associated with brain plasticity, and this only for GMD changes. After 6 months, weight loss overlapped with altered GMD in the hypothalamus, the brain's homeostatic control site, the lateral orbitofrontal cortex, assumed to host reward and gustatory processes, as well as abdominal representations in somatosensory cortex. After 12 months, weight loss scaled with GMD changes in right cerebellar lobule VII, involved in language-related/cognitive processes, and, by trend, with the striatum, assumed to underpin (food) reward. These findings suggest time-dependent and weight-loss related gray matter plasticity in brain regions involved in the control of eating, sensory processing and cognitive functioning.
Conventional kiln drying of wood operates by the evaporation of water at elevated temperature. In the initial stage of drying, mobile water in the wood cell lumen evaporates. More slowly, water bound in the wood cell walls evaporates, requiring the breaking of hydrogen bonds between water molecules and cellulose and hemicellulose polymers in the cell wall. An alternative for wood kiln drying is a patented process for green wood dewatering through the molecular interaction of supercritical carbon dioxide with water of wood cell sap. When the system pressure is reduced to below the critical point, phase change from supercritical fluid to gas occurs with a consequent large change in CO2 volume. This results in the efficient, rapid, mechanical expulsion of liquid sap from wood. The end-point of this cyclical phase-change process is wood dewatered to the cell wall fibre saturation point. This paper describes dewatering over a range of green wood specimen sizes, from laboratory physical chemistry studies to pilot-plant trials. Magnetic resonance imaging and nuclear magnetic resonance spectroscopy were applied to study the fundamental mechanisms of the process, which were contrasted with similar studies of conventional thermal wood drying. In conclusion, opportunities and impediments towards the commercialisation of the green wood dewatering process are discussed.
Objective:
Over the past decade, myocardial triglyceride content has become an accepted biomarker for chronic metabolic and cardiac disease. The purpose of this study was to use proton (hydrogen 1)-magnetic resonance spectroscopy (\(^{1}\)H-MRS) at 3Tesla (3 T) field strength to assess potential gender-related differences in myocardial triglyceride content in healthy individuals.
Methods:
Cardiac MR imaging was performed to enable accurate voxel placement and obtain functional and morphological information. Double triggered (i.e., ECG and respiratory motion gating) \(^{1}\)H-MRS was used to quantify myocardial triglyceride levels for each gender. Two-sample t-test and Mann-Whitney U-test were used for statistical analyses.
Results:
In total, 40 healthy volunteers (22 male, 18 female; aged >18 years and age matched) were included in the study. Median myocardial triglyceride content was 0.28% (interquartile range [IQR] 0.17–0.42%) in male and 0.24% (IQR 0.14–0.45%) in female participants, and no statistically significant difference was observed between the genders. Furthermore, no gender-specific difference in ejection fraction was observed, although on average, male participants presented with a higher mean ± SD left ventricular mass (136.3 ± 25.2 g) than female participants (103.9 ± 16.1 g).
Conclusions:
The study showed that \(^{1}\)H-MRS is a capable, noninvasive tool for acquisition of myocardial triglyceride metabolites. Myocardial triglyceride concentration was shown to be unrelated to gender in this group of healthy volunteers.
In biological tissue, an accumulation of similarly shaped objects with a susceptibility difference to the surrounding tissue generates a local distortion of the external magnetic field in magnetic resonance imaging. It induces stochastic field fluctuations that characteristically influence proton spin dephasing in the vicinity of these magnetic perturbers. The magnetic field correlation that is associated with such local magnetic field inhomogeneities can be expressed in the form of a dynamic frequency autocorrelation function that is related to the time evolution of the measured magnetization. Here, an eigenfunction expansion for two simple magnetic perturber shapes, that of spheres and cylinders, is considered for restricted spin diffusion in a simple model geometry. Then, the concept of generalized moment analysis, an approximation technique that is applied in the study of (non-)reactive processes that involve Brownian motion, allows deriving analytical expressions of the correlation function for different exponential decay forms. Results for the biexponential decay for both spherical and cylindrical magnetized objects are derived and compared with the frequently used (less accurate) monoexponential decay forms. They are in asymptotic agreement with the numerically exact value of the correlation function for long and short times.
