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J Am Coll Cardiol, 2006; 47:1967-1975, doi:10.1016/j.jacc.2005.12.058 (Published online 20 April 2006).
© 2006 by the American College of Cardiology Foundation
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CLINICAL RESEARCH: ATHEROSCLEROSIS

Relationship Between Cardiovascular Risk Factors and Atherosclerotic Disease Burden Measured by Intravascular Ultrasound

Stephen J. Nicholls, MBBS, PhD*,1,4, E. Murat Tuzcu, MD*,3,4, Tim Crowe, BS*, Ilke Sipahi, MD*,2, Paul Schoenhagen, MD*, Samir Kapadia, MD*, Stanley L. Hazen, MD, PhD*,3,4, Chuan-Chuan Wun, PhD{dagger}, Michele Norton, PhD{dagger}, Fady Ntanios, PhD{dagger} and Steven E. Nissen, MD*,3,4,*

* Department of Cardiovascular Medicine, The Cleveland Clinic Foundation, Cleveland, Ohio
{dagger} Pfizer Pharmaceuticals, New York, New York

Manuscript received September 19, 2005; revised manuscript received December 7, 2005, accepted December 13, 2005.

* Reprint requests and correspondence: Dr. Steven E. Nissen, Department of Cardiovascular Medicine, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio 44195 (Email: nissens{at}ccf.org).


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
OBJECTIVES: The goal of this study was to determine the relationship between established cardiovascular risk factors and the extent of coronary atherosclerotic plaque.

BACKGROUND: Few data exist correlating cardiovascular risk factors with volumetric measurements of coronary atheroma burden in patients with coronary artery disease.

METHODS: Clinical characteristics, quantitative coronary angiography, and intravascular ultrasound (IVUS) were evaluated in subjects enrolled in a study comparing atorvastatin and pravastatin. Plaque areas were measured at 1-mm intervals to compute atheroma volume. The percent of cross sections with an abnormal intimal thickness (>0.5 mm) was determined. Data on cardiovascular risk factors were collected.

RESULTS: In 654 subjects, atheroma volume averaged 174.5 mm3 and percent atheroma volume 38.9%. Atherosclerosis was present in 81.2% of 25,897 cross sections. In univariate analysis, there was a strong association between diabetes, male gender, and a history of either prior revascularization or stroke with percent atheroma volume. Hypertension or prior myocardial infarction was also predictive of more severe disease. Low-density lipoprotein and C-reactive protein were not significant predictors of greater disease burden. In multivariate analysis, diabetes, male gender, and a history of a prior interventional procedure remained strong predictors of increased atheroma volume. History of stroke, non-Caucasian race, and smoking status remained significant. Although multiple measures of IVUS disease burden were worse in subjects with diabetes, angiographic stenosis severity was not different.

CONCLUSIONS: Male gender, diabetes, and a history of prior revascularization are strong independent predictors of atherosclerotic burden in coronary disease patients. Many risk factors did not predict angiographic disease severity, suggesting different mechanisms drive stenosis development and atheroma accumulation.

Abbreviations and Acronyms
  BMI = body mass index
  CAD = coronary artery disease
  CRP = C-reactive protein
  EEM = external elastic membrane
  HDL = high-density lipoprotein
  IVUS = intravascular ultrasound
  LDL = low-density lipoprotein
  PAV = percent atheroma volume
  QCA = quantitative coronary angiography
  TAV = total atheroma volume

Necropsy examinations typically demonstrate extensive atherosclerosis in patients who succumb to coronary artery disease (CAD) (1–3). Although the relationship between a number of cardiovascular risk factors and clinical event rates is well established, it remains unclear whether the presence of risk factors correlate with the extent of atherosclerosis. Several groups have employed quantitative coronary angiography (QCA), cross-sectional assessment of a single slice of coronary artery by intravascular ultrasound (IVUS), carotid intimal-medial thickness, myocardial perfusion abnormalities, and coronary calcification to address this question (4–8). Some of these groups have reported relationships between individual risk factors or clinical risk scores and both the extent and annual progression rate of plaque. However, none of these techniques measure the actual volume of coronary atherosclerotic plaque.

Intravascular ultrasound is a relatively new imaging technique that generates high-quality tomographic images of coronary atheromata (9). Using a motorized pullback apparatus, a series of cross-sectional plaque measurements can be obtained and summated to determine atheroma burden. Intravascular ultrasound has been applied to study the effects of lipid-lowering therapy on atherosclerosis progression in patients with CAD and hyperlipidemia (10). Quantitative coronary angiography and IVUS were performed, enabling systematic analysis of the relationship between a wide variety of risk factors and plaque burden.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Study design.   The Reversal of Atherosclerosis with Aggressive Lipid Lowering (REVERSAL) trial was a prospective, double-blind, multicenter, parallel-treatment study comparing the effects of atorvastatin 80 mg and pravastatin 40 mg. Patients between the ages of 30 and 75 years, with a clinical indication for diagnostic coronary angiography were enrolled. Eligibility required evidence of CAD on screening angiography, defined as the presence of one or more stenoses in a native coronary artery with ≥20% luminal diameter narrowing by visual estimation. A "target vessel" containing a segment >30 mm in length with ≤50% reduction in lumen diameter was selected for IVUS examination. A target vessel was considered suitable only if the artery had never undergone revascularization. At baseline, a physical examination was performed, and lipid levels and high-sensitivity C-reactive protein (CRP) were measured in a core laboratory (Medical Research Laboratory, Highland Heights, Kentucky). Lipid entry criteria required a low-density lipoprotein (LDL) cholesterol between 125 and 210 mg/dl after a 4- to 10-week washout period. The presence of the metabolic syndrome was defined by an adaptation of the Adult Treatment Panel (ATPIII) of the National Cholesterol Education Program. Because measures of abdominal girth were not recorded, this component was replaced by a body mass index (BMI) ≥30 kg/m2.

