Relationship of Carotid Distensibility and Thoracic Aorta Calcification: Multi-Ethnic Study of Atherosclerosis (MESA)

Abstract

Stiffening of the central elastic arteries is one of the earliest detectable manifestations of adverse change within the vessel wall. While an association between carotid artery stiffness and adverse events has been demonstrated, little is known about the relationship between stiffness and atherosclerosis. Even less is known about the impact of age, gender, and race on this association. To elucidate this question, we used baseline data from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2002). Carotid artery distensibility coefficient (DC) was calculated after visualization of the instantaneous waveform of common carotid diameter using high resolution B-mode ultrasound. Thoracic aorta calcification (TAC) was identified using non-contrast cardiac CT. We found a strong association between decreasing DC (increasing carotid stiffness) and increasing TAC as well as a graded increase in TAC score (p<0.001). After controlling for age, gender, race, and traditional and emerging cardiovascular risk factors, individuals in the stiffest quartile had a prevalence ratio of 1.52 (95% CI 1.15-2.00) for TAC compared to the least stiff quartile. In exploratory analysis, carotid stiffness was more highly correlated with calcification of the aorta than calcification of the coronary arteries (ρ=0.32 vs. 0.22, p<0.001 for comparison). In conclusion, there is a strong independent association between carotid stiffness and thoracic aorta calcification. Carotid stiffness is more highly correlated with calcification of the aorta, a central elastic artery, than calcification of the coronary arteries. The prognostic significance of these findings requires longitudinal follow-up of the MESA cohort.

Introduction

Stiffening of the central elastic arteries is one of the earliest detectable manifestations of adverse change within the vessel wall^{1, 2}. Accompanying decreased arterial compliance is closely associated with aging³ and other traditional cardiovascular risk factors^{4, 5}. Measures of central artery stiffness, including aortic pulse wave velocity⁶, have been associated with coronary artery disease^7-9, congestive heart failure^{10, 11}, stroke¹², as well as all-cause mortality^13-15. Although aortic and systemic stiffness have proven difficult to apply in the clinical setting, local stiffening within the carotid artery remains appealing because it is more directly accessible to measurement.

Mechanical properties of the carotid arteries are mostly easily visualized using high resolution ultrasound¹⁶. On a real-time sweep of the common carotid artery, dynamic measurements of carotid diameter can be made that enable calculation of several indices of stiffness: distensibility coefficient (DC), Young's elastic modulus (YM), β stiffness index, and carotid distension¹⁷. These indices have been shown to predict coronary heart disease and stroke amongst apparently healthy individuals in the Rotterdam¹⁸ and Three-City studies¹⁹.

Despite the association between carotid stiffness and poor outcomes, little is known about the association between stiffness and atherosclerosis. Even less is known about the impact of age, gender, and race on this association. The little available data correlating carotid stiffness with aortic atherosclerosis used plain radiography of the abdomen as the measure of plaque burden²⁰. Definitive conclusions have been limited by the use of this insensitive and difficult-to-quantify measure of atherosclerosis. In contrast, measurement of arterial calcification by computed tomography (CT) allows quantification of the volumetric burden of atherosclerosis, including that found within the more central ascending and descending thoracic aorta²¹.

To better describe the association between stiffness and atherosclerosis, we assessed the cross-sectional association between carotid DC measured with ultrasound and thoracic aortic calcification (TAC) measured by CT in a large multi-ethnic cohort. In further analysis, we looked for regional variability in the association between carotid stiffness and calcification in the aorta (an elastic central artery) and the coronary arteries (peripheral arteries).

Methods

Study Design and Patient Population

We used baseline data from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2002). The MESA study design, patient recruitment and selection have been previously described²². In summary, MESA enrolled 6,814 asymptomatic men and women of 4 different ethnic groups (Whites, Chinese, African-American, and Hispanic), aged 45 to 84, into a population-based prospective cohort study aimed at describing the prevalence, progression, and significance of subclinical atherosclerosis. Patients were drawn from 6 geographically distinct population centers in the United States. All patients were free of known cardiovascular disease at enrollment.

Each MESA participant underwent 2 baseline cardiac CT scans for the evaluation of coronary and extra-coronary calcification. In 6,529 (96%) participants, baseline carotid ultrasound imaging was sufficient to calculate DC. Patients without sufficient carotid imaging were more likely to be female and African-American, but did not differ in age or any other measured covariate. All participants gave informed consent for the study protocol, which was approved by the institutional review boards of all 6 MESA field centers.

