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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]

An editorial is presented on plaque burden and vulnerable features being at higher risk of cerebrovascular symptoms. Topics include evaluating carotid plaques using computed tomography angiography (CTA) in symptomatic patients with bilateral intraplaque hemorrhage; and computed tomography angiography being quicker and more cost-effective imaging technique than MRI and identifying vulnerable carotid plaque features.

Objective Patients with SLE have increased prevalence of clinical cardiovascular disease (CVD) and subclinical atherosclerosis. Although 30–40% of patients with SLE have vascular plaque on ultrasound scanning, this study is the first to consider the relationship between total burden of plaque and subsequent CVD risk. Methods One hundred patients with SLE and without any previous clinical CVD underwent vascular ultrasound scans of both carotid and both common femoral bifurcations between 2011 and 2013. Clinical, serological, demographic and treatment data were collected at baseline. Patients were followed till 2020 to identify those who developed new onset coronary disease or stroke. Statistical analysis to identify factors associated with increased risk of developing CVD events was carried out. Results Thirty-six patients had plaque at baseline. During follow-up five patients (all had baseline plaque) developed coronary disease and two, without baseline plaque, developed lacunar strokes. Mean (s. d.) age of these patients was 46.5 (4.5) years. Patients with three or more baseline bifurcations with plaque were 10 times more likely to develop CVD than those with 0–2 bifurcations with plaques (OR 9.9, P  = 0.009). TPA > 16mm2 was associated with six-fold increased risk of CVD (OR = 6.44, P  = 0.028). Patients with disease duration > 14 years were more likely than those with disease duration < 14 years to develop CVD (OR 8.3 P  = 0.043) Conclusions The number of bifurcations with plaque and TPA in patients with SLE may be valuable in assessing risk of CVD and deciding on clinical measures to reduce this risk. [ABSTRACT FROM AUTHOR]

Atherosclerosis has a long preclinical phase, and the risk of cardiovascular (CV) events may be high in asymptomatic subjects. Conventional risk factors provide information for the statistical probability of developing CV events, but they lack precision in asymptomatic subjects. This review aims to summarize the role of some widely publicized indicators of early atherosclerosis in predicting CV events. The earliest measurable indicator of the atherosclerotic process is endothelial dysfunction, measured by flow-mediated dilation (FMD) of the brachial artery. However, reduced FMD is a stronger predictor of future CV events in patients with existing CV disease than in apparently healthy persons. Alternatively, measurement of carotid artery intima-media thickness does not improve the predictive value of risk factor scores, while detection of asymptomatic atherosclerotic plaques in carotid or common femoral arteries by ultrasound indicates high CV risk. Coronary calcium is a robust and validated help in the estimation of vascular changes and risk, which may improve risk stratification beyond traditional risk factors with relatively low radiation exposure. Arterial stiffness of the aorta, measured as the carotid-femoral pulse wave velocity is an independent marker of CV risk at the population level, but it is not recommended as a routine procedure because of measurement difficulties. Low ankle-brachial index (ABI) indicates flow-limiting atherosclerosis in the lower limbs and indicates high CV risk, while normal ABI does not rule out advanced asymptomatic atherosclerosis. Novel circulating biomarkers are associated with the atherosclerotic process. However, because of limited specificity, their ability to improve risk classification at present remains low. [Display omitted] • Traditional risk factors for cardiovascular (CV) disease inform on the probability of developing atherosclerosis and related CV events. • Detecting preclinical atherosclerosis enables the identification of individuals with ongoing atherosclerosis. • Preclinical atherosclerosis can be identified by functional/morphologic deterioration of the arterial wall or by circulating biomarkers. • The predictive value of indicators of preclinical atherosclerosis for future CV events is not completely elucidated. • Ankle-brachial index, calcium score, and asymptomatic plaques may improve risk stratification for CV events beyond traditional risk factors. [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]

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]

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]

