nach oben

Erschienen in:

Open Access 01.04.2022 | Review

Evaluation of Intima-Media Thickness and Arterial Stiffness as Early Ultrasound Biomarkers of Carotid Artery Atherosclerosis

verfasst von: Verónica Fernández-Alvarez, Miriam Linares Sánchez, Fernando López Alvarez, Carlos Suárez Nieto, Antti A. Mäkitie, Kerry D. Olsen, Alfio Ferlito

Erschienen in: Cardiology and Therapy | Ausgabe 2/2022

Abstract

Carotid atherosclerosis is a major and potentially preventable cause of ischemic stroke. It begins early in life and progresses silently over the years. Identification of individuals with subclinical atherosclerosis is needed to initiate early aggressive vascular prevention. Although carotid plaque appears to be a powerful predictor of cardiovascular risk, carotid intima-media thickness (CIMT) and arterial stiffness can be detected at the initial phases and, therefore, they are considered important new biomarkers of carotid atherosclerosis. There is a well-documented association between CIMT and cerebrovascular events. CIMT provides a reliable marker in young people, in whom plaque formation or calcification is not established. However, the usefulness of CIMT measurement in the improvement of risk cardiovascular models is still controversial. Carotid stiffness is also significantly associated with ischemic stroke. Carotid stiffness adds value to the existing risk prediction based on Framingham risk factors, particularly individuals at intermediate cardiovascular risk. Carotid ultrasound is used to assess carotid atherosclerosis. During the last decade, automated techniques for sophisticated analysis of vascular mechanics have evolved, such as speckle tracking, and new methods based on deep learning have been proposed with promising outcomes. Additional research is needed to investigate the imaging-based cardiovascular risk prediction of CIMT and stiffness.

This article was written by members and invitees of the International Head and Neck ScientificGroup (www.IHNSG.com).

Key Summary Points

Subclinical carotid atherosclerosis is an early marker of atherosclerosis disease and its timely recognition is necessary for a prompt primary prevention.
carotid intima-media thickness (CIMT) and arterial stiffness are strong predictors of stroke and cardiovascular events. Recent studies showed that increased CIMT and arterial stiffness are noninvasive biomarkers of atherosclerotic disease, even in the asymptomatic stage.
Several methods for assessing CIMT and arterial stiffness have been developed. Speckle tracking ultrasound and new technological images based on automated measurements and artificial intelligence are evolving in this setting.
Current primary prevention guidelines for cardiovascular disease determine risk stratification by using clinical risk scores. Nonetheless, the current data are rather limited regarding the value of cardiovascular risk scores associated with CIMT and arterial stiffness as biomarkers of subclinical atherosclerosis.
CIMT and arterial stiffness might improve the cardiovascular risk stratification in asymptomatic patients.

Introduction

Worldwide, stroke is a leading cause of death and disability. According to the 2019 Global Burden of Disease Stroke Statistics, ischemic stroke affected an estimated 77.2 million people [1] and caused 2.7 million deaths each year [2].

Carotid atherosclerosis is a major and potentially preventable cause of cerebral ischemic events, accounting for 15–20% of all ischemic strokes [3, 4]. Atherosclerosis begins early in life and remains latent for a long time before the formation of atherosclerotic plaques [5, 6]. Identification of individuals with subclinical atherosclerosis is needed to initiate early aggressive vascular disease prevention [7, 8]. This has led to an increasing interest in finding new markers for carotid atherosclerosis. Carotid intima-media thickness (CIMT) and arterial stiffness changes can be recognized early and are thus considered important markers of future severe atherosclerosis [5, 9]. Carotid atherosclerotic plaques represent later stages of disease than CIMT and arterial stiffness [10].

Carotid ultrasound is a widely used noninvasive technique for measurement of early structural changes in the carotid artery such as CIMT and arterial stiffness [8, 10]. Ultrasound imaging enables practitioners to predict future cerebrovascular events and thus stratify patients into different risk groups. Subjects with low risk should reduce their risk factors; high-risk subjects are also given medical therapy [11]. These biomarkers seem to be best applicable in individuals with intermediate risk in order to readjust cardiovascular risk. Standardization of measurements is necessary to detect subclinical carotid atherosclerosis.

Consequently, the purpose of the present review is to identify the role of CIMT and carotid artery stiffness as biomarkers of subclinical carotid atherosclerosis and their clinical implications in improving the cardiovascular risk stratification.

A PubMed search was performed using the string “intima-media thickness OR arterial stiffness AND cardiovascular risk”. English-language articles on carotid ultrasound atherosclerosis were reviewed in detail.

Compliance with Ethics Guidelines

This article is based on previously conducted studies and does not contain any studies with human participants or animals performed by any of the authors.

Historical Perspective

Carotid atherosclerosis has been conventionally assessed by the degree of stenosis and surface irregularities in the artery. Other biomarkers have been suggested as valuable surrogates for future significant carotid disease.

In 1986, Pignoli et al. documented the first in vitro results investigating arterial wall thickness. They demonstrated a significant association between the intima-media thickness (IMT) measured on histological study of the CCA (common carotid artery) and the distance between two parallel echogenic lines found on ultrasound studies using B-mode imaging. The authors concluded that B-mode ultrasound represented a useful tool for the measurement of CIMT of in vivo human arteries [12].

Persson et al. used B-mode ultrasound for quantification of early (thickening of the intima-media complex) and late (plaque) atherosclerosis in the carotid and the femoral arteries. They demonstrated that IMT measurement with B-mode ultrasound was highly reproducible and allowed for accurate intra-observer and inter-observer differences [13].

In 1982, Kawasaki et al. measured the stiffness of the CCA wall using an ultrasound system. The stiffness parameter was the β-stiffness index, which expressed the relationship of stress strain on the artery. They found higher values of β-stiffness index in a group of patients with stroke compared with a healthy group. They confirmed the usefulness of carotid stiffness measurements from an echo system as an indirect diagnostic method of carotid arteriosclerosis [14].

During the past decade, further automated techniques have evolved. Clinical investigation of circumferential and longitudinal mechanics of the carotid wall better identified early local vascular stiffening [15]. The presence of a well-defined motion pattern was shown in the carotid artery using B-mode echo-tracking ultrasound images [13, 16‐19].

Carotid Ultrasound Methodology

Several studies suggest that carotid artery B-mode ultrasound imaging is safe, noninvasive, and relatively inexpensive. This permits an assessment of subclinical carotid atherosclerosis [20‐22] and could improve risk stratification for cardiovascular disease (CVD) [23‐25].

In 2012, the Mannheim Carotid Intima-Media Thickness and Plaque Consensus published the last update guidelines for CIMT measurement [20]. CIMT is observed as a double line pattern visualized between the intimal-luminal and the medial-adventitial interfaces of the carotid wall in a longitudinal view by B-mode ultrasound (Fig. 1). CIMT should be measured near the carotid bifurcation in a region that is free of plaque usually found in a segment of the distal CCA. The arterial wall should be assessed in a lateral probe position with an insonification angle of 90° to acquire good-quality images. CIMT is measured along a 10 mm length, preferably on the posterior wall of the CCA at least 5 mm below its termination to avoid inter-individual variability. Semiautomated reading software provides accurate measurements of CIMT. Manual reading demonstrates a higher reader-subjectivity compared to automatic or semiautomatic measurement software. Moreover, automated systems can perform 150 measurements on a 10-mm segment of CCA instantaneously [20].