Carotid Imaging and Distensibility Coefficient

The right and left carotid arteries were imaged according to a common scanning protocol using high resolution B-mode ultrasonography with a Logiq 700 machine (General Electric Medical Systems). Carotid IMT was measured in the common carotid artery, and reported as the mean of the maximum IMT measured in the right and left sides for both the near and far walls. Data necessary for calculating DC were obtained from a separate 20 second-long acquisition of longitudinal images of the right distal common carotid artery. All images were interpreted at a central MESA ultrasound reading center (Tufts Medical Center) by readers blinded to all clinical information.

For each participant, an edge detector was used to process the images and extract carotid arterial diameter curves. Diastolic and systolic diameters were determined as the smallest and largest diameter values during a cardiac cycle. Blood pressure measurements were taken by upper arm sphygmomanometry (DINAMAP system, GE Medical Systems) at the time of the carotid artery ultrasound.

These data were used to calculate a simplified DC via the following equations described by Gamble²³:

$$\text{Destensibility coefficient}:\frac{2\mathrm{\Delta }D}{\mathrm{\Delta }P{D}_s}$$

Where ΔD is the change in systolic/diastolic diameter, ΔP is the brachial pulse pressure, D_s is the systolic diameter, D is the average common carotid artery diameter, and h is the, mean wall thickness (IMT) measured 10 mm proximal to the carotid bulb.

Reproducibility studies were performed in 221 participants; 211 were intraobserver repeated image analyses, and 10 interobserver correlations. For DC and YM, the intraobserver class correlation coefficient (ICC) was 0.71 and 0.69, respectively. The interobserver ICC was 0.85 and 0.84, respectively. The intraobserver variability in reading exams was assessed in 204 patients, revealing an ICC of 0.68 for DC and 0.80 for YM. This reflects good to excellent agreement.

Cardiac CT protocol

Cardiac CT was performed at 3 sites using a cardiac-gated electron-beam CT scanner (Imatron C-150XL, GE-Imatron, San Francisco, CA), and at 3 sites using 4-slice multidetector CT. All participants were scanned over phantoms of known physical calcium concentration. Images were read at the MESA CT reading center (Harbor-UCLA).

The MESA scanning protocol has been described previously²⁴. Images slices were obtained with the participant supine, with no couch angulation, during a single breath hold. A minimum of 35 contiguous images were obtained, beginning above the left main coronary artery and proceeding below both ventricles. Section thickness of 3 mm, field of view 35 cm, and matrix 512 × 512 were used to reconstruct the raw data. Nominal section thickness was 3.0 mm for electron beam CT and 2.5 mm for 4-detector row CT. Spatial resolution, expressed as the smallest voxel able to be discriminated, was 1.38 mm³ (0.68 × 0.68 × 3.00 mm) for electron beam CT and 1.15 mm³ (0.68 × 0.68 × 2.50 mm) for 4-detector row CT.

The ascending and descending thoracic aorta was visualized from the lower edge of the pulmonary artery bifurcation to the cardiac apex on each cardiac CT. TAC is defined as total calcification in the ascending + descending portions. For this study, TAC is considered both as a binary measure (present vs. not present) and a continuous measure (Agatston score).

The reproducibility of extracoronary measures of calcification within MESA has been discussed in detail previously²⁵. To summarize for TAC, among 1,729 randomly chosen participants undergoing rescanning on dual scanners, the intra-scan kappa statistic for agreement on presence of TAC was 0.95 (0.94 – 0.97). This varied slightly by scanner type, with MDCT outperforming EBCT (0.97 vs. 0.94). The mean rescan percentage absolute difference in Agatston score for measurement of TAC>0 was 10.2%. This variability is most likely due to slightly different starting points for the two scans, such that that slightly different anatomy may be examined in scan 1 and scan 2. The reproducibility of CAC within MESA has also been thoroughly described²⁶. The kappa statistic for agreement on presence of CAC was 0.92, and the mean rescan percentage absolute difference in CAC>0 was 20.1%.

