Ultrasound assessment of carotid arteries: Current concepts, methodologies, diagnostic criteria, and technological advancements

Early detection of cardiovascular risk markers through non-invasive ultrasound methodologies in periodontitis patients

Objectives

This narrative review aims to update the current evidence and offer insight into the new non-invasive ultrasound techniques used to early identify degenerative vascular changes in subjects with periodontitis and to investigate if these methodologies could be useful to identify subclinical cardiovascular disease (CVD) dysfunction in periodontitis patients and to monitor changes in CVD risk after periodontal treatment.

Methods

Studies examining the assessment of vascular endothelial function through the latest methodologies were analyzed. Systematic reviews, observational studies, and clinical trials in the English language were identified using PubMed, Web of Science, and Google Scholar databases with key search terms such as "periodontitis," "endothelial dysfunction (ED)," "arterial stiffness," and "periodontal therapy."

Results

Several mechanisms are involved in the association between periodontitis and CVD. The key players are periodontal bacteria and their toxins, which can enter the circulation and infiltrate blood vessel walls. The increase in proinflammatory molecules such as interleukins and chemokines, c-reactive protein, fibrinogen, and oxidative stress also plays a decisive role. In addition, an increase in parameters of ED, arterial stiffness, and atherosclerosis, such as carotid intima-media thickness, pulse wave velocity, and flow-mediated dilatation, has been shown in periodontal patients.

Conclusions

The literature today agrees on the association of periodontitis and CVD and the positive role of periodontal therapy on systemic inflammatory indices and cardiovascular outcomes. Hopefully, these non-invasive methodologies could be extended to periodontal patients to provide a comprehensive understanding of the CVD-periodontitis link from the perspective of a personalized medicine approach in periodontology.

Systemic immune-inflammation index mediates the association between metabolic dysfunction-associated fatty liver disease and sub-clinical carotid atherosclerosis: a mediation analysis

Background

Limited research has been conducted to quantitatively assess the impact of systemic inflammation in metabolic dysfunction-associated fatty liver disease (MAFLD) and sub-clinical carotid atherosclerosis (SCAS). The systemic immune-inflammation index (SII), which integrates inflammatory cells, has emerged as a reliable measure of local immune response and systemic inflammation Therefore, this study aims to assess the mediating role of SII in the association between MAFLD and SCAS in type 2 diabetes mellitus (T2DM).

Method

This study prospectively recruited 830 participants with T2DM from two centers. Unenhanced abdominal CT scans were conducted to evaluate MAFLD, while B-mode carotid ultrasonography was performed to assess SCAS. Weighted binomial logistic regression analysis and restricted cubic splines (RCS) analyses were employed to analyze the association between the SII and the risk of MAFLD and SCAS. Mediation analysis was further carried out to explore the potential mediating effect of the SII on the association between MAFLD and SCAS.

Results

The prevalence of both MAFLD and SCAS significantly increased as the SII quartiles increased (P<0.05). MAFLD emerged as an independent factor for SCAS risk across three adjusted models, exhibiting odds ratios of 2.15 (95%CI: 1.31-3.53, P < 0.001). Additionally, increased SII quartiles and Ln (SII) displayed positive associations with the risk of MAFLD and SCAS (P < 0.05). Furthermore, a significant dose-response relationship was observed (P for trend <0.001). The RCS analyses revealed a linear correlation of Ln (SII) with SCAS and MAFLD risk (P for nonlinearity<0.05). Importantly, SII and ln (SII) acted as the mediators in the association between MAFLD and SCAS following adjustments for shared risk factors, demonstrating a proportion-mediated effect of 7.8% and 10.9%.

Conclusion

SII was independently correlated with MAFLD and SCAS risk, while also acting as a mediator in the relationship between MAFLD and SCAS.

A deep learning algorithm to identify carotid plaques and assess their stability

Background

Carotid plaques are major risk factors for stroke. Carotid ultrasound can help to assess the risk and incidence rate of stroke. However, large-scale carotid artery screening is time-consuming and laborious, the diagnostic results inevitably involve the subjectivity of the diagnostician to a certain extent. Deep learning demonstrates the ability to solve the aforementioned challenges. Thus, we attempted to develop an automated algorithm to provide a more consistent and objective diagnostic method and to identify the presence and stability of carotid plaques using deep learning.

Methods

A total of 3,860 ultrasound images from 1,339 participants who underwent carotid plaque assessment between January 2021 and March 2023 at the Shanghai Eighth People's Hospital were divided into a 4:1 ratio for training and internal testing. The external test included 1,564 ultrasound images from 674 participants who underwent carotid plaque assessment between January 2022 and May 2023 at Xinhua Hospital affiliated with Dalian University. Deep learning algorithms, based on the fusion of a bilinear convolutional neural network with a residual neural network (BCNN-ResNet), were used for modeling to detect carotid plaques and assess plaque stability. We chose AUC as the main evaluation index, along with accuracy, sensitivity, and specificity as auxiliary evaluation indices.

Results

Modeling for detecting carotid plaques involved training and internal testing on 1,291 ultrasound images, with 617 images showing plaques and 674 without plaques. The external test comprised 470 ultrasound images, including 321 images with plaques and 149 without. Modeling for assessing plaque stability involved training and internal testing on 764 ultrasound images, consisting of 494 images with unstable plaques and 270 with stable plaques. The external test was composed of 279 ultrasound images, including 197 images with unstable plaques and 82 with stable plaques. For the task of identifying the presence of carotid plaques, our model achieved an AUC of 0.989 (95% CI: 0.840, 0.998) with a sensitivity of 93.2% and a specificity of 99.21% on the internal test. On the external test, the AUC was 0.951 (95% CI: 0.962, 0.939) with a sensitivity of 95.3% and a specificity of 82.24%. For the task of identifying the stability of carotid plaques, our model achieved an AUC of 0.896 (95% CI: 0.865, 0.922) on the internal test with a sensitivity of 81.63% and a specificity of 87.27%. On the external test, the AUC was 0.854 (95% CI: 0.889, 0.830) with a sensitivity of 68.52% and a specificity of 89.49%.

Conclusion

Deep learning using BCNN-ResNet algorithms based on routine ultrasound images could be useful for detecting carotid plaques and assessing plaque instability.