Many invasive and noninvasive techniques to measure arterial stiffness have been described (Table 1) [9, 26, 27]. A classic method to assess arterial stiffness is the carotid-femoral pulse-wave velocity (PWV). This is based on pulse pressure and its waveform and estimates the propagation speed of the arterial pulse wave. It is measured directly, using the foot-to-foot velocity method from various waveforms obtained, transcutaneously at the right CCA and the right femoral artery. PWV is calculated as the ratio of the distance between two measurement points divided by the time required for the pressure wave to travel this distance. To date, the measurement of PWV is generally accepted as the most simple, noninvasive, robust, and reproducible method to determine arterial stiffness [28]. Other classic methods such as distensibility, compliance, elastic modulus, and β-stiffness index are based upon the assessment of diameter and volume change during the cardiac cycle for the corresponding change in arterial pressure [19, 29].

Table 1

Definitions, formulae, and units of the different measurement parameters of arterial stiffness

Parameter	Formula	Units	Description
Arterial compliance	ΔD/ΔP	cm²/mmHg	Absolute diameter change for a given pressure step at fixed vessel length
Arterial distensibility	ΔD/ΔP × D	mmHg⁻¹	Relative diameter change for a pressure increment; the inverse of elastic modulus
Pulse wave velocity	Distance/Δt	m/s	Speed of travel of the pulse along an arterial segment
Elastic modulus	ΔP × D/ΔD	mmHg	Pressure step required for theoretical 100% increase in volume
Young’s modulus	ΔP × D/(ΔD × h)	mmHg/cm	Elastic modulus per unit area; the pressure step per square centimeter required for resting length
β-stiffness index	Ln (Ps/Pd)/[(Ds − Dd)/Dd]	Nondimensional	Ratio of logarithm (systolic/diastolic pressures) to (relative change in diameter)
Strain	ΔL/L1 = (L2 − L1)/L1	%	Deformation (proportion between the change of length and original length of the vessel)
Strain rate	ε/s	s⁻¹	Amount of strain accumulated in a time interval

D diameter, P pressure, t time, h height, Ln logarithm, Ps systolic pressure, Pd diastolic pressure, L length, ε strain

Recently, new methods for assessing vascular tissue motion and deformation (strain) during the cardiac cycle have been developed using speckle tracking ultrasound (Fig. 2). The analysis of vascular wall motion is performed with short- and long-axis views of the carotid artery using conventional 2D grayscale echocardiography combined with a stable electrocardiographic (ECG) recording. The technique identifies acoustic tissue markers, the speckles, in a 2D grayscale image and tracks these speckles frame by frame during the cardiac cycle and calculates the motion and deformation of the carotid wall [5, 19, 30]. Parameters of arterial mechanics, including displacement, velocity, strain, and strain rate, can be measured. Speckle tracking strain is relatively angle independent and analyzes the vascular deformation patterns by longitudinal, radial, and circumferential directions. Nevertheless, circumferential analysis is the one typically performed, including strain and strain rate determinations. This is a useful technique in the evaluation of new elastic properties of vascular walls [15, 31].

Reference Values

Obtaining accurate reference values requires specific measurement protocols to be utilized on a large population. As a result of a lack of a standardized method for image acquisition, there are differences found in CIMT and arterial stiffness values in healthy populations from different countries [7, 11, 20, 32].

Therefore, there are two main pathways for determining normal CIMT values: the utilization of a fixed cutoff value or a percentile distribution. A value of 0.9 mm is a cutoff in the European Society of Cardiology (ESC) guidelines [33] while a value above the 75th percentile of a reference population is recommended as a threshold by the American Society of Echocardiography [34] (Fig. 3). In a recent systematic review from The Lancet Global Health, Song et al. reported that in 2020, approximately 28% of individuals aged 30–79 years in the general population had an abnormal CIMT of 1.0 mm and above, implying this effect applies to just over one billion people [6].

Many methods have been studied to quantify arterial stiffness, also with a variability in the measurement approach and values obtained [14, 30‐32, 35‐42]. Currently, normal and reference values for PWV have been defined in the Caucasian population by “The Reference Values for Arterial Stiffness Collaboration” [41]. Table 2 summarizes the main values provided from a literature survey.

Table 2

Mean carotid stiffness values with the different measurement parameters

Parameter	Author (study)	n	Age (years)	Value mean (SD)	Unit
Elastic modulus	Kawasaki et al. [14]	70	20–39	0.7	Dynes ×10 ⁻⁶/cm²
	Liao et al. (ARIC) [35]	6992	56	124.0	kPa
	Yang et al. (ARIC) [36]	10,407	56	153.0 (65.0)	kPa
Arterial distensibility	Van Sloten et al. (HOORN) [37]	579	67	11.2 (4.2)	10⁻³/kPa
	Gepner et al.(MESA) [32]	389	59	3.2 (1.3)	10⁻³ mmHg⁻¹
	Mattace-Raso et al. (Rotterdam) [38]	2265	71	10.6 (4.4)	10⁻³/kPa
	Yang et al. (ARIC) [36]	10,407	56	1.5 (0.6)	% kPa
Arterial compliance	Laurent et al. [39]	39	50	8.7	m² × kPa ⁻¹ × 10 ⁻⁷
	Yang et al. (ARIC) [36]	10,407	56	7.7 (2.8)	Mm²/kPa
	Van Sloten et al. (HOORN) [37]	579	67	0.5 (0.2)	Mm²/kPa
Young’s modulus	Liao et al. (ARIC) [35]	6992	56	678.0	kPa
	Yang et al. (ARIC) [36]	10,407	56	895.0 (422.0)	kPa
	Gepner et al. (MESA) [32]	389	59	1526.0 (780.0)	mmHg
	Van Sloten et al. (HOORN) [37]	579	67	980.0 (460.0)	kPa
PWV	Mattace-Raso et al. (Rotterdam) [38]	2835	71	13.3 (2.9)	m/s
	Yang et al. (ARIC) [36]	100	44	8.3	m/s
	Van Sloten et al. (HOORN) [37]	579	67	10.0 (3.5)	m/s
	Wei et al. (Chinese community) [40]	583	56	8.4 (1.8)	m/s
	Mattace-Raso et al. (Arterial Stiffness Collaboration) [41]	11,092	50	7.4 female	m/s
	Mattace-Raso et al. (Arterial Stiffness Collaboration) [41]	11,092	50	8.2 male	m/s
Stiffness index	Kawasaki et al. [14]	70	6–81	4.3–11.3	Dimensionless
	Liao et al. (ARIC) [35]	6992	56	11.8	Dimensionless
	Yang et al. (ARIC) [36]	10,407	56	0.1	Dimensionless
	Wei et al. (Chinese community) [40]	583	56	15.5 (10.2)	Dimensionless
Circumferential strain	Yang et al. (ARIC) [36]	10,407	56	5.1 (1.6)	%
	Catalano et al. [30]	47	57	3.6 (2.0)	%
	Park et al. [42]	1057	53	3.3 (1.3)	%

CIMT and Arterial Stiffness as Early Biomarkers of Carotid Atherosclerosis and Stroke

The measurement of CIMT by ultrasonography remains a strong predictor of CVD in various populations [24, 43‐45]. Increased CIMT has also been associated with diabetes [46, 47], chronic kidney disease [48], subclinical hypothyroidism [49], rheumatic disease [50], low serum vitamin D [51], peripheral artery disease [52], HIV-positive persons [53], long-term exposure to particulate air pollution [54], and radiotherapy (RT) [55]. Toprak et al. found in irradiated patients as soon as 6 weeks after RT a new plaque formation and increased CIMT compared to controls (0.68 ± 0.11 versus 0.87 ± 0.16, p < 0.001) [56]. In a traditional meta-analysis, patients treated with statins showed a significant benefit with a reduced mean CIMT of − 0.17 mm compared with the “no statin groups” (95% CI − 0.22 to − 0.12, p < 0.001) [57].

