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Background: Studies have indicated that the presence and size of subclinical atherosclerotic plaques improve the prediction of atherosclerotic cardiovascular events (ASCVE) over and above that provided by conventional risk factors alone. However, the relative contribution of different ultrasonographic measurements and sites of measurements on the 10-year ASCVD risk is largely unknown.Objectives: Our aims were to determine the relative performance of carotid intima-media thickness, plaque thickness, and plaque area in 10-year ASCVD prediction when added to conventional risk factors as well as whether the vascular territory of these measurements, carotid or common femoral bifurcation, and the number of bifurcations with plaque (NBP) influence prediction.Methods: We enrolled 985 adults (mean age: 58.1 ± 10.2 years) free of atherosclerotic cardiovascular disease. Conventional risk factors were recorded, and both carotid and common femoral bifurcations were scanned with ultrasonography. The primary endpoint was a composite of first-time fatal or nonfatal ASCVE.Results: Over a mean ± SD follow-up of 13.2 ± 3.7 years, ASCVE occurred in 154 (15.6%) participants. By adding different plaque measurements to conventional risk factors in a Cox model, net reclassification improvement was 10.4% with maximum intima-media thickness, 9.5% with carotid plaque thickness, and 14.2% with carotid plaque area. It increased to 16.1%, 16.6%, and 16.6% (P < 0.0001) by adding measurements from 4 bifurcations: NBP, total plaque thickness, and total plaque area, respectively.Conclusions: NBP, total plaque thickness, or total plaque area from both the carotid and common femoral bifurcations provides a better prediction of future ASCVE than measurements from a single site. The results need to be validated in an independent cohort. [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]

Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients' left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 69 ± 11 years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators. Graphical abstract AECRS1.0: Carotid ultrasound image phenotype-based 10-year cardiovascular risk calculator. The figure provides brief overview of the proposed carotid image phenotype-based 10-year cardiovascular risk calculator called AECRS1.0. AECRS1.0 was also benchmarked against five conventional cardiovascular risk calculators (Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score). [ABSTRACT FROM AUTHOR]

Manual ultrasound (US)-based methods are adapted for lumen diameter (LD) measurement to estimate the risk of stroke but they are tedious, error prone, and subjective causing variability. We propose an automated deep learning (DL)-based system for lumen detection. The system consists of a combination of two DL systems: encoder and decoder for lumen segmentation. The encoder employs a 13-layer convolution neural network model (CNN) for rich feature extraction. The decoder employs three up-sample layers of fully convolution network (FCN) for lumen segmentation. Three sets of manual tracings were used during the training paradigm leading to the design of three DL systems. Cross-validation protocol was implemented for all three DL systems. Using the polyline distance metric, the precision of merit for three DL systems over 407 US scans was 99.61%, 97.75%, and 99.89%, respectively. The Jaccard index and Dice similarity of DL lumen segmented region against three ground truth (GT) regions were 0.94, 0.94, and 0.93 and 0.97, 0.97, and 0.97, respectively. The corresponding AUC for three DL systems was 0.95, 0.91, and 0.93. The experimental results demonstrated superior performance of proposed deep learning system over conventional methods in literature. Graphical abstract ᅟ. [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]

In the case of carotid atherosclerosis, to avoid unnecessary surgeries in asymptomatic patients, it is necessary to develop a technique to effectively differentiate symptomatic and asymptomatic plaques. In this paper, we have presented a data mining framework that characterizes the textural differences in these two classes using several grayscale features based on a novel combination of trace transform and fuzzy texture. The features extracted from the delineated plaque regions in B-mode ultrasound images were used to train several classifiers in order to prepare them for classification of new test plaques. Our CAD system was evaluated using two different databases consisting of 146 (44 symptomatic to 102 asymptomatic) and 346 (196 symptomatic and 150 asymptomatic) images. Both these databases differ in the way the ground truth was determined. We obtained classification accuracies of 93.1 and 85.3 %, respectively. The techniques are low cost, easily implementable, objective, and non-invasive. For more objective analysis, we have also developed novel integrated indices using a combination of significant features. [ABSTRACT FROM AUTHOR]

