MRI-based Biomechanical Modeling of Carotid Atherosclerotic Plaques

__Abstract__ Carotid atherosclerosis is a common cause of acute ischemic stroke and places a major burden on worldwide health-related quality of life. The currently-used stenosis-degree guidelines to decide on surgical intervention through carotid endarterectomy in order to prevent a future event are imperfect. This is because they insufficiently target plaque vulnerability. To provide an alternative carotid plaque vulnerability assessment, one can compute the biomechanical peak cap stress using noninvasive magnetic resonance imaging (MRI). In this dissertation, we used MRI simulations to assess the accuracy of plaque segmentation and stress analysis. We also investigated plaque elasticity estimation through combining inverse finite element analysis and ultrasound strain measurements. A comparison between peak cap stress and histological classification led to the finding that a reliable identification of thick-cap stable carotid plaques might be a more fruitful approach to reduce carotid surgeries on

A Framework for Local Mechanical Characterization of Atherosclerotic Plaques: Combination of Ultrasound Displacement Imaging and Inverse Finite Element Analysis

Biomechanical models have the potential to predict plaque rupture. For reliable models, correct material properties of plaque components are a prerequisite. This study presents a new technique, where high resolution ultrasound displacement imaging and inverse finite element (FE) modeling is combined, to estimate material properties of plaque components. Iliac arteries with plaques were excised from 6 atherosclerotic pigs and subjected to an inflation test with pressures ranging from 10 to 120 mmHg. The arteries were imaged with high frequ

Can we use in vivo MRI and FEA to determine peak cap stress in carotid plaques? MRI simulations provide answers

Vulnerable plaques are characterized by a large lipid-rich necrotic core (LRNC) separated by a thin fibrous cap (FC) from the lumen. Plaque rupture occurs when the peak stress in the FC exceeds its strength. Carotid in vivo magnetic resonance imaging (MRI) data can be segmented to obtain the plaque geometry noninvasively. An increasing number of studies use MR imaging for biomechanical finite element analysis (FEA) to compute peak cap stresses [1, 2]. Previous studies have shown that the thickness of the FC is an important determinant of peak cap stress: the thinner the FC, the higher the stress, the higher the plaque rupture risk [3]

The influence of inaccuracies in carotid MRI segmentation on atherosclerotic plaque stress computations

Biomechanical finite element analysis (FEA) based on in vivo carotid magnetic resonance imaging (MRI) can be used to assess carotid plaque vulnerability noninvasively by computing peak cap stress. However, the accuracy of MRI plaque segmentation and the influence this has on FEA has remained unreported due to the lack of a reliable submillimeter ground truth. In this study, we quantify this influence using novel numerical simulations of carotid MRI. Histological sections from carotid plaques from 12 patients were used to create 33 ground truth plaque models. These models were subjected to numerical computer simulations of a currently used clinically applied 3.0 T T1-weighted black-blood carotid MRI protocol (in-plane acquisition voxel size of 0.62 × 0.62 mm2) to generate simulated in vivo MR images from a known underlying ground truth. The simulated images were manually segmented by three MRI readers. FEA models based on the MRI segmentations were compared with the FEA models based on the ground truth. MRI-based FEA model peak cap stress was consistently underestimated, but still correlated (R) moderately with the ground truth stress: R = 0.71, R = 0.47, and R = 0.76 for the three MRI readers respectively (p <0.01). Peak plaque stretch was underestimated as well. The peak cap stress in thick-cap, low stress plaques was substantially more accurately and precisely predicted (error of-12 ± 44 kPa) than the peak cap stress in plaques with caps thinner than the acquisition voxel size (error of-177 ± 168 kPa). For reliable MRI-based FEA to compute the peak cap stress of carotid plaques with thin caps, the current clinically used in-plane acquisition voxel size (∼0.6 mm) is inadequate. FEA plaque stress computations would be considerably more reliable if they would be used to identify thick-cap carotid plaques with low stresses instead

Viral diseases of wild and farmed European eel Anguilla anguilla with particular reference to the Netherlands

Diseases are an important cause of losses and decreased production rates in freshwater eel farming, and have been suggested to play a contributory role in the worldwide decline in wild freshwater eel stocks. Three commonly detected pathogenic viruses of European eel Anguilla anguilla are the aquabirnavirus eel virus European (EVE), the rhabdovirus eel virus European X (EVEX), and the alloherpesvirus anguillid herpesvirus 1 (AngHV1). In general, all 3 viruses cause a nonspecific haemorrhagic disease with increased mortality rates. This review provides an overview of the current knowledge on the aetiology, prevalence, clinical signs and gross pathology of these 3 viruses. Reported experimental infections showed the temperature dependency and potential pathogenicity of these viruses for eels and other fish species. In addition to the published literature, an overview of the isolation of pathogenic viruses from wild and farmed A. anguilla in the Netherlands during the past 2 decades is given. A total of 249 wild A. anguilla, 39 batches of glass eels intended for farming purposes, and 239 batches of farmed European eels were necropsied and examined virologically. AngHV1 was isolated from wild A. anguilla yellow and silver eels from the Netherlands from 1998 until the present, while EVEX was only found sporadically, and EVE was never isolated. In farmed A. anguilla AngHV1 was also the most commonly isolated virus, followed by EVE and EVEX

Carotid plaque elasticity estimation using ultrasound elastography, MRI, and inverse FEA - A numerical feasibility study