Artificial intelligence and duplex ultrasound for detection of carotid artery disease

OBJECTIVE

The aim of this study is to evaluate the feasibility, applicability and accuracy of artificial intelligence (AI) in the detection of normal versus carotid artery disease through greyscale static duplex ultrasound (DUS) images.

METHODS

A prospective image acquisition of individuals undergoing duplex sonography for the suspicion of carotid artery disease at a single hospital was conducted. A total of n = 156 images of normal and stenotic carotid arteries (based on NASCET criteria) were evaluated by using geometry group network based on convolutional neural network (CNN) architecture. Outcome was reported based on sensitivity, specificity and accuracy of the network (artificial intelligence) for detecting normal versus stenotic carotid arteries as well as various categories of carotid artery stenosis.

RESULTS

The overall sensitivity, specificity and accuracy of AI in the detection of normal carotid artery was 91%, 86% and 92%, respectively, and for any carotid artery stenosis was 87%, 82% and 90%, respectively. Subgroup analyses demonstrated that the network has the ability to detect stenotic carotid artery images (<50%) versus normal with a sensitivity of 92%, specificity of 87% and an accuracy of 94%. This value (sensitivity, specificity and accuracy) for group of 50-75% stenosis versus normal was 84%, 80% and 88% and for carotid artery disease of more than 75% was 90%, 83% and 92%, respectively.

CONCLUSION

This study demonstrates the feasibility, applicability and accuracy of artificial intelligence in the detection of carotid artery disease in greyscale static DUS images. This network has the potential to be used as a stand-alone software or to be embedded in any DUS machine. This can enhance carotid artery disease recognition with limited or no vascular experience or serve as a stratification tool for tertiary referral, further imaging and overall management.

Characteristics and evaluation of atherosclerotic plaques: an overview of state-of-the-art techniques

Atherosclerosis is an important cause of cerebrovascular and cardiovascular disease (CVD). Lipid infiltration, inflammation, and altered vascular stress are the critical mechanisms that cause atherosclerotic plaque formation. The hallmarks of the progression of atherosclerosis include plaque ulceration, rupture, neovascularization, and intraplaque hemorrhage, all of which are closely associated with the occurrence of CVD. Assessing the severity of atherosclerosis and plaque vulnerability is crucial for the prevention and treatment of CVD. Integrating imaging techniques for evaluating the characteristics of atherosclerotic plaques with computer simulations yields insights into plaque inflammation levels, spatial morphology, and intravascular stress distribution, resulting in a more realistic and accurate estimation of plaque state. Here, we review the characteristics and advancing techniques used to analyze intracranial and extracranial atherosclerotic plaques to provide a comprehensive understanding of atheroma.

Contrast-Enhanced Ultrasound Feasibility in Assessing Carotid Plaque Vulnerability-Narrative Review

The risk assessment for carotid atherosclerotic lesions involves not only determining the degree of stenosis but also plaque morphology and its composition. Recently, carotid contrast-enhanced ultrasound (CEUS) has gained importance for evaluating vulnerable plaques. This review explores CEUS's utility in detecting carotid plaque surface irregularities and ulcerations as well as intraplaque neovascularization and its alignment with histology. Initial indications suggest that CEUS might have the potential to anticipate cerebrovascular incidents. Nevertheless, there is a need for extensive, multicenter prospective studies that explore the relationships between CEUS observations and patient clinical outcomes in cases of carotid atherosclerotic disease.

Mathematical model of aging in COVID-19

Background

The aim was examination of the intimamedia thickness of carotid arteries in COVID-19 infection.

Methods

In 50 patients, the thickness of the intimomedial complex (IMT) in the common carotid arteries was measured. The values were compared with the control group in 2006-9. The condition of the lungs was assessed by ultrasound score (It score) (0-42) as mild (0-14) or mediumsevere (15-28) Covid. IMT thickening risk factors and the value of fibrinogen, IL-6 and CRP were recorded. Two IMT prediction models were formed. The socio-epidemiological model predicts the development of IMT based on epidemiological factors. Apart from these factors, the second model also includes the values of the mentioned biomarkers.

Results

It score 20±6, IMT values right: median 0.99 mm, p25=0.89, p75=1.14; left: 1±0.22 mm. Control: IMTright: median 0.7 mm, p25=0.68 mm; p75=0-9 mm; left: median=0.75 mm, p25=0.6 mm, p75=1.0 mm. The group/control difference is highly significant. Epide mio - logical model: logit (IMT)= 4.463+(2.021+value for GEN)+(0.055x AGE value)+(-3.419x RF value)+(-4.447x SM value)+(5.115x HTA value)+(3.56x DM value)+ (22.389x LIP value)+(24.206x CVD value)+(1.449x other value)+(-0.138x It score value)+(0.19xBMI value). Epidemiological-inflammatory model: logit (IMT)=5.204+ (2.545x GEN value)+(0.076x AGE value)+(-6.132x RF value)+(-7.583x SM value)+(8.744x HTA value)+(6.838x DM value)+(25.446x LIP value)+(28.825x CVD value)+ (2.487x other value)+(-0.218xIt score value)+(0.649x BMI value) +(-0.194x fibrinogen value)+(0.894x IL-6 value)+(0.659x CRP value). Values for both models Exp(B)=4.882; P of sample=0.83; logit=-0.19; OR= 23.84; model accuracy for the first model 87% and for the second 88%; Omnibus test of the first model c2=34.324; p=0.000; reliability coefficient -2LogLH=56.854; Omnibus test of the second model c2=39.774; p=0.000; and -2LogLH=51.403.

Conclusions

The ageing of blood vessels in COVID-19 can be predicted.

Development and validation of explainable machine-learning models for carotid atherosclerosis early screening

BACKGROUND

Carotid atherosclerosis (CAS), an important factor in the development of stroke, is a major public health concern. The aim of this study was to establish and validate machine learning (ML) models for early screening of CAS using routine health check-up indicators in northeast China.