The selection of carotid atherosclerosis patients for surgery or stenting is a crucial task in atherosclerosis disease management. In order to select only those symptomatic cases who need surgery, we have, in this work, presented a computer-aided diagnostic technique to effectively classify symptomatic and asymptomatic plaques from B-mode ultrasound carotid images. We extracted several grayscale features that quantify the textural differences inherent in the manually delineated plaque regions and selected the most significant among these extracted features. These features, along with the degree of stenosis (DoS), were used to train and test a support vector machine (SVM) classifier using threefold stratified cross-validation using a data set consisting of 160 (50 symptomatic and 110 asymptomatic) images. Using 32 features in an SVM classifier with a polynomial kernel of order 1, we obtained the best accuracy of 90.66%, sensitivity of 83.33%, and specificity of 95.39%. The DoS was found to be a valuable feature in addition to other texture-based features. We have also proposed the plaque risk index ( PRI) made up of a combination of significant features such that the PRI has unique ranges for both plaque classes. PRI can be used in monitoring the variations in features over a period of time which will provide evidence on how and which features change as asymptomatic plaques become symptomatic. [ABSTRACT FROM PUBLISHER]

Carotid plaques have been associated with ipsilateral neurological symptoms. High-resolution ultrasound can provide information not only on the degree of carotid artery stenosis but also on the characteristics of the arterial wall including the size and consistency of atherosclerotic plaques. The aim of this study is to determine whether the addition of ultrasonic plaque texture features to clinical features in patients with asymptomatic internal carotid artery stenosis (ACS) improves the ability to identify plaques that will produce stroke. 1121 patients with ACS have been scanned with ultrasound and followed for a mean of 4 years. It is shown that the combination of texture features based on second-order statistics spatial gray level dependence matrices (SGLDM) and clinical factors improves stroke prediction (by correctly predicting 89 out of the 108 cases that were symptomatic). Here, the best classification results of 77 \pm 1.8\% were obtained from the use of the SGLDM texture features with support vector machine classifiers. The combination of morphological features with clinical features gave slightly worse classification results of 76 \pm 2.6\%. These findings need to be further validated in additional prospective studies. [ABSTRACT FROM PUBLISHER]

Computer-aided diagnosis (CAD) of carotid atherosclerosis into symptomatic or asymptomatic is useful in the analysis of cardiac health. This paper describes a patented CAD system called Atheromatic™ for symptomatic versus asymptomatic plaque classification in carotid ultrasound images. The system involves two steps: 1) feature extraction using a combination of discrete wavelet transform and averaging algorithms and 2) classification using a support vector machine (SVM) classifier for automated decision making. The CAD system was evaluated using a database consisting of 150 asymptomatic and 196 symptomatic plaque regions which were labeled using the ground truth based on the presence or absence of symptoms. Threefold cross-validation protocol was adapted for developing and testing the classifiers. We observed that the SVM classifier with a polynomial kernel of order 2 was to achieve a classification accuracy of 83.7%. [ABSTRACT FROM PUBLISHER]

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima–media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale–space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen–intima (LI) and media–adventitia (MA) interfaces for the far (distal) wall and IMT measurement. Our database of 365 B-mode longitudinal carotid images is taken from four different institutions covering different ethnic backgrounds. The ground-truth (GT) database was the average manual segmentation from three clinical experts. The mean distance \pm standard deviation of CAMES with respect to GT profiles for LI and MA interfaces were 0.081 \pm 0.099 and 0.082 \pm 0.197 mm, respectively. The IMT measurement error between CAMES and GT was 0.078 \pm 0.112 mm. CAMES was benchmarked against a previously developed automated technique based on an integrated approach using feature-based extraction and classifier (CALEX). Although CAMES underestimated the IMT value, it had shown a strong improvement in segmentation errors against CALEX for LI and MA interfaces by 8% and 42%, respectively. The overall IMT measurement bias for CAMES improved by 36% against CALEX. Finally, this paper demonstrated that the figure-of-merit of CAMES was 95.8% compared with 87.4% for CALEX. The combination of multiresolution CA recognition and far-wall segmentation led to an automated, low-complexity, real-time, and accurate technique for carotid IMT measurement. Validation on a multiethnic/multi-institutional data set demonstrated the robustness of the technique, which can constitute a clinically valid IMT measurement for assistance in atherosclerosis disease management. [ABSTRACT FROM AUTHOR]

