Multimodal ultrasound parameters aided carotid plaque risk stratification in patients with asymptomatic carotid stenosis

Abstract

Background

Risk stratification of asymptomatic carotid plaque remains an issue in stroke prevention in clinical practice.

Purpose

To investigate whether a multimodal ultrasound (MMU) model would help plaque risk stratification in patients with asymptomatic carotid stenosis.

Material and Methods

A prospective study was conducted of symptomatic and asymptomatic patients with > 50% proximal internal carotid artery (ICA) stenosis. All patients underwent MMU examination. Multivariable regression analyses were performed to identify parameters associated with ischemic vascular events (IVE). These parameters were used to develop a scoring nomogram to assess the probability of IVE. We elaborated the diagnostic performance of the MMU nomogram using receiver operating characteristic (ROC) curves.

Results

From December 2018 to December 2019, 98 patients (75 men, mean age 67 ± 8 years) were included; 50 were symptomatic and 48 were asymptomatic. Multivariable regression analyses revealed that plaque surface morphology (PSM) (odds ratio [OR] 2.99, 95% confidence interval [CI] 1.26–7.12, P = 0.013), intraplaque neovascularization (IPN) grades (OR 3.23, 95% CI 1.77–5.89, P<0.001), and carotid stenosis degree (CSD) (OR 4.12, 95% CI 1.47–11.55, P = 0.007) were independently associated with IVE. For the nomogram, the area under the ROC curve was 0.85 (95% CI 0.77–0.92) and the Hosmer-Lemeshow test P value was 0.822.

Conclusions

In patients with proximal ICA > 50%, PSM, IPN grades, and CSD were independent variables associated with IVE. The MMU nomogram provided favorable value to risk stratification of IVE. Future large-scale studies with long-term follow-up are needed to validate these findings.

Keywords

Carotid plaque risk stratification multimodal ultrasound superb microvascular imaging nomogram

Introduction

Stroke is the leading cause of mortality and disability worldwide (1,2). Severe carotid stenosis is a strong indicator of stroke and stroke recurrence (3). In clinical practice, stroke caused by lumen narrowing can be effectively prevented by carotid endarterectomy. The selection of patients for carotid endarterectomy is based on the grade of carotid stenosis and the presence of ischemic vascular events (IVE) (4). However, the management of patients with asymptomatic carotid stenosis is still controversial until now.

In recent years, it is becoming clear that a significant proportion of strokes are caused by thrombo-emboli from vulnerable carotid plaques (5). Carotid multimodal ultrasound (MMU) is a non-invasive and widely used technique for the screening of carotid plaque. Research in carotid ultrasound has focused on identifying features that can determine the unstable plaque that may lead to an IVE (6,7). Therefore, carotid MMU should be used to identify high-risk carotid plaques in patients with asymptomatic carotid stenosis to help aid precise preventive intervention strategies (8).

Among various plaque features, carotid stenosis degree, especially severe stenosis, has been frequently reported to be one of the risk factors of IVE (9). Plaque thickness, echogenicity, surface morphology, and length of stenosis are also suggested as risk indicators of IVE (10,11). In contrast, intraplaque neovascularization (IPN) evaluated by superb microvascular imaging (SMI), a new ultrasound technique that enables the visualization of plaque neovessels without using contrast agent, has been relatively less investigated. The presence of plaque neovessels can lead to intraplaque hemorrhage and inflammation, which plays a key role in the loss of plaque stability (12). However, no evidence has demonstrated that IPN level on SMI is associated with IVE in patients with carotid stenosis until now. There have also been no useful clinical techniques for quantitative risk stratification of carotid plaque.

Nomograms are evidence-based quantitative tools for estimating the probability of clinical outcomes (13). The aim of the present study was to explore whether a nomogram incorporating plaque characteristics and lumen narrowing would improve the identification of high-risk carotid plaque in patients with asymptomatic carotid stenosis.

Material and Methods

Patients

This prospective study consecutively included patients with > 50% proximal internal carotid artery (ICA) stenosis confirmed by carotid ultrasound at Beijing Tiantan Hospital from December 2018 to December 2019. Patients underwent grayscale ultrasound, color Doppler flowing imaging (CDFI), spectral Doppler ultrasound, and SMI of the bilateral carotid arteries before carotid endarterectomy during hospitalization or at a routine outpatient ultrasonographic control for the asymptomatic carotid stenosis patients. The study was approved by the Institutional Review Board of Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China (IRB No. KY2019-113-01). Informed consent was obtained from all participants before inclusion.

