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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]

Objectives Patients with SLE have an increased risk of developing cardiovascular disease (CVD). Multiple studies have shown that these patients have increased numbers of carotid plaques and greater intima-media thickness (IMT) than healthy controls. Measures such as total plaque area (TPA) and plaque echogenicity may be more sensitive and more relevant to cardiovascular risk than presence of plaque and IMT alone. Our objective was to produce the first report of TPA and echogenicity in a population of patients with SLE. Methods One hundred patients with SLE and no history of clinical CVD were recruited. Clinical, serological and treatment variables were recorded and serum was tested for antibodies to apolipoprotein A-1 and high-density lipoprotein. Both carotid and both femoral artery bifurcations of each patient were scanned to determine IMT, TPA and echogenicity of plaques. Univariable and multivariable statistical analyses were carried out to define factors associated with each of these outcomes. Results Thirty-six patients had carotid and/or femoral plaque. Increasing age was associated with presence of plaque and increased IMT. Triglyceride levels were associated with presence of plaque. Mean (s. d.) TPA was 60.8 (41.6) mm2. Patients taking prednisolone had higher TPA. Most plaques were echolucent, but increased echogenicity was associated with prednisolone therapy and persistent disease activity. Conclusion TPA and plaque echogenicity in patients with SLE are associated with different factors than those associated with presence of plaque and IMT. Longitudinal studies may show whether these outcome measures add value in the management of cardiovascular risk in SLE. [ABSTRACT FROM AUTHOR]

The objectives of this study are to (1) examine the "10-year cardiovascular risk" in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0) and (2) evaluate the performance of AECRS2.0 against "conventional cardiovascular risk calculators." These objectives are met by measuring (1) image-based phenotypes and AECRS2.0 score computation and (2) performance evaluation of AECRS2.0 against 12 conventional cardiovascular risk calculators. The Asian–Indian cohort (n = 379) with type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), or hypertension were retrospectively analyzed by acquiring the 1516 carotid ultrasound scans (mean age: 55 ± 10.1 years, 67% males, ∼92% with T2DM, ∼83% with CKD [stage 1-5], and 87.5% with hypertension [stage 1-2]). The carotid bulb showed a higher 10-year cardiovascular risk compared to the CCA by 18% (P <.0001). Patients with T2DM and/or CKD also followed a similar trend. The carotid bulb demonstrated a superior risk assessment compared to CCA in patients with T2DM and/or CKD by showing: (1) ∼13% better than CCA (0.93 vs 0.82, P =.0001) and (2) ∼29% better compared with 12 types of risk conventional calculators (0.93 vs 0.72, P =.06). [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]

Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients' left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system. [ABSTRACT FROM AUTHOR]

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings. [ABSTRACT FROM AUTHOR]

Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DP) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application. [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]

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]

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]

Intima-media thickness (IMT) is now being considered as an indicator of atherosclerosis. Our group has developed several feature-based IMT measurement algorithms such as the Completely Automated Layer EXtraction (CALEX) (which is a class of patented AtheroEdge Systems from Global Biomedical Technologies, Inc., CA, USA). These methods are based on the hypothesis that the highest pixel intensities are in the far wall of the common carotid artery (CCA) or the internal carotid artery (ICA). In this paper, we verify that this hypothesis holds true for B-mode longitudinal ultrasound (US) images of the carotid wall. This patented methodology consists of generating the composite image (the arithmetic sum of images) from the database by first registering the carotid image frames with respect to a nearly straight carotid-artery frame from the same database using: 1) B-spline-based nonrigid registration and 2) affine registration. Prior to registration, we segment the carotid-artery lumen using a level-set-based algorithm followed by morphological image processing. The binary lumen images are registered, and the transformations are applied to the original grayscale CCA images. We evaluated our technique using a database of 200 common carotid images of normal and pathologic carotids. The composite image presented the highest intensity distribution in the far wall of the CCA/ICA, validating our hypothesis. We have also demonstrated the accuracy and improvement in the IMT segmentation result with our CALEX 3.0 system. The CALEX system, when run on newly acquired US images, shows the IMT error of about 30 \mu\m. Thus, we have shown that the CALEX algorithm is able to exploit the far-wall brightness for accurate IMT measurements. [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]