Purpose: The development of completely automated techniques for arterial wall segmentation and intima-media thickness measurement requires the recognition of the artery in the image frame. Conceptually, automated techniques can be thought of as the combination of two cascaded stages: artery recognition and wall segmentation. In this paper, the authors show three carotid artery recognition systems (CARS) that are fully automated. Methods: The first technique is based on a first-order derivative Gaussian edge analysis (CARSgd). The second method is based on an integrated approach (CARSia) that combines image feature extraction, fitting, and classification. The third strategy is based on signal analysis (CARSsa). The output of all the three paradigms provide tracing of the far adventitial (ADF). The authors validated CARSgd, CARSia, and CARSsa on a dataset of 365 longitudinal B-Mode carotid images, acquired by different sonographers. Performance evaluation of the carotid recognition process was done in three ways: (1) visual inspection by experts; (2) by measuring the Hausdorff distance (HD) between the automatic far adventitial (ADF) and the manually traced ADF, and (3) by measuring the HD between ADF and the lumen-intima (GTLI) and media-adventitia (GTMA) borders of the arterial walls. Results: The average HD between ADF and the manual ADF was 1.53 ± 1.51 mm for CARSgd, 1.82 ± 3.08 mm for CARSia, and 2.56 ± 2.89 mm for CARSsa. The average HD between GTLI and ADF for CARSgd, CARSia, and CARSsa were 2.16 ± 1.16 mm, 2.71 ± 2.89 mm, and 2.66 ± 1.52 mm, respectively. The average HD between ADF and GTMA for CARSgd, CARSia, and CARSsa were 1.54 ± 1.19 mm, 1.86 ± 2.66 mm, and 1.95 ± 1.64 mm, respectively. Considering a maximum distance of 50 pixels (about 3 mm), CARSgd showed an identification accuracy of 100%, CARSia of 92%, and CARSsa of 96%. These identification accuracies were confirmed by visual inspection. All the three systems work on MATLAB, Windows OS, and on a PC based cross platform medical application written in Java called ATHEROEDGE™ with 1 s per image. Conclusions: CARSgd showed very accurate ADF profiles coupled with a low computational burden and without the need for specific tuning. It can be thought of as a reference technique for carotid localization, to be used in automated intima-media thickness measurement strategies. [ABSTRACT FROM AUTHOR]

The evaluation of the carotid artery wall is essential for the diagnosis of cardiovascular pathologies or for the assessment of a patient's cardiovascular risk. This paper presents a completely user-independent algorithm, which automatically extracts the far double line (lumen-intima and media-adventitia) in the carotid artery using an Edge Flow technique based on directional probability maps using the attributes of intensity and texture. Specifically, the algorithm traces the boundaries between the lumen and intima layer (line one) and between the media and adventitia layer (line two). The Carotid Automated Ultrasound Double Line Extraction System based on Edge-Flow (CAUDLES-EF) is characterized and validated by comparing the output of the algorithm with the manual tracing boundaries carried out by three experts. We also benchmark our new technique with the two other completely automatic techniques (CALEXia and CULEXsa) we previously published. Our multi-institutional database consisted of 300 longitudinal B-mode carotid images with normal and pathologic arteries. We compared our current new method with previous methods, and showed the mean and standard deviation for the three methods: CALEXia, CULEXsa, and CAUDLES-EF as 0.134 ± 0.088, 0.074 ± 0.092, and 0.043 ± 0.097 mm, respectively. Our IMT was slightly underestimated with respect to the ground truth IMT, but showed a uniform behavior over the entire database. Regarding the Figure of Merit (FoM), CALEXia and CULEXsa showed the values of 84.7% and 91.5%, respectively, while our new approach, CAUDLES-EF, performed the best at 94.8%, showing a good improvement compared to previous methods. [ABSTRACT FROM AUTHOR]

