Neovascularization in carotid atherosclerotic plaques can be effectively evaluated by superb microvascular imaging (SMI): Initial experience

Novel ultrasound techniques in the identification of vulnerable plaques-an updated review of the literature

Atherosclerosis is an inflammatory disease partly mediated by lipoproteins. The rupture of vulnerable atherosclerotic plaques and thrombosis are major contributors to the development of acute cardiovascular events. Despite various advances in the treatment of atherosclerosis, there has been no satisfaction in the prevention and assessment of atherosclerotic vascular disease. The identification and classification of vulnerable plaques at an early stage as well as research of new treatments remain a challenge and the ultimate goal in the management of atherosclerosis and cardiovascular disease. The specific morphological features of vulnerable plaques, including intraplaque hemorrhage, large lipid necrotic cores, thin fibrous caps, inflammation, and neovascularisation, make it possible to identify and characterize plaques with a variety of invasive and non-invasive imaging techniques. Notably, the development of novel ultrasound techniques has introduced the traditional assessment of plaque echogenicity and luminal stenosis to a deeper assessment of plaque composition and the molecular field. This review will discuss the advantages and limitations of five currently available ultrasound imaging modalities for assessing plaque vulnerability, based on the biological characteristics of the vulnerable plaque, and their value in terms of clinical diagnosis, prognosis, and treatment efficacy assessment.

The Value of Superb Microvascular Imaging and Contrast-enhanced Ultrasound for the Evaluation of Neovascularization in Carotid Artery Plaques

OBJECTIVE

To compare the consistency between superb microvascular imaging (SMI) and contrast-enhanced ultrasound (CEUS) for the detection of neovascularization in carotid plaques of different thicknesses and to evaluate the applied value of these two methods for detecting neovascularization in carotid plaques in the clinic.

METHODS

A total of 45 patients with carotid artery plaques who were diagnosed in our hospital involving 76 hypoechoic plaques with a thickness ≥2.0 mm were selected. According to thickness, the plaques were divided into three groups: 2.0-2.5 mm, 2.5-3.0 mm and ≥3.0 mm. Each group underwent both SMI and CEUS, and two experienced sonographers (A and B) analyzed the ultrasound images to evaluate the neovascularization of carotid plaques. The amount of the neovascular signal was assessed using a semi-quantitative grading scale (vascularity grade: grade 0-3). SMI and CEUS were graded respectively according to the visual methods as follows: grade 0: no blood flow signal/enhancement within plaques; grade 1: a few blood flow signals/enhancement within plaques; grade 2: medium blood flow signals/enhancement within plaques; and grade 3: extensive blood flow signals/enhancement within plaques. Kappa consistency test was used to analyze the consistency of the grade of neovascularization in plaques between SMI with CEUS. Gamma rank correlation analysis was used to examine the correlation between neovascularization grade by SMI and CEUS in plaque and plaque thickness.

RESULTS

Of these patients, 14 had unilateral plaques and 31 had bilateral plaques. The two sonographers were highly consistent in terms of applying SMI and CEUS methods for diagnosing neovascularization in carotid plaques (Kappa values were 0.736 and 0.680>0). Consistency was found between SMI and CEUS by sonographers (sonographer A: Kappa=0.823; sonographer B: Kappa=0.842) in evaluating the neovascular grade in the carotid plaques. SMI and CEUS grades were positively correlated with plaque thickness (sonographer A: γ = 0.735 and 0.772; sonographer B: γ = 0.805 and 0.798).

CONCLUSION

Neovascularization in carotid plaques was successfully detected by SMI in a manner that concurred well with CEUS results. Our data indicate that both CEUS and SMI have high diagnostic value for assessing the neovascularization of plaques.