There is a well-documented association between CIMT and cerebrovascular events [7]. Several longitudinal studies have validated the relationship between finding an abnormal CIMT and risk of stroke. Van den Oord et al. reported in their meta-analysis that a 1-SD increase in CCA-CIMT increases the risk of stroke by 31% [7]. Kumar et al. suggested a strong association between increased CCA-IMT with risk of ischemic stroke as compared to control subjects (1.46, 95% CI 0.90–2.02) [58]. Sun et al. demonstrated that an SD increase in mean CIMT was positively associated with the risk of first ischemic stroke (1.10, 95% CI 1.01–1.20) [59]. Silent brain ischemic events in stroke-free individuals were also associated with increased CIMT [60]. A total of 13 follow-up studies showed a significant association between CIMT with the onset of a stroke (Table 3) [61‐73]. In accordance with these studies, CIMT can be used as a diagnostic marker for predicting the risk of future stroke events [58, 74].

Table 3

Summary of the studies reporting the association of CIMT with future stroke

Author (study)	n	Age (years)	Mean CIMT (SD)	FU (years)	Stroke	Stroke HR (95% CI)
O’Leary et al. (CHS) [61]	4476	72	1.03 (0.20)	6.2	NR	1.36 (1.25–2.28)
Chambless et al. (ARIC) [62]	14,214	45–64	0.84 (0.40) male	7.2	199	1.21 (1.05–1.39) male
Chambless et al. (ARIC) [62]	14,214	45–64	0.81 (0.30) female	7.2	199	1.36 (1.16–1.59) female
Hollander et al. (Rotterdam) [63]	6913	69	0.80 (0.16)	6.1	378	1.28 (1.15–1.44)
Lorenz et al. (CAPS) [64]	5056	50	0.71 (0.17) right	4.2	107	1.11 (0.97–1.28)
Lorenz et al. (CAPS) [64]	5056	50	0.74 (0.20) left	4.2	107	1.11 (0.97–1.28)
Price et al. (EAS) [65]	1007	69	0.82 (0.10)	12.0	65	1.59 (1.07–2.37)*
Prabhakaran et al. (NOMAS) [66]	1118	68	0.65 (0.15)	2.7	20	1.60 (0.80–3.20)*
Folsom et al. (MESA) [67]	6698	45–84	0.87 (0.19)	3.9	59	1.40 (1.20–1.80)*
Polak et al. (FHS) [68]	2965	58	0.66 (0.15)	7.2	74	1.13 (1.02–1.24)*
Anderson et al. (FATE) [69]	1574	49	0.70 (0.17)	7.2	12	1.86 (1.53–2.28)
Mathiesen et al. (Tromsø) [70]	6584	60	0.89 (0.19) male	9.6	397	1.08 (0.95–1.22) male
Mathiesen et al. (Tromsø) [70]	6584	60	0.83 (0.17) female	9.6	397	1.24 (1.05–1.48) female
Lorenz et al. (PROG-IMT) [71]	36,984	NR	NR	7.0	1339	1.21 (1.09–1.35)
Ruijter et al. (USE-IMT) [72]	45,828	58	0.73 (0.16)	11.0	1971	1.12 (1.10–1.15)
Elias-Smale et al. (Rotterdam) [73]	3580	64	0.82 (0.14) male	12.2	207	1.33 (1.18–1.50)
Elias-Smale et al. (Rotterdam) [73]	3580	64	0.77 (0.12) female	12.2	207	1.33 (1.18–1.50)

FU follow-up, NR not reported

*Includes HR of both myocardial infarction and stroke

Furthermore, a recent meta-analysis showed that interventions reducing CIMT progression are also likely to reduce cardiovascular event rates and estimated a relative risk for CVD of 0.91 (95% CI 0.87–0.94) per 10 μm/year reduction of CIMT progression [75].

Besides CIMT, stiffness is another parameter used to detect mechanical changes in the arterial wall during arteriosclerotic progression. This finding can theoretically occur earlier than any structural change [76]. Both CIMT and various indices of arterial stiffness are associated with coronary atherosclerosis, stroke, and cardiovascular mortality [30, 77].

Carotid distensibility was also found to be significantly associated with a higher prevalence of a previous transient ischemic attack (TIA) or ischemic stroke in patients with at least 50% carotid stenosis. Patients in the quartile with the lowest distension had a 2.1 times (95% CI 1.1–4.1) higher prevalence of a previous TIA or ischemic stroke compared with the patients in the quartile with the highest distension [78, 79]. Moreover, carotid distensibility has also been associated with increased risk of ischemic stroke in a population free from cerebrovascular disease [80]. Van Sloten et al. demonstrated that a 1-SD greater carotid distensibility significantly predicted stroke with an HR 1.18 (95% CI 1.05–1.33). When Young’s elastic modulus is used instead of distensibility, the HR was 1.08 (95% CI 0.96–1.22) for a 1-SD decrease [37].

Growing evidence indicates that PWV is a strong predictor of stroke [9, 28, 29, 36, 38]. The Rotterdam Study estimated that those in the upper tertile of PWV index had an age- and gender-adjusted hazard ratio of stroke of 2.34 (1.13–4.82; p < 0.03) when compared with the reference category with an estimated HR of 1.28 for stroke for a 1-SD increase in PWV [38]. In addition, carotid-cerebral PWV reflects cerebral arterial stiffness and it is also associated with atherosclerosis. Carotid-cerebral PWV was positively correlated with the number of lesions and the degree of stenosis and it showed the vascular structure change in acute ischemic stroke [81].

The ARIC (Atherosclerosis Risk in Communities) study indicated an independent association between carotid stiffness and stroke. This study showed that all arterial stiffness parameters were significantly associated with an increased incidence of stroke. They reported that individuals with stroke had lower baseline value for arterial compliance (7.10 mm³/kPa versus 7.92 mm³/kPa, P < 0.03), arterial distensibility (1.41%/kPa versus 1.75%/kPa, p < 0.0001), carotid arterial strain (7.10 mm³/kPa versus 7.92 mm³/kPa, p = 0.03), higher values for stiffness index (0.13 versus 0.11, p < 0.0001), Ep (175.76 kPa versus 137.54 kPa, p < 0.0001), and Young’s elastic modulus (1028.09 kPa versus 851.66 kPa, p < 0.0001) when compared with those individuals without stroke. After adjustments for age, gender, race, and vascular risk factors, arterial distensibility (HR 1.19 [95% CI 1.02–1.38]), carotid arterial strain (HR 1.13 [95% CI 1.01–1.27]), stiffness index (HR 1.14 [95% CI 1.04–1.25]), Ep (HR 1.15 [95% CI 1.05–1.27]), and Young’s elastic modulus (HR 1.15 [95% CI 1.05–1.28]) continued to have a significant association with incident stroke [36].