Objectives: The aim was to determine the diagnostic value of a juxtaluminal black (hypoechoic) area without a visible echogenic cap (JBA) in ultrasonic images of internal carotid artery plaques. Methods: Ultrasonic images of plaques from 324 patients with asymptomatic (n = 139) and symptomatic (n = 185) internal carotid 50% to 99% stenosis in relation to the bulb (European Carotid Surgery Trial) referred for duplex scanning were studied. The JBA in mm2 and the gray-scale median (GSM) were obtained after image normalization. Cut-off points for GSM and JBA (combined highest sensitivity with highest specificity) were determined from receiver operator characteristic (ROC) curves. Results: JBA ≥ 8 mm2 was associated with a high prevalence of symptomatic plaques in all grades of stenosis. In a multiple logistic regression model, increasing stenosis (mild, moderate, severe), GSM ≤ 15 and JBA ≥ 8 mm2 were independent predictors of the presence of hemispheric symptoms. This model could identify a high-risk group of 188 plaques that contained 142 (77%) of the 185 symptomatic plaques (odds ratio [OR], 6.7; 95% confidence interval [CI], 4.08-10.91), (P < .001), (sensitivity: 77%; specificity 66%; positive predictive value 75%; negative predictive value 68%). Conclusions: The results of this study indicate the diagnostic value and for the first time suggest a cut-off point of 8 mm2 for JBA. This cut-off point needs to be validated in other groups and then applied to prospective studies of asymptomatic patients. [Copyright &y& Elsevier]

The Cyprus Study is a prospective cohort study of cardiovascular disease (CVD). Its aim is to determine the relationship of intima-media thickness (IMT) of the common carotid (IMTcc), maximum thickness of IMT in the carotid bifurcation (IMTmax), number of carotid and femoral bifurcations with plaque and total plaque thickness (TPT) (sum of the maximum plaque measurements taken from the four bifurcations scanned) with the prevalence of clinical CVD. A total of 767 individuals (46% male) over the age of 40 years were recruited from a mountain village and a town outside the capital Nicosia. In addition to clinical examination, carotid and common femoral bifurcations were scanned with ultrasound. After controlling for conventional risk factors, there was little evidence of an association of IMTcc with CVD prevalence. However, IMTmax and TPT were associated with 2.9-fold (1.22 to 7.07) and 6.87-fold (2.42 to 19.43) increased odds of CVD prevalence, respectively. In conclusion, the TPT and number of bifurcations with plaque are more strongly associated with the prevalence of CVD. These findings warrant investigation in prospective studies to document associations with incident CVD events. [ABSTRACT FROM AUTHOR]

Background: Unstable carotid plaques on subjective, visual, assessment using B-mode ultrasound scanning appear as echolucent and heterogeneous. Although previous studies on computer assisted plaque characterisation have standardised B-mode images for brightness, improving the objective assessment of echolucency, little progress has been made towards standardisation of texture analysis methods, which assess plaque heterogeneity. The aim of the present study was to investigate the influence of image zooming during ultrasound scanning on textural features and to test whether or not resolution standardisation decreases the variability introduced. Methods: Eighteen still B-mode images of carotid plaques were zoomed during carotid scanning (zoom factor 1.3) and both images were transferred to a PC and normalised. Using bilinear and bicubic interpolation, the original images were interpolated in a process of simulating off-line zoom using the same interpolation factor. With the aid of the colour-coded image, carotid plaques of the original, zoomed and two resampled images for each case were outlined and histogram, first order and second order statistics were subsequently calculated. Results: Most second order statistics (21/25, 84%) were significantly (p < 0.05) sensitive to image zooming during scanning, in contrast to histogram and first order statistics (4/25, 16%, p < 0.001, Fisher's exact test). Median (interquartile range) change of those features sensitive to zooming was 18.14% (4.94-28.43). Image interpolation restored these changes, the bicubic interpolation being superior compared to bilinear interpolation (p = 0.036). Conclusion: Texture analysis of ultrasonic plaques should be performed under standardised resolution settings; otherwise a resolution normalisation algorithm should be applied. [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]