Primary outcome

Patients who had already experienced ipsilateral acute stroke, transient ischemic attack (TIA), or amaurosis fugax within 30 days before study inclusion were categorized in the symptomatic plaque group. The TIA-Stroke Questionnaire (14) was used to verify whether there is a history of IVE and whether there was a sudden onset of focal neurologic symptoms. Stroke was defined as an acute neurologic event with focal symptoms and signs, lasting for 24 h or more, that were consistent with focal cerebral ischemia (15). Patients who had demonstrated no signs of IVE were categorized in the asymptomatic plaque group. All events were reviewed and confirmed by a neurologist blinded to the ultrasound findings.

Exclusion criteria were patients with severe stroke unable to complete ultrasound examination, patients diagnosed with other non-atherosclerotic carotid artery diseases, patients with serious systematic diseases, and poor ultrasound imaging quality.

Conventional ultrasound data

Conventional ultrasound images were collected using a Canon ultrasound system Aplio 900 (Canon Medical Systems, Otawara, Japan) equipped with a 7.5-MHz linear probe on bilateral carotid arteries for grayscale ultrasound, CDFI, and spectral Doppler ultrasound. With the patient in the supine position, the bilateral carotid arteries were scanned in longitudinal and transverse planes in standard carotid ultrasound. All images were independently analyzed by two vascular sonographers with 10 years of experience, blinded to patient risk factors and research neurologist findings.

ICA stenosis degree (CSD) was graded as 50%–69% and 70%–99%, and was determined based on peak-systolic and end-diastolic velocities according to ultrasound consensus (16). Carotid plaque was defined as a focal protrusion thickness >1.5 mm or as the appearance of focal wall thickness that is at least 50% greater than the surrounding vessel wall (17). Data were collected on maximal internal carotid plaque thickness (MICPT), plaque size (area), calcified plaque (yes or no), plaque echogenicity, plaque surface morphology (PSM) (smooth, irregular, and ulceration) and length of stenosis (18). Plaque risk parameters were analyzed in longitudinal planes according to consensus, and markers were chosen because they have shown a certain correlation with IVE according to previous studies (19,20). An image was frozen when the plane showing the thickest plaque, and the intimal-medial wall thickness (including the plaque) was measured as the MICPT (21). In the same image, a plaque was manually delineated and recorded as the plaque size. Plaque echogenicity was divided visually in grayscale ultrasound according to refined category as follows: type 1 = uniformly hypoechoic; type 2 = predominantly hypoechoic; type 3 = predominantly hyperechoic; and type 4 = uniformly hyperechoic (22). Ulceration plaque was defined as a concavity (at least 2 × 2 mm) in the plaque with the basal border echo weaker than the adjacent plaque surface, filled with blood flow signals on CDFI or SMI (23).

SMI data

After recording conventional ultrasound data, the ultrasound scanner was switched to monochrome SMI mode to show a double-view display of the plaque of interest in grayscale and SMI mode side-by-side. The SMI interest box was positioned around the whole plaque. Other SMI settings on the scanner were modified as follows: mechanical index = 1.5; frame rate = 50–60 fps; dynamic range = 55–60 dB; and velocity range of 1.0–2.0 cm/s. Plaques were first observed in the transverse plane and then in the longitudinal plane for 1 min, respectively. The video images were stored in the ultrasound equipment for later analysis. Moving enhancements were defined as intraplaque microvascular flow (IMVF). IMVF levels were categorized on a visual scale according to the category proposed by Zamani et al. (24) as follows: grade 0 = no IMVF or IMVF confined to the adjacent adventitia; grade 1 = moving IMVF confined to the adventitial side; grade 2 = moving IMVF at the plaque shoulder; grade 3 = IMVF moving to the plaque core (Supplemental figure S1); and grade 4 = extensive IMVF (24). SMI assessments were carried out in all plaques on two occasions, which were >2 weeks apart, to assess the intra- and inter-observer agreement using κ statistics.

Clinical information

Clinical information that are possibly associated with IVE were extracted from all patients by a well-trained research neurologist, who was blinded to ultrasound findings. A standard questionnaire was used to collect variables, including age, sex, body mass index (BMI), smoking and drinking status, hypertension, diabetes, hyperlipidemia, chronic heart disease, and use of medications.