Item does not contain fulltextThe material properties of atherosclerotic plaques govern the biomechanical environment, which is associated with rupture-risk. We investigated the feasibility of noninvasively estimating carotid plaque component material properties through simulating ultrasound (US) elastography and in vivo magnetic resonance imaging (MRI), and solving the inverse problem with finite element analysis. 2D plaque models were derived from endarterectomy specimens of nine patients. Nonlinear neo-Hookean models (tissue elasticity C1) were assigned to fibrous intima, wall (i.e., media/adventitia), and lipid-rich necrotic core. Finite element analysis was used to simulate clinical cross-sectional US strain imaging. Computer-simulated, single-slice in vivo MR images were segmented by two MR readers. We investigated multiple scenarios for plaque model elasticity, and consistently found clear separations between estimated tissue elasticity values. The intima C1 (160 kPa scenario) was estimated as 125.8 +/- 19.4 kPa (reader 1) and 128.9 +/- 24.8 kPa (reader 2). The lipid-rich necrotic core C1 (5 kPa) was estimated as 5.6 +/- 2.0 kPa (reader 1) and 8.5 +/- 4.5 kPa (reader 2). A scenario with a stiffer wall yielded similar results, while realistic US strain noise and rotating the models had little influence, thus demonstrating robustness of the procedure. The promising findings of this computer-simulation study stimulate applying the proposed methodology in a clinical setting

Atherosclerotic plaque fibrous cap assessment under an oblique scan plane orientation in carotid MRI

Carotid magnetic resonance imaging (MRI) is used to noninvasively assess atherosclerotic plaque fibrous cap (FC) status, which is closely related to ischemic stroke. Acquiring anisotropic voxels improves in-plane visualization, however, an oblique scan plane orientation could then obscure a FC (i.e., contrast below the noise level) and thus impair a reliable status assessment. To quantify this, we performed single-slice numerical simulations of a clinical 3.0T, 2D T1-weighted, black-blood, contrast-enhanced pulse sequence with various voxel dimensions: in-plane voxel size of 0.62 mm × 0.62 mm and 0.31 mm × 0.31 mm, slice thickness of 1, 2, and 3 mm. Idealized plaque models (FC thickness of 0.5, 1, and 1.5 mm) were imaged at various scan plane angles (0°-40° in steps of 10°), and the FC contrast was quantified. We found that when imaging thin FCs with anisotropic voxels, the FC contrast decreased when the scan plane orientation angle increased. However, a reduced in-plane voxel size at the cost of an increased slice thickness often led to enhanced FC contrast even in the presence of scan plane orientation angles of up to 40°. It can be concluded that while isotropic-voxel imaging eliminates the issue of scan plane obliqueness, it comes at the cost of reduced FC contrast, thus likely decreasing the reliability of FC status assessment in carotid MRI. If scan plane orientation obliquity at the slice of interest is moderate (<40°) or otherwise diminished through careful scan planning, voxel anisotropy could increase FC contrast and, in effect, increase the reliability of FC status assessment.ImPhys/Imaging PhysicsApplied Science

Numerical simulations of carotid MRI quantify the accuracy in measuring atherosclerotic plaque components in vivo

Purpose Atherosclerotic carotid plaques can be quantified in vivo by MRI. However, the accuracy in segmentation and quantification of components such as the thin fibrous cap (FC) and lipid-rich necrotic core (LRNC) remains unknown due to the lack of a submillimeter scale ground truth. Methods A novel approach was taken by numerically simulating in vivo carotid MRI providing a ground truth comparison. Upon evaluation of a simulated clinical protocol, MR readers segmented simulated images of cross-sectional plaque geometries derived from histological data of 12 patients. Results   MR readers showed high correlation (R) and intraclass correlation (ICC) in measuring the luminal area (R = 0.996, ICC = 0.99), vessel wall area (R = 0.96, ICC = 0.94) and LRNC area (R = 0.95, ICC = 0.94). LRNC area was underestimated (mean error, −24%). Minimum FC thickness showed a mediocre correlation and intraclass correlation (R = 0.71, ICC = 0.69). Conclusion Current clinical MRI can quantify carotid plaques but shows limitations for thin FC thickness quantification. These limitations could influence the reliability of carotid MRI for assessing plaque rupture risk associated with FC thickness. Overall, MRI simulations provide a feasible methodology for assessing segmentation and quantification accuracy, as well as for improving scan protocol design

Boundary layer characteristics and turbulent exchange mechanisms in highly complex terrain

The Mesoscale Alpine Programme's Riviera project investigated the turbulence structure and related exchange processes in an Alpine valley by combining a detailed experimental campaign with high-resolution numerical modelling. The present contribution reviews published material on the Riviera Valley's boundary layer structure and discusses new material on the near-surface turbulence structure. The general conclusion of the project is that despite the large spatial variability of turbulence characteristics and the crucial influence of topography at all scales, the physical processes can accurately be understood and modelled. Nevertheless, many of the "text book characteristics" like the interaction between the valley and slope wind systems or the erosion of the nocturnal valley inversion need reconsideration, at least for small non-ideal valleys like the Riviera Valley. The project has identified new areas of research such as post-processing methods for turbulence variables in complex terrain and new approaches for the surface energy balance when advection is non-negligible. The exchange of moisture and heat between the valley atmosphere and the free troposphere is dominated by local "secondary" circulations due to the curvature of the valley axis. Because many curved valleys exist, and operational models still have rather poor resolution, parameterization of these processes may be required