Objective: It has been previously shown that the SCD Response Compression System, by sensing the postcompression refill time of the lower limbs, delivers more compression cycles over time, resulting in as much as a 76% increase in the total volume of blood expelled per hour. Extended indications for pneumatic compression have necessitated the introduction of portable devices. The aim of our study was to test the hemodynamic effectiveness of a new portable sequential compression system (the SCD Express), which has the ability to detect the individual refill time of the two lower limbs separately. Methods: This was an open, controlled trial with 30 normal volunteers. The new SCD Express was compared with the SCD Response Compression System in the supine and semirecumbent positions. The refilling time sensed by the device was compared with that determined from velocity recordings of the superficial femoral vein using duplex ultrasonography. Baseline and augmented flow velocity and volume flow, including the total volume of blood expelled per hour during compression with the SCD Express, were compared with those produced by the SCD Response compression system in the same volunteers and positions. Results: Both devices significantly increased venous flow velocity as much as 2.26 times baseline in supine position and 2.67 times baseline in semirecumbent position (all P < .001). There was a linear relationship between duplex ultrasonography-derived refill time and the SCD Express-derived refill time in both the supine (r = 0.39, P = .03) and semirecumbent (r = 0.71, P < .001) positions but not with the SCD Response. Refill time measured by the SCD Express device was significantly shorter and the cycle rate higher in comparison with the SCD Response in both positions. The single-cycle flow velocity and volume flow parameters generated by the two devices were similar in both positions. However, median (interquartile range) total volume of blood expelled per hour was slightly higher with the SCD Express device in the supine position (7206 mL/h [range, 5042–8437] vs 6712 mL/h [4941–10,676]; P = .85) and semirecumbent position (4588 mL/h [range, 3721–6252] vs 4262 mL/h [3520–5831]; P = .22). Peak volume of blood expelled per hour by the SCD Express device in the semirecumbent position was significantly increased by 10% in comparison with the SCD Response (P = .03). Conclusions: Flow velocity and volume flow enhancement by the SCD Response and SCD Express were essentially similar. The latter, a portable device with optional battery power that detects the individual refill time of the lower limbs separately, is anticipated to be associated with improved overall compliance and therefore optimized thromboprophylaxis. Studies testing its potential for improved efficacy in preventing deep vein thrombosis are justified. [Copyright &y& Elsevier]

The aim of this study was to determine the effect of image normalization on plaque classification and the risk of ipsilateral ischemic neurologic events in patients with asymptomatic carotid stenosis. The first 1,115 patients recruited to the Asymptomatic Carotid Stenosis and Risk of Stroke (ACSRS) study with a follow-up of 6 to 84 months (mean 37.1 months) were included in this study. Duplex ultrasonography was used for grading the degree of internal carotid artery stenosis and for plaque characterization (types 1-5), which was performed before and after image normalization. One hundred sixteen ipsilateral ischemic hemispheric events occurred. Image normalization resulted in 60% of plaques being reclassified. Before image normalization, a high event rate was associated with all types of plaque. After image normalization, 109 (94%) of the events occurred in patients with plaque types 1 to 3. For patients with European Carotid Stenosis Trial (ECST) 70 to 99% diameter stenosis (equivalent to North American Symptomatic Carotid Endarterectomy Trial [NASCET] 50-99%) with plaque types 1 to 3, the cumulative stroke rate was 14% at 7 years (2% per year), and for patients with plaque types 4 and 5, the cumulative stroke rate was 0.9% at 7 years (0.14% per year). The results suggest that asymptomatic patients with plaque types 4 and 5 classified as such after image normalization are at low risk irrespective of the degree of stenosis. [ABSTRACT FROM AUTHOR]

