Development of 3D ultrasound techniques for carotid artery disease assessment and monitoring

Stress distribution analysis in healthy and stenosed carotid artery models reconstructed from in vivo ultrasonography

Purpose

This study investigated the accuracy of models reconstructed from ultrasound image processing by comparing the radial displacement waveforms of a subject-specific artery model and evaluated stress changes in the proximal shoulder, throat, and distal shoulder of the plaques depending on the degree of carotid artery stenosis.

Methods

Three groups of subjects (healthy and with less than 50% or more carotid stenosis) were evaluated with ultrasonography. Two-dimensional transverse imaging of the common carotid artery was performed to reconstruct the geometry. A longitudinal view of the same region was recorded to extract the Kelvin viscoelastic model parameters. The pulse pressure waveform and the effective pressure of perivascular tissue were loaded onto the internal and external walls of the model. Effective, circumferential, and principal stresses applied to the plaque throat, proximal shoulder, and distal shoulder in the transverse planes were extracted.

Results

The radial displacement waveforms of the model were closely correlated with those of image processing in all three groups. The mean of the effective, circumferential, and principal stresses of the healthy arteries were 15.01±4.93, 12.97±5.07, and 12.39±2.86 kPa, respectively. As stenosis increased from mild to significant, the mean values of the effective, circumferential, and first principal stresses increased significantly (97%, 74%, and 103% at the plaque throat, respectively) (P<0.05). The minimum effective stress was at the lipid pool. The effective stress in calcified areas was higher than in other parts of the artery wall.

Conclusion

This model can discriminate differences in stresses applied to mildly and severely stenotic plaques.

Three-dimensional ultrasound evaluation of the effects of pomegranate therapy on carotid plaque texture using locality preserving projection

BACKGROUND AND OBJECTIVE

Dietary supplements are expected to confer a smaller beneficial effect than medical treatments. Therefore, there is a need to develop cost-effective biomarkers that can demonstrate the efficacy of such supplements for carotid atherosclerosis. The aim of this study is to develop such a biomarker based on the changes of 376 plaque textural features measured from 3D ultrasound images.

METHODS

Since the number of features (376) was greater than the number of subjects (171) in this study, principal component analysis (PCA) was applied to reduce the dimensionality of feature vectors. To generate a scalar biomarker for each subject, elements in the reduced feature vectors produced by PCA were weighted using locality preserving projections (LPP) to capture essential patterns exhibited locally in the feature space. 96 subjects treated by pomegranate juice and tablets, and 75 subjects receiving placebo-matching juice and tablets were evaluated in this study. The discriminative power of the proposed biomarker was evaluated and compared with existing biomarkers using t-tests. As the cost of a clinical trial is directly related to the number of subjects enrolled, the cost-effectiveness of the proposed biomarker was evaluated by sample size estimation.

RESULTS

The proposed biomarker was more able to discriminate plaque changes exhibited by the pomegranate and placebo groups than total plaque volume (TPV) according to the result of t-tests (TPV: p=0.34, Proposed biomarker: p=1.5×10^-5). The sample size required by the new biomarker to detect a significant effect was 20 times smaller than that required by TPV.

CONCLUSION

With the increase in cost-effectiveness afforded by the proposed biomarker, more proof-of-principle studies for novel treatment options could be performed.

Concise biomarker for spatial-temporal change in three-dimensional ultrasound measurement of carotid vessel wall and plaque thickness based on a graph-based random walk framework: Towards sensitive evaluation of response to therapy

