Vessel-wall-plus-plaque Thickness Research Articles

A Dual-Stream Centerline-Guided Network for Segmentation of the Common and Internal Carotid Arteries From 3D Ultrasound Images.

Segmentation of the carotid section encompassing the common carotid artery (CCA), the bifurcation and the internal carotid artery (ICA) from three-dimensional ultrasound (3DUS) is required to measure the vessel wall volume (VWV) and localized vessel-wall-plus-plaque thickness (VWT), shown to be sensitive to treatment effect. We proposed an approach to combine a centerline extraction network (CHG-Net) and a dual-stream centerline-guided network (DSCG-Net) to segment the lumen-intima (LIB) and media-adventitia boundaries (MAB) from 3DUS images. Correct arterial location is essential for successful segmentation of the carotid section encompassing the bifurcation. We addressed this challenge by using the arterial centerline to enhance the localization accuracy of the segmentation network. The CHG-Net was developed to generate a heatmap indicating high probability regions for the centerline location, which was then integrated with the 3DUS image by the DSCG-Net to generate the MAB and LIB. The DSCG-Net includes a scale-based and a spatial attention mechanism to fuse multi-level features extracted by the encoder, and a centerline heatmap reconstruction side-branch connected to the end of the encoder to increase the generalization ability of the network. Experiments involving 224 3DUS volumes produce a Dice similarity coefficient (DSC) of 95.8±1.9% and 92.3±5.4% for CCA MAB and LIB, respectively, and 93.2±4.4% and 89.0±10.0% for ICA MAB and LIB, respectively. Our approach outperformed four state-of-the-art 3D CNN models, even after their performances were boosted by centerline guidance. The efficiency afforded by the framework would allow it to be incorporated into the clinical workflow for improved quantification of plaque change.

Segmentation of 3D ultrasound carotid vessel wall using U-Net and segmentation average network.

Segmentation of carotid vessel wall is required in vessel wall volume (VWV) and local vessel-wall-plus-plaque thickness (VWT) quantification of the carotid artery. Manual segmentation of the vessel wall is time-consuming and prone to interobserver variability. In this paper, we proposed a convolutional neural network (CNN) to segment the common carotid artery (CCA) from 3D carotid ultrasound images. The proposed CNN involves three U-Nets that segmented the 3D ultrasound (3DUS) images in the axial, lateral and frontal orientations. The segmentation maps generated by three U-Nets were consolidated by a novel segmentation average network (SAN) we proposed in this paper. The experimental results show that the proposed CNN improved the segmentation accuracies. Compared to only using U-Net alone, the proposed CNN improved the Dice similarity coefficient (DSC) for vessel wall segmentation from 64.8% to 67.5%, the sensitivity from 63.8% to 70.5%, and the area under receiver operator characteristic curve (AUC) from 0.89 to 0.94.

Area-Preserving Mapping of 3D Carotid Ultrasound Images Using Density-Equalizing Reference Map.

Atherosclerotic plaques are focal and tend to occur at arterial bends and bifurcations. To quantitatively monitor the local changes in the carotid vessel-wall-plus-plaque thickness (VWT) and compare the VWT distributions for different patients or for the same patients at different ultrasound scanning sessions, a mapping technique is required to adjust for the geometric variability of different carotid artery models. In this work, we propose a novel method called density-equalizing reference map (DERM) for mapping 3D carotid surfaces to a standardized 2D carotid template, with an emphasis on preserving the local geometry of the carotid surface by minimizing the local area distortion. The initial map was generated by a previously described arc-length scaling (ALS) mapping method, which projects a 3D carotid surface onto a 2D non-convex L-shaped domain. A smooth and area-preserving flattened map was subsequently constructed by deforming the ALS map using the proposed algorithm that combines the density-equalizing map and the reference map techniques. This combination allows, for the first time, one-to-one mapping from a 3D surface to a standardized non-convex planar domain in an area-preserving manner. Evaluations using 20 carotid surface models show that the proposed method reduced the area distortion of the flattening maps by over 80% as compared to the ALS mapping method. The proposed method is capable of improving the accuracy of area estimation for plaque regions without compromising inter-scan reproducibility.