METHODS

A total of 69,601 health check-up records from the health examination center of the First Hospital of China Medical University (Shenyang, China) were collected between 2018 and 2019. For the 2019 records, 80% were assigned to the training set and 20% to the testing set. The 2018 records were used as the external validation dataset. Ten ML algorithms, including decision tree (DT), K-nearest neighbors (KNN), logistic regression (LR), naive Bayes (NB), random forest (RF), multiplayer perceptron (MLP), extreme gradient boosting machine (XGB), gradient boosting decision tree (GBDT), linear support vector machine (SVM-linear), and non-linear support vector machine (SVM-nonlinear), were used to construct CAS screening models. The area under the receiver operating characteristic curve (auROC) and precision-recall curve (auPR) were used as measures of model performance. The SHapley Additive exPlanations (SHAP) method was used to demonstrate the interpretability of the optimal model.

RESULTS

A total of 6315 records of patients undergoing carotid ultrasonography were collected; of these, 1632, 407, and 1141 patients were diagnosed with CAS in the training, internal validation, and external validation datasets, respectively. The GBDT model achieved the highest performance metrics with auROC of 0.860 (95% CI 0.839-0.880) in the internal validation dataset and 0.851 (95% CI 0.837-0.863) in the external validation dataset. Individuals with diabetes or those over 65 years of age showed low negative predictive value. In the interpretability analysis, age was the most important factor influencing the performance of the GBDT model, followed by sex and non-high-density lipoprotein cholesterol.

CONCLUSIONS

The ML models developed could provide good performance for CAS identification using routine health check-up indicators and could hopefully be applied in scenarios without ethnic and geographic heterogeneity for CAS prevention.

Ultrasound Evaluation of Extracranial Cerebral Circulation (The Common, External and Internal Carotid Artery) in Different Breeds of Dogs

Noninvasive Doppler ultrasonography (US) examination is a standard method for the clinical evaluation of the carotid arteries. Extracranial cerebral circulation includes the common carotid artery (CCA), the external carotid artery (ECA), and the extracranial part of the internal carotid artery (ICA). The present study was conducted with the objective of assessing physiological normative values and describing the appearance of spectral waveforms of extracranial arteries in 104 healthy dogs of eight breeds divided into four groups according to weight. We also focused on searching for correlations for carotid blood velocities with the resistive index (RI), body weight and diameter, and differences between observers and the influence of sex in the calculations of Doppler parameters. In the evaluated breeds, significant differences were found in the velocity of peak systolic velocity (PSV) and end diastolic velocity (EDV). There was a strong correlation between body weight and peak systolic velocity, the RI index and CCA diameter. The intra-observer agreement for the PSV and EDV parameters in each vessel was considered excellent reliability, and overall interobserver agreement showed very good reliability. This study could improve the descriptions of physiological values and waveforms recorded in carotid arteries. Defining the physiological values of velocity and the resistive index (RI) helps in the easier identification of pathology and diagnosis of disease. Our results may be used for further studies of vascular diseases in veterinary medicine that correlate with the pathology of neurological disorders of ischemic origin, further in thromboembolism, oncologic disease and degenerative, proliferative and inflammatory diseases of the arteries that lead to stenosis.

New Technologies in the Assessment of Carotid Stenosis: Beyond the Color-Doppler Ultrasound-High Frame Rate Vector-Flow and 3D Arterial Analysis Ultrasound

Atherosclerotic plaque in the carotid artery is the main cause of ischemic stroke, with a high incidence rate among people over 65 years. A timely and precise diagnosis can help to prevent the ischemic event and decide patient management, such as follow up, medical, or surgical treatment. Presently, diagnostic imaging techniques available include color-Doppler ultrasound, as a first evaluation technique, computed tomography angiography, which, however, uses ionizing radiation, magnetic resonance angiography, still not in widespread use, and cerebral angiography, which is an invasively procedure reserved for therapeutically purposes. Contrast-enhanced ultrasound is carving out an important and emerging role which can significantly improve the diagnostic accuracy of an ultrasound. Modern ultrasound technologies, still not universally utilized, are opening new horizons in the arterial pathologies research field. In this paper, the technical development of various carotid artery stenosis diagnostic imaging modalities and their impact on clinical efficacy is thoroughly reviewed.

Fully automatic carotid arterial stiffness assessment from ultrasound videos based on machine learning

Arterial stiffness (AS) refers to the loss of arterial compliance and alterations in vessel wall properties. The study of local carotid stiffness (CS) is particularly important since carotid artery stiffening raises the risk of stroke, cognitive impairment, and dementia. So, stiffness measurement as a screening tool approach is crucial because it can reduce mortality and facilitate therapy planning. This study aims to evaluate the stiffness of the CCA using machine learning (ML) through the features of diameter change (ΔD) and stiffness parameters. This study was conducted in seven stages: data collection, preprocessing, CCA segmentation, CCA lumen diameter (DCCA) computing during cardiac cycles, denoising signals of DCCA, computational of AS parameters, and stiffness assessment using ML. The 51 videos (with 25 s) of CCA B-mode ultrasound (US) were used and analyzed. Each US video yielded approximately 750 sequential frames spanning about 24 cardiac cycles. Firstly, US preset settings with time gain compensation with a U-pattern were employed to enhance CCA segmentations. The study showed that auto region-growing, employed three times, is appropriate for segmenting walls with a short running time (4.56 s/frame). The diameter computed for frames constructs a signal (diameter signal) with noisy parts in the shape of peak variance and an un-smooth side. Among the 12 employed smoothing methods, spline fitting with a mean peak difference per cycle (MPDCY) of 0.58 pixels was the most effective for the diameter signal. The authors propose the MPDCY as a new selection criterion for smoothing methods with highly preserved peaks. The ΔD (D_sys-D_dia) determined in this study was validated by statistical analysis as a viable replacement for manual ΔD measurement. Statistical analysis was carried out by Mann-Whitney t-test with a p-value of 0.81, regression line R² = 0.907, and there was no difference in means between the two groups for box plots. The stiffness parameters of the carotid arteries were calculated based on auto-ΔD and pulse pressure. Five ML models, including K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), logistic regression (LR), and random forest (RF), fed by distension (ΔD) and five stiffness parameters, were used to distinguish between the stiffened and un-stiffened CCA. Except for SVM, all models performed excellently in terms of specificity, sensitivity, precision, and area under the curve (AUC). In addition, the scatterplot and statistical analysis of the fed features confirm these remarkable outcomes. The scatter plot demonstrates that a linear hyperline can easily distinguish between the two classes. The statistical analysis shows that the stiffness parameters computed from the database of this work were statistically (p < 0.05) distributed into the non-stiffness and stiffness groups. The presented models are validated by applying them to additional datasets. Applying models to other datasets reveals a model performance of 100%. The proposed ML models could be applied in clinical practice to detect CS early, which is essential for preventing stroke.