Common carotid intima-media thickness (CIMT) is a commonly used marker for atherosclerosis and is often computed in carotid ultrasound images. An analysis of different computerized techniques for CIMT measurement and their clinical impacts on the same patient data set is lacking. Here we compared and assessed five computerized CIMT algorithms against three expert analysts' manual measurements on a data set of 1088 patients from two centers. Inter- and intra-observer variability was assessed, and the computerized CIMT values were compared with those manually obtained. The CIMT measurements were used to assess the correlation with clinical parameters, cardiovascular event prediction through a generalized linear model and the Kaplan-Meier hazard ratio. CIMT measurements obtained with a skilled analyst's segmentation and the computerized segmentation were comparable in statistical analyses, suggesting they can be used interchangeably for CIMT quantification and clinical outcome investigation. To facilitate future studies, the entire data set used is made publicly available for the community at http://dx.doi.org/10.17632/fpv535fss7.1. [ABSTRACT FROM AUTHOR]

Aim: The study investigated the association of carotid ultrasound echolucent plaque-based biomarker with HbA1c, measured as age-adjusted grayscale median (AAGSM) as a function of chronological age, total plaque area, and conventional grayscale median (GSMconv).Methods: Two stages were developed: (a) automated measurement of carotid parameters such as total plaque area (TPA); (b) computing the AAGSM as a function of GSMconv, age, and TPA. Intra-operator (novice and experienced) analysis was conducted.Results: IRB approved, 204 patients' left/right CCA (408 images) ultrasound scans were collected: mean age: 69 ± 11 years; mean HbA1c: 6.12 ± 1.47%. A moderate inverse correlation was observed between AAGSM and HbA1c (CC of -0.13, P = 0.01), compared to GSM (CC of -0.06, P = 0.24). The RCCA and LCCA showed CC of -0.18, P < 0.01 and -0.08; P < 0.24. Female and males showed CC of -0.29, P < 0.01 and -0.10, P = 0.09. Using the threshold for AAGSM and HbA1c as: low-risk (AAGSM > 100; HbA1c < 5.7%), moderate-risk (40 < AAGSM < 100; 5.7% < HbA1c < 6.5%) and high-risk (AAGSM < 40; HbA1c > 6.5%), the area under the curve showed a better performance of AAGSM over GSMconv. A paired t-test between operators and expert (P < 0.0001); inter-operator CC of 0.85 (P < 0.0001).Conclusions: Echolucent plaque in patients with diabetes can be more accurately characterized for risk stratification using AAGSM compared to GSMconv. [ABSTRACT FROM AUTHOR]