Statistical analysis

Data are presented as the mean ± SD for continuous variables and counts with proportions for categorical variables. Non-parametric tests were used for continuous variables. Chi-square tests and Fisher’s exact tests were used for categorical variables. Included and adjusted predictors with univariable logistic P < 0.10 in the multivariable logistic model to determine the risk markers of IVE. Parameters were selected after checking for multicollinearity using a tolerance and variance inflation factor. Then, a nomogram was constructed using the multivariable analysis. For comparison, a conventional ultrasound prediction model was developed based on grayscale ultrasound risk markers alone. Receiver operating characteristic (ROC) curves were generated using various combination of parameters independently associated with IVE. Discrimination and calibration performance of the MMU nomogram was evaluated using the area under the ROC curve (AUC) and calibration curves. Clinical utility of the nomogram was analyzed by clinical decision curve. The predictive improvement of the nomogram was calculated by net reclassification index (NRI) and integrated discriminatory improvement (IDI). The Delong test was used for comparisons of different AUC.

R 3.6.3 (SPSS Inc., Chicago, IL, USA) software were used for data analyses. Glm, rms, ggplot2, and gROC packages (open source) were used in R analysis. All results were considered significant when P < 0.05.

Results

Clinical demographics

From the 117 patients with > 50% proximal ICA stenosis during the study period, four patients with severe stroke, three patients diagnosed with carotid artery dissection, two patients diagnosed with Takayasu’s arteritis, five patients with serious systematic diseases, and five patients with poor imaging quality were excluded. Finally, 98 patients, including 75 men (mean age = 65 ± 8 years) and 23 women (mean age = 66 ± 7 years), who had complete MMU data were eligible; of these participants, 50 had symptomatic plaques, whereas the rest had asymptomatic plaques. Baseline characteristics of patients and comparisons between the symptomatic and asymptomatic groups are listed in Table 1.

Table 1.

Demographics of asymptomatic and symptomatic patients included in the study.

Variables	Asymptomatic group (n = 48)	Symptomatic group (n = 50)	P
Demographics
Man sex	68.8 (33/48)	84 (42/50)	0.075
Age (years)	65 ± 8	66 ± 9	0.770
BMI (kg/m²)	24.15 ± 2.16	25.22 ± 3.79	0.076
Co-morbidities
SBP (mmHg)	141 ± 21	141 ± 20	0.934
DBP (mmHg)	85 ± 9	82 ± 11	0.270
Previous or current smoker	70.8 (34/48)	74 (37/50)	0.726
Previous or current drinker	68.8 (33/48)	72 (36/50)	0.725
Hypertension	77.1 (37/48)	70 (35/50)	0.427
Diabetes mellitus	29.2 (14/48)	24 (12/50)	0.563
Hyperlipidemia	25 (12/48)	50 (25/50)	0.011
Chronic heart disease	25 (12/48)	32 (16/50)	0.443
Medications
Antiplatelet	62.5 (30/48)	80 (40/50)	0.055
Antihypertension	75 (36/48)	62 (31/50)	0.167
Statin	72.9 (35/48)	84 (42/50)	0.181
Antidiabetic	29.2 (14/48)	28 (14/50)	0.898

Values are given as n (%) or mean ± SD.

BMI, body mass index; DBP, diastolic blood pressure; SBP, systolic blood pressure.

Plaque characteristics assessed by conventional ultrasound

The MICPT was in the range of 0.23–0.58 cm, plaque area 0.22–1.11 cm², and length of stenosis 1.03–3.88 cm. The proportions of plaque echogenicity for uniformly hypoechoic plaque, predominantly hypoechoic plaque, predominantly hyperechoic plaque, and uniformly hyperechoic plaque were 9.2% (9/98), 41.8% (41/98), 31.6% (31/98), and 17.4% (17/98), respectively. Plaque surface morphology was smooth in 43 of 98 (43.9%) plaques, irregular in 45 of 98 (45.9%) plaques, and ulceration in 10 of 98 (10.2%) plaques. Characteristics comparison between the symptomatic and asymptomatic plaques are summarized in Table 2.

Table 2.

Plaque characteristics using multimodal ultrasound between asymptomatic and symptomatic groups in the study.

