Lingyun Huang

Ultrasound-Based Carotid Elastography for Detection of Vulnerable Atherosclerotic Plaques Validated by Magnetic Resonance Imaging

Ultrasound-based carotid elastography has been developed to estimate the mechanical properties of atherosclerotic plaques. The objective of this study was to evaluate the in vivo capability of carotid elastography in vulnerable plaque detection using high-resolution magnetic resonance imaging as reference. Ultrasound radiofrequency data of 46 carotid plaques from 29 patients (74 ± 5 y old) were acquired and inter-frame axial strain was estimated with an optical flow method. The maximum value of absolute strain rate for each plaque was derived as an indicator for plaque classification. Magnetic resonance imaging of carotid arteries was performed on the same patients to classify the plaques into stable and vulnerable groups for carotid elastography validation. The maximum value of absolute strain rate was found to be significantly higher in vulnerable plaques (2.15 ± 0.79 s(-1), n = 27) than in stable plaques (1.21 ± 0.37 s(-1), n = 19) (p < 0.0001). Receiver operating characteristic curve analysis was performed, and the area under the curve was 0.848. Therefore, the in vivo capability of carotid elastography to detect vulnerable plaques, validated by magnetic resonance imaging, was proven, revealing the potential of carotid elastography as an important tool in atherosclerosis assessment and stroke prevention.

Performance comparison of rigid and affine models for motion estimation using ultrasound radio-frequency signals

Tissue motion estimation is widely used in many ultrasound techniques. Rigid-model-based and nonrigid-modelbased methods are two main groups of space-domain methods of tissue motion estimation. The affine model is one of the commonly used nonrigid models. The performances of the rigid model and affine model have not been compared on ultrasound RF signals, which have been demonstrated to obtain higher accuracy, precision, and resolution in motion estimation compared with B-mode images. In this study, three methods, i.e., the normalized cross-correlation method with rigid model (NCC), the optical flow method with rigid model (OFRM), and the optical flow method with affine model (OFAM), are compared using ultrasound RF signals, rather than the B-mode images used in previous studies. Simulations, phantom, and in vivo experiments are conducted to make the comparison. In the simulations, the root-mean-square errors (RMSEs) of axial and lateral displacements and strains are used to assess the accuracy of motion estimation, and the elastographic signal-tonoise ratio (SNRe) and contrast-to-noise ratio (CNRe) are used to evaluate the quality of axial strain images. In the phantom experiments, the registration error between the pre- and postdeformation RF signals, as well as the SNRe and CNRe of axial strain images, are utilized as the evaluation criteria. In the in vivo experiments, the registration error is used to evaluate the estimation performance. The results show that the affinemodel- based method (i.e., OFAM) obtains the lowest RMSE or registration error and the highest SNRe and CNRe among all the methods. The affine model is demonstrated to be superior to the rigid model in motion estimation based on RF signals.

A robust and accurate two-step auto-labeling conditional iterative closest points (TACICP) algorithm for three-dimensional multi-modal carotid image registration

Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP) algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US) and magnetic resonance (MR). Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP) algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS) transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods.

Performance optimization of lateral displacement estimation with spatial angular compounding

HIGHLIGHTSThe performance optimization of spatial angular compounding was investigated.The effects of key factors were investigated through simulations and experiments.It is necessary to filter the GLN for better displacement estimation.Better estimation performance is associated with a larger NSA and bigger MSA.The results are in agreement with theoretical analysis. ABSTRACT Elastography provides tissue mechanical information to differentiate normal and disease states. Nowadays, axial displacement and strain are usually estimated in clinical practice whereas lateral estimation is rarely used given that its accuracy is typically one order of magnitude worse than that of axial estimation. To improve the performance of lateral estimation, spatial angular compounding of multiple axial displacements along ultrasound beams transmitting in different steering angles was previously proposed. However, few studies have been conducted to evaluate the influence of key factors such as grating lobe noise (GLN), the number of steering angles (NSA) and maximum steering angle (MSA) in terms of performance optimization. The aim of this study was thus to investigate the effects of these factors through both computer simulations and phantom experiments. Only lateral rigid motion was considered in this study to separate its effects from those of axial and lateral strains on lateral displacement estimation. The performance as indicated by the root mean square error (RMSE) and standard deviation (SD) of the estimated lateral displacements validates the capability of spatial angular compounding in improving the performance of lateral estimation. It is necessary to filter the GLN for better estimation, and better performance is associated with a larger NSA and bigger MSA in both simulations and experiments, which is in agreement with the theoretical analysis. As indicated by the RMSE and SD, two steering angles with a larger steering angle are recommended. These results could provide insights into the performance optimization of lateral displacement estimation with spatial angular compounding.