We evaluated the association between automatically measured carotid total plaque area (TPA) and the estimated glomerular filtration rate (eGFR), a biomarker of chronic kidney disease (CKD). Automated average carotid intima–media thickness (cIMTave) and TPA measurements in carotid ultrasound (CUS) were performed using AtheroEdge (AtheroPoint). Pearson correlation coefficient (CC) was then computed between the TPA and eGFR for (1) males versus females, (2) diabetic versus nondiabetic patients, and (3) between the left and right carotid artery. Overall, 339 South Asian Indian patients with either type 2 diabetes mellitus (T2DM) or CKD, or hypertension (stage 1 or stage 2) were retrospectively analyzed by acquiring cIMTave and TPA measurements of their left and right common carotid arteries (CCA; total CUS: 678, mean age: 54.2 ± 9.8 years; 75.2% males; 93.5% with T2DM). The CC between TPA and eGFR for different scenarios were (1) for males and females −0.25 (P <.001) and −0.35 (P <.001), respectively; (2) for T2DM and non-T2DM −0.26 (P <.001) and −0.49 (P =.02), respectively, and (3) for left and right CCA −0.25 (P <.001) and −0.23 (P <.001), respectively. Automated TPA is an equally reliable biomarker compared with cIMTave for patients with CKD (with or without T2DM) with subclinical atherosclerosis. [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]

Motivation: This study presents a novel nonlinear model which can predict 10‐year carotid ultrasound image‐based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low‐density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima‐media thickness (IMT), wall variability, and total plaque area). Methodology: Two‐step process was adapted: First, five baseline carotid image‐based phenotypes were automatically measured using AtheroEdge™ (AtheroPoint™, CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10‐year predictions of carotid phenotypes. Results: Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10‐year carotid phenotypes. Mean correlation coefficient (CC) between 10‐year carotid image‐based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10‐year measurements of five phenotypes IMTave10yr, IMTmax10yr, IMTmin10yr, IMTV10yr, and TPA10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter‐operator variability between two operators showed significant CC (P < 0.0001). Conclusions: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image‐based phenotypes for predicting the 10‐year carotid ultrasound image‐based phenotypes which may be used risk assessment. [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]

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]

Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30, 600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm, 27.79 ± 10.94 mm, 46.44 ± 19.13 mm and 35.92 ± 16.44 mm respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student's t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80 %. Out procedure and protocol is along the line with method previously published clinically. [ABSTRACT FROM AUTHOR]

Interventional cardiologists have a deep interest in risk stratification prior to stenting and percutaneous coronary intervention (PCI) procedures. Intravascular ultrasound (IVUS) is most commonly adapted for screening, but current tools lack the ability for risk stratification based on grayscale plaque morphology. Our hypothesis is based on the genetic makeup of the atherosclerosis disease, that there is evidence of a link between coronary atherosclerosis disease and carotid plaque built up. This novel idea is explored in this study for coronary risk assessment and its classification of patients between high risk and low risk. This paper presents a strategy for coronary risk assessment by combining the IVUS grayscale plaque morphology and carotid B-mode ultrasound carotid intima-media thickness (cIMT) – a marker of subclinical atherosclerosis. Support vector machine (SVM) learning paradigm is adapted for risk stratification, where both the learning and testing phases use tissue characteristics derived from six feature combinational spaces, which are then used by the SVM classifier with five different kernels sets. These six feature combinational spaces are designed using 56 novel feature sets. K -fold cross validation protocol with 10 trials per fold is used for optimization of best SVM-kernel and best feature combination set. IRB approved coronary IVUS and carotid B-mode ultrasound were jointly collected on 15 patients (2 days apart) via : (a) 40 MHz catheter utilizing iMap (Boston Scientific, Marlborough, MA, USA) with 2865 frames per patient (42,975 frames) and (b) linear probe B-mode carotid ultrasound (Toshiba scanner, Japan). Using the above protocol, the system shows the classification accuracy of 94.95% and AUC of 0.95 using optimized feature combination. This is the first system of its kind for risk stratification as a screening tool to prevent excessive cost burden and better patients’ cardiovascular disease management, while validating our two hypotheses. [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]