Intimal thickness determines the detection of non-calcified plaques by computed tomography angiography

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LDA measurements in a non-stenosed and a stenosed model of the carotid artery bifurcation

In order to gain quantitative information of the velocity fields in non-stenosed and stenosed models of the carotid artery bifurcation. Laser Doppler Anemometer (LDA) experiments have been performed. For this purpose a two component backscatter LDA system has been used. The experiments have been conducted in a 1:2.5 enlarged plexiglass model of the carotid artery bifurcation. Both axial and secondary velocities were measured as a function of time at locations of interest. The data were ensemble averaged and analyzed in the frequency domain in order to find characteristic flow phenomena. For the frequency analyses, the transfer functions between velocities at specific sites in the bifurcation and the input flow signal have been calculated for both the non-stenosed and the stenosed bifurcation. Both from the results of the velocity fields and the transfer functions, it can be concluded that the main differences between the flow fields in the non-stenosed and the stenosed bifurcation can be found in an area with high velocity and in a shear layer, which is located at the border between a region with low shear rates at the non-divider wall and a region with high shear rates at the divider wall. The values of the transfer function at these locations seem to be useful for the characterization of the influence of the stenosis

Visualizing the 3D collagen structure of human atherosclerotic plaques using Diffusion Tensor Imaging

Introduction Ischemic strokes and heart attacks are mainly caused by rupture of the fibrous cap of an atherosclerotic plaque. Reliable prediction of the fibrous cap rupture is, therefore, crucial to prevent these potentially lethal cardiovascular events. Since cap rupture occurs when the stresses in the cap exceed the strength of the cap, biomechanical modeling may help to improve cap rupture prediction. Biomechanical models depend strongly on the material parameters used as input. Previous studies focused on the anisotropic mechanical behaviour of atherosclerotic plaques and produced stiffness values for the collagen fibers in plaques [1]. However, for a more complete characterization knowledge of the global 3D collagen architecture in atherosclerotic plaques is required. Therefore, for the first time diffusion tensor imaging (DTI) was used to investigate the 3D collagen structure of human atherosclerotic plaques. Methods Until now five human carotid atherosclerotic plaques were obtained from endarterectomy patients and embedded in 4 % type VII agarose. The samples were placed in a 9.4 T horizontal-bore MRI scanner to conduct DTI. DTI enabled the tracking of the fiber directions and visualisation of the collagen fibers [2]. Results The consistent results of five different plaques suggest that collagen fibers are deposited in a new layer in a different direction during the development of atherosclerosis (see figure for one representative result). Two distinct layers of collagen fibers were found; an outer layer, where the collagen is aligned in the circumferential direction (14.5°±28.0°), similar to healthy arteries [2], and an inner layer where the collagen follows a longitudinal direction (77.4°±22.4°). Conclusions DTI allowed the visualization of the global 3D collagen architecture of atherosclerotic plaques. The inner collagen layer showed a surprising result and implies a change of strain distribution in the artery during the later stage of atherosclerosis, possibly due to the thickening and stiffening of the diseased intimal tissue. These data, combined with collagen stiffness data found in previous studies [1], will be used as input for biomechanical models including the anisotropic mechanical behaviour of plaque tissue. Models using general over-simplified assumptions like isotropic behaviour can be replaced by models including the anisotopic behavior and thereby improve the stress analysis of plaques. Improved models might help in the diagnosis and treatment of plaque rupture preventing heart attacks and ischemic strokes. References [1] Chai C-K, Akyildiz AC, Speelman L, Gijsen FJH, Oomens CWJ, Sambeek MRHM, van der Lugt A, Baaijens FTP, Anisotropic mechanical behaviour of carotid atherosclerotic plaques at large strain, The 8th international symposium on Biomechanics in Vascular Biology and Cardiovascular Disease, Rotterdam, 2013. [2] Ghazanfari S, Driessen-Mol A, Strijkers GJ, Kanters FMW, Baaijens FPT, Bouten CVC, A comparative analysis of the collagen architecture in the carotid artery: Second harmonic generation versus diffusion tensor imaging, Biochemical and Biophysical Research Communications, 426(1): 54-58, 2012