Study Covariates

Hypertension, smoking, diabetes, and family history of heart attack are presented as binary variables. Hypertension was defined as use of anti-hypertensive medication or baseline sphygmomanometric measurements of blood pressure fulfilling Joint National Committee (JNC) guidelines (≥140/90 mmHg identifying hypertension). Smoking was defined as prior or present use of tobacco cigarettes. Diabetes was defined according to American Diabetes Association (ADA) guidelines (fasting blood sugar >126 mg/dL) or the use of hypoglycemic medications. Replacement of hypertension, smoking, and diabetes with absolute systolic and diastolic blood pressure, pack-years of smoking, and fasting blood glucose in the study models resulted in minimal change with no overall impact on study conclusions. Medication use was defined as present use of prescription medications for the treatment of hypertension or hypercholesterolemia. Family history was positive if an immediate family member (parents, siblings, or children) had suffered a heart attack.

Statistical Analysis

Baseline characteristics of the study participants are presented over decreasing quartiles of distensibility coefficient (increasing carotid stiffness). The 4^th quartile (most distensible) is used as the reference group for subsequent analyses. Frequencies and proportions are reported for categorical variables, and either means with standard deviations or medians with interquartile ranges are reported for continuous variables based on normality of distribution. Chi-square tests, Fisher's exact tests, one-way ANOVA, or Kruskal-Wallis tests were used for comparison of variables between groups.

Because the prevalence of CAC in our cohort is greater than 10%, odds ratios (ORs) overestimate relative risk. Therefore, prevalence ratio estimates are presented from the regression model y=exp(X^Tβ), with the exponentiated parameter β interpreted as the relative risk or prevalence ratio. Using this method we assessed the relationship between DC and presence of TAC, in a hierarchal fashion. Model 1 adjusts for key demographic variables: age, gender, and race. Model 2 adds traditional and emerging cardiovascular risk factors: body mass index, heart rate, LDL cholesterol, hypertension, diabetes mellitus, cigarette smoking, family history of heart attack, and lipid-lowering medication use. Model 3 adds the inflammatory variable C-reactive protein and baseline measures of subclinical vascular disease: coronary artery calcium (CAC), and carotid IMT.

To better discern the influence of important study covariates, additional stratified analyses were conducted, with results are expressed as the prevalence ratio of having TAC per one standard deviation increase in DC. Finally, to explore differential correlations between DC and calcification of thoracic aorta and coronary arteries, we constructed a Spearman correlation coefficient matrix between DC, TAC, and CAC. We used logarithmically transformed values of TAC and CAC (ln [score +1]) to normalize their distributions.

All analyses used a 5% two-sided significance level. Calculations were performed using STATA software, version 8.2.

Results

Baseline Characteristics of the MESA participants

The mean age of the 6,526 study participants was 62 ± 10 years. Approximately 53% were male, with mean calculated 10-year Framingham risk for the entire cohort of 8.2 ± 7%. Mean DC for the study cohort was 2.51 mmHg, with standard deviation 1.1 mmHg × 10^-3. Median DC was 2.36 mmHg × 10^-3 reflecting slight rightward skew. The mean and median DC values are similar to those reported in other studies after adjusting for differences in calculation¹⁸.

Patients were divided into 4 categories based on their values for DC (See Table 1). Across decreasing DC quartiles (increasing carotid stiffness), patients were on average older, more likely to be female, and enriched in the African-American and Hispanic ethnicities. Most traditional and emerging cardiac risk factors were associated with decreasing DC, including body mass index (BMI), blood pressure, diabetes, smoking, and C-reactive protein (CRP). In addition, decreasing DC was associated with a higher prevalence of CAC, a higher CAC score, and lower carotid IMT (all p<0.001).

Table 1.

Characteristics of the study participants.

Abbreviations: BMI = body mass index, Cr = creatinine, CRP = C-reactive protein, CAC = coronary artery calcium, FRS = Framingham Risk Score.