Variables	Asymptomaticgroup (n = 48)	Symptomatic group (n = 50)	p
MICPT (cm)	0.37 ± 0.07	0.39 ± 0.06	0.548
Plaque area (cm²)	0.56 ± 0.23	0.65 ± 0.19	0.026
Length of stenosis (cm)	1.89 ± 0.56	1.99 ± 0.49	0.211
Plaque echogenicity			0.346
Uniformly hypoechoic	8.3 (4/48)	10 (5/50)
Predominantly hypoechoic	33.3 (16/48)	50 (25/50)
Predominantly hyperechoic	37.5 (18/48)	26 (13/50)
Uniformly hyperechoic	20.8 (10/48)	14 (7/50)
Plaque surface morphology			0.001
Smooth	62.5 (30/48)	26 (13/50)
Irregular	33.3 (16/48)	58 (29/50)
Ulceration	4.2 (2/48)	16 (8/50)
Plaque calcification	58.3 (28/48)	52 (26/50)	0.529
Carotid stenosis degree			<0.001
50%–69%	64.6 (31/48)	28 (14/50)
70%–99%	35.4 (17/48)	72 (36/50)
Intraplaque neovascularization level			<0.001
Grade 0	27.1 (13/48)	6 (3/50)
Grade 1	47.9 (23/48)	18 (9/50)
Grade 2	18.8 (9/48)	44 (22/50)
Grade 3	6.3 (3/48)	28 (14/50)
Grade 4	0 (0/48)	4 (2/50)

Values are given as n (%) or mean ± SD.

IPN assessed using SMI

SMI visualized IMVF signals in 82 (83.7%) of the 98 plaques. Sixteen plaques (16.3%) had no IMVF signals (grade 0), 32 (32.7%) plaques had signals confined to the adventitial side (grade 1), 31 (31.6%) plaques had signals at the plaque shoulder (grade 2), 17 (17.3%) plaques had signal moving to the plaque core (grade 3), and 2 (2%) plaques were found to have extensive IMVF signals (grade 4) on SMI.

IPN on SMI was significantly different between the symptomatic and asymptomatic groups (P = 0.006). Of the 16 non-neovascularization plaques, 3 (18.8%) had IVE. However, 47 of 82 (57.3%) neovascularization plaques had IVE. Significant differences were observed between the two groups with respect to the different grades of IMVF using SMI (P < 0.001). By grades of neovascularization, the risks of presenting with IVE were 18.8% (3/16) in grade 0, 28.1% (9/32) in grade 1, 70.9% in grade 2 (22/31), 82.4% (14/17) in grade 3, and 100% (2/2) in grade 4 patients.

Intra- and inter-observer agreement for assessment of IPN using the five-level category with SMI was favorable with a kappa coefficient of 0.748 and 0.802, respectively, between the two vascular sonographers.

Univariable and multivariable analysis of IVE

In the univariable logistic regression analyses, we observed that the following parameters indicate the presence of IVE: sex; BMI; hyperlipidemia; use of antiplatelet drugs; plaque area; PSM; CSD; and IPN grades on SMI. The remaining factors were not significantly associated with symptomatic plaque. Hyperlipidemia was excluded in the multivariable model for showing significant multicollinearity. The difference in antiplatelet drug use between the symptomatic and asymptomatic groups, although P = 0.058 < 0.10, was not clinically meaningful (percentages of antiplatelet drug use in symptomatic and asymptomatic group were 80% and 62.5%, respectively).

When applying the including parameters to the multivariable regression analyses, PSM (odds ratio [OR] = 2.99, 95% confidence interval [CI] = 1.26–7.12, P = 0.013), CSD (OR = 4.12, 95% CI = 1.47–11.55, P = 0.007), and IPN grades on SMI (OR = 3.23, 95% CI = 1.77–5.89, P < 0.001) were identified as independent variables associated with IVE (Table 3). This association remained after adjusting for sex, BMI, and plaque area.

Table 3.

Multivariable logistic regression analyses for investigating the correlations of ultrasound parameters and ischemic vascular events.

	Unadjusted model*			Adjusted model^†
Variables	OR	95% CI	P	OR	95% CI	P
PSM	2.99	1.26–7.12	0.013	3.02	1.23–7.45	0.016
CSD	4.12	1.47–11.55	0.007	4.48	1.51–13.33	0.007
IPN level	3.23	1.77–5.89	<0.001	3.06	1.65–5.66	<0.001

*Unadjusted for any variables.

^†Adjusted for sex, BMI, and plaque area.