CIMT and Arterial Stiffness Assessment in Cardiovascular Risk Prediction

To date, cardiovascular risk prediction has been based on assessing traditional cardiovascular risk factors such as age, gender, lipid levels, smoking status, diabetes, and elevated blood pressure [7, 82]. Individuals were classified as having low cardiovascular risk, intermediate, and high risk using a 10-year cardiovascular risk estimation tool. The European Guidelines on cardiovascular disease prevention in clinical practice recommend the use of the SCORE (Systematic Coronary Risk Estimation) which can be recalibrated for use in different populations by adjusting for secular changes in mortality and risk factor prevalence. Subjects with low risk should reduce their risk factors and high-risk subjects are also given medical therapy [83].

Several studies investigated risk prediction models with and without CIMT [24, 44, 45]. The British Regional Heart Study found that CCA-IMT was strongly associated with risk for stroke, whereas bulb IMT and plaque were more directly associated with ischemic heart disease [84]. Nambi et al. evaluated whether the Framingham risk score (FRS) had a significant improvement by using CIMT measurement. Their analyses suggested that plaque formation was a more effective finding than CIMT in predicting future CV events [24]. Furthermore, Inaba et al. estimated that plaque assessment is 35% better than CIMT in predicting cardiovascular events [85]. Although the improved risk prediction model using CIMT was small, some authors recommend taking into consideration the clinical relevance of this increase in populations at intermediate risk [7, 68, 73, 86]. On the other hand, Lorenz et al. found CIMT derived from the CCA, the bulb, and the internal carotid artery to be less predictive than the traditional Framingham and SCORE risk models [21]. This controversy surrounding the usefulness of CIMT measurement in risk stratification appears to result from the inconsistent methodology used in CIMT studies.

Regarding the assessment of vascular stiffness, patients at intermediate risk could be reclassified into a higher or lower cardiovascular risk category when arterial stiffness was measured [38, 87, 88]. Up to 15% of the patients at intermediate risk in the Framingham heart study could be reclassified into a higher (14.3%) or lower (1.4%) risk category when arterial stiffness was assessed [88].

Carotid distensibility is a significant predictor for future CVD and all-cause mortality. The predictive value, however, is not as strong as is PWV [89, 90]. Van Sloten et al. demonstrated that greater carotid stiffness is associated with a higher incidence of stroke independently of PWV and improved risk prediction of stroke, thus identifying carotid stiffness as a potential separate target for stroke prevention strategies [91]. Circumferential strain can be used as a screening tool for subclinical atherosclerosis. Vascular mechanics and the number of risk factors for vascular disease have been shown to correlate significantly [15, 42]. Park et al. showed that as the number of risk factors for atherosclerosis increased from 0 to at least 4, circumferential strain decreased accordingly. Patients with a high Framingham risk score also showed lower circumferential strain (5.01 ± 2.19; 3.46 ± 1.34, 3.08 ± 1.38; p < 0.001) for FRS less than 5%, 5–15%, and greater than 15% [42]. The addition of carotid strain to CIMT significantly improved the ability to detect patients at high cardiovascular risk [15, 42].

Implications for Clinical Management

Current guidelines from the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) recommend lifestyle advice in primary prevention in low and intermediate cardiovascular risk, including smoking cessation, healthy diet low in saturated fat, and physical activity. In high risk cases, pharmacologic intervention adding low-dose aspirin among people less than 70 years of age who are not at increased bleeding risk and statin is suggested. In intermediate risk cases, adding statins depends on a function of cardiovascular risk uncontrolled after lifestyle modifications and low-density lipoprotein (LDL) level [83].

The addition of a surrogate marker for atherosclerosis for asymptomatic people at intermediate risk could further suggest reclassifying them into a higher risk group and providing earlier and better medical and lifestyle management. In young people, CIMT provides a reliable marker for early atherosclerotic disease where vascular events will likely not occur for decades and where plaque formation or calcification is not yet established [86].

Ruijter et al. demonstrated that CIMT had a small, yet significant potential for reclassification in intermediate risk individuals, with a clinical net reclassification index (NRI) of 3.2% in men and 3.9% in women [46]. Romanens et al. showed how carotid ultrasound can be used to better detect higher-risk subjects defined as being at low risk by SCORE. Subjects were shifted in 7–34% of cases from low to a higher risk category. Those shifted were treated with 20 mg rosuvastatin per day and the relative risk reduction per 1 mmol/l LDL reduction was 35% (primary care patient with cardiovascular risk less than 20%) in 10 years. This approach allowed them to calculate the maximum cost per ultrasound examination that would allow cost-efficiency. Using these assumptions, they found a high cost-efficiency when carotid ultrasound was added to the clinical workup in low-risk patients [92]. As the interest in risk prediction is currently shifting from a 10-year risk to lifetime risk, the added value of a CIMT measurement and its cost-effectiveness using a horizon of 20–30 years may be worthwhile to explore [46].

A small change in CIMT (on the order of 0.01–0.1 mm) cannot be measured in individuals in clinically meaningful time frames, especially taking into consideration reader error and patient factors leading to variability. Follow-up measurement of CIMT is only recommended in large research studies in which standardized CIMT protocols including multiple angles, anatomic landmarks, and automated edge detection software technology are used to assess CIMT progression or regression on serial measurements in a large dataset [86].

Although the routine noninvasive evaluation of arterial stiffness and the CIMT may provide a more precise risk stratification factor compared with that achieved from the usual common risk score alone [30], measurements should not routinely be performed in the general population, as the overall added value may be too limited to result in health benefits. On the basis of this decision, the target patient population may be individuals classified as being at low or intermediate risk, in whom information on the CIMT measurements may improve the cardiovascular risk stratification and therefore the pharmacological intervention would be started or modified [46].

PWV adds value to the existing risk prediction based on standard Framingham risk factors. This was particularly true in younger individuals with intermediate CVD risk. Although PWV is also predictive in patients with preexisting CVD, there is little point in attempting to refine risk estimation in people who have known CVD or who are categorized as high risk based on established risk factors. Such individuals are going to be treated anyway, so addition of PWV would not alter management of these patients. The converse probably is true for individuals at very low risk. National thresholds vary but those with low risk and abnormal PWV would have a 10-year CVD risk of 5–15%. For people at intermediate risk, the addition of PWV to a model that includes standard risk factors yields a net reclassification of 15% (coronary heart disease events) to 27% (CVD death), underscoring the potential utility of PWV as a guide to early intervention [89].

One of the limitations of ultrasound is image quality, which depends highly on the sonographer’s experience to use appropriate standardized carotid angles. In attempt to avoid it, the advances in software and hardware engineering have developed new automatic methods for the measurements of CIMT and arterial stiffness including novel artificial intelligence-based approaches.

Future Perspective

Diverse approaches for measuring CIMT and arterial stiffness are in use today. Standardization of acquisition and outcome measures are needed. Studies investigating the value of CIMT and stiffness should provide a uniform way to report their results. This would enable homogenous data collection and analysis to facilitate future data interpretation. Further advances in the development of these early biomarkers may help to improve the diagnosis of subclinical carotid atherosclerosis.