Tips for carotid ultrasound in the intensive care unit

The ultrasonography of carotid arteries plays a key role in evaluating cerebrovascular disease. There are some useful considerations to perform it correctly in the intensive care unit, such as using different kind of transducer, Doppler mode optimization, and the correct interpretation of the findings.

Carotid atherosclerosis in people of European, South Asian and African Caribbean ethnicity in the Southall and Brent revisited study (SABRE)

Background

Atherosclerotic cardiovascular disease (ASCVD) risk differs by ethnicity. In comparison with Europeans (EA) South Asian (SA) people in UK experience higher risk of coronary heart disease (CHD) and stroke, while African Caribbean people have a lower risk of CHD but a higher risk of stroke.

Aim

To compare carotid atherosclerosis in EA, SA, and AC participants in the Southall and Brent Revisited (SABRE) study and establish if any differences were explained by ASCVD risk factors.

Methods

Cardiovascular risk factors were measured, and carotid ultrasound was performed in 985 individuals (438 EA, 325 SA, 228 AC). Carotid artery plaques and intima-media thickness (cIMT) were measured. Associations of carotid atherosclerosis with ethnicity were investigated using generalised linear models (GLMs), with and without adjustment for non-modifiable (age, sex) and modifiable risk factors (education, diabetes, hypertension, total cholesterol, HDL-C, alcohol consumption, current smoking).

Results

Prevalence of any plaque was similar in EA and SA, but lower in AC (16, 16, and 6%, respectively; p < 0.001). In those with plaque, total plaque area, numbers of plaques, plaque class, or greyscale median did not differ by ethnicity; adjustment for risk factors had minimal effects. cIMT was higher in AC than the other ethnic groups after adjustment for age and sex, adjustment for risk factors attenuated this difference.

Conclusion

Prevalence of carotid artery atherosclerotic plaques varies by ethnicity, independent of risk factors. Lower plaque prevalence in in AC is consistent with their lower risk of CHD but not their higher risk of stroke. Higher cIMT in AC may be explained by risk factors. The similarity of plaque burden in SA and EA despite established differences in ASCVD risk casts some doubt on the utility of carotid ultrasound as a means of assessing risk across these ethnic groups.

Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study

OBJECTIVES

Accurate detection of carotid plaque using ultrasound (US) is essential for preventing stroke. However, the diagnostic performance of junior radiologists (with approximately 1 year of experience in carotid US evaluation) is relatively poor. We thus aim to develop a deep learning (DL) model based on US videos to improve junior radiologists' performance in plaque detection.

METHODS

This multicenter prospective study was conducted at five hospitals. CaroNet-Dynamic automatically detected carotid plaque from carotid transverse US videos allowing clinical detection. Model performance was evaluated using expert annotations (with more than 10 years of experience in carotid US evaluation) as the ground truth. Model robustness was investigated on different plaque characteristics and US scanning systems. Furthermore, its clinical applicability was evaluated by comparing the junior radiologists' diagnoses with and without DL-model assistance.

RESULTS

A total of 1647 videos from 825 patients were evaluated. The DL model yielded high performance with sensitivities of 87.03% and 94.17%, specificities of 82.07% and 74.04%, and areas under the receiver operating characteristic curve of 0.845 and 0.841 on the internal and multicenter external test sets, respectively. Moreover, no significant difference in performance was noted among different plaque characteristics and scanning systems. Using the DL model, the performance of the junior radiologists improved significantly, especially in terms of sensitivity (largest increase from 46.3 to 94.44%).

CONCLUSIONS

The DL model based on US videos corresponding to real examinations showed robust performance for plaque detection and significantly improved the diagnostic performance of junior radiologists.

KEY POINTS

• The deep learning model based on US videos conforming to real examinations showed robust performance for plaque detection. • Computer-aided diagnosis can significantly improve the diagnostic performance of junior radiologists in clinical practice.

Development and Validation of Machine Learning Models to Classify Artery Stenosis for Automated Generating Ultrasound Report

Duplex ultrasonography (DUS) is a safe, non-invasive, and affordable primary screening tool to identify the vascular risk factors of stroke. The overall process of DUS examination involves a series of complex processes, such as identifying blood vessels, capturing the images of blood vessels, measuring the velocity of blood flow, and then physicians, according to the above information, determining the severity of artery stenosis for generating final ultrasound reports. Generation of transcranial doppler (TCD) and extracranial carotid doppler (ECCD) ultrasound reports involves a lot of manual review processes, which is time-consuming and makes it easy to make errors. Accurate classification of the severity of artery stenosis can provide an early opportunity for decision-making regarding the treatment of artery stenosis. Therefore, machine learning models were developed and validated for classifying artery stenosis severity based on hemodynamic features. This study collected data from all available cases and controlled at one academic teaching hospital in Taiwan between 1 June 2020, and 30 June 2020, from a university teaching hospital and reviewed all patients' medical records. Supervised machine learning models were developed to classify the severity of artery stenosis. The receiver operating characteristic curve, accuracy, sensitivity, specificity, and positive and negative predictive value were used for model performance evaluation. The performance of the random forest model was better compared to the logistic regression model. For ECCD reports, the accuracy of the random forest model to predict stenosis in various sites was between 0.85 and 1. For TCD reports, the overall accuracy of the random forest model to predict stenosis in various sites was between 0.67 and 0.86. The findings of our study suggest that a machine learning-based model accurately classifies artery stenosis, which indicates that the model has enormous potential to facilitate screening for artery stenosis.

Application of Model-Building Based on Arterial Ultrasound Imaging Evaluation to Predict CHD Risk

Objective

Atherosclerotic is a chronic systemic disease that may occur in multiple vascular beds, including the carotid arteries, renal arteries, lower limb arteries, and cerebral vessels. Coronary atherosclerosis shares similar risk factors, pathogenesis, and pathophysiological basis with the atherosclerotic lesions of arteries at these sites. Arterial ultrasound assessment data were used to explore the correlation of atherosclerotic disease with CHD lesions and their severity and the number of lesion branches, as well as to evaluate its value in predicting CHD risk, in combination with traditional risk factors.