BMI, body mass index; CI, confidence interval; CSD, carotid stenosis degree; IPN, intraplaque neovascularization; OR, odds ratio; PSM, plaque surface morphology.

ROC analysis of MMU parameters in identifying symptomatic plaque

The accuracy of differentiating symptomatic plaques from asymptomatic ones was evaluated using different combinations of parameters associated with symptomatic plaques (Fig. 1): ROC curve of PSM plus CSD, IPN grades plus PSM, IPN grades plus CSD, and IPN grades plus PSM and CSD. The combination of all three factors yielded the best discrimination power to identify symptomatic plaques (AUC = 0.85, 95% CI = 0.77–0.92, P < 0.001).

Fig. 1.

ROC curve analysis with accuracy of different ultrasound parameters in identifying symptomatic plaque. The accuracy of identify symptomatic plaque was measured using different combination of parameters: PSM plus CSD (blue line), IPN grades plus PSM (green line), IPN grades plus CSD (red line), and IPN grades plus PSM and CSD (purple line). CSD, carotid stenosis degree; IPN, intraplaque neovascularization; PSM, plaque surface morphology; ROC, receiver operating characteristic.

Nomogram of MMU for symptomatic plaque probability

We constructed a preliminary MMU nomogram that included the three parameters (Fig. 2a). ROC analysis showed good discrimination ability of the nomogram with an AUC of 0.85 (95% CI = 0.77–0.92). The calibration curve (Fig. 2b) and Hosmer-Lemeshow test of the nomogram showed good calibration (P = 0.822) in the internal validation datasets. Therefore, our nomogram performed well in our derivation sample.

Fig. 2.

Nomogram for MMU parameters of symptomatic plaque risk and its discrimination performance. (a) Using a nomogram, find the position of each parameter on the corresponding axis, draw a vertical line to the points axis for the number of points, add the points from all of the parameters, and draw a line from the total points axis to determine the symptomatic plaque risk at the lower line of the nomogram. (b) Calibration curves showed the calibration of MMU model according to the consistency between the predicted probabilities of symptomatic plaque and observed outcomes of symptomatic plaque. The nomogram showed good agreement on the calibration curves. (c) DCA of conventional ultrasound model and MMU nomogram for symptomatic plaque. Decision curves for two risk models for plaque status (symptomatic and asymptomatic plaques). The vertical axis displayed standardized net benefit. The two horizontal axes revealed the correspondence between risk threshold and cost:benefit ratio. The DCA curves showed that using the MMU nomogram (red curve) derived in our study, if the threshold probability is between 0 and 0.78, to predict symptomatic plaque yielded a better benefit than the conventional ultrasound model (blue curve). CSD, carotid stenosis degree; DCA, decision curve analysis; IPN grades, intraplaque neovascularization grades on SMI; MMU, multimodal ultrasound; PSM, plaque surface morphology; SMI, superb microvascular imaging.

Comparison between MMU nomogram and conventional ultrasound model

The discrimination ability of the MMU nomogram was better than that of the conventional ultrasound model (AUC = 0.85 vs. 0.76, P = 0.025). Further analysis showed that the discriminatory power and risk reclassification of MMU nomogram appeared to be substantially better in terms of NRI and IDI compared with the conventional ultrasound model (Supplemental Table S1).

Decision curve analysis (DCA) (25) indicated that the MMU nomogram had a higher overall net benefit than the conventional ultrasound model to predict plaque status when the threshold probability for a participant was in the range of 0–0.78. The nomogram can bring more benefit than either a treat-all or treat-none approach (Fig. 2c).

Discussion

Our main results were as follows. First, we found that MMU parameters incorporating plaque surface morphology (OR = 2.99, 95% CI = 1.26–7.12, P = 0.013), carotid stenosis degree (OR = 4.12, 95% CI = 1.47–11.55, P = 0.007), and intraplaque neovascularization grades (OR = 3.23, 95% CI = 1.77–5.89, P < 0.001) were independent variables associated with ischemic vascular events in patients with ICA stenosis. Second, our MMU nomogram showed better discrimination ability in identifying symptomatic plaque than the conventional ultrasound model (AUC = 0.85 and 0.76, respectively; P = 0.025). These findings indicated that using MMU combined with nomogram scoring system for stroke risk stratification may provide a more convenient and efficient tool.