Detection of Carotid Atherosclerotic Intraplaque Neovascularization Using Superb Microvascular Imaging: A Meta-Analysis

OBJECTIVES

Although superb microvascular imaging (SMI) (Toshiba/Canon, Tokyo, Japan) has enabled routine characterization of intraplaque neovascularization (IPN) features in patients with carotid stenosis, no reports have been published on the multicenter and large sample size research in this aspect. The efficacy of SMI in detecting carotid IPN has not been concluded. This study aimed to assess the efficacy of SMI comparing with contrast-enhanced carotid ultrasonography (CEUS) in the detection of carotid IPN or pathologic evaluations of IPN correlated with a history of stroke or transient ischemic attack (TIA).

METHODS

Web of Science, Cochrane Library, PubMed, Embase, and Scopus were searched up to August 2020 to identify peer-reviewed human studies on the diagnostic accuracy of SMI in detecting IPN. For the selected study, the correlation coefficient R and Kappa index between SMI and CEUS in detecting IPN were calculated. The correlation coefficient R between SMI in identifying IPN and pathologic evaluations of IPN and the odds ratio of IPN detected by SMI and history of stroke or TIA were also extracted. The subgroup analysis was performed to indicate the source of heterogeneity.

RESULTS

Our search identified 11 reports enrolling a total of 605 carotid stenosis patients. Carotid IPN detected by SMI was significantly correlated with which detected by CEUS (R, 0.89; 95% CI, 0.80-0.94; P = .00, and Kappa index, 0.73; 95% CI, 0.67-0.80; P = .00). Notably, a significant correlation was observed in SMI in detecting IPN and pathologic evaluations of IPN (R, 0.52; 95% CI, 0.40-0.62; P = .00). The odds ratio of IPN detected by SMI and history of stroke or TIA was pooled summary with statistical significance (OR, 3.33; 95% CI, 1.78-6.23; P = .00). In subgroup analysis, lower heterogeneity was associated with the degree of carotid stenosis, patients from which country, and types of equipment.

CONCLUSIONS

SMI and CEUS display an excellent agreement in detecting carotid IPN. IPN detected by SMI shows high consistency with pathologic evaluations of IPN. Individuals with carotid IPN are more likely to develop stroke or TIA than those without carotid IPN.

Deep learning-based carotid plaque vulnerability classification with multicentre contrast-enhanced ultrasound video: a comparative diagnostic study

OBJECTIVES

The aim of this study was to evaluate the performance of deep learning-based detection and classification of carotid plaque (DL-DCCP) in carotid plaque contrast-enhanced ultrasound (CEUS).

METHODS AND ANALYSIS

A prospective multicentre study was conducted to assess vulnerability in patients with carotid plaque. Data from 547 potentially eligible patients were prospectively enrolled from 10 hospitals, and 205 patients with CEUS video were finally enrolled for analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effectiveness of DL-DCCP and two experienced radiologists who manually examined the CEUS video (RA-CEUS) in diagnosing and classifying carotid plaque vulnerability. To evaluate the influence of dynamic video input on the performance of the algorithm, a state-of-the-art deep convolutional neural network (CNN) model for static images (Xception) was compared with DL-DCCP for both training and holdout validation cohorts.

RESULTS

The AUCs of DL-DCCP were significantly better than those of the experienced radiologists for both the training and holdout validation cohorts (training, DL-DCCP vs RA-CEUS, AUC: 0.85 vs 0.69, p<0.01; holdout validation, DL-DCCP vs RA-CEUS, AUC: 0.87 vs 0.66, p<0.01), that is, also better than the best deep CNN model Xception we had performed, for both the training and holdout validation cohorts (training, DL-DCCP vs Xception, AUC:0.85 vs 0.82, p<0.01; holdout validation, DL-DCCP vs Xception, AUC: 0.87 vs 0.77, p<0.01).

CONCLUSION

DL-DCCP shows better overall performance in assessing the vulnerability of carotid atherosclerotic plaques than RA-CEUS. Moreover, with a more powerful network structure and better utilisation of video information, DL-DCCP provided greater diagnostic accuracy than a state-of-the-art static CNN model.

TRIAL REGISTRATION NUMBER

ChiCTR1900021846.