Rapid progression in total plaque area and volume measured from ultrasound images has been shown to be associated with an elevated risk of cardiovascular events. Since atherosclerosis is focal and predominantly occurring at the bifurcation, biomarkers that are able to quantify the spatial distribution of vessel-wall-plus-plaque thickness (VWT) change may allow for more sensitive detection of treatment effect. The goal of this paper is to develop simple and sensitive biomarkers to quantify the responsiveness to therapies based on the spatial distribution of VWT-Change on the entire 2D carotid standardized map previously described. Point-wise VWT-Changes computed for each patient were reordered lexicographically to a high-dimensional data node in a graph. A graph-based random walk framework was applied with the novel Weighted Cosine (WCos) similarity function introduced, which was tailored for quantification of responsiveness to therapy. The converging probability of each data node to the VWT regression template in the random walk process served as a scalar descriptor for VWT responsiveness to treatment. The WCos-based biomarker was 14 times more sensitive than the mean VWT-Change in discriminating responsive and unresponsive subjects based on the p-values obtained in T-tests. The proposed framework was extended to quantify where VWT-Change occurred by including multiple VWT-Change distribution templates representing focal changes at different regions. Experimental results show that the framework was effective in classifying carotid arteries with focal VWT-Change at different locations and may facilitate future investigations to correlate risk of cardiovascular events with the location where focal VWT-Change occurs.

Advances in the development of an imaging device for plaque measurement in the area of the carotid artery

This paper describes the advances in the development and subsequent testing of an imaging device for three-dimensional ultrasound measurement of atherosclerotic plaque in the carotid artery. The embolization from the atherosclerotic carotid plaque is one of the most common causes of ischemic stroke and, therefore, we consider the measurement of the plaque as extremely important. The paper describes the proposed hardware for enhancing the standard ultrasonic probe to provide a possibility of accurate probe positioning and synchronization with the cardiac activity, allowing the precise plaque measurements that were impossible with the standard equipment. The synchronization signal is derived from the output signal of the patient monitor (electrocardiogram (ECG)), processed by a microcontroller-based system, generating the control commands for the linear motion moving the probe. The controlling algorithm synchronizes the movement with the ECG waveform to obtain clear images not disturbed by the heart activity.

An integrated system for the segmentation of atherosclerotic carotid plaque ultrasound video

The robust border identification of atherosclerotic carotid plaque, the corresponding degree of stenosis of the common carotid artery (CCA), and also the characteristics of the arterial wall, including plaque size, composition, and elasticity, have significant clinical relevance for the assessment of future cardiovascular events. To facilitate the follow-up and analysis of the carotid stenosis in serial clinical investigations, we propose and evaluate an integrated system for the segmentation of atherosclerotic carotid plaque in ultrasound videos of the CCA based on video frame normalization, speckle reduction filtering, M-mode state-based identification, parametric active contours, and snake segmentation. Initially, the cardiac cycle in each video is identified and the video M-mode is generated, thus identifying systolic and diastolic states. The video is then segmented for a time period of at least one full cardiac cycle. The algorithm is initialized in the first video frame of the cardiac cycle, with human assistance if needed, and the moving atherosclerotic plaque borders are tracked and segmented in the subsequent frames. Two different initialization methods are investigated in which initial contours are estimated every 20 video frames. In the first initialization method, the initial snake contour is estimated using morphology operators; in the second initialization method, the Chan-Vese active contour model is used. The performance of the algorithm is evaluated on 43 real CCA digitized videos from B-mode longitudinal ultrasound segments and is compared with the manual segmentations of an expert, available every 20 frames in a time span of 3 to 5 s, covering, in general, 2 cardiac cycles. The segmentation results were very satisfactory, according to the expert objective evaluation, for the two different methods investigated, with true-negative fractions (TNF-specificity) of 83.7 ± 7.6% and 84.3 ± 7.5%; true-positive fractions (TPF-sensitivity) of 85.42 ± 8.1% and 86.1 ± 8.0%; and between the ground truth and the proposed segmentation method, kappa indices (KI) of 84.6% and 85.3% and overlap indices of 74.7% and 75.4%. The segmentation contours were also used to compute the cardiac state identification and radial, longitudinal, and shear strain indices for the CCA wall and plaque between the asymptomatic and symptomatic groups were investigated. The results of this study show that the integrated system investigated in this study can be successfully used for the automated video segmentation of the CCA plaque in ultrasound videos.