Characteristic	Total (N = 6,526)	DC Quartile 4 (≥3.02)	DC Quartile 3 (2.36-3.01)	DC Quartile 2 (1.78-2.35)	DC Quartile 1 (≤1.77)	P
Age, years	62 ± 10	55 ± 8	60 ± 9	64 ± 9	69 ± 9	<0.001
Gender, women	53%	51%	50%	54%	56%	0.001
Race
▪ Whites	39%	46%	42%	37%	29%	<0.001
▪ Chinese	12%	11%	14%	12%	12%
▪ African American	27%	23%	32%	29%	35%
▪ Hispanic	22%	21%	21%	23%	24%
Heart rate, beats/min	63 ± 10	61 ± 9	63 ± 9	64 ± 10	65 ± 11	<0.001
BMI, kg/m2	28.3 ± 5	27.3 ± 5	28.1 ± 5	28.9 ± 6	28.8 ± 5	0.022
Systolic blood pressure, mmHg	127 ± 22	114 ± 16	122 ± 17	129 ± 19	142 ± 23	<0.001
Diastolic blood pressure, mmHg	72 ± 10	69 ± 10	71 ± 9	73 ± 10	75 ± 11	<0.001
Hypertension	45%	22%	35%	51%	71%	<0.001
Fasting glucose	104 ± 31	99 ± 29	102 ± 26	106 ± 32	110 ± 35	<0.001
Diabetes	14%	8%	12%	15%	22%	<0.001
Cr, mg/dL	0.95 ± 0.3	0.93 ± 0.2	0.94 ± 0.3	0.95 ± 0.3	0.99 ± 0.3	<0.001
Smoking						<0.001
▪ Former	37%	34%	36%	38%	39%
▪ Current	13%	21%	13%	10%	8%
LDL, mg/dL	117 ± 32	117 ± 32	112 ± 31	118 ± 32	116 ± 32	0.61
HDL, mg/dL	51 ± 15	51 ± 15	50 ± 14	51 ± 15	51 ± 15	0.27
Triglycerides, mg/dL	111 (77 – 161)	102 (72 – 152)	115 (79 – 166)	113 (80 – 163)	114 (81 – 162)	<0.001
Family history of heart attack	40%	40%	41%	41%	39%	0.67
Medications for hypertension	37%	22%	32%	42%	53%	<0.001
Medications for cholesterol	16%	11%	15%	18%	19%	<0.001
hsCRP, mg/L	1.90 (0.83 – 4.19)	1.56 (0.66 – 3.88)	1.71 (0.76 – 3.80)	2.07 (0.94 – 4.46)	2.25 (0.99 – 4.61)	<0.001
CAC	50%	36%	47%	53%	63%	<0.001
Ln (CAC+1), (score)	2.19 ± 2.5	1.42 ± 2.2	2.03 ± 2.5	2.38 ± 2.6	2.94 ± 2.6	<0.001
Carotid IMT, mm	0.87 ± 0.19	0.80 ± 0.16	0.84 ± 0.18	0.89 ± 0.19	0.95 ± 0.21	<0.001
10-yr FRS (%)	8.2 ± 7%	5.6 ± 6%	7.3 ± 7%	8.7 ± 7%	12 ± 8%	<0.001

Prevalence of TAC by DC Quartile

The prevalence of TAC was 28% for the study cohort. Across all four ethnicities, there was a graded association between increasing DC quartile and decreasing prevalence of TAC (p<0.001, See Figure 1). The prevalence of TAC reached 61% among whites for quartile 1, the group with the stiffest arteries. The association between DC and TAC remained strong among African-Americans, the ethnicity known to have the lowest incidence of TAC.

Figure 1.

Unadjusted prevalence of thoracic aorta calcium (TAC) by increasing distensibility coefficient quartile, stratified by race.

Calcification of the aorta decreased with increasing carotid distensibility. Overall prevalence of TAC is 28% (dotted line). p<0.001 in each race for the trend across DC quartiles.

Association between DC and TAC Score

Considering only patients with prevalent TAC (score > 0), there remains a “dose-response” relationship between DC quartile and TAC score (See Figure 2). From the least to the most distensible carotid artery quartile, the median TAC scores were 367, 275, 187, and 133 respectively (p<0.001). To better demonstrate this graded relationship, we examined median DC over quartiles of TAC score, retaining the large TAC=0 group as a distinct category (See Figure 3). Across all races, mean DC was higher among patients with no TAC (p<0.001), with a modest threshold effect for lower DC among individuals in the highest TAC score quartile. In linear aggression analysis adjusting for age, race, and gender, one standard deviation decrease in DC corresponded to a 12% relative increase in log-transformed TAC score (p=0.008).

Figure 2.

Median, interquartile range, and adjacent values of thoracic aorta calcium (TAC) by distensibility coefficient (DC) quartile in those with TAC>0.

In those with TAC, the mean TAC score decreased with increasing distensibility of the carotid artery. P<0.001 for the association across DC quartiles.

Figure 3.