Superb Microvascular Imaging Ultrasound for Cervical Carotid Artery Stenosis for Prediction of the Development of Microembolic Signals on Transcranial Doppler during Carotid Exposure in Endarterectomy

Introduction

During exposure of the carotid arteries, embolism from the surgical site is recognized as a primary cause of neurological deficits or new cerebral ischemic lesions following carotid endarterectomy (CEA), and associations have been reported between histological neovascularization in the carotid plaque and both plaque vulnerability and the development of artery-to-artery embolism. Superb microvascular imaging (SMI) enables accurate visualization of neovessels in the carotid plaque without the use of intravenous contrast. This study aimed to determine whether preoperative SMI ultrasound for cervical carotid artery stenosis predicts the development of microembolic signals (MES) on transcranial Doppler (TCD) during exposure of the carotid arteries in CEA.

Methods

Preoperative cervical carotid artery SMI ultrasound followed by CEA under TCD monitoring of MES in the ipsilateral middle cerebral artery was conducted in 70 patients previously diagnosed with internal carotid artery stenosis (defined as ≥70%). First, observers visually identified intraplaque microvascular flow (IMVF) signals as moving enhancements located near the surface of the carotid plaque within the plaque on SMI ultrasonograms. Next, regions of interest (ROI) were manually placed at the identified IMVF signals (or at arbitrary places within the plaque when no IMVF signals were identified within the carotid plaque) and the carotid lumen, and time-intensity curves of the IMVF signal and lumen ROI were generated. Ten heartbeat cycles of both time-intensity curves were segmented into each heartbeat cycle based on gated electrocardiogram findings and averaged with respect to the IMVF signal and lumen ROI. The difference between the maximum and minimum intensities (ID) was calculated based on the averaged IMVF signal (ID_IMVF) and lumen (ID_l) curves. Finally, the ratio of ID_IMVF to ID_l was calculated.

Results

MES during exposure of the carotid arteries were detected in 17 patients (24%). The incidence of identification of IMVF signals was significantly greater in patients with MES (94%) than in those without (57%; p = 0.0067). The ID_IMVF/ID_l ratio was significantly greater in patients with MES (0.108 ± 0.120) than in those without (0.017 ± 0.042; p < 0.0001). The specificity and positive predictive value for the ID_IMVF/ID_l ratio for prediction of the development of MES were significantly higher than those for the identification of IMVF signals. Logistic regression analysis revealed that only the ID_IMVF/ID_l ratio was significantly associated with the development of MES (95% CI 101.1–3,628.9; p = 0.0048).

Conclusion

Preoperative cervical carotid artery SMI ultrasound predicts the development of MES on TCD during exposure of the carotid arteries in CEA.

Assessment of neovascularization of carotid artery atherosclerotic plaques using superb microvascular imaging: a comparison with contrast-enhanced ultrasound imaging and histology

Background

This study aimed to investigate the usefulness of superb microvascular imaging (SMI), a novel non-contrast-enhanced ultrasound technique, in characterizing neovessels within carotid atherosclerotic plaques through comparison with contrast-enhanced ultrasound (CEUS) and histology.

Methods

Patients with carotid plaque were recruited and underwent SMI and CEUS ultrasound imaging of the carotid arteries. The maximum plaque thickness, length, and stenosis of each plaque were measured. Grade of the neovessels was determined by SMI and CEUS, respectively. Grade 0 was defined as no blood flow signal/microbubbles within plaques; grade 1 was defined as moderate blood flow signals/microbubbles confined to the shoulder and/or adventitial side of the plaque; and grade 2 was defined as extensive intraplaque signals/microbubbles. Patients with symptomatic carotid stenosis (stenosis ≥50%) or asymptomatic carotid stenosis (stenosis ≥70%) underwent endarterectomy, and plaque specimens were subjected to immunohistochemical analysis of CD31 expression. The neovessels were quantified by histology. The agreement of SMI with CEUS and histology in characterizing neovessels was analyzed using weighted Kappa statistic and Spearman's correlation analyses.

