|Impaired aortic distensibility measured by computed tomography is associated with the severity of coronary artery disease.|
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|PMID: 20711815 Owner: NLM Status: MEDLINE|
|Impaired aortic distensibility index (ADI) is associated with cardiovascular risk factors. This study evaluates the relation of ADI measured by computed tomographic angiography (CTA) with the severity of coronary atherosclerosis in subjects with suspected coronary artery disease (CAD). Two hundred and twenty-nine subjects,age 63 ± 9 years, 42% female, underwent coronary artery calcium (CAC) scanning and CTA, and their ADI and Framingham risk score (FRS) were measured. End-systolic and end-diastolic (ED) cross-sectional-area(CSA) of ascending-aorta (AAo) was measured 15-mm above the left-main coronary ostium. ADI was defined as: [(Δlumen-CSA)/(lumen-CSA in ED × systemic-pulse-pressure) × 10(3)]. ADI measured by 2D-trans-thoracic echocardiography (TTE) was compared with CTA-measured ADI in 26 subjects without CAC. CAC was defined as 0, 1-100, 101-400 and 400+. CAD was defined as luminal stenosis 0, 1-49% and 50%+. There was an excellent correlation between CTA- and TTE-measured ADI (r(2)=0.94, P=0.0001). ADI decreased from CAC 0 to CAC 400+; similarly from FRS 1-9% to FRS 20% + (P<0.05). After adjustment for risk factors, the relative risk for each standard deviation decrease in ADI was 1.66 for CAC 1-100, 2.26 for CAC 101-400 and 2.32 for CAC 400+ as compared to CAC 0; similarly, 2.36 for non-obstructive CAD and 2.67 for obstructive CAD as compared to normal coronaries. The area under the ROC-curve to predict significant CAD was 0.68 for FRS, 0.75 for ADI, 0.81 for CAC and 0.86 for the combination (P<0.05). Impaired aortic distensibility strongly correlates with the severity of coronary atherosclerosis. Addition of ADI to CAC and traditional risk factors provides incremental value to predict at-risk individuals.|
|Naser Ahmadi; Vahid Nabavi; Fereshteh Hajsadeghi; Ferdinand Flores; Shahdad Azmoon; Hussain Ismaeel; David Shavelle; Song S Mao; Ramin Ebrahimi; Matthew J Budoff|
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|Type: Comparative Study; Journal Article Date: 2010-08-15|
|Title: The international journal of cardiovascular imaging Volume: 27 ISSN: 1875-8312 ISO Abbreviation: Int J Cardiovasc Imaging Publication Date: 2011 Mar|
|Created Date: 2011-05-11 Completed Date: 2011-09-06 Revised Date: 2013-05-29|
Medline Journal Info:
|Nlm Unique ID: 100969716 Medline TA: Int J Cardiovasc Imaging Country: United States|
|Languages: eng Pagination: 459-69 Citation Subset: IM|
|© The Author(s) 2010.|
|Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, 1124 W. Carson Street, RB2, Torrance, CA 90502, USA. email@example.com|
|APA/MLA Format Download EndNote Download BibTex|
Analysis of Variance
Aorta / physiopathology*, ultrasonography
Coronary Angiography / methods*
Coronary Stenosis / physiopathology, radiography*, ultrasonography
Predictive Value of Tests
Severity of Illness Index
Tomography, X-Ray Computed*
Journal ID (nlm-ta): Int J Cardiovasc Imaging
Publisher: Springer Netherlands, Dordrecht
© The Author(s) 2010
Received Day: 15 Month: 1 Year: 2010
Accepted Day: 28 Month: 7 Year: 2010
Electronic publication date: Day: 15 Month: 8 Year: 2010
pmc-release publication date: Day: 15 Month: 8 Year: 2010
Print publication date: Month: 3 Year: 2011
Volume: 27 Issue: 3
First Page: 459 Last Page: 469
PubMed Id: 20711815
Publisher Id: 9680
|Impaired aortic distensibility measured by computed tomography is associated with the severity of coronary artery disease|
Address: +310-222-2773 +310-787-0448 firstname.lastname@example.org
|Song S. Mao1|
|Matthew J. Budoff1|
1Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, 1124 W. Carson Street, RB2, Torrance, CA 90502 USA
2Greater Los Angeles VA Medical Center, UCLA, School of Medicine, Los Angeles, CA USA
3University of Southern California, Los Angeles, CA USA
4New York Medical College, Valhalla, NY USA
Vascular dysfunction has been shown to be an independent predictor of adverse cardiovascular events [1–3]. Impaired vascular function is associated with coronary artery disease , hypertension , diabetes [6, 7], and hypercholesterolemia [8–10].