Conformal mapping of carotid vessel wall and plaque thickness measured from 3D ultrasound images.

Measurements of vessel-wall-plus-plaque thickness (VWT) from 3D carotid ultrasound have been shown to be sensitive to the effect of pharmaceutical interventions. Since the geometry of carotid arteries is highly subject-specific, quantitative comparison of the distributions of point-wise VWT measured for different patients or for the same patients at different ultrasound scanning sessions requires the development of a mapping strategy to adjust for the geometric variability of different carotid surface models. In this paper, we present an algorithm mapping each 3D carotid surface to a 2D carotid template with an emphasis on preserving the local geometry of the carotid surface by minimizing local angular distortion. The previously described arc-length scaling (AL) approach was applied to generate an initial 2D VWT map. Using results established in the quasi-conformal theory, a new map was computed to compensate for the angular distortion incurred in AL mapping. As the 2D carotid template lies on an L-shaped non-convex domain, one-to-one correspondence of the mapping operation was not guaranteed. To address this issue, an iterative Beltrami differential chopping and smoothing procedure was developed to enforce bijectivity. Evaluations performed in the 20 carotid surface models showed that the reduction in average angular distortion made by the proposed algorithm was highly significant (P = 2.06 × 10-5). This study is the first study showing that a bijective conformal map to a non-convex domain can be obtained using the iterative Beltrami differential chopping and smoothing procedure. The improved consistency exhibited in the 2D VWT map generated by the proposed algorithm will allow for unbiased quantitative comparisons of VWT as well as local geometric and hemodynamic quantities in population studies.

Correspondence optimization in 2D standardized carotid wall thickness map by description length minimization: A tool for increasing reproducibility of 3D ultrasound-based measurements.

The previously described 2D standardized vessel-wall-plus-plaque thickness (VWT) maps constructed from 3D ultrasound vessel wall measurements using an arc-length (AL) scaling approach adjusted the geometric variability of carotid arteries and has allowed for the comparisons of VWT distributions in longitudinal and cross-sectional studies. However, this mapping technique did not optimize point correspondence of the carotid arteries investigated. The potential misalignment may lead to errors in point-wise VWT comparisons. In this paper, we developed and validated an algorithm based on steepest description length (DL) descent to optimize the point correspondence implied by the 2D VWT maps. The previously described AL approach was applied to obtain initial 2D maps for a group of carotid arteries. The 2D maps were reparameterized based on an iterative steepest DL descent approach, which consists of the following two steps. First, landmarks established by resampling the 2D maps were aligned using the Procrustes algorithm. Then, the gradient of the DL with respect to horizontal and vertical reparameterizations of each landmark on the 2D maps was computed, and the 2D maps were subsequently deformed in the direction of the steepest descent of DL. These two steps were repeated until convergence. The quality of the correspondence was evaluated in a phantom study and an in vivo study involving ten carotid arteries enrolled in a 3D ultrasound interscan variability study. The correspondence quality was evaluated in terms of the compactness and generalization ability of the statistical shape model built based on the established point correspondence in both studies. In the in vivo study, the effect of the proposed algorithm on interscan variability of VWT measurements was evaluated by comparing the percentage of landmarks with statistically significant VWT-change before and after point correspondence optimization. The statistical shape model constructed with optimized correspondence was more compact and had a better generalization ability than that constructed using the AL approach in both the phantom and in vivo studies. A statistical test on the group-average VWT-Change at each point of the 2D carotid template showed that the group-average VWT-change was significantly different from 0 in 18% of landmarks when the AL approach was used, and this percentage was reduced to 11% after correspondence optimization. The optimized correspondence resulted in a more compact and generalizable statistical shape model, and the algorithm was shown to reduce interscan variability of point-wise VWT measurements obtained using the previously described arc-length scaling parameterization approach.

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.

Three-dimensional ultrasound measurements of carotid vessel wall and plaque thickness and their relationship with pulmonary abnormalities in ex-smokers without airflow limitation.