Results

Seventy-eight patients (mean age: 67.3±8.9 years old, 63 males) were recruited. Of these patients, 52 (66.7%) had a unilateral plaque and 26 (33.3%) had bilateral plaques in the carotid arteries. For the 104 carotid plaques detected, the mean plaque thickness and length were 4.3±1.1 and 18.8±6.6 mm, respectively. The prevalence of <50%, 50-69%, and ≥70% stenosis was 43.3%, 24.0%, and 32.7%, respectively. Excellent agreement was found between SMI and CEUS (κ=0.825 at the plaque level; κ=0.820 at the patient level) in evaluating the neovessel grade within the carotid plaques. Of the 25 patients who underwent carotid endarterectomy, a strong correlation (r=0.660, P<0.001) was found between SMI and histology in the evaluation of intraplaque neovessels. SMI had excellent scan-rescan (κ=0.857), intra-reader (κ=0.810), and inter-reader (κ=0.754) agreement in the assessment of intraplaque neovessels.

Conclusions

The SMI technique is capable of reliably characterizing neovessels within carotid atherosclerotic plaques and demonstrates good to excellent agreement with histology and CEUS.

Advance ultrasound techniques for the assessment of plaque vulnerability in symptomatic and asymptomatic carotid stenosis: a multimodal ultrasound study

Background

Advanced carotid ultrasound techniques may be useful in characterizing plaque vulnerability, but comprehensive studies are still lacking. The aim of this study was to identify factors associated with vulnerable plaques using advanced ultrasound techniques.

Methods

This is a prospective observational study of patients with >50% internal carotid stenosis (ICA). All patients underwent conventional ultrasound, superb microvascular imaging (SMI) and shear wave elastography (SWE) examinations. Plaque size, echogenicity, stiffness and intraplaque neovascularization (IPN) were assessed and compared between symptomatic and asymptomatic groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of SWE and SMI of the vulnerable plaques.

Results

The final analysis included 123 patients (78.9% male; mean age, 66±8 years), 65 were enrolled in the symptomatic group, and 58 were enrolled in the asymptomatic group. The mean elasticity was 78.1±25.4 kPa for asymptomatic and 51.5±18.3 kPa for symptomatic plaques. Symptomatic plaques showed higher visual IPN grades on SMI than asymptomatic plaques (P<0.001). Multivariate regression analysis showed that plaque stiffness (PS) (OR 0.95, 95% CI, 0.919-0.974) and IPN level (OR 4.17, 95% CI, 2.008-8.664) were independently associated with symptomatic plaques. The combination of the two factors had a preferable accuracy to discriminate symptomatic plaques (AUC 0.89, 95% CI, 0.827-0.944).

Conclusions

Advanced carotid ultrasound techniques can identify plaque characteristics that are associated with ischemic events and may be potentially indicative of plaque vulnerability. These factors may ultimately be used in the clinical management of carotid stenosis.

Vascular imaging of atherosclerosis: Strengths and weaknesses

Atherosclerosis is an inflammatory disease that can lead to several complications such as ischemic heart disease, stroke, and peripheral vascular disease. Therefore, researchers and clinicians rely heavily on the use of imaging modalities to identify, and more recently, quantify the burden of atherosclerosis in the aorta, carotid arteries, coronary arteries, and peripheral vasculature. These imaging techniques vary in invasiveness, cost, resolution, radiation exposure, and presence of artifacts. Consequently, a detailed understanding of the risks and benefits of each technique is crucial prior to their introduction into routine cardiovascular screening. Additionally, recent research in the field of microvascular imaging has proven to be important in the field of atherosclerosis. Using techniques such as contrast-enhanced ultrasound and superb microvascular imaging, researchers have been able to detect blood vessels within a plaque lesion that may contribute to vulnerability and rupture. This paper will review the strengths and weaknesses of the various imaging techniques used to measure atherosclerotic burden. Furthermore, it will discuss the future of advanced imaging modalities as potential biomarkers for atherosclerosis.