Arterial distensibility, a measure of vascular function, can serve as a marker of coronary heart disease risk in humans [11, 12], In addition animal studies suggest that reduced arterial distensibility is an early sign of atherosclerotic change . Previous studies revealed an inverse relationship between aortic distensibility and cardiovascular risk factors and may predict outcome [14–16].
The aorta maintains low left ventricular after-load, promotes optimal subendocardial coronary blood flow , and transforms pulsatile into more luminar blood flow. Impaired aortic distensibility leads to higher left ventricular systolic pressures, diminished subendocardial blood supply  and may ultimately contribute to left ventricular dysfunction [18, 19].
Coronary artery calcium (CAC) is a marker of overall atherosclerotic burden and correlates well with the total plaque burden, the presence of obstructive coronary artery disease (CAD) and future cardiovascular events in both genders across ethnicities [20–22]. Systemic vascular dysfunction measured through reactive hyperemia procedure is strongly correlated with increasing Framingham risk score (FRS) and CAC independent of age, sex, and traditional cardiac risk factors and is superior to FRS for the prediction of significant CAC .
This study evaluates whether impaired aortic distensibility index (ADI) is associated with the severity of coronary atherosclerosis in at-risk individuals.
Two hundred and twenty-nine consecutive subjects referred for coronary artery calcium (CAC) scanning and CTA for suspected coronary artery disease (CAD) were enrolled. Patients with established cardiovascular disease, stroke, diabetic retinopathy, Raynaud’s syndrome, infection, cancer, immunosuppression, systemic inflammation, advanced renal or liver disease, creatinine >1.4 mg/dl, and triglyceride >400 mg/dl were excluded. In a sub-study, 26 patients with normal coronaries and CAC 0 underwent 2D trans-thoracic echocardiography (TTE). The ascending aorta diameter and cross-sectional area measured by CTA and TTE were compared. Risk factors were determined, and FRS was calculated to assess the risk of developing total coronary disease events (angina, myocardial infarction, or cardiovascular death) over the next 10 years .
The coronary arteries were imaged with 30–40 contiguous 3 mm slices during mid-diastole using ECG-triggering during a 15 s breath hold. CAC was considered present in a coronary artery when a density of >130 Hounsfield units (HU) was detected in ≥3 contiguous pixels (>1 mm2) overlying that coronary artery and quantified using the previously described Agatston scoring method .
Beta blockers were administered for pulses greater than 65 bpm. CTA was performed according to standard clinical technique with retrospective ECG gating and ECG pulsing applied. Mean heart rate during the scan was 57 ± 2 bpm.
A 64- Multi-detector Computed Tomography (MDCT) scanner (Lightspeed VCT, General Electric Healthcare Technologies, Milwaukee, WI) was used for all subjects. Imaging was started 1 inch above the left main ostium and continued to 1 inch below the bottom of the heart. The following imaging and reconstruction parameters were applied: data acquisition collimation 0.625 mm × 64 = 4 cm; 120 kVp; 220–670 mAs; pitch 0.18–0.24 (depending on heart rate); rotation time 0.35 s; slice width 0.625 mm; matrix 512 × 512 and pixel size 0.39 mm2. ECG-triggered dose modulation was applied in each case with 400–600 mA in 60–80% R–R interval and 250–350 mA for the rest of the cardiac cycle (81 to 59% of the next cycle).
Cardiac data were reconstructed from 5 to 95% of R–R interval and with 10% intervals. Coronary vessels were reviewed (AW Volume Share™, GE Medical Systems, Milwaukee, WI) and volume renderings and curved multi-planar reformations were done. CAC was defined as CAC 0, CAC 1–100, CAC 101–400 and CAC 400+. CAD was defined as normal coronaries, non-obstructive and obstructive CAD (luminal stenosis 1–49 and 50%, respectively). Two skilled cardiologists blinded to the clinical data measured the CAC and interpreted CTA separately.
The principle of aortic distensibility measurement is illustrated in Fig. 1. The window level and width of 300 and 800 HU was used. True CSA and diameter of ascending aorta (AAo) was measured both manually and with the automated software (Workstation AW 4.4, GE Medical Systems, Milwaukee, WI) using the aligned and adjusted planes. The CSA and diameter of AAo were measurements 15 mm above the ostium of left main artery . AAo diameter and CSA were measured from 5 to 95% of the R–R interval in 10% increments. Maximum AAo diameter and CSA was observed at end-systolic phase, 35% of R–R interval in individuals with a heart rate ≤60 bpm. AAo diameter and CSA decreased linearly from end-systole to end-diastole phases from 35 to 95% of R–R interval; which the minimum AAo diameter and CSA was observed at the end-diastolic (95% of R–R interval) phase.