Irregular plaque morphology, especially the presence of ulceration, indicates vulnerable plaques (26). Plaque ulceration was associated with intraplaque hemorrhage, large lipid core, less fibrous, and decreased stability (27). Kuk et al. (28) reported a total plaque ulceration volume > 5 mm³ on carotid 3D ultrasound had a significantly (P = 0.009) higher risk of IVE or death. Carotid stenosis is a well-known marker of plaque destabilization. Elevated shear stress caused by carotid stenosis can result in a certain activation of biological processes, e.g. intraplaque inflammation, which may indirectly contribute to plaque rupture (29).

IPN is associated with plaque activity, which increases the risk of intraplaque hemorrhage, inflammation, and plaque rupture. In 2018, guidelines from the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) recommended that contrast-enhanced ultrasound (CEUS) can be useful for the assessment of carotid plaque neovascularization which suggests plaque vulnerability (31). A recent study reported that CEUS had a sensitivity of 87.1%, a specificity of 58.3%, and an AUC of 72.7% in the diagnosis of vulnerable carotid plaque compared with histology, which indicated that CEUS was an effective modality for the evaluation of plaque instability (32). Oura et al. (33) reported that SMI had a good consistency with CEUS in visualizing IPN. However, CEUS is a complex, minimally invasive, enhancement ultrasound technique requiring a contrast agent; thus, CEUS cannot be used as a screening tool for plaque stability. SMI was a new ultrasound technique which enables the visualization of IPN without using contrast agent. However, evidence linking IPN grades and IVE is insufficient at present (30). We confirmed that IPN grades identified by SMI were higher in patients with IVE history than those without IVE history (P < 0.001). This indicates the visualized IPN grades may be an important marker for the risk stratification of carotid plaques.

Recently, nomograms have attracted great interest of many researchers for predicting clinical outcomes with quantitative clinical and imaging factors (34). A nomogram incorporating CSD, T1-SIR, and T2-SIR imaging of carotid plaque and surgical procedures had an AUC of 0.79 for the preoperative prediction of new ischemic brain lesions in patients with carotid stenosis after surgery (35). To the best of our knowledge, systematically investigating the discrimination performance of different combinations of MMU parameters using nomograms for carotid plaque stability have not previously been well established in the literature.

To offer a feasible tool for clinical practice, we constructed a preliminary MMU nomogram that includes PSM, CSD, and IPN grades based on multivariable logistic analysis. Our nomogram showed a better discriminatory power than the conventional ultrasound model (AUC = 0.85 and 0.76, respectively). The addition of IPN grades to conventional ultrasound model significantly increased the NRI and IDI and revealed that IPN grades could be a useful marker for plaque risk stratification. The DCA curves illustrated that the MMU nomogram could increase the recognition ability of high-risk carotid plaques. Therefore, our MMU nomogram may serve as a reliable and easy-to-use tool for carotid plaque risk stratification in patients with asymptomatic carotid stenosis.

The present study has some limitations. First, this was a single-center study and there were no carotid ultrasound data of participants before the occurrence of IVE. The MMU evidence would have been more powerful with a multicenter and long observation time study. Second, the plaque we chose was the largest one of ICA stenosis; we did not investigate information about the other plaques. Third, in some calcified plaques, it can be difficult to differentiate microvessel signals from plaque calcification signals on monochrome SMI mode. The development of a color SMI mode will improve the accuracy of the examination. Finally, we validated our MMU nomogram only by internal samples; further large-scale external studies are needed to validate its predictive value.

In conclusion, MMU parameters including plaque surface morphology, intraplaque neovascularization grades, and carotid stenosis degree may be useful in the carotid plaque risk stratification of patients with asymptomatic carotid stenosis. An easy-to-use MMU nomogram based on these parameters was constructed for assessing the probability of ischemic vascular events in similar patients population.

Supplemental Material

sj-pdf-1-acr-10.1177_0284185121989189 - Supplemental material for Multimodal ultrasound parameters aided carotid plaque risk stratification in patients with asymptomatic carotid stenosis

Supplemental material, sj-pdf-1-acr-10.1177_0284185121989189 for Multimodal ultrasound parameters aided carotid plaque risk stratification in patients with asymptomatic carotid stenosis by Yi Li, Shuai Zheng, Jinghan Zhang, Fumin Wang and Wen He in Acta Radiologica

Footnotes

Acknowledgements

We acknowledge all the co-authors for their hard work in this study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Natural Science Foundation of China (ID 8173000716).

ORCID iD

Wen He

Supplemental Material

Supplemental material for this article is available online.

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