Described here is a detailed novel pilot study on whether the SYNTAX (Synergy between percutaneous coronary intervention with TAXUS and cardiac surgery) score, a measure of coronary artery disease complexity, could be better predicted with carotid intima–media thickness (cIMT) measures using automated IMT all along the common carotid and bulb plaque compared with manual IMT determined by sonographers. Three hundred seventy consecutive patients who underwent carotid ultrasound and coronary angiography were analyzed. SYNTAX score was determined from coronary angiograms by two experienced interventional cardiologists. Unlike most methods of cIMT measurement commonly used by sonographers, our method involves a computerized automated cIMT measurement all along the carotid artery that includes the bulb region and the region proximal to the bulb (under the class of AtheroEdge systems from AtheroPoint, Roseville, CA, USA). In this study, the correlation between automated cIMT that includes bulb plaque and SYNTAX score was found to be 0.467 ( p < 0.0001), compared with 0.391 ( p < 0.0001) for the correlation between the sonographer's IMT reading and SYNTAX score. The correlation between the automated cIMT and the sonographer's IMT was 0.882. When compared against the radiologist's manual tracings, automated cIMT system performance had a lumen–intima error of 0.007818 ± 0.0071 mm, media–adventitia error of 0.0179 ± 0.0125 mm and automated cIMT error of 0.0099 ± 0.00988 mm. The precision of automated cIMT against the manual radiologist's reading was 98.86%. This current automated algorithm revealed a significantly stronger correlation between cIMT and coronary SYNTAX score as compared with the sonographer's cIMT measurements with multiple cardiovascular risk factors. We benchmarked our correlation between the automated cIMT that includes bulb plaque and SYNTAX score against a previously published ( Ikeda et al. 2013 ) AtheroEdgeLink (AtheroPoint) correlation between the automated cIMT that does not include bulb plaque and SYNTAX score and had an improvement of 44.58%. By sampling cIMT in the bulb region, the automated cIMT technique improves the degree of correlation between coronary artery disease lesion complexity and carotid atherosclerosis characteristics. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate the measurement error and inter- and intra-observer variability of completely off-line automated and semi-automated carotid intima-media thickness (cIMT) measurement software (AtheroEdge™). Two hundred carotid ultrasound images from 50 asymptomatic women were analyzed. AtheroEdge™ was benchmarked against a commercial system (Syngo, Siemens) using automated and semi-automated modes. The measurement error and inter- and intra-observer variability of AtheroEdge™ were tested using three readings. The measurement error of AtheroEdge™ compared to the commercial software was 0.002 ± 0.019 mm (r=0.99) in the automated mode and -0.001 ± 0.004 mm in the semi-automated mode (r=0.99). The measurement error of AtheroEdge™ compared to the mean value of the three expert Readers (cIMT bias) for the automated and semi-automated methods was -0.0004 ± 0.158 mm and -0.008 ± 0.157 mm, respectively. The Figure-of-Merit was 99.8% and 99.9% when compared to the commercial ultrasound scanner (using the automated and semi-automated method, respectively) and was 99.9% and 98.9% when compared to the mean value of the three expert Readers. Regarding inter- and intra-observer variability, the intra-class correlation coefficient of the three independent users using the semi-automated AtheroEdge™ was 0.98. AtheroEdge™ showed a measurement performance comparable to the commercial ultrasound scanner software and the expert Readers' tracings. AtheroEdge™ belongs to a class of automated systems that could find application in processing large datasets for common carotid arteries, avoiding subjectivity in cIMT measurements. [ABSTRACT FROM AUTHOR]

Aims: The purpose of this study was to evaluate whether carotid IMT (cIMT) identified using automated software is associated with HbA1c in Japanese patients with coronary artery disease. Methods: 370 consecutive patients (males 218; median age 69 years±11) who underwent carotid-US and first coronary angiography were prospectively analyzed. After ultrasonographic examinations were performed, the plaque score (PS) was calculated and automated IMT analysis was obtained with a dedicated algorithm. Pearson correlation analysis was performed to calculate the association between automated IMT, PS and HbA1c. Results: The mean value of cIMT was 1.00±0.47mm for the right carotid and 1.04±0.49mm for the left carotid; the average bilateral value was 1.02±0.43mm. No significant difference of cIMT was detected between men and women. We found a direct correlation between cIMT values and HbA1c (p =0.0007) whereas the plaque score did not correlate with the HbA1c values (p >0.05) Conclusion: The results of our study confirm that automated cIMT values and levels of HbA1c in Japanese patients with coronary artery disease are correlated whereas the plaque score does not show a statistically significant correlation. [ABSTRACT FROM AUTHOR]

Abstract: Automated and high performance carotid intima-media thickness (IMT) measurement is gaining increasing importance in clinical practice to assess the cardiovascular risk of patients. In this paper, we compare four fully automated IMT measurement techniques (CALEX, CAMES, CARES and CAUDLES) and one semi-automated technique (FOAM). We present our experience using these algorithms, whose lumen-intima and media-adventitia border estimation use different methods that can be: (a) edge-based; (b) training-based; (c) feature-based; or (d) directional Edge-Flow based. Our database (DB) consisted of 665 images that represented a multi-ethnic group and was acquired using four OEM scanners. The performance evaluation protocol adopted error measures, reproducibility measures, and Figure of Merit (FoM). FOAM showed the best performance, with an IMT bias equal to 0.025±0.225mm, and a FoM equal to 96.6%. Among the four automated methods, CARES showed the best results with a bias of 0.032±0.279mm, and a FoM to 95.6%, which was statistically comparable to that of FOAM performance in terms of accuracy and reproducibility. This is the first time that completely automated and user-driven techniques have been compared on a multi-ethnic dataset, acquired using multiple original equipment manufacturer (OEM) machines with different gain settings, representing normal and pathologic cases. [Copyright &y& Elsevier]