Consensus was reached with a third expert measurement in case of disagreements between the manual and automated measures (2 cases).
ADI was defined as: [ADI = (∆ lumen AAo CSA)/(end-diastole AAo CSA × systemic pulse pressure) × 103] [27, 28]. Δlumen AAo CSA is defined as: end-systolic AAo CSA − end-diastolic AAo CSA. Brachial artery blood pressure was measured before and after CTA acquisition, and the mean value was calculated.
In a sub-study, 26 subjects with normal coronaries and CAC 0 underwent TTE within a week after cardiac CTA. AAo diameter was measured 15 mm above sinotubular junction in the M-mode tracings, guided by the two-dimensional long parasternal axis  using Hewlett-Packard Sonos 5,500 echocardiographic system (Hewlett-Packard Corporation, Palo Alto, CA). Simultaneous recording of the ECG during TTE permitted evaluation of changes in AAo diameter during various phases of cardiac cycle, and reliable comparison with CTA measured AAo diameter. AAo cross section area (CSA) was calculated from 35%, end-systolic-, and 95%, end-diastolic-phase, of echocardiogram measured diameter with the assumption that the CSA is circular (area = (diameter/2)2 × (π)). TTE and CTA measured ADI was driven from calculated and measured AAo CSA, respectively.
Mean ± SD and proportions were used to summarize the characteristics of the study group. Continuous variables were compared by ANOVA, and categorical variables were compared by the Kruskal–Wallis multivariate analysis. Inter-observer and inter-modality (CTA vs. TTE) variability of AAo diameter measurement were calculated using intra-class correlation coefficient (ICC), and Bland & Altman plots . Relative risk regression analyses were employed to assess the association between the severity of CAC and ADI, also the association between ADI and CAD before and after adjustment for conventional cardiovascular risk factors, as well as for Framingham risk score. ROC curves were constructed and the area under the ROC curve (AUC) was calculated to predict the ability of each model to detect a) significant CAC (CAC 100+), and B) significant CAD (obstructive CAD), respectively. All statistical analyses were performed with PASW version 18.0 (SPSS Institute Inc, Chicago, IL, http://www.spss.com). The level of significance was set at P < 0.05 (two-tailed). The study protocol was approved by the IRB Committee Board of the Los Angeles Biomedical Research Institute at Harbor UCLA, Torrance, California and all patients provided written informed consent.
CTA measured ADI was compared to the TTE measured ADI. There was excellent correlation between CTA and TTE measured ADI (r2 = 0.94, ICC = 0.99, P = 0.0001). However, CTA measured ADI was 3.4% higher than TTE. (Figure 2a) There was excellent inter-observer agreement in measuring ADI using TTE and CTA. The inter-observer variability was higher with TTE than CTA (Fig. 2b).
Patients were characterized based upon the severity of CAC and placed into one of 4 groups (CAC 0, 1–100, 101–400 and 400+) (Table 1). There were no significant differences in gender, smoking status, diabetes mellitus, hypertension, hypercholesterolemia, lipid profile, and family history of premature CAD between the cohorts. The mean age was higher in patients with significant CAC as compared to normal cohort. The Framingham risk score increased substantially with increasing CAC. In a sub-study in subjects with CAC zero, ADI decreased with the metabolic status from normal cohorts to diabetes mellitus (P < 0.05).
There was strong inverse correlation between ADI and CAC (r2 = −0.69, P = 0.0001). ADI decreased proportionally from CAC 0 to CAC 1–100 to CAC 101–400 to CAC 400+ in both genders (Fig. 3a and b). Furthermore, severity of CAC increased incrementally in each FRS category as ADI decreased; similarly, in each ADI category as FRS increased. The highest CAC was noted with the combination of the lowest tertile of ADI and FRS 20%+; The lowest ADI was observed in subjects with highest CAC and FRS (Fig. 3b). ADI decreased with the severity of metabolic status in each CAC category in which diabetics with CAC 400+ had the least ADI. (Figure 3c) After adjustment for age, gender, conventional cardiac risk factors, and FRS by relative risk regression analyses, the risk of each standard deviation decrease in ADI was 1.66 for CAC 1–100, 2.26 for CAC 101–400 and 2.32 for CAC 400+ as compared to CAC 0. (Table 2) Multivariate regression analysis showed that ADI was an independent predictor of the severity of CAC.