The relationship between carotid disease and modestly abnormal airflow in ex-smokers without chronic obstructive pulmonary disease (COPD) is not well-understood. We generated 3D ultrasound measurements of carotid vessel-wall-plus-plaque thickness (VWT) and vessel wall volume (VWV) to quantify and evaluate such carotid ultrasound measurements in ex- and never-smokers without airflow limitation. These patients did not fulfill the diagnostic criteria for COPD. We also investigated the relationship of carotid atherosclerosis with pulmonary phenotypes of COPD. We evaluated 61 subjects without a clinical diagnosis of pulmonary or vascular diseases including 34 never-smokers (72 ± 6year) and 27 ex-smokers (73 ± 9year). We measured mean VWT ([Formula: see text]) and mean VWT specific to carotid regions-of-interest ([Formula: see text]) and evaluated potential differences between ex- and never-smokers. Carotid ultrasound and pulmonary disease measurement relationships were also evaluated using correlation coefficients (r) and multivariate regression analyses. Ex-smokers had a significantly greater [Formula: see text] (p = 0.003) and [Formula: see text] (p < 0.00001) than never-smokers, whereas a significant difference between the two groups was not detected by VWV (p = 1.0). There were significant correlations between the ventilation defect percent (VDP) measured by MRI with [Formula: see text] (r = 0.42, p = 0.001) and [Formula: see text] (r = 0.56, p = 0.00001). Multivariate regression models showed that VDP significantly predicted [Formula: see text] (β = 0.38, p = 0.004) and [Formula: see text] (β = 0.50, p = 0.00001). VWT-based measurements detected differences in vessel-wall-plus-plaque burden in ex- and never-smokers, which were not revealed using VWV. There were significant correlations between cardiovascular and pulmonary disease biomarkers in these ex-smokers who did not have a clinical diagnosis of pulmonary or carotid disease.

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)

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

Quantitative measurements of carotid plaque burden are used to monitor patients and evaluate established interventions as well as new treatment options. Three-dimensional ultrasound (3D US) techniques were developed to noninvasively monitor the progression of carotid artery disease in both symptomatic and asymptomatic patients. Three-dimensional carotid US images were acquired and reconstructed, and methods for quantitative assessment were developed. The measurement of intima-media thickness (IMT) based on two-dimensional ultrasound (2D US) images was extended to a 3D vessel-wall-plus- plaque thickness (VWT), obtained by computing the distance between the carotid wall and lumen surfaces on a point-by-point basis. VWT measurements were superimposed on the arterial wall to produce 3D VWT maps. VWT changes were determined by comparing the 3D VWT maps obtained at two different time points. To facilitate the visualization and interpretation of the VWT and VWT-Change maps, a technique to flatten these maps was developed. Carotid remodeling involving changes in both arterial wall and plaque thickness was assessed with VWT maps obtained from in vivo 3D ultrasound images. 3D carotid ultrasound image evaluation with VWT mapping provides a feasible means for the analysis of plaque burden volumes and changes.

Area-preserving flattening maps of 3D ultrasound carotid arteries images

Quantitative measurements of the progression (or regression) of carotid plaque burden are important in monitoring patients and evaluating new treatment options. 3D ultrasound (US) has been used to monitor the progression of carotid artery plaques in symptomatic and asymptomatic patients, and different methods of measuring various ultrasound phenotypes of atherosclerosis have been developed. We have developed a quantitative metric used to analyze changes in carotid plaque morphology from 3D US. This method matched the vertices on the carotid arterial wall surface with those on the luminal surface. Vessel-wall-plus-plaque thickness (VWT) was obtained by computing the distance between each corresponding pair, which was then superimposed on the arterial wall to produce the VWT map. Since the progression of plaque thickness is important in monitoring patients who are at risk for stroke, we also computed the change of VWT by comparing the VWT maps obtained for a patient at two different time points. In this paper, we propose a technique to flatten the 3D VWT and VWT-Change maps in an area-preserving manner, in order to facilitate the visualization and interpretation of these maps.