Ultrasonographic strain imaging with speckle tracking technique is a recent method for the assessment of carotid stiffness. This method has the potential to become a valuable noninvasive tool in the detection of early subclinical carotid artery disease [15, 19, 36, 42].

Recently, a combination of deep learning and machine learning was proposed for CIMT measurements showing up to 20% improvement in CIMT readings for the artificial intelligence system compared to the conventional methods [93]. This new method may be useful to further characterize cardiovascular risk and identify earlier biomarkers in an asymptomatic population [94, 95].

Conclusions

CIMT is a well-accepted early surrogate marker for subclinical carotid atherosclerosis, predicting CVD and improving the cardiovascular risk prediction models. Arterial stiffening is one of the earliest manifestations of the structural and functional changes in the carotid artery wall. Assessment of carotid artery stiffness allows one to predict CVD and can be useful to refine risk stratification. This is particularly important in individuals classified as being at intermediate cardiovascular risk by the assessment of traditional risk factors alone, in whom CIMT and arterial stiffness measurements may reclassify them into a higher risk and therefore pharmacological therapy should be started.

A combination of multiple imaging markers will likely further improve imaging-based cardiovascular risk prediction. Further research is clearly needed to standardize and investigate the cardiovascular risk prognostication of CIMT and stiffness.

Acknowledgements

Funding

No funding or sponsorship was received for publication of this article.

Authorship

All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Author contributions

Verónica Fernández-Alvarez (primary authorship, development of the concept and design, drafting the manuscript), Miriam Linares Sánchez (supporting image data), Fernándo López Alvarez (development of concept and design, writing original draft), Carlos Suárez Nieto (writing original draft, editing revision), Antti A. Mäkitie (writing original draft, editing revision), Kerry D. Olsen (writing original draft) and Alfio Ferlito (supervision, editing revision). All authors read and approved the final manuscript.

Disclosures

Verónica Fernández-Alvarez, Miriam Linares Sánchez, Fernando López Alvarez, Carlos Suárez Nieto, Antti A. Mäkitie, Kerry D. Olsen and Alfio Ferlito have nothing to disclose.

Compliance with Ethics Guidelines

This article is based on previously conducted studies and does not contain any studies with human participants or animals performed by any of the authors.

Data Availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204–1222.

Lindsay MP, Norving B, Sacco RL, et al. World Stroke Organization (WSO): global stroke fact sheet 2019. Int J Stroke. 2019;14(8):806–17.PubMedCrossRef

Dossabhoy S, Arya S. Epidemiology of atherosclerotic carotid artery disease. Semin Vasc Surg. 2021;34(1):3–9.PubMedCrossRef

Messas E, Goudot G, Halliday A, et al. Management of carotid stenosis for primary and secondary prevention of stroke: state-of-the-art 2020: a critical review. Eur Heart J Suppl. 2020;6(22):M35–42.CrossRef

Flore R, Ponziani FR, Tinelli G, et al. New modalities of ultrasound-based intima-media thickness, arterial stiffness and non-coronary vascular calcifications detection to assess cardiovascular risk. Eur Rev Med Pharmacol Sci. 2015;19(8):1430–41.PubMed

Song P, Fang Z, Wang H, et al. Global and regional prevalence, burden, and risk factors for carotid atherosclerosis: a systematic review, meta-analysis, and modelling study. Lancet Glob Health. 2020;8:e721-729.PubMedCrossRef

Van den Oord SCH, Sijbrands EJG, ten Kate GL, et al. Carotid intima-media thickness for cardiovascular risk assessment: systematic review and meta-analysis. Atherosclerosis. 2013;228(1):1–11.PubMedCrossRef

Zyriax BC, Dransfeld K, Windler E. Carotid intima-media thickness and cardiovascular risk factors in healthy volunteers. Ultrasound J. 2021;13(1):17.PubMedPubMedCentralCrossRef

Vlachopoulos C, Aznaouridis K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with arterial stiffness. J Am Coll Cardiol. 2010;55(13):1318–27.PubMedCrossRef

10.

Kurkowska-Jastrzebska I, Karlinski MA, Blazejewska-Hyzorek B, et al. Carotid intima-media thickness and blood biomarkers of atherosclerosis in patients after. Stroke or myocardial infarction. Croat Med J. 2016;57:548–557.

11.

Bauer M, Caviziel S, Teynor A, et al. Carotid intima-media thickness as a biomarker of subclinical atherosclerosis. Swiss Med Wkly. 2012;142:w13705.PubMed

12.

Pignoli P, Tremoli E, Poli A, et al. Intimal plus medial thickness of the arterial wall: a direct measurement with ultrasound imaging. Circulation. 1986;74(6):1399–406.PubMedCrossRef

13.

Persson J, Stavenow L, Wikstrand J, et al. Non invasive quantification of atherosclerotic lesions. Reproducibility of ultrasonographic measurement of arterial wall thickness and plaque size. Arterioscler Thromb. 1992;12(2)261–266.

14.

Kawasaki T, Takeuchi K, Hasegawa M, et al. The measurement of the stiffness parameter betadistribution along the common carotid artery by the ultrasonic, phase-locked echo tracking system—comparison between the healthy and the cerebral infarction groups. Nihon Ronen Igakkai Zasshi. 1982;19(6):588–95.PubMedCrossRef

15.

Teixeira R, Vieira MJ, Gonçalves A, et al. Ultrasonographic vascular mechanics to assess arterial stiffness: a review. Eur Heart J Cardiovasc Imaging. 2016;17(3):233–46.PubMedCrossRef

16.

Rizi FY, Au J, Yli-Ollila H, et al. Carotid wall longitudinal motion in ultrasound imaging: an expert consensus review. Ultrasound Med Biol. 2020;46(10):2605–24.PubMedCrossRef

17.

Golemati S, Sassano A, Lever MJ, et al. Carotid artery wall motion estimated from B-mode ultrasound using region tracking and block matching. Ultrasound Med Biol. 2003;29(3):387–99.PubMedCrossRef

18.

Cinthio M, Ahlgren AR, Jansson T, et al. Evaluation of an ultrasonic echo-tracking method for measurements of arterial wall movements in two dimensions. IEEE Trans Ultrason Ferroelectr Freq Control. 2005;52(8):1300–11.PubMedCrossRef

19.

Bjällmark A, Lind B, Peolsson M, et al. Ultrasonographic strain imaging is superior to conventional non-invasive measures of vascular stiffness in the dettection of age-dependent differences in the mechanical properties of the common carotid artery. Eur J Echocardiogr. 2010;11(7):630–6.PubMedCrossRef

20.

Touboul PJ, Hennerici MG, Meairs S, et al. Mannheim Carotid Intima-Media Thickness and Plaque Consensus (2004–2006–2011): an update on behalf of the advisory board of the 3rd and 4th watching the risk symposium 13th and 15th European Stroke Conferences, Mannheim, Germany, 2004, and Brussels, Belgium, 2006. Cerebrovasc Dis. 2012;34(4):290–6.PubMedCrossRef

21.

Lorenz M, Schaefer C, Steinmetz H, et al. Is carotid intima media thickness useful for individual prediction of cardiovascular risk? Ten years results from the Carotid Atherosclerosis Progression Study (CAPS). Eur Heart J. 2010;31:2041–8.PubMedCrossRef

22.