Model-based cap thickness and peak cap stress prediction for carotid MRI

A rupture-prone carotid plaque can potentially be identified by calculating the peak cap stress (PCS). For these calculations, plaque geometry from MRI is often used. Unfortunately, MRI is hampered by a low resolution, leading to an overestimation of cap thickness and an underestimation of PCS. We developed a model to reconstruct the cap based on plaque geometry to better predict cap thickness and PCS. We used histological stained plaques from 34 patients. These plaques were segmented and served as the ground truth. Sections of these plaques contained 93 necrotic cores with a cap thickness <0.62 mm which were used to generate a geometry-based model. The histological data was used to simulate in vivo MRI images, which were manually delineated by three experienced MRI readers. Caps below the MRI resolution (n = 31) were (digitally removed and) reconstructed according to the geometry-based model. Cap thickness and PCS were determined for the ground truth, readers, and reconstructed geometries. Cap thickness was 0.07 mm for the ground truth, 0.23 mm for the readers, and 0.12 mm for the reconstructed geometries. The model predicts cap thickness significantly better than the readers. PCS was 464 kPa for the ground truth, 262 kPa for the readers and 384 kPa for the reconstructed geometries. The model did not predict the PCS significantly better than the readers. The geometry-based model provided a significant improvement for cap thickness estimation and can potentially help in rupture-risk prediction, solely based on cap thickness. Estimation of PCS estimation did not improve, probably due to the complex shape of the plaques

Fast and Accurate Pressure-Drop Prediction in Straightened Atherosclerotic Coronary Arteries

Atherosclerotic disease progression in coronary arteries is influenced by wall shear stress. To compute patient-specific wall shear stress, computational fluid dynamics (CFD) is required. In this study we propose a method for computing the pressure-drop in regions

Calcifications in atherosclerotic plaques and impact on plaque biomechanics

The catastrophic mechanical rupture of an atherosclerotic plaque is the underlying cause of the majority of cardiovascular events. The infestation of vascular calcification in the plaques creates a mechanically complex tissue composite. Local stress concentrations and plaque tissue strength properties are the governing parameters required to predict plaque ruptures. Advanced imaging techniques have permitted insight into fundamental mechanisms driving the initiating inflammatory-driven vascular calcification of the diseased intima at the (sub-) micron scale and up to the macroscale. Clinical studies have potentiated the biomechanical relevance of calcification through the derivation of links between local plaque rupture and specific macrocalcification geometrical features. The clinical implications of the data presented in this review indicate that the combination of imaging, experimental testing, and computational modelling efforts are crucial to predict the rupture risk for atherosclerotic plaques. Specialised experimental tests and mo

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

Quantification of fibrous cap thickness in intracoronary optical coherence tomography with a contour segmentation method based on dynamic programming

OBJECTIVES: Fibrous cap thickness is the most critical component of plaque stability. Therefore, in vivo quantification of cap thickness could yield valuable information for estimating the risk of plaque rupture. In the context of preoperative planning and perioperative decision making, intracoronary optical coherence tomography imaging can provide a very detailed characterization of the arterial wall structure. However, visual interpretation of the images is laborious, subject to variability, and therefore not always sufficiently reliable for immediate decision of treatment. METHODS: A novel semiautomatic segmentation method to quantify coronary fibrous cap thickness in optical coherence tomography is introduced. To cope with the most challenging issue when estimating cap thickness (namely the diffuse appearance of the anatomical abluminal interface to be detected), the proposed method is based on a robust dynamic programming framework using a geometrical a priori. To determine the optimal parameter settings, a training phase was conducted on 10 patients. RESULTS: Validated on a dataset of 179 images from 21 patients, the present framework could successfully extract the fibrous cap contours. When assessing minimal cap thickness, segmentation results from the proposed method were in good agreement with the reference tracings performed by a medical expert (mean absolute error and standard deviation of [Formula: see text] ) and were similar to inter-observer reproducibility ([Formula: see text] , R = .74), while being significantly faster and fully reproducible. CONCLUSION: The proposed framework demonstrated promising performances and could potentially be used for online identification of high-risk plaques