Methods

A total of 363 inpatients with suspected CHD in the Department of Cardiology of the First Hospital of Harbin Medical University from November 2017 to June 2021 were selected. Patient clinical data, blood biochemical examination results, and ultrasound examination of neck vessels, abdominal arteries, and limb arteries were collected to obtain atherosclerosis assessment data. We then compared the differences between the CHD group and the control group, analyzed their correlation with CHD lesions and severity and the number of lesion branches, and evaluated the correlation with the coronary Gensini score. After adjustment for traditional risk factors, logistic regression was applied to analyze the relationship between arterial ultrasound assessment data and the risk of CHD. In addition, ROC plots were drawn to evaluate the risk of arterial ultrasound assessment data, combined with traditional risk factors, to predict CHD.

Results

With regard to abnormal blood biochemical index values, differences in lipids, HDL-C, FIB, CK-MB, hs-cTnI, BNP, and GGT were found between the CHD group and the control group. Carotid plaque count, abdominal aortic flow velocity, inferior mesenteric artery flow velocity, classification of the number of stenotic branches of abdominal aortic branch arteries, lower-extremity-artery plaque count, degree of lower-extremity-artery stenosis, and lower-extremity-artery AS were risk factors for arterial ultrasound assessment data of CHD. Carotid plaque count, carotid artery AS, inferior mesenteric artery flow velocity, abdominal aortic flow velocity, abdominal aortic plaque count, abdominal aortic branch artery stenosis branch classification, lower-extremity-artery plaque count, lower-extremity-artery stenosis branch classification, degree of lower-extremity-artery stenosis, and lower-extremity-artery AS, combined with traditional risk factors, were mostly more effective than traditional risk factor models in predicting CHD, its severity, and the number of branch lesions; moreover, the predictive value was higher. Specifically, carotid plaque count, carotid AS, lower-extremity-artery AS, the degree of stenosis of lower-extremity arteries, and abdominal aortic branch artery stenosis branch classification can be used as predictor variables for CHD risk. Among these variables, the carotid plaque count can be used as an independent predictor of CHD.

Conclusion

The incidence of arterial intima–media thickening (IMT), plaques, and stenosis can provide a reference for understanding the pattern of systemic atherogenesis and the distribution of atherosclerosis.

Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis

OBJECTIVE

This study aims to establish the predictive model of carotid plaque formation and carotid plaque location by retrospectively analyzing the clinical data of subjects with carotid plaque formation and normal people, and to provide technical support for screening patients with carotid plaque.

METHODS

There were 4300 subjects in the ultrasound department of Maanshan People's Hospital collected from December 2013 to December 2018. We used demographic and biochemical data from 3700 subjects to establish predictive models for carotid plaque and its location. The leave-one-out cross-validated classification, 600 external data validation, and area under the receiver operating characteristic curve (AUC) were used to verify the accuracy, sensitivity, specificity, and application value of the model.

RESULTS

There were significant difference of age (F = - 34.049, p < 0.01), hypertension (χ² = 191.067, p < 0.01), smoking (χ² = 4.762, p < 0.05) and alcohol (χ² = 8.306, p < 0.01), Body mass index (F = 15.322, p < 0.01), High-density lipoprotein (HDL) (F = 13.840, p < 0.01), Lipoprotein a (Lp a) (F = 52.074, p < 0.01), Blood Urea Nitrogen (F = 2.679, p < 0.01) among five groups. Prediction models were built: carotid plaque prediction model (Model CP); Prediction model of left carotid plaque only (Model CP Left); Prediction model of right carotid plaque only (Model CP Right). Prediction model of bilateral carotid plaque (Model CP Both). Model CP (Wilks' lambda = 0.597, p < 0.001, accuracy = 78.50%, sensitivity = 78.07%, specificity = 79.07%, AUC = 0.917). Model CP Left (Wilks' lambda = 0.605, p < 0.001, accuracy = 79.00%, sensitivity = 86.17%, specificity = 72.70%, AUC = 0.880). Model CP Right (Wilks' lambda = 0.555, p < 0.001, accuracy = 83.00%, sensitivity = 81.82%, specificity = 84.44%, AUC = 0.880). Model CP Both (Wilks' lambda = 0.651, p < 0.001, accuracy = 82.30%, sensitivity = 89.50%, specificity = 72.70%, AUC = 0.880).

CONCLUSION

Demographic characteristics and blood biochemical indexes were used to establish the carotid plaque and its location discriminant models based on Fisher discriminant analysis (FDA), which has high application value in community screening.

VALUE OF CORRECTED FLOW TIME IN COMMON CAROTID ARTERY IN PREDICTING VOLUME RESPONSIVENESS UNDER MECHANICAL VENTILATION

ABSTRACT

Objective: The present study aimed to investigate whether corrected flow time (FTc) in common carotid artery could predict volume responsiveness under mechanical ventilation and to further explore whether the sensitivity and specificity would be influenced by positive end-expiratory pressure (PEEP). Methods: The first stage of this study included 80 patients from the general surgery department undergoing laparotomy. After induction of general anesthesia, FTc in the common carotid artery was measured when hemodynamic indicators, such as blood pressure, heart rate, and cardiac output (CO), were stabilized. Then, 7 mg/kg (ideal body weight) of hydroxyethyl starch 130/0.4 sodium chloride was rapidly infused from the peripheral venous system. The infusion was completed within 15 minutes, and hemodynamic indicators were measured again immediately to evaluate volume responsiveness. The patients with change rate of CO (ΔCO ≥15%) were categorized into the responsive (R) group, whereas those with ΔCO <15% were categorized into the nonresponsive group (NR) group. In the second stage, 29 patients undergoing laparotomy were included. After induction of general anesthesia, PEEP of 0, 5, and 10 cmH 2 O was applied sequentially. Corrected flow time and hemodynamic indicators were recorded. Then, 7 mg/g of hydroxyethyl starch 130/0.4 sodium chloride was rapidly infused for 15 minutes, after which PEEP of 0, 5, and 10 cmH 2 O was applied sequentially, and the indicators were measured again. The patients with FTc equal to or less than the threshold in the first stage were categorized into the R group, otherwise into the NR group. Results: In the first stage of the study, CO and FTc differed significantly between the 2 groups, before and after volume load ( P < 0.05). Mean arterial pressure in the R group was significantly different, whereas heart rate did not differ before and after fluid infusion. Also, heart rate and mean arterial pressure were not significantly different before and after fluid infusion in the NR group. The area under the receiver operating characteristic curve was 0.786 ± 0.056 (95% confidence interval, 0.676-0.896; P = 0.00) for FTc before infusing volume load for predicting volume responsiveness. In the second stage of the study, PEEP did not have significant effects on FTc ( F2, 56 = 1.930, P = 0.155), whereas volume load had statistically significant effects on FTc ( F1, 28 ) = 9.381, P < 0.05). Moreover, FTc differed significantly different before and after fluid infusion ( P < 0.05). The area under the receiver operating characteristic curve for FTc in predicting volume responsiveness was 0.921, 0.805, and 0.719 when PEEP was 0, 5, and 10 cmH 2 O ( P < 0.05), respectively, and the cutoff value of FTc for diagnosing volume responsiveness was 323.42 milliseconds, 326.69 milliseconds, and 312.03 milliseconds, respectively. Conclusion: Corrected flow time in the common carotid artery can predict volume responsiveness under mechanical ventilation, and the predictive performance is not influenced by PEEP. Clinical Trial Registration Clinical register number: ChicTR2000029519.