Median, interquartile range, and adjacent values of distensibility coefficient by absence/quartiles of thoracic aortic calcium

Carotid distensibility is greatest in those with no TAC, with a threshold effect for decrease distensibility among individuals in the highest TAC score quartile. P<0.001 for the association across all TAC groups

Multivariable Regression Models

The results from three different regression models are presented in Table 2. Adjusted for demographic variables, the prevalence ratio for having TAC amongst the least distensible compared to the most distensible quartile was 1.79 (95% CI 1.41 – 2.26). Adding cardiovascular risk factors to the model, the prevalence ratio was slightly attenuated to 1.52 (95% CI 1.19 – 1.96). Adding measures of subclinical vascular disease resulted in little change, with prevalence ratio 1.52 (95% CI 1.15 – 2.00). Additional analyses including creatinine and fasting glucose into the model did not change these results.

Table 2.

Multivariable-adjusted prevalence ratio (95% CI) for thoracic aorta calcium by decreasing quartile of distensibility coefficient.

Prevalence Ratio for TAC	Distensibility Coefficient (decreasing quartiles, in 1/mmHg × 103)
	Quartile 4 (≥3.02)	Quartile 3 (2.36-3.01)	Quartile 2 (1.78-2.35)	Quartile 1 (≤1.77)
Model 1	1 (ref group)	1.15 (0.90-1.47)	1.50 (1.19-1.89)	1.79 (1.41-2.26)
Model 2	1 (ref group)	1.17 (0.91-1.50)	1.43 (1.13-1.83)	1.52 (1.19-1.96)
Model 3	1 (ref group)	1.24 (0.95-1.64)	1.43 (1.09-1.87)	1.52 (1.15-2.00)

Model 1: Adjusted for age, gender, and race

Model 2: Model 1 + body mass index, heart rate, LDL cholesterol, hypertension, diabetes mellitus, cigarette smoking, family history of heart attack, cholesterol-lowering medications

Model 3: Model 2 + log transformed C-reactive protein, log transformed CAC+1, carotid IMT

Table 3 show the results of stratified multivariable analyses examining the prevalence ratio for TAC with one standard deviation change in DC (See Table 3). For the entire cohort, one standard deviation decrease in distensibility coefficient resulted in 25% increase in TAC prevalence (95% CI 1.12 – 1.41). In stratified analyses, individual risk factors did not have a major impact on this association, with numerous statistically significant associations and overlapping confidence intervals. Associations between DC and TAC remained strong in middle-aged participants and individuals in the lower Framingham risk categories.

Table 3.

Prevalence ratio (95% CI) for thoracic aortic calcium with one standard deviation decrease in distensibility coefficient.

Characteristic	N	N with TAC>0	Relative Risk (95% CI)	P value
Age
Tertile 1 (45-56 yo)	2,239	107	1.58 (0.70 – 3.57)	0.27
Tertile 2 (57-67 yo)	2,125	480	1.15 (0.97 – 1.36)	0.10
Tertile 3 (68-84 yo)	2,162	1,239	1.33 (1.14 – 1.55)*	<0.001
Gender
Females	3,427	992	1.30 (1.10 – 1.54)*	0.002
Males	3,099	834	1.21 (1.03 – 1.41)*	0.017
Race
Whites	2,517	814	1.27 (1.10 – 1.47)*	0.001
Chinese	783	252	1.24 (0.89 – 1.73)	0.21
African-American	1,779	401	1.17 (0.85 – 1.61)	0.34
Hispanic	1,447	359	1.32 (0.96 – 1.82)	0.09
Risk Factor Status
Normotensive	3.613	651	1.34 (1.14 – 1.58)*	<0.001
Hypertension	2,913	1,175	1.21 (1.02 – 1.43)*	0.03
Non-Diabetic	5,605	1,482	1.23 (1.09 – 1.39)*	0.001
Diabetes	921	334	1.46 (1.10 – 1.94)*	0.008
Non-Smoker	5,681	1,602	1.27 (1.12 – 1.45)*	<0.001
Smoking	845	224	1.22 (0.97 – 1.54)	0.09
Framingham Risk Score†
Low (0-6%)	2,890	414	1.30 (1.05 – 1.63)*	0.02
Intermediate (6-20%)	2,570	806	1.21 (1.03 – 1.44)*	0.03
High (≥20%)	1,066	606	1.12 (0.85 – 1.47)	0.42
Total	6,526	1,826	1.25 (1.12 – 1.41)*	<0.001

Standard deviation = 1.1 mmHg × 10^-3

^*Association statistically significant (p<0.05).