Abstract: Introduction: Emerging data suggests that 3-dimensional (D) ultrasound (US) may provide us with a new tool for the identification of the vulnerable carotid plaque. Methods: A systematic review of the PubMed, Scopus and Cochrane databases regarding the reproducibility and effectiveness of 3D US in evaluation of carotid plaque disease (CPD) was performed. Results: Seven studies on the reproducibility of 3D ultrasound evaluation of plaque volume (PV) were identified. All studies reported good intra- and inter-observer reproducibility ranging from 2.8–6.0% to 4.2–7.6%, respectively. In addition, ten studies evaluating 3D carotid plaque progression with and without treatment were retrieved. In the 4 studies where 2D and 3D US features were compared, PV rather than intima media thickness (IMT) was a more sensitive marker of plaque change as a response to treatment. However, there were no studies evaluating changes in plaque morphology or specific composition features post-treatment with both 2 and 3D US. Finally, only one study was identified regarding the 3D composition differences of CPD between symptomatic and asymptomatic patients. Conclusion: The current evidence supports the good reproducibility of the 3D US on the evaluation of carotid plaque volume, however with high heterogeneity between studies. There is also preliminary evidence that PV measurements may be more sensitive than IMT in the identification of plaque change post-treatment, though, more plaque-related evidence is necessary. Further research is needed to establish if 3D is superior to 2D US in the identification of the vulnerable carotid plaque in clinical settings. [Copyright &y& Elsevier]

Abstract: Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws’ texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke. (E-mail: knikita@cc.ece.ntua.gr) [Copyright &y& Elsevier]

The motion of the carotid atheromatous plaque relative to the adjacent wall may be related to the risk of cerebral events. A quantitative method for motion estimation was applied to analyse arterial wall movement from sequences of 2-D B-mode ultrasound (US) images. Image speckle patterns were tracked between successive frames using the correlation coefficient as the matching criterion. The size of the selected region-of-interest (ROI) was shown to affect the motion analysis results; an optimal size of 3.2 × 2.5 mm2 was suggested for tracking a region at the wall-lumen interface and of 6.3 × 2.5 mm2 for one within the tissue. The results showed expected cyclical motion in the radial direction and some axial movement of the arterial wall. The method can be used to study further the axial motion of the carotid artery wall and plaque and, thus, provide useful insight into the mechanisms of atherosclerosis. [Copyright &y& Elsevier]

In this paper, a pilot study regarding carotid atherosclerotic plaque instability using B-mode ultrasound (US) images was carried out. The fractal dimension of plaques obtained from ten symptomatic subjects (i.e., subjects having experienced neurological symptoms) as well as from nine asymptomatic subjects, was estimated using a novel method, called the kth nearest neighbour (KNN) method. The results indicated a significant difference, as per the fractal dimension, between the two groups, providing a significantly lower value for the asymptomatic group. Moreover, the phase of the cardiac cycle (systole/diastole) during which the fractal dimension was estimated had no systematic effect on the calculations. The fractal dimension of the plaques was also estimated using a well-known method, namely the box-counting (BC) method. No significant differences between the two groups, as per the fractal dimension, were observed using the BC method. The presented pilot study suggests that the fractal dimension, estimated by the proposed method, could be used as a single determinant for the discrimination of symptomatic and asymptomatic subjects. (E-mail: knikita@cc.ece.ntua.gr) [Copyright &y& Elsevier]