A feasibility study of carotid elastography for risk assessment of atherosclerotic plaques validated by magnetic resonance imaging

Stroke is a leading cause of mortality worldwide. One of its main reasons is rupture of carotid atherosclerotic plaques. Conventional B-mode ultrasound images and Doppler/color flow measurements are mostly used to evaluate degree of stenosis, which underestimates plaque vulnerability. Alternatively, the correspondence between multi-contrast magnetic resonance imaging (MRI) features, plaque composition and histology has been well established. In this study, the feasibility of ultrasound carotid elastography in risk assessment of carotid atherosclerotic plaques is investigated. Preliminarily in-vivo results on a small number of human subjects are initially validated by multi-contrast, highresolution MRI, and it shows that maximum strain rate might be feasible to evaluate the plaque vulnerability.

A feasibility study of ultrasound B-mode and strain imaging for risk assessment of carotid atherosclerotic plaques validated by magnetic resonance imaging

Stroke is a leading cause of mortality worldwide. One of its main reasons is rupture of carotid atherosclerotic plaques. Conventional B-mode ultrasound images and Doppler/color flow measurements are mostly used to evaluate degree of carotid atherosclerotic stenosis. However, stenosis underestimates plaque vulnerability due to positive remodeling. In addition, studies have shown that traditional B-mode ultrasound has limited capability in characterizing vulnerability associated plaque compositional features, particularly intraplaque hemorrhage. In contrast, the correspondence between multi-contrast magnetic resonance imaging (MRI) features, including morphology and plaque compositions, and histology has been well established. In this study, the feasibility of B-mode image combined with strain image in composition characterization and risk assessment of carotid atherosclerotic plaques is investigated. Preliminarily in-vivo results on a small number of human subjects are initially validated by multi-contrast, high-resolution MRI, and it shows that combination of echogenicity and strain values might be feasible to evaluate the plaque vulnerability.

A Noninvasive Sonographic Study of Multisite Atherosclerosis in an Elderly Chinese Population: Noninvasive Sonographic Study of Multisite Atherosclerosis

A sonographic study was conducted to determine the prevalence of atherosclerosis across multiple arterial beds in an elderly Chinese population and to examine relationships between detected atherosclerosis and traditional risk factors.

Identification of early atherosclerotic lesions in carotid arteries with quantitative characteristics measured by 3D MRI

To evaluate the usefulness of quantitative characteristics of morphology and signal intensity of arterial wall measured by 3D multicontrast magnetic resonance vessel wall imaging (MRVWI) in identification of carotid early atherosclerosis (CEAS).

Performance comparison of rigid and affine models for motion estimation using ultrasound RF signals: Simulations and phantom experiments

Rigid model-based and non-rigid model-based methods are two main groups of space-domain methods of tissue motion estimation. Affine model is one of the commonly used non-rigid models. The performances of the rigid model and affine model have not been compared on ultrasound radio-frequency (RF) signals. In this study, three methods, i.e., the normalized cross-correlation method with rigid model (NCC), the optical flow method with rigid model (OFRM) and optical flow method with affine model (OFAM), are compared using ultrasound RF signals, rather than B-mode images used in previous studies. Simulations and phantom experiments are conducted to make the comparison. The results show that the affine model-based method (i.e., OFAM) obtains the lowest root-mean-square error (RAISE) or registration error among all the methods. The affine model is demonstrated to be superior to the rigid model in motion estimation based on RF signals.

A new ultrasound imaging indicator for vulnerability evaluatation of carotid atherosclerotic plaques

Rupture of atherosclerotic plaques is the key factor leading to ischemic stroke. In conventional ultrasound, B-mode imaging and/or color flow/pulsed wave Doppler can be used to evaluate the stenosis of blood vessels but not the vulnerability of plaques. In this paper, we propose an ultrasound strain rate imaging based indicator called mean maximum strain rate (MMSR) to evaluate the vulnerability of carotid atherosclerotic plaques validated using multi-sequence magnetic resonance (MR) imaging characterization. This indicator was tested on 47 plaques from 34 human subjects. Statistical significance was found (p=0.01) between stable plaques and vulnerable plaques. The sensitivity and specificity at the cost effective point of receiver operating characteristic (ROC) curve is 76% and 81%, respectively. This indicator is shown to be effective in evaluating the vulnerability of carotid atherosclerotic plaques.