Adjusted for age tertile, gender, race, body mass index, heart rate, LDL cholesterol, hypertension, diabetes mellitus, smoking, family history of heart attack, cholesterol lowering medications, transformed C-reactive protein, log transformed CAC+1, and carotid IMT when not first stratifying by these variables.

^†Adjusted for age tertile, gender, race, body mass index, heart rate, diabetes, family history of heart attack, cholesterol-lowering medications, transformed C-reactive protein, log transformed CAC+1, and carotid IMT

Correlation between DC and Regional Calcification

Table 4 displays a stratified Spearman correlation matrix between DC, TAC, and CAC. All individual correlation coefficients were statistically significant at p<0.001. In general, the correlation between DC and calcification was least strong among men and African-Americans. There was a tighter correlation between DC and TAC than between DC and CAC (ρ=0.315 vs. 0.221, p<0.001 for comparison of coefficients across the entire study population). This difference remained statistically significant in both genders (females p<0.001, males p=0.01) and all races (whites p<0.001, Chinese p=0.03, African Americans p=0.03, Hispanics p=0.008).

Table 4. Correlation between distensibility coefficient, coronary artery calcium, and thoracic aorta calcium.

Correlation Coefficients [ρ] between:
Characteristic	ρ DC, TAC	ρ DC, CAC	ρ TAC, CAC
Females	-0.349	-0.271	0.487
Males	-0.275	-0.214	0.441
Whites	-0.374	-0.279	0.450
Chinese	-0.361	-0.261	0.441
African Americans	-0.243	-0.172	0.387
Hispanics	-0.358	-0.269	0.454

Coronary Artery Calcium (CAC) and Thoracic Aorta Calcium (TAC) defined as continuous variables by the equation: natural log (calcification score + 1).

^*All individual correlations significant at p<0.001

^*p<0.001 for ρ DC, TAC vs. ρ DC, CAC for the entire population (ρ=-0.315 vs. -0.221).

^*Difference remains significant across both genders (p<0.01) and all races: whites (p<0.001), Chinese (p=0.03), African Americans (p=0.03), and Hispanics (p=0.008).

Supplementary Analysis

To facilitate comparison with existing literature, we subsequently conducted exploratory analyses using Young's Modulus (YM), a measure of arterial elasticity, as well as a parameter indicating ‘distension’ achieved by adjusting our primary analysis for pulse pressure. Results were similar to those seen with the analysis using DC. For YM quartile 4 (most elastic), there was a statistically significant 35% increase in TAC prevalence (95% CI 1.02 – 1.80). After adjusting for pulse pressure, there remained a strong association between carotid ‘distention’ and TAC. Point estimates of the association were slightly attenuated, but remained statistically significant (S1-2, please see http://hyper.ahajournals.org).

Discussion

In this large multi-ethnic cohort, we demonstrate a strong association between decreasing carotid distensibility (increasing carotid stiffness) and increasing prevalence of TAC as well as a graded increase in TAC score. This association is independent of age, gender, race, and traditional and emerging cardiovascular risk factors, and importantly remains broadly applicable to low and intermediate Framingham risk groups. In addition, we demonstrate regional variability in the association with calcific atherosclerosis, with carotid DC more highly correlated with TAC than CAC.

Distensibility Coefficient

We chose the distensibility coefficient (DC) as a measure of stiffness because of its intuitive calculation, its common use in the epidemiologic literature²⁷, and its use in the Rotterdam studies enabling direct comparison of results^{18, 20}. Pre-specified analysis with a single index also avoids problems with ‘multiple looks’ seen in studies that test every index of stiffness. We did subsequently conduct an exploratory analysis using Young's Modulus, a measure of arterial elasticity, which revealed similar associations although less strong point estimates of risk (please see http://hyper.ahajournals.org). This pattern is consistent with prior studies relating these two indices¹¹.

Indices such as DC that rely on blood pressure have been criticized due to their reliance on pulse pressure, which is itself an independent predictor of cardiovascular risk²⁸. To adjust for the influence of pulse pressure, we repeated our analyses adjusting for this variable, resulting in attenuated but continued statistically significant associations (see Appendix). After adjustments for pulse pressure, the stiffness parameter becomes more similar to a measure of carotid ‘distention’²⁰.

While inversely correlated (ρ=-0.25), our study demonstrates that DC provides information that is independent of carotid IMT (see Table 2, Model 3). This is consistent with prior studies^{18, 20}. Both DC and carotid IMT can be calculated from the same longitudinal scanning sequence using high resolution ultrasound. This raises the possibility of combining these non-invasive measures for a more comprehensive evaluation of vascular disease²⁹.