Diffusion-Weighted Imaging Combined with Cervical Vascular Ultrasound in the Elderly Patients with Multiple Cerebral Infarction

Objective

This study is aimed at evaluating the diagnostic value of diffusion-weighted imaging combined with cervical vascular ultrasound in the elderly patients with multiple cerebral infarctions and at demonstrating whether the diagnostic value is affected by the history of diabetes.

Methods

From January 2020 to November 2021, the case data of 30 elderly patients with multiple cerebral infarction diagnosed in our hospital were included. Diffusion-weighted magnetic resonance imaging (DWI) and cervical vascular ultrasound (CAU) were performed, respectively. The diagnosis rates of the simple diffusion-weighted imaging group, the simple cervical vascular ultrasound group, and the diffusion-weighted imaging combined with cervical vascular ultrasound group were compared.

Results

The median onset time of 30 patients was 26.5 (4.75, 43.0) hours. There were 10 hyperacute patients and 20 acute patients. The proportion of diagnosable patients in the diffusion-weighted imaging group was 83.8% (25/30), which was lower than the proportion of diagnosable patients in the diffusion-weighted imaging combined with cervical vascular ultrasound group, which was 90% (27/30). The difference was statistically significant (χ² = 16.667; P < 0.001). The ratio of diagnosable patients in the cervical vascular ultrasound group alone was 66.7% (20/30), which was lower than 90% (27/30) in the diffusion-weighted imaging combined with cervical vascular ultrasound group. The difference was statistically significant (χ² = 6.7; P = 0.010). In the hyperacute phase, the proportion of diagnosable patients in the diffusion-weighted imaging combined with cervical vascular ultrasound group was higher than that in the diffusion-weighted imaging group alone (χ² = 5.833; P = 0.016) and the cervical vascular ultrasound group alone (χ² = 2.500; P = 0.004). In the acute phase, the proportion of diagnosable patients in the diffusion-weighted imaging combined with cervical vascular ultrasound group was also higher those that in the diffusion-weighted imaging group alone (χ² = 9.474; P = 0.002) and the cervical vascular ultrasound group alone (χ² = 3.158; P = 0.006). The diagnostic accuracy of diffusion-weighted imaging combined with cervical vascular ultrasound was not significantly different between patients with history of diabetes and without history of diabetes (χ² = 1.014; P = 0.314)

Conclusion

The combined application of diffusion-weighted imaging and cervical vascular ultrasound has important value in improving the diagnosis rate of multiple cerebral infarction in the elderly, regardless of diabetes history, and it is worthy of clinical application.

Long-Term Functionality Prediction for First Time Ischemic Middle Cerebral Artery Stroke Patients Receiving Conventional Medical Treatment

BACKGROUND

Middle cerebral artery (MCA) ischemic stroke poses a major threat to human beings and prompts intravenous thrombolytic and/or thrombectomy management remains the gold standard treatment. However, not all MCA stroke patients fit in the inclusion and exclusion criteria that many patients only receive conventional medical therapy. We attempt to seek the baseline parameters that can effectively predict patients' long-term functionality, as well as hypothesizing that the carotid duplex derived resistance/pulsatility index might be capable of fulfilling this purpose.

METHODS

The 741 MCA ischemic stroke patients have been retrospectively recruited for the project. Under the initial screening, matching the inclusion and exclusion criteria, there are 471 participants to be enrolled in the study. The patients' basic information, along with outcome assessments, pre-admission Barthel index and NIHSS score, and pre- and post-treatment mRS are recorded. All statistical analyses were performed using R for Windows (version 3.6.3). The significance level was set at P < 0.05 for all analyses.

RESULTS

Of the 471 patients, 239 participants show a net mRS improvement, whereas the other 232 show deterioration. Hyperlipidaemia, chronic kidney disease, and dementia are related to long-term functionality improvement. The multivariate logistic regression analysis shows that right common carotid artery (CCA) resistance index (RI) and ischemic heart disease play a significant role in favourable outcome functionality. The ROC and Youden Index models are formulated, and it shows that Barthel Index and the NIHSS are most significant in the outcome measurement group (AUC: 0.675, 0.653; cut-off point: 57.5, 3.5, respectively). The right-side CCA RI is the solely important outcome predictor for the baseline carotid duplex study (AUC: 0.5; cut-off point: 0.785).

CONCLUSION

The favourable long-term functionality of MCA ischemic stroke patients receiving conventional medical treatment seems to correlate fairly with pre-admission NIHSS and Barthel index scores. Underlying hyperlipidaemia, chronic kidney disease, and dementia are conversely associated with favourable long-term capability. Moreover, the value of CCA RI appears to significantly alter the long-term outcomes in this group of patients.

The Association Between Insomnia and Atherosclerosis: A Brief Report

AIM

The objective of the study was to clarify the occurrence of atherosclerosis in patients with insomnia.