Novel methodology for 3D reconstruction of carotid arteries and plaque characterization based upon magnetic resonance imaging carotid angiography data

In this study, we present a novel methodology that allows reliable segmentation of the magnetic resonance images (MRIs) for accurate fully automated three-dimensional (3D) reconstruction of the carotid arteries and semiautomated characterization of plaque type. Our approach uses active contours to detect the luminal borders in the time-of-flight images and the outer vessel wall borders in the T(1)-weighted images. The methodology incorporates the connecting components theory for the automated identification of the bifurcation region and a knowledge-based algorithm for the accurate characterization of the plaque components. The proposed segmentation method was validated in randomly selected MRI frames analyzed offline by two expert observers. The interobserver variability of the method for the lumen and outer vessel wall was -1.60%±6.70% and 0.56%±6.28%, respectively, while the Williams Index for all metrics was close to unity. The methodology implemented to identify the composition of the plaque was also validated in 591 images acquired from 24 patients. The obtained Cohen's k was 0.68 (0.60-0.76) for lipid plaques, while the time needed to process an MRI sequence for 3D reconstruction was only 30 s. The obtained results indicate that the proposed methodology allows reliable and automated detection of the luminal and vessel wall borders and fast and accurate characterization of plaque type in carotid MRI sequences. These features render the currently presented methodology a useful tool in the clinical and research arena.

A review of noninvasive ultrasound image processing methods in the analysis of carotid plaque morphology for the assessment of stroke risk

Noninvasive ultrasound imaging of carotid plaques allows for the development of plaque-image analysis methods associated with the risk of stroke. This paper presents several plaque-image analysis methods that have been developed over the past years. The paper begins with a review of clinical methods for visual classification that have led to standardized methods for image acquisition, describes methods for image segmentation and denoising, and provides an overview of the several texture-feature extraction and classification methods that have been applied. We provide a summary of emerging trends in 3-D imaging methods and plaque-motion analysis. Finally, we provide a discussion of the emerging trends and future directions in our concluding remarks.

Three-dimensional carotid ultrasound segmentation variability dependence on signal difference and boundary orientation

Quantitative measurements of the progression (or regression) of carotid plaque burden are important in monitoring patients and evaluating new treatment options. We previously developed a quantitative metric to analyze changes in carotid plaque morphology from 3-D ultrasound (US) on a point-by-point basis. This method requires multiple segmentations of the arterial wall and lumen boundaries to obtain the local standard deviation (SD) of vessel-wall-plus-plaque thickness (VWT) so that t-tests could be used to determine whether a change in VWT is statistically significant. However, the requirement for multiple segmentations makes clinical trials laborious and time-consuming. Therefore, this study was designed to establish the relationship between local segmentation SD and local signal difference on the arterial wall and lumen boundaries. We propose metrics to quantify segmentation SD and signal difference on a point-by-point basis, and studied whether the signal difference at arterial wall or lumen boundaries could be used to predict local segmentation SD. The ability to predict the local segmentation SD could eliminate the need of repeated segmentations of a 2-D transverse image to obtain the local segmentation standard deviation, thereby making clinical trials less laborious and saving time. Six subjects involved in this study were associated with different degrees of atherosclerosis: three carotid stenosis subjects with mean plaque area >3 cm(2) and >60% carotid stenosis were involved in a clinical study evaluating the effect of atorvastatin, a cholesterol-lowering and plaque-stabilizing drug; and three subjects with carotid plaque area >0.5 cm(2) were subjects with moderate atherosclerosis. Our results suggest that when local signal difference is higher than 8 greyscale value (GSV), the local segmentation SD stabilizes at 0.05 mm and is thus predictable. This information provides a target value of local signal difference on the arterial boundaries that should be achieved to obtain an accurate prediction of local segmentation SD. (E-mail: bcychiu@alumni.uwo.ca).