Carotid Distensibility and Arterial Calcification

Why is DC more highly correlated with TAC than CAC? There is increasing evidence that the determinants of calcification and atherosclerosis are different for different vascular beds³⁰. For example, studies by Nasir et al. within MESA have shown that while whites have more CAC than Chinese, their burden of TAC is similar³¹. Gender associations are reversed – while men have more CAC than women, women appear to have more TAC than me³¹. This observation has been corroborated by Post et al with data from the Pennsylvania Amish, showing that male gender is associated with CAC and not TAC³². In the Amish population, aging is more highly associated with TAC. CAC and TAC are in fact loosely correlated before the age of 50 (ρ=0.135).

There are likely distinct features characterizing the pathophysiology of calcification within the thoracic aorta versus the coronary arteries. Histologic studies demonstrate that calcification of the coronary arteries is largely confined to the intimal layer. However, within the large arteries including the aorta calcification can be present both in the intima and tunica media³³. Medial calcification is more strongly associated with aging, diabetes, and severe renal disease³⁴. Structural features of different vascular beds likely also play a role. The elastic carotid artery can be considered structurally more similar to central arteries (such as the aorta³⁵) than the non-elastic predominantly conduit coronary arteries, perhaps contributing to the tighter correlation.

While CAC is a well-established predictor of cardiovascular events³⁶, TAC has been less thoroughly studied with regard to cardiovascular outcomes. Thoracic aortic calcification measured by plain radiography and transesophogeal echocardiography has a well established correlation with obstructive coronary disease^{37, 38}. TAC measured by CT is highly correlated CAC and predicts incidence and progression of CAC³⁹. Amongst patients with stable angina pectoris, TAC is an independent predictor of adverse cardiovascular events⁴⁰. However, among 2,304 asymptomatic self-referred adults, TAC failed to predict events beyond the Framingham Risk Score and beyond CAC⁴¹. A total of 31% of patients (724 total patients) had measurable TAC in this study, likely limiting its discriminatory power. It has not been explored whether TAC predicts adverse aortic outcomes, such as aortic aneurysm, dissection, or rupture, although aortic atherosclerosis is closely associated with ischemic stroke⁴².

Limitations

Before clinical utility of this application of carotid ultrasound can be established, the chicken-and-egg question remains paramount – does carotid stiffness precede the development of aortic calcification, or is calcinosis a generalized phenomenon that alters the elastic properties of the artery wall? The first major limitation of this study is its cross-sectional nature. While we are able to describe the association of carotid stiffness with calcific atherosclerosis, we are unable to establish temporal relationship. The utility of measures of carotid stiffness would be augmented if early vascular disease was identified, in anticipation of the development of measurable calcification and atherosclerosis. We have planned follow-up studies within MESA to help address this question.

The second major limitation is the use of brachial pulse pressure, rather than a direct measurement of carotid pulse pressure. Peripheral arteries, such as the brachial artery, have pressure wave reflection sites that are closer than for central arteries. Reflected waves travel faster on peripheral arteries, which are stiffer, than on the elastic central arteries, which in asymptomatic patients are more elastic. Due to this ‘amplification phenomenon’, the pulse pressure in the brachial artery will be higher than in the carotid artery, which may lead to systematic underestimation of true carotid distensibility⁴³. MESA participants did not undergo carotid applanation tonometry, which would be required for direct measurement of local carotid pressure. However, it has been suggested that use of brachial blood pressure would in fact lead to systematic underestimation of the association between stiffness and adverse events⁴⁴.

Perspectives

The results of this study suggest that non-invasive ultrasound measures of carotid artery stiffness demonstrate a “dose-response” association with calcification of the thoracic aorta. The independence of this relationship from carotid IMT, in addition to the greater association with TAC compared to CAC, raises important mechanistic questions and highlights the complexity of the interplay between stiffening, calcinosis, and atherosclerosis. In the future, a combination of these measurements may provide the most comprehensive evaluation of subclinical vascular disease. To evaluate the prognostic significance of these relationships, we have planned longitudinal studies within MESA.

Abbreviations List

DC

distensibility coefficient

TAC

thoracic aorta calcification

CT

computed tomography

IMT

intima-media thickness

CRP

C-reactive protein