Shah PK. Screening asymptomatic subjects for subclinical atherosclerosis. Can we, does it matter, and should we? J Am Coll Cardiol. 2010;56:98–105.PubMedCrossRef

23.

Touboul PJ, Vicaut E, Labreuche J, et al. Correlation between the Framingham risk score and intima media thickness: The Paroi Arterielle et Risque Cardio-vasculaire (PARC) study. Atherosclerosis. 2007;192:363–9.PubMedCrossRef

24.

Nambi V, Chambless L, He M, et al. Common carotid artery intima-media thickness is as good as carotid intima-media thickness of all carotid artery segments in improving prediction of coronary heart disease risk in the Atherosclerosis Risk in Communities (ARIC) study. Eur Heart J. 2012;33:183–90.PubMedCrossRef

25.

Taylor AJ, Burke AP, O’Malley PG, et al. A comparison of the Framingham risk index, coronary artery calcification, and culprit plaque morphology in sudden cardiac death. Circulation. 2000;101:1243–8.PubMedCrossRef

26.

Texakalidis P, Giannopoulus S, Tsouknidas I, et al. Prevalence of carotid stenosis following radiotherapy for head and neck cancer: a systematic review and meta-analysis. Head Neck. 2020;42(5):1077–88.PubMedCrossRef

27.

O’Rourke MF, Staessen JA, Vlachopoulos C, et al. Clinical applications of arterial stiffness; definitions and reference values. AJH. 2002;15:426–444.

28.

Laurent S, Cockcroft J, Van Bortel L, et al. Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J. 2006;27(21):2588–605.PubMedCrossRef

29.

Palombo C, Kozakova M. Arterial stiffness, atherosclerosis and cardiovascular risk: pathophysiologic mechanisms and emerging clinical indications. Vascul Pharmacol. 2016;77:1–7.PubMedCrossRef

30.

Catalano M, Lamberti-Castronuovo A, Catalano A, et al. Two-dimensional speckle-tracking strain imaging in the assessment of mechanical properties of carotid arteries: feasibility and comparison with conventional markers of subclinical atherosclerosis. Eur J Echocardiogr. 2011;12(7):528–35.PubMedCrossRef

31.

Patton DM, Li T, Hétu MF, et al. Speckle tracking carotid artery circumferential strain is a marker of arterial sclerosis but not coronary atherosis. J Clin Ultrasound. 2018;46:575–81.PubMedCrossRef

32.

Gepner AD, Colangelo LA, Reilly N, et al. Carotid artery longitudinal displacement, cardiovascular disease and risk factors: the multi-ethnic study of atherosclerosis. PLoS One. 2015;10(11):e0142138.PubMedPubMedCentralCrossRef

33.

Mancia MG, Fagard R, Narkiewicz K, et al. ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J. 2013;2013(34):2159–219.

34.

Stein JH, Korcarz CE, Hurst RT, et al. Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: a consensus statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force. Endorsed by the Society for Vascular Medicine. J Am Soc Echocardiogr. 2008; 21:93–111.

35.

Liao D, Arnett DK, Tyroler HA, et al. Arteria stiffness and the development of hypertension. ARIC Study Hypertens. 1999;34(2):201–6.CrossRef

36.

Yang EY, Chambless L, Sharrett AR, et al. Carotid arterial wall characteristics are associated with incident ischemic stroke but not coronary heart disease in the Atherosclerosis Risk in Communities (ARIC) Study. Stroke. 2012;43(1):103–8.PubMedCrossRef

37.

Van Sloten TT, Schram MT, van den Hurk K, et al. Local stiffness of the carotid and femoral artery is associated with incident cardiovascular events and all-cause mortality. J Am Coll Cardiol. 2014;63(17):1739–47.PubMedCrossRef

38.

Mattace-Raso FUS, van der Cammen TJM, Hofman A, et al. Arterial stiffness and risk of coronary heart disease and stroke. Rotterdam Study Circ. 2006;113(5):657–63.

39.

Laurent S, Caviezel B, Beck L, et al. Carotid artery distensibility and distending pressure in humans. Hypertension. 1994;23:878–83.PubMedCrossRef

40.

Wei Y, Wang M, Gui Y, et al. Carotid artery stiffness in rural adult Chinese: a cross-sectional analysis of the community-based China stroke cohort study. BMJ Open. 2020;10(10):e036398.PubMedPubMedCentralCrossRef

41.

Mattace-Raso FU, Hofman A, Verwoert GC, et al. Determinants of pulse wave velocity in healthy people and in the presence of cardiovascular risk factors: ‘establishing normal and reference values.’ Eur Heart J. 2010;31(19):2338–50.CrossRef

42.

Park HE, Cho GY, Kim HK, et al. Validation of circumferential carotid artery strain as a screening tool for subclinical atherosclerosis. J Atheroscler Thromb. 2012;19(4):349–56.PubMedCrossRef

43.

Amato M, Veglia F, de Faire ULF, et al. Carotid plaque-thickness and common carotid IMT show additive value in cardiovascular risk prediction and reclassification. Atherosclerosis. 2017;263:412–9.PubMedPubMedCentralCrossRef

44.

Roumeliotis A, Roumeliotis S, Panagoutsos S, et al. Carotid intima-media thickness is an independent predictor of all-cause mortality and cardiovascular morbidity in patients with diabetes mellitus type 2 and chronic kidney disease. Ren Fail. 2019;41(1):131–8.PubMedPubMedCentralCrossRef

45.

Zhang Y, Fang X, Hua Y, et al. Carotid artery plaques, carotid intima-media thickness, and risk of cardiovascular events and all-cause death in older adults: a 5-year prospective, community-based study. Angiology. 2018;69(2):120–9.PubMedCrossRef

46.

Ruijter HMD, Peters SAE, Anderson TJ, et al. Common carotid intima-media thickness measurements in cardiovascular risk prediction: a meta-analysis. JAMA. 2012;308(8):796–803.CrossRef

47.

Lorenz MW, Price JF, Robertson C, et al. Carotid intima-media thickness progression and risk of vascular events in people with diabetes: results from the PROG-IMT collaboration. Diabetes Care. 2015;38(10):1921–9.PubMedPubMedCentralCrossRef

48.

Kouis P, Kousios A, Kanari A, et al. Association of non-invasive measures of subclinical atherosclerosis and arterial stiffness with mortality and major cardiovascular events in chronic kidney disease: systematic review and meta-analysis of cohort studies. Clin Kidney J. 2019;13(5):842–54.PubMedPubMedCentralCrossRef

49.

Gong N, Gao C, Chen X, et al. Endothelial function in patients with subclinical hypothyroidism: a meta-analysis. Rev Horm Metab Res. 2019;51(11):691–702.CrossRef

50.

Tyrrell PN, Beyene J, Feldman BM, et al. Rheumatic disease and carotid intima-media thickness: a systematic review and meta-analysis. Arterioscler Thromb Vasc Biol. 2010;30(5):1014–26.PubMedCrossRef

51.

Säidifard N, Tangestani H, Djafarian K, et al. Serum vitamin D level and carotid intima-media thickness: a systematic review and meta-analysis of observational studies and randomized control trials. Horm Metab Res. 2020;52(5):305–15.PubMedCrossRef

52.