Purpose:
Bolus‐based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in‐silico model of the coronary arteries down to the pre‐arteriolar vessels has been developed.
Methods:
In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre‐arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification.
Results:
Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are −28% ± 16% and −8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree.
Conclusion:
Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus‐based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.
Background
Atrial fibrillation (AF) without other stroke risk factors is assumed to have a low annual stroke risk comparable to patients without AF. Therefore, current clinical guidelines do not recommend oral anticoagulation for stroke prevention of AF in patients without stroke risk factors. We analyzed brain magnetic resonance imaging (MRI) imaging to estimate the rate of clinically inapparent (“silent”) ischemic brain lesions in these patients.
Methods
We pooled individual patient-level data from three prospective studies comprising stroke-free patients with symptomatic AF. All study patients underwent brain MRI within 24–48 h before planned left atrial catheter ablation. MRIs were analyzed by a neuroradiologist blinded to clinical data.
Results
In total, 175 patients (median age 60 (IQR 54–67) years, 32% female, median CHA\(_2\)DS\(_2\)-VASc = 1 (IQR 0–2), 33% persistent AF) were included. In AF patients without or with at least one stroke risk factor, at least one silent ischemic brain lesion was observed in 4 (8%) out of 48 and 10 (8%) out of 127 patients, respectively (p > 0.99). Presence of silent ischemic brain lesions was related to age (p = 0.03) but not to AF pattern (p = 0.77). At least one cerebral microbleed was detected in 5 (13%) out of 30 AF patients without stroke risk factors and 25 (25%) out of 108 AF patients with stroke risk factors (p = 0.2). Presence of cerebral microbleeds was related to male sex (p = 0.04) or peripheral artery occlusive disease (p = 0.03).
Conclusion
In patients with symptomatic AF scheduled for ablation, brain MRI detected silent ischemic brain lesions in approximately one in 12 patients, and microbleeds in one in 5 patients. The prevalence of silent ischemic brain lesions did not differ in AF patients with or without further stroke risk factors.
Even as medical data sets become more publicly accessible, most are restricted to specific medical conditions. Thus, data collection for machine learning approaches remains challenging, and synthetic data augmentation, such as generative adversarial networks (GAN), may overcome this hurdle. In the present quality control study, deep convolutional GAN (DCGAN)-based human brain magnetic resonance (MR) images were validated by blinded radiologists. In total, 96 T1-weighted brain images from 30 healthy individuals and 33 patients with cerebrovascular accident were included. A training data set was generated from the T1-weighted images and DCGAN was applied to generate additional artificial brain images. The likelihood that images were DCGAN-created versus acquired was evaluated by 5 radiologists (2 neuroradiologists [NRs], vs 3 non-neuroradiologists [NNRs]) in a binary fashion to identify real vs created images. Images were selected randomly from the data set (variation of created images, 40%-60%). None of the investigated images was rated as unknown. Of the created images, the NRs rated 45% and 71% as real magnetic resonance imaging images (NNRs, 24%, 40%, and 44%). In contradistinction, 44% and 70% of the real images were rated as generated images by NRs (NNRs, 10%, 17%, and 27%). The accuracy for the NRs was 0.55 and 0.30 (NNRs, 0.83, 0.72, and 0.64). DCGAN-created brain MR images are similar enough to acquired MR images so as to be indistinguishable in some cases. Such an artificial intelligence algorithm may contribute to synthetic data augmentation for "data-hungry" technologies, such as supervised machine learning approaches, in various clinical applications.
Background:
Local aortic pulse wave velocity (PWV) is a measure for vascular stiffness and has a predictive value for cardiovascular events. Ultra high field CMR scanners allow the quantification of local PWV in mice, however these systems are yet unable to monitor the distribution of local elasticities.