METHODS

A total of 60 patients with insomnia and 58 patients in a control group were selected to measure blood glucose, blood lipids and other biochemical and physiological indicators. Brachial-ankle pulse wave velocity (baPWV) was measured to assess arterial stiffness, and color Doppler ultrasound was used to examine carotid artery intima-media thickness (CIMT) and plaque incidence. These indicators were used to determine the occurrence and degree of carotid atherosclerosis, and to compare the differences between the two groups.

RESULTS

While there was no significant difference in biochemical or physiological indicators between the two groups (P > 0.05), the baPWV, CIMT, and incidence of carotid plaque in the insomnia group were higher than the control group. In addition, the baPWV, CIMT, and incidence of carotid plaque in the chronic insomnia group were higher than that in the short-term insomnia group. Multiple linear regression analysis was carried out to analyze the effects of insomnia, systolic blood pressure, blood glucose, triglycerides, cholesterol, BMI, age and low-density lipoprotein on atherosclerosis. The results showed that increased CIMT was significantly correlated with insomnia in atherosclerosis group (R²=0.27 on the left, R²=0.37 on the right, P < 0.001).

CONCLUSION

Insomnia correlated with increased arterial stiffness and carotid atherosclerosis, and as the duration of insomnia prolongs, the correlation between them became more obvious.

Application Value of Rehabilitation Nursing in Patients with Stroke Based on the Theory of Interactive Standard: A Randomized Controlled Study

Objective

To explore the application value of rehabilitation nursing based on the theory of interactive standards in stroke patients.

Methods

A total of 120 stroke patients who were treated in our hospital from December 2018 to September 2020 were selected as the research objects, and the patients were divided into a control group (60 cases) and an observation group (60 cases) according to the random number table method. The control group used routine nursing care, and the observation group used interactive rehabilitation care based on the control group. The Barthel Index, National Institute of Health Stroke Scale (NIHSS) score, Specific Quality Of Life Scale (SS-QOL) score, rehabilitation standard rate, nursing satisfaction, improvement time of limb function, and compliance with rehabilitation exercise were compared between the two groups of patients.

Results

After intervention, the Barthel Index of the two groups increased, and the Barthel Index of the observation group was comparatively higher (P < 0.05); the NIHSS scores of the two groups of patients reduced, and the NIHSS scores of the observation group were significantly lower than those of the control group (P < 0.05); the SS-QOL scores of the two groups of patients improved, and the increase in SS-QOL scores in the observation group was found to be significantly higher than those in the control group (P < 0.05); the compliance rate was found to be in favor of the observation group (83.33 (50/60) vs 63.33 (38/60)) (χ² = 6.136, P˂0.05); the total satisfaction of nursing care of patients in the observation group was superior to the control group (96.67% vs 78.33%) (χ² = 9.219, P˂0.05); the limb function improvement time of the observation group was significantly shorter (P < 0.05); the observation group had significantly higher rehabilitation exercise compliance scores (P < 0.05).

Conclusion

The rehabilitation nursing based on the interactive standard theory can promote the stroke patients to complete the rehabilitation goals, improve the neurological and limb functions, and enhance the patients' daily living ability, quality of life, and nursing satisfaction, which is worthy of clinical promotion and application.

Carotid Phase-Contrast Magnetic Resonance before Treatment: 4D-Flow versus Standard 2D Imaging

The purpose of this study was to evaluate the level of agreement between flow/velocity data obtained from 2D-phase-contrast (PC) and 4D-flow in patients scheduled for treatment of carotid artery stenosis. Image acquisition was performed using a 1.5 T scanner. We compared mean flow rates, vessel areas, and peak velocities obtained during the acquisition with both techniques in 20 consecutive patients, 15 males and 5 females aged 69 ± 5 years (mean ± standard deviation). There was a good correlation between both techniques for the CCA flow (r = 0.65, p < 0.001), whereas for the ICA flow and ECA flow the correlation was only moderate (r = 0.4, p = 0.011 and r = 0.45, p = 0.003, respectively). Correlations of peak velocities between methods were good for CCA (r = 0.56, p < 0.001) and moderate for ECA (r = 0.41, p = 0.008). There was no correlation for ICA (r = 0.04, p = 0.805). Cross-sectional area values between methods showed no significant correlations for CCA (r = 0.18, p = 0.269), ICA (r = 0.1, p = 0.543), and ECA (r = 0.05, p = 0.767). Conclusion: the 4D-flow imaging provided a good correlation of CCA and a moderate correlation of ICA flow rates against 2D-PC, underestimating peak velocities and overestimating cross-sectional areas in all carotid segments.

Beta-2-Microglobulin is an Independent Risk Factor for Asymptomatic Carotid Atherosclerosis in Patients with Primary Aldosteronism

Aim: To identify the association between serum beta-2-microglobulin (B2M) or cystatin C (CysC) and asymptomatic carotid atherosclerosis in patients with primary aldosteronism (PA).

Methods: In this cross-sectional study, 265 subjects were enrolled, including 83 patients with PA, 91 with essential hypertension (EH), and 91 normotensive (NT) controls. B2M, CysC, plasma renin activity (PRA), and plasma aldosterone concentration (PAC) were measured, and the aldosterone-to-renin ratio (ARR) was calculated. Carotid intima-media thickness (cIMT), increased cIMT, and presence of carotid plaque or carotid stenosis ＜50% in the carotid artery were measuredvia ultrasonography to evaluate the degree of asymptomatic carotid atherosclerosis.

Results: CIMT increased in the NT, EH, and PA groups (0.60 (0.50, 0.80) mm vs. 0.80 (0.60, 1.00) mm vs. 0.90 (0.70, 1.10) mm,P＜0.01), so as the prevalence of increased cIMT and presence of carotid plaque (bothP＜0.05). The B2M and CysC levels exhibited the same trend (B2M: 1.60±0.34 mg/L, 1.80±0.41 mg/L, 1.98±0.64 mg/L,P＜0.05; CysC: 0.76±0.12 mg/L, 0.88±0.17 mg/L, 0.94±0.23 mg/L,P＜0.05). B2M, CysC, PAC, and ARR were all positively associated with cIMT (allP＜0.01) in the PA group. After adjusting for potential confounders, B2M, PAC, but not CysC or ARR were independently associated with increased cIMT and presence of carotid plaque and carotid stenosis ＜50%, respectively. The receiver operating characteristic (ROC) curve analysis revealed that B2M and PAC demonstrated significant predictive ability for increased cIMT and presence of carotid plaque and carotid stenosis ＜50%.