Clemens RK, Annema W, Baumann F, et al. Cardiac biomarkers but not measures of vascular atherosclerosis predict mortality in patients with peripheral artery disease. Clin Chim Acta Int J Clin Chem. 2019;495:215–20.CrossRef

53.

Msoka TF, Van Guilder GP, van Furth M, et al. The effect of HIV infection, antiretroviral therapy on carotid intima-media thickness: a systematic review and meta-analysis. Life Sci. 2019;235:116851.PubMedCrossRef

54.

Provost EB, Madhloum N, Panis L, et al. Carotid intima-media thickness, a marker of subclinical atherosclerosis, and particulate air pollution exposure: the meta-analytical evidence. Meta Anal PLoS One. 2015;10(5):e0127014.CrossRef

55.

Fernandez-Alvarez V, Lopez F, Suarez C, et al. Radiation-induced carotid artery lesions. Strahlenther Onkol. 2018;194(8):699–710.PubMedCrossRef

56.

Toprak U, Aytas I, Ustuner E, et al. Sonographic assessment of acute changes in plaque size and echogenicity and in intima-media thickness of carotid arteries after neck radiation therapy. J Clin Ultrasound. 2012;40:566–71.PubMedCrossRef

57.

Fang HW, Gong W, et al. Atorvastatin treatment for carotid intima-media thickness in Chinese patients with type 2 diabetes: a meta-analysis. Med (Baltimore). 2015;94(44):e1920.CrossRef

58.

Kumar P, Sharma R, Misra S, et al. CIMT as a risk factor for stroke subtype: a systematic review. Eur J Clin Invest. 2020;50(11):e13348.PubMedCrossRef

59.

Sun P, Liu L, Liu C, et al. Carotid intima-media thickness and the risk of first stroke in patients with hypertension. Stroke. 2020;51(2):379–86.PubMedCrossRef

60.

Finn C, Giambrone AE, Gialdini G, et al. The association between carotid artery atherosclerosis and silent brain infarction: a systematic review and meta-analysis. J Stroke Cerebrovasc Dis. 2017;26(7):1594–601.PubMedPubMedCentralCrossRef

61.

O’Leary DH, Polak JF, Kronmal RA, et al. Carotid artery intima and media thickness as a risk factor of myocardial infarction and stroke in older adults. N Engl J Med. 1999;340(1):14–22.

62.

Chambless LE, Folsom AR, Clegg LX, et al. Carotid wall thickness is predictive of incident clinical stroke: the Atherosclerosis Risk in Communities (ARIC) study. Am J Epidemiol. 2000;151(5):478–87.PubMedCrossRef

63.

Hollander M, Hak AE, Koudstaal PJ, et al. Comparison between measures of atherosclerosis and risk of stroke: the Rotterdam Study. Stroke. 2003;34(10):2367–72.PubMedCrossRef

64.

Lorenz MW, von Kegler S, Steinmetz H, et al. Carotid intima-media thickening indicates a higher vascular risk across a wide age range: prospective data from the Carotid Atherosclerosis Progression Study (CAPS). Stroke. 2006;37(1):87–92.PubMedCrossRef

65.

Price JF, Tzoulaki I, Lee AJ, et al. Ankle brachial index and intima media thickness predict cardiovascular events similarly and increased prediction when combined. J Clin Epidemiol. 2007;60(10):1067–75.PubMedCrossRef

66.

Prabhakaran S, Singh R, Zhou X, et al. Presence of calcified carotid plaque predicts vascular events: the Northern Manhattan Study. Atherosclerosis. 2007;195(1):e197-201.PubMedPubMedCentralCrossRef

67.

Folsom AR, Kronmal RA, Detrano RC, et al. Coronary artery calcification compared with carotid intima- media thickness in prediction of cardiovascular disease incidence: The Multi-Ethnic Study of Atherosclerosis (MESA). Arch Intern Med. 2008;168(12):1333–9.PubMedPubMedCentralCrossRef

68.

Polak JF, Pencina MJ, Pencina KM, et al. Carotid-wall intima-media thickness and cardiovascular events. N Engl J Med. 2011;365(3):213–21.PubMedPubMedCentralCrossRef

69.

Anderson TJ, Charbonneau F, Title LM, et al. Microvascular function predicts cardiovascular events in primary prevention: long-term results from the Firefighters and Their Endothelium (FATE) study. Circulation. 2011;123(2):163–9.PubMedCrossRef

70.

Mathiesen EB, Johnsen SH, Wilsgaard T, et al. Carotid plaque area and intima-media thickness in prediction of first-ever ischemic stroke: a 10-year follow-up of 6584 men and women: the Tromsø Study. Stroke. 2011;42(4):972–8.PubMedCrossRef

71.

Lorenz MW, Polak JF, Kavousi M, et al. Carotid intima-media thickness progression to predict cardiovascular events in the general population (the PROG-IMT collaborative project): a meta-analysis of individual participant data. Lancet. 2012;379(9831):2053–62.PubMedPubMedCentralCrossRef

72.

Ruijter HM, Peters SAE, Groenewegen KA, et al. Common carotid intima-media thickness does not add to Framingham risk score in individuals with diabetes mellitus: the USE-IMT initiative. Diabetologia. 2013;56(17):1494–502.CrossRef

73.

Elias-Smale SE, Kavousi M, Verwoert GC, et al. Common carotid intima-media thickness in cardiovascular risk stratification of older people: the Rotterdam Study. Eur J Prev Cardiol. 2012;19(4):698–705.PubMedCrossRef

74.

Saba L, Jamthikar A, Gupta D, et al. Global perspective on carotid intima-media thickness and plaque: should the current measurement guidelines be revisited? Int Angiol. 2019;38(6):451–65.PubMed

75.

Willeit P, Tschiderer L, Allara E, et al. Carotid intima-media thickness progression as surrogate marker for cardiovascular risk: meta-analysis of 119 clinical trials involving 100 667 patients. Circulation. 2020;142(7):621–42.PubMedPubMedCentralCrossRef

76.

Lino H, Okano T, Daimon M, et al. Usefulness of carotid arterial strain values for evaluating the arteriosclerosis. J Atheroscler Thromb. 2019;26:476–87.CrossRef

77.

Mancini GB, Dahlo Fb, Diez J. Surrogate markers for cardiovascular disease-structural markers. Circulation. 2004;109(Suppl. IV):IV-22–30.

78.

Dijk JM, van der Graaf Y, Grobbee DE, et al. Carotid stiffness indicates risk of ischemic stroke and TIA in patients with internal carotid artery stenosis. The SMART Study. Stroke. 2004;35:2258–62.PubMedCrossRef

79.

Boesen ME, Singh D, Menon BK, et al. A systematic literature review of the effect of carotid atherosclerosis on local vessel stiffness and elasticity. Atherosclerosis. 2015;243(1):211–22.PubMedCrossRef

80.

Baradaran H, Delic A, Wong KH, et al. Using ultrasound and inflammation to improve prediction of ischemic stroke: a secondary analysis of the multi-ethnic study of atherosclerosis. Cerebrovasc Dis Extra. 2021;11(1):37–43.PubMedPubMedCentralCrossRef

81.

Fu X, Liu Q, Zeng X, et al. Association between cerebral arterial stiffness and large artery atherosclerosis in acute ischemic stroke. J Stroke Cerebrovasc Dis. 2018;27(11):2993–3000.PubMedCrossRef

82.

