Search

The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of the development of cardiovascular disease (CVD). It was proposed but not thoroughly investigated that the media layer (ML) thickness (MLT), its composition, and its texture may be indicative of cardiovascular risk and for differentiating between patients with high and low risk. In this study, we investigate an automated method for segmenting the ML and the intima layer (IL) and measurement of the MLT and the intima layer thickness (ILT) in ultrasound images of the CCA. The snakes segmentation method was used and was evaluated on 100 longitudinal ultrasound images acquired from asymptomatic subjects, against manual segmentation performed by a neurovascular expert. The mean ± standard deviation (Sd) for the first and second sets of manual and the automated IMT, MLT, and ILT measurements were 0.71 ± 0.17 mm, 0.72 ± 0.17 mm, 0.67 ± 0.12 mm; 0.25 ± 0.12 mm, 0.27 ± 0.14 mm, 0.25 ± 0.11 mm; and 0.43 ± 0.10 mm, 0.44 ± 0.13 mm, and 0.42 ± 0.10 mm, respectively. There was overall no significant difference between the manual and the automated IMC, ML, and IL segmentation measurements. Therefore, the automated segmentation method proposed in this study may be used successfully in the measurement of the MLT and ILT complementing the manual measurements. MLT was also shown to increase with age (for both the manual and the automated measurements). Future research will incorporate the extraction of texture features from the segmented ML and IL bands, which may indicate the risk of future cardiovascular events. However, more work is needed for validating the proposed technique in a larger sample of subjects. [ABSTRACT FROM AUTHOR]

Recent studies have suggested that textural characteristics of the intima-media complex (IMC) may be more useful than the intima-media thickness (IMT) in evaluating cardiovascular risk. The primary aim of our study was to investigate the association between texture features of the common carotid IMC and prevalent clinical cardiovascular disease (CVD). The secondary aim was to determine whether IMT and IMC texture features vary between the left and right carotid arteries. The study was performed on 2208 longitudinal-section ultrasound images of the left (L) and right (R) common carotid artery (CCA), acquired from 569 men and 535 women out of which 125 had clinical CVD. L and R sides of the IMC were intensity normalized and despeckled. The IMC was semiautomatically delineated for all images using a semiautomated segmentation system, and 61 different texture features were extracted. The corresponding IMT semiautomated measurements (mean±SD) of the L and R sides were 0.73±0.21 mm/0.69±0.19 mm for the normal population and 0.83±0.17 mm/0.79±0.18 mm for those with CVD. IMC texture features did not differ between the right- and left-hand sides. Several texture features were independent predictors of the presence of CVD. The multivariate logistic regression analysis combining age, IMT, and texture features produced a receiver operating characteristic curve with an area under the curve of 89%. A correct classification rate of 77% for separating the normal subject (NOR) versus CVD subjects was achieved using the support vector machine classifier with a combination of clinical features, IMT, and extracted texture features. Texture features provide additional information on the presence of clinical CVD, which is over and above that provided by conventional risk factors or IMT alone. The value of IMC texture features in the prediction of future cardiovascular events should be tested in prospective studies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

It is well-known that speckle is a multiplicative noise that degrades the visual evaluation in ultrasound imaging. The recent advancements in ultrasound instrumentation and portable ultrasound devices necessitate the need of more robust despeckling techniques for enhanced ultrasound medical imaging for both routine clinical practice and teleconsultation. The objective of this work was to carry out a comparative evaluation of despeckle filtering based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts in the assessment of 440 (220 asymptomatic and 220 symptomatic) ultrasound images of the carotid artery bifurcation. In this paper a total of 10 despeckle filters were evaluated based on local statistics, median filtering, pixel homogeneity, geometric filtering, homomorphic filtering, anisotropic diffusion, nonlinear coherence diffusion, and wavelet filtering. The results of this study suggest that the first order statistics filter lsmv, gave the best performance, followed by the geometric filter gf4d, and the homogeneous mask area filter lsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by the two experts. More specifically, filters lsmv or gf4d can be used for despeckling asymptomatic images in which the expert is interested mainly in the plaque composition and texture analysis; and filters lsmv, gf4d, or lsminsc can be used for the despeckling of symptomatic images in which the expert is interested in identifying the degree of stenosis and the plaque borders. The proper selection of a despeckle filter is very important in the enhancement of ultrasonic imaging of the carotid artery. Further work is needed to evaluate at a larger scale and in clinical practice the performance of the proposed despeckle filters in the automated segmentation, texture analysis, and classification of carotid ultrasound imaging. [ABSTRACT FROM AUTHOR]