Conclusion: B2M is an independent risk factor for asymptomatic carotid atherosclerosis in patients with PA.

Vitamin K Supplementation for the Prevention of Cardiovascular Disease: Where Is the Evidence? A Systematic Review of Controlled Trials

Matrix gla protein (MGP) is an important vitamin K-dependent inhibitor of vascular calcification. High levels of uncarboxylated, dephosphorylated MGP have been associated with vascular calcification and are responsive to vitamin K treatment. In this systematic review, we summarize the available evidence examining whether vitamin K supplementation improves surrogate measures of cardiovascular disease including artery and valve calcification, atherosclerosis and artery stiffening. Data from controlled trials of adults were obtained by searching Ovid MEDLINE, Embase, the Cochrane Central Register of Controlled Trials and the Web of Science Core Collection. We identified nine randomized controlled trials for review, including trials of vitamin K1 or vitamin K2 supplementation, that assessed a surrogate measure of cardiovascular disease including arterial calcification, atherosclerosis or arterial stiffening. For each trial, the risk of bias was assessed applying Cochrane Collaboration methodology. The findings indicate that vitamin K does not consistently prevent progression of calcification, atherosclerosis or arterial stiffness. There may be some benefit in people with calcification at study entry. Studies were heterogenous, with relatively short follow-up and outcome measures were varied. While vitamin K supplementation clearly improves the carboxylation of dephosphoylated MGP, its role in mitigating vascular calcification is uncertain, based on current evidence.

Elevated serum sortilin is related to carotid plaque concomitant with calcification

Aim: To explore whether elevated serum sortilin was associated with calcified carotid plaque and ischemic stroke. Methods: A total of 171 patients with cardiovascular risk factors were enrolled. Ultrasonography was performed to evaluate calcified plaques and noncalcified plaques. Serum sortilin concentration was measured by ELISA. Results: Serum sortilin level was higher in patients with calcified carotid plaque and positively related to carotid plaque burden, but not with ischemic stroke during the follow-up. Multivariable logistic regression analysis revealed serum sortilin level was an independent determinant for calcified carotid plaque (p = 0.001). Receiving operating characteristic analysis showed an area under the curve of sortilin for carotid calcification was 0.759. Conclusion: Higher serum sortilin level was associated with carotid calcification and severe carotid plaque score.

Network Medicine: A Clinical Approach for Precision Medicine and Personalized Therapy in Coronary Heart Disease

Early identification of coronary atherosclerotic pathogenic mechanisms is useful for predicting the risk of coronary heart disease (CHD) and future cardiac events. Epigenome changes may clarify a significant fraction of this "missing hereditability", thus offering novel potential biomarkers for prevention and care of CHD. The rapidly growing disciplines of systems biology and network science are now poised to meet the fields of precision medicine and personalized therapy. Network medicine integrates standard clinical recording and non-invasive, advanced cardiac imaging tools with epigenetics into deep learning for in-depth CHD molecular phenotyping. This approach could potentially explore developing novel drugs from natural compounds (i.e. polyphenols, folic acid) and repurposing current drugs, such as statins and metformin. Several clinical trials have exploited epigenetic tags and epigenetic sensitive drugs both in primary and secondary prevention. Due to their stability in plasma and easiness of detection, many ongoing clinical trials are focused on the evaluation of circulating miRNAs (e.g. miR-8059 and miR-320a) in blood, in association with imaging parameters such as coronary calcifications and stenosis degree detected by coronary computed tomography angiography (CCTA), or functional parameters provided by FFR/CT and PET/CT. Although epigenetic modifications have also been prioritized through network based approaches, the whole set of molecular interactions (interactome) in CHD is still under investigation for primary prevention strategies.

Is There a Link Between Carotid Atherosclerosis and Idiopathic Overactive Bladder Among Women with Metabolic Syndrome?

Purpose

To evaluate the association between increased intima-media thickness (IMT) and atherosclerotic carotid plaque (CP) with idiopathic overactive bladder syndrome (OAB) in women with metabolic syndrome (MetS).

Methods

This is a cross-sectional study, which included consecutive women aged 40–75 years with MetS, seeking medical assistance at a reference center between April and December 2016. OAB-V8 questionnaire was used to estimate the prevalence of OAB symptoms, which were defined by a score ≥8 points. All patients underwent bilateral carotid artery ultrasound to assess IMT and CP. Atherosclerosis was defined by the identification of CP during ultrasound, which was diagnosed according to the Mannheim carotid intima-media thickness and plaque consensus.

Results

Forty-five women were prospectively included. Mean age was 60±9.3 years (range 40–75 ys). Eighteen (40%) patients were diagnosed with OAB. IMT in the general population was 0.72 mm (SD = 0.20). Overall prevalence of atherosclerosis, defined by the presence of the carotid artery plaque, was 51%. OAB prevalence among women with atherosclerosis was higher than in those without atherosclerosis (56.52% versus 22.73%), with a prevalence ratio of 2.49 (p=0.04). Additionally, OAB was associated with degree of carotid stenosis (p = 0.029).

Conclusion

In this cohort of female patients with MetS, there was an association between carotid atherosclerosis and OAB. Identification of carotid ultrasound abnormalities may lead to refined treatment decision-making among OAB patients.

Hypertension in Thyroid Disorders

Arterial hypertension represents a major global health concern; more than one fourth of the population is affected by high blood pressure. Albeit the underlying cause of the disease remains unclear in the vast majority of the cases, ~10% are of secondary origin. Endocrine disorders are common illnesses and some of them may lead to elevated blood pressure, among which thyroid diseases are of high prevalence and often overlooked, especially in mild cases. Overt and subclinical hyper- and hypothyroidism can both lead to (mostly mild) hypertension; however, the underlying mechanisms are only partially understood. The results of clinical studies are often controversial. During the past decades, some genetic mutations in the hypothalamus-pituitary-thyroid axis with cardiovascular consequences were revealed. Atherosclerotic changes resulting from lipid abnormalities due to thyroid dysfunction also affect the vasculature and can cause elevated blood pressure. The review gives a synopsis of our knowledge how thyroid hormone metabolism and functional thyroid diseases affect the cardiovascular system, their negative impact and causative role in the development of hypertension.