D’Agostino RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743–753.

83.

Mach F, Baigent C, Catapano AL, et al. 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Atherosclerosis. 2019;290:140–205.CrossRef

84.

Ebrahim S, Papacosta O, Whincup P, et al. Carotid plaque, intima media thickness, cardiovascular risk factors, and prevalent cardiovascular disease in men and women: the British Regional Heart Study. Stroke. 1999;30:841–50.PubMedCrossRef

85.

Inaba Y, Chen JA, Bergmann SR. Carotid plaque, compared with carotid intima-media thickness, more accurately predicts coronary artery disease events: a meta-analysis. Atherosclerosis. 2012;220(1):128–33.PubMedCrossRef

86.

Navqi TZ, Lee MS. Carotid intima-media thickness and plaque in cardiovascular risk assessment. JACC Cardiovasc Imaging. 2014;7(10):1025–38.CrossRef

87.

Sehestedt T, Jeppesen J, Hansen TW, et al. Risk prediction is improved by adding markers of subclinical organ damage to SCORE. Eur Heart J. 2010;31(7):883–91.PubMedCrossRef

88.

Mitchell GF, Hwang SJ, Vasan RS, et al. Arterial stiffness and cardiovascular events the Framingham heart study. Circulation. 2010;121(4):505–11.PubMedPubMedCentralCrossRef

89.

Wilkinson IB, Mäki-Petäjä KM, Mitchell GF. Uses of arterial stiffness in clinical practice. Arterioscler Thromb Vasc Biol. 2020;40(5):1063–7.PubMedPubMedCentralCrossRef

90.

Yuan C, Wang J, Ying M. Predictive value of carotid distensibility coefficient for cardiovascular diseases and all-cause mortality: a meta-analysis. PLos One. 2016;11(4):e0152799.PubMedPubMedCentralCrossRef

91.

Van Sloten TT, Sedaghat S, Laurent S, et al. Carotid stiffness is associated with incident stroke: a systematic review and individual participant data meta-analysis. J Am Coll Cardiol. 2015;66(19):2116–25.PubMedCrossRef

92.

Romanens M, Sudano I, Adams A, Warmuth W. Advanced carotid atherosclerosis in middle-aged subjects: comparison with PROCAM and SCORE risk categories, the potential for reclassification and cost-efficiency of carotid ultrasound in the setting of primary care. Swiss Med Wkly. 2019;149:w20006.PubMed

93.

Biswas M, Kuppili V, Araki T, et al. Deep learning strategy for accurate carotid intima-media thickness measurement: an ultrasound study on Japanese diabetic cohort. Comput Biol Med. 2018;98:100–17.PubMedCrossRef

94.

Ambale-Venkatesh B, Yang X, Wu CO, et al. Cardiovascular event prediction by machine learning: the ethnic study of atherosclerosis. Cric Resp. 2017;121(9):1092–101.CrossRef

95.

Saba L, Sanagala S, Gupta SK, et al. Ultrasound-based internal carotid artery plaque characterization using deep learning paradigm on a supercomputer: a cardiovascular disease/stroke risk assessment system. Int J Cardiovasc Imaging. 2021;37(5):1511–28.PubMedCrossRef

Titel: Evaluation of Intima-Media Thickness and Arterial Stiffness as Early Ultrasound Biomarkers of Carotid Artery Atherosclerosis
verfasst von: Verónica Fernández-Alvarez
Miriam Linares Sánchez
Fernando López Alvarez
Carlos Suárez Nieto
Antti A. Mäkitie
Kerry D. Olsen
Alfio Ferlito
Publikationsdatum: 01.04.2022
Verlag: Springer Healthcare
Erschienen in: Cardiology and Therapy / Ausgabe 2/2022
Print ISSN: 2193-8261
Elektronische ISSN: 2193-6544
DOI: https://doi.org/10.1007/s40119-022-00261-x

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Neu im Fachgebiet Innere Medizin

Notfall-TEP der Hüfte ist auch bei 90-Jährigen machbar

26.04.2024 Hüft-TEP Nachrichten

Ob bei einer Notfalloperation nach Schenkelhalsfraktur eine Hemiarthroplastik oder eine totale Endoprothese (TEP) eingebaut wird, sollte nicht allein vom Alter der Patientinnen und Patienten abhängen. Auch über 90-Jährige können von der TEP profitieren.

Niedriger diastolischer Blutdruck erhöht Risiko für schwere kardiovaskuläre Komplikationen

25.04.2024 Hypotonie Nachrichten

Wenn unter einer medikamentösen Hochdrucktherapie der diastolische Blutdruck in den Keller geht, steigt das Risiko für schwere kardiovaskuläre Ereignisse: Darauf deutet eine Sekundäranalyse der SPRINT-Studie hin.

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

25.04.2024 Allergien und Intoleranzreaktionen Nachrichten

Insektenstiche sind bei Erwachsenen die häufigsten Auslöser einer Anaphylaxie. Einen wirksamen Schutz vor schweren anaphylaktischen Reaktionen bietet die allergenspezifische Immuntherapie. Jedoch kommt sie noch viel zu selten zum Einsatz.

Therapiestart mit Blutdrucksenkern erhöht Frakturrisiko

25.04.2024 Hypertonie Nachrichten

Beginnen ältere Männer im Pflegeheim eine Antihypertensiva-Therapie, dann ist die Frakturrate in den folgenden 30 Tagen mehr als verdoppelt. Besonders häufig stürzen Demenzkranke und Männer, die erstmals Blutdrucksenker nehmen. Dafür spricht eine Analyse unter US-Veteranen.

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Springer Medizin

Abstract

Introduction

Compliance with Ethics Guidelines

Historical Perspective

Carotid Ultrasound Methodology

Reference Values

CIMT and Arterial Stiffness as Early Biomarkers of Carotid Atherosclerosis and Stroke

CIMT and Arterial Stiffness Assessment in Cardiovascular Risk Prediction

Implications for Clinical Management

Future Perspective

Conclusions

Acknowledgements

Funding

Authorship

Author contributions

Disclosures

Compliance with Ethics Guidelines

Data Availability

Weitere Artikel der Ausgabe 2/2022

Coronary Artery Disease and Aspirin Intolerance: Background and Insights on Current Management

Große stationäre Studie: Thrombotische und kardiovaskuläre Ereignisse aufgrund von COVID-19

Patients with Atrial Fibrillation Benefit from SAVR with Surgical Ablation Compared to TAVR Alone

Endovascular Repair of an Iliac Arteriovenous Fistula in a 30-Year-Old Female Patient with Suspected Severe Cardiac Insufficiency: A Case Report

Treatment Changes, Healthcare Resource Utilization, and Costs Among Patients with Symptomatic Obstructive Hypertrophic Cardiomyopathy: A Claims Database Study

Imaging Findings in Pediatric COVID-19: A Review of Current Literature

Leitlinien kompakt für die Innere Medizin

Neu im Fachgebiet Innere Medizin

Notfall-TEP der Hüfte ist auch bei 90-Jährigen machbar

Niedriger diastolischer Blutdruck erhöht Risiko für schwere kardiovaskuläre Komplikationen

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

Therapiestart mit Blutdrucksenkern erhöht Frakturrisiko

Update Innere Medizin