Methods:
In the present study we provide a new accelerated method to quantify local aortic PWV in mice with phase-contrast cardiovascular magnetic resonance imaging (PC-CMR) at 17.6 T. Based on a k-t BLAST (Broad-use Linear Acquisition Speed-up Technique) undersampling scheme, total measurement time could be reduced by a factor of 6. The fast data acquisition enables to quantify the local PWV at several locations along the aortic blood vessel based on the evaluation of local temporal changes in blood flow and vessel cross sectional area. To speed up post processing and to eliminate operator bias, we introduce a new semi-automatic segmentation algorithm to quantify cross-sectional areas of the aortic vessel. The new methods were applied in 10 eight-month-old mice (4 C57BL/6J-mice and 6 ApoE\(^{(-/-)}\)-mice) at 12 adjacent locations along the abdominal aorta.
Results:
Accelerated data acquisition and semi-automatic post-processing delivered reliable measures for the local PWV, similiar to those obtained with full data sampling and manual segmentation. No statistically significant differences of the mean values could be detected for the different measurement approaches. Mean PWV values were elevated for the ApoE\(^{(-/-)}\)-group compared to the C57BL/6J-group (3.5 ± 0.7 m/s vs. 2.2 ± 0.4 m/s, p < 0.01). A more heterogeneous PWV-distribution in the ApoE \(^{(-/-)}\)-animals could be observed compared to the C57BL/6J-mice, representing the local character of lesion development in atherosclerosis.
Conclusion:
In the present work, we showed that k-t BLAST PC-MRI enables the measurement of the local PWV distribution in the mouse aorta. The semi-automatic segmentation method based on PC-CMR data allowed rapid determination of local PWV. The findings of this study demonstrate the ability of the proposed methods to non-invasively quantify the spatial variations in local PWV along the aorta of ApoE\(^{(-/-)}\)-mice as a relevant model of atherosclerosis.
Background: Regular exercise is beneficial for cardiovascular health but a recent meta-analysis indicated a relationship between extensive endurance sport and a higher risk of atrial fibrillation, an independent risk factor for stroke. However, data on the frequency of cardiac arrhythmias or (clinically silent) brain lesions during and after marathon running are missing.
Methods/Design: In the prospective observational "Berlin Beat of Running" study experienced endurance athletes underwent clinical examination (CE), 3 Tesla brain magnetic resonance imaging (MRI), carotid ultrasound imaging (CUI) and serial blood sampling (BS) within 2-3 days prior (CE, MRI, CUI, BS), directly after (CE, BS) and within 2 days after (CE, MRI, BS) the 38\(^{th}\) BMW BERLIN-MARATHON 2011. All participants wore a portable electrocardiogram (ECG)-recorder throughout the 4 to 5 days baseline study period. Participants with pathological MRI findings after the marathon, troponin elevations or detected cardiac arrhythmias will be asked to undergo cardiac MRI to rule out structural abnormalities. A follow-up is scheduled after one year.
Results: Here we report the baseline data of the enrolled 110 athletes aged 36-61 years. Their mean age was 48.8 \(\pm\) 6.0 years, 24.5% were female, 8.2% had hypertension and 2.7% had hyperlipidaemia. Participants have attended a mean of 7.5 \(\pm\) 6.6 marathon races within the last 5 years and a mean of 16 \(\pm\) 36 marathon races in total. Their weekly running distance prior to the 38\(^{th}\) BMW BERLIN-MARATHON was 65 \(\pm\) 17 km. Finally, 108 (98.2%) Berlin Beat-Study participants successfully completed the 38\(^{th}\) BMW BERLIN-MARATHON 2011.
Discussion: Findings from the "Berlin Beats of Running" study will help to balance the benefits and risks of extensive endurance sport. ECG-recording during the marathon might contribute to identify athletes at risk for cardiovascular events. MRI results will give new insights into the link between physical stress and brain damage.