Increasing severity of CAD was associated with increase in CAC and FRS, and decrease in ADI (Table 1). After adjustment for age, gender, conventional cardiac risk factors, and CAC, ADI was independent predictor of significant CAD. (Table 3).
ROC curves were constructed to assess the ability of cardiovascular risk factors and ADI to predict: a) significant CAC, and b) significant CAD. The AUC for proposed models is summarized in Fig. 4. Addition of ADI to FRS increased the area under the ROC curve to predict significant CAC significantly from 0.63 to 0.84 (P < 0.05) and provided the largest contributor to significant CAC prediction. Similarly, addition of ADI to CAC and traditional risk factors increased the area under the ROC curve to predict significant CAD from 0.68 to 0.86.
The current study demonstrates that: 1. Excellent correlation exists between TTE and CTA measured ADI, 2- ADI decreased with the severity of metabolic status, 3. CTA measured ADI decreased proportionally with the severity of CAC independent of cardiovascular risk factors, and 4. Addition of ADI to FRS improved the ability to detect significant CAC from 0.63 to 0.84.
There is considerable heterogeneity in the magnitude of vascular dysfunction in individuals with similar risk factor profiles [31, 32]. In this regard, vascular dysfunction may be seen as an important “integrative factor” of the inherent atherosclerotic risk of an individual which takes into account the cumulative effects of various risk and protective factors . In addition to improving risk assessment for the prediction of cardiovascular outcomes, another important application of vascular function assessment is to evaluate response to therapies [33–37].
Arterial distensibility serves as a marker of the structure and function of the artery (i.e. vascular function) and has been shown to diminish with advancing age and with increasing cardiovascular risk factors . Recent studies have demonstrated that oxidative modification of LDL particles, and vascular wall remodeling induced by hyperglycemia may play a pathophysiological role in reducing arterial distensibility and revealed that aortic distensibility decreased with increasing cardiovascular risk factors [6, 8–10, 18, 19, 39].
Previous studies provided evidence that reduced arterial distensibility predicts future cardiovascular events [10, 15, 40]. Haluska et al. studied the association of arterial distensibility and long-term clinical outcome of 719 patients. They reported that impaired arterial distensibility independently correlated with poor outcome in patients with varying degrees of cardiovascular risk, and arterial distensibility can identify patients at risk of future fatal and non-fatal events . Finally, recent studies have shown that functional changes in arteries precede the development of structural changes and also reverse more quickly in response to therapies [37, 42–44].
Clinical guidelines recommend risk management based on the Framingham score [45, 46] followed by goal-directed therapy when necessary [47–49] in patients without known prior CAD. Recent studies have showed that FRS has significant limitation in identifying high risk subjects without known CAD [50, 51]. Current findings revealed that CTA provides an accurate measure for vascular function rather than just anatomical studies; Furthermore, in this study aortic distensibility decreased substantially with the severity of coronary atherosclerosis in both genders. The excellent correlations between impaired aortic distensibility measured by CTA and FRS, and, in particular, the superior independent and incremental value of aortic distensibility for predicting significant coronary atherosclerosis, highlight the role of vascular function assessment as a part of cardiovascular risk assessment to improve identification of high risk individuals and optimizing patient management.
Beta blockers which are vasoactive medications were administered for heart rates greater than 65 bpm. However, recent studies demonstrated that concomitant therapy with non-nitrate vasoactive drugs has no significant effect on vascular function assessment . The effect of data acquisition and analysis during a breath-hold is another potential source of error. Nonetheless, the CTA measurements correlated well with the TTE measurements, suggesting that potential errors introduced by non-simultaneous blood pressures and breath-hold are minimal.
Aortic distensibility measured by CTA correlates well with corresponding values measured by TTE. Impaired aortic distensibility is associated with the severity of coronary atherosclerosis independent of age, gender, and cardiovascular risk factors. Furthermore, addition of ADI to traditional risk factors and CAC provided the largest contribution to detect significant coronary atherosclerosis, and highlights the diagnostic utility of ADI in the early detection and monitoring of patients with atherosclerotic cardiovascular disease by a single noninvasive diagnostic study.
Disclosures Matthew Budoff has a financial disclosure in relationship to this study, as he is on the speaker’s bureau for General Electric, whereas other authors have no conflicts to disclose.
Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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Cardiovascular risk factors and the severity of coronary artery calcium
|Coronary artery calcium||Normal (N = 78)||CAC 1–100 (N = 42)||CAC 101–400 (N = 40)||CAC 400+ (N = 69)||P value|
|Age (years)||55 ± 10||55 ± 9||57 ± 9||61 ± 8||0.001|
|Family history of CHD||||40%||43%||57%||58%||0.1|
|BMI (kg/m2)||28.1 ± 3.6||28.8 ± 3.9||27.6 ± 5.1||28.4 ± 4.7||0.6|
|Total Cholesterol (md/dL)||191 ± 42||186 ± 37||171 ± 27||178 ± 43||0.7|
|HDL-C (mg/dL)||50 ± 10||46 ± 11||50 ± 14||46 ± 12||0.5|
|LDL-C (mg/dL)||116 ± 34||120 ± 26||100 ± 34||105 ± 39||0.4|
|Triglyceride (mg/dL)||112 ± 37||115 ± 28||96 ± 34||120 ± 32||0.2|
|SPB (mm Hg)||121 ± 11||129 ± 10||128 ± 15||132 ± 18||0.1|
|DBP (mm Hg)||75 ± 9||76 ± 8||76 ± 9||76 ± 9||0.9|
|Framingham risk score (%)||4.6 ± 2.6||5.2 ± 2.8||6.1 ± 3.3||8.9 ± 4.6||0.001|
|AAo 35% CSA (mm3)||49.71 ± 2.10||48.82 ± 1.77||47.02 ± 1.68||46.66 ± 1.75||0.08|
|AAo 95% CSA (mm3)||32.76 ± 1.91||33.34 ± 1.81||33.69 ± 1.69||34.14 ± 2.01||0.8|
|∆ AAo CSA/AAo 95% CSAΩ||0.57 ± 0.10||0.50 ± 0.07||0.39 ± 0.07||0.34 ± 0.06||0.003|
|ADI∆||10.7 ± 1.31||8.87 ± 1.13||7.29 ± 1.09||6.18 ± 0.92||0.003|
|CTA-Diagnosed coronary artery disease||Normal (N = 78)||CAD 1–29% (N = 35)||CAD 30–49% (N = 61)||CAD 70% (N = 55)||P value|
|Framingham risk score (%)||4.6 ± 2.6||5.2 ± 2.5||7.4 ± 4.7||9.8 ± 5.7||0.001|
|Coronary artery calcium||0||43 ± 26||279 ± 115||385 ± 220||0.0001|
|ADI∆||10.7 ± 1.31||8.62 ± 1.19||7.26 ± 1.21||5.71 ± 1.21||0.0001|
Values presented as mean ± SD or %
NS = Non-significant (P > 0.05)
† Self-reported diagnosis of hypertension, prescribed medication for hypertension, or current blood pressure >140 mmHg systolic or >90 mmHg diastolic (>130/80 mmHg if diabetic)
‡ Self-reported diagnosis of high cholesterol, prescribed medication for high cholesterol, or current total cholesterol >200 mg/dL
§ Self-reported diagnosis of diabetes (type 1 or 2) or prescribed medication for diabetes
|| First degree relative; female < 65 yrs, male < 55 years
Ω ∆ AAo CSA = (AAo 35% CSA- AAo 95% CSA)/AAo 95% CSA
∆ ADI = (∆ AAo CSA/systemic pulse pressure) × 103
Multivariate relative risk regression analysis of the relationship between the extent of coronary artery calcium and aortic artery distensibility
|Model||Normal||CAC 1–100||CAC 101–400||CAC 400+|
|ADI¥||1 (ref)||1.57 (1.28–1.93), P = 0.0001||2.18 (1.69–2.82), P = 0.0001||2.23 (1.78–2.78), P = 0.0001|
|Adjusted for age, gender, diabetes mellitus, hypertension, hypercholesterolemia, family history of CHD, and smoking status|
|ADI¥||1 (ref)||1.66 (1.39–3.46), P = 0.0001||2.26 (1.73–3.28), P = 0.0001||2.32 (1.85–5.62), P = 0.0001|
Relative risk for each standard deviation (SD) decrease in ADI (SD: 1.2)
Multivariate relative risk regression analysis of the relationship between the severity of coronary artery diseases and aortic artery distensibility
|Model||Normal||Non-obstructive CAD||Obstructive CAD|
|ADI¥||1 (ref)||2.29 (1.26–2.75), P = 0.0001||2.56 (1.94–3.36), P = 0.0001|
|Adjusted for age, gender, diabetes mellitus, hypertension, hypercholesterolemia, family history of CHD, smoking status and CAC|
|ADI¥||1 (ref)||2.36 (1.35–3.15), P = 0.0001||2.67 (1.93–3.56), P = 0.0001|
Relative risk for each standard deviation (SD) decrease in ADI (SD: 1.2)
Keywords: Keywords Aortic distensibility index, Computed tomographic angiography, Coronary artery calcium score, 2D Trans-thoracic echocardiography.
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