Quantitative angiography.   Coronary angiography of the target vessel was performed using standardized methods. Patients were pre-treated with 100 to 300 µg of intracoronary nitroglycerin and selective contrast angiography performed using pre-defined acquisition angles. Measurements were performed using a computer-assisted system (11). Angiographic images were analyzed in a blinded core laboratory (Cleveland Clinic Foundation) where technicians identified the segment imaged during the IVUS procedure and subsequently measured vessel borders to calculate luminal diameters and percent stenosis. Measurements were only made in the segment that was assessed by IVUS. Comparison of the diameter of the contrast-filled angiographic catheter tip with its known dimensions was used to calibrate the system. The percent diameter stenosis and percent area stenosis are reported for the site with the smallest lumen diameter.

IVUS acquisition.   After diagnostic angiography, the operator performed a motorized IVUS pullback in a single major epicardial vessel as previously described (12). After anticoagulation with heparin, a guidewire was subselectively placed in the vessel, and a 30-MHz, 2.6-F (0.87-mm) IVUS catheter (Ultracross, Boston Scientific Scimed, Inc., Maple Grove, Minnesota) was advanced into the target vessel. The transducer was positioned distal to a side branch and a motorized pullback apparatus employed to progressively withdraw the IVUS transducer at a pullback speed of 0.5 mm/s. During pullback, IVUS images were obtained at 30 frames/s and recorded on Super-VHS videotape (Fig. 1).


Figure 1
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  		Figure 1 Method for selection of cross sections for analysis. Cross sections are obtained for "slices" selected at 1-mm intervals (top). Three of the 48 cross sections illustrated for this vessel are shown at the bottom (cross sections 10, 26, and 48).

 
IVUS core laboratory analysis.   Videotapes containing the IVUS pullbacks were analyzed in a core laboratory by personnel blinded to all patient characteristics (Cleveland Clinic Foundation). An operator digitized the videotape and selected the origin of a distal side-branch as a "fiduciary point" from which to begin analysis (Fig. 1). This frame was selected as the image immediately before the takeoff of the distal side branch. Subsequently, every 60th image in the pullback was selected for analysis, representing a series of cross sections spaced exactly 1 mm apart over a length of 30 to 90 mm. The final analyzed cross section is the last image in the sequence before appearance of the left main coronary artery or right coronary ostium (Fig. 1).

Direct IVUS measurements.   Intravascular ultrasound measurements were performed in accordance with the standards of the American College of Cardiology and European Society of Cardiology (13). A calibration procedure was performed by measuring 1-mm grid marks encoded in the IVUS image by the scanner. For each cross section selected for analysis, the operator performed manual planimetry to trace the leading edges of the luminal and external elastic membrane (EEM) borders (Fig. 2). The minimum and maximum diameters of the vessel and the minimum and maximum intimal thicknesses were directly measured. A cross section was defined as atherosclerotic if maximum intimal thickness exceeded 0.5 mm at any point in the vessel circumference (4 standard deviations greater than the upper limit of normal) (14).


Figure 2
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  		Figure 2 Method for analysis of atheroma area. The left panel shows a representative intravascular ultrasound cross section. The right panel illustrates the boundaries planimetered for the external elastic membrane (EEM) and lumen. Atheroma area is calculated.

 
Derived IVUS measurements.   Atheroma area was calculated as EEM area minus luminal area. The total atheroma volume (TAV) was calculated as the sum of atheroma areas for each 1-mm cross section (13).

Formula
As the pullback length was determined by the distance between the proximal and distal side branches, there was considerable heterogeneity in the length of segment that was analyzed. To compensate for this difference between subjects, a normalized TAV was derived for each subject by multiplication of mean atheroma area (total volume for the subject divided by the number of images analyzed) for a subject by the median number of analyzable segments for all subjects (10).

Formula
The percent atheroma volume was computed as the ratio of sum of atheroma areas divided by the sum of EEM areas (15).

Formula
This represents the average percent of EEM area occupied by atheroma within the examined vessel. The IVUS percent area stenosis was determined for the site with the smallest lumen diameter as the ratio of atheroma area divided by EEM area. For each vessel, the percentage of cross sections meeting the predefined criteria for atherosclerosis (intimal thickness >0.5 mm) was determined, and this value is reported as "percent abnormal cross sections" (13).

Statistical methods.   Analyses were performed using SAS 6.12 software (SAS, Inc., Cary, North Carolina). Demographics and clinical characteristics are summarized for all randomized patients. Categorical variables are described using frequencies, while continuous variables are reported as median and interquartile ranges. Univariate predictors are reported using linear regression analysis of rank-transformed outcome. Multivariate analysis used multiple linear regression analysis of rank-transformed outcome. Two regression model selection approaches were used. The forward regression approach initially contained no variables (null model). Only variables with a p value <0.15 on univariate analysis were included. One variable was added at a time into the multivariate model from the most significant to the least significant. Only variables that resulted in a p value <0.5, when comparing the current model with the previous model, were included. In the backward elimination approach, the multivariate model commenced including all variables. One variable was removed at a time, proceeding from the least significant to the most significant. Only variables with p values <0.1 were retained in the model at each step. This process was continued until all remaining variables in the model had p values <0.1.


   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Patient demographics.   A total of 654 patients were enrolled in the study. Patient characteristics are summarized in Tables 1 and 2Go as previously reported (10). The cohort included a relatively young median age (56 years), a history of angina in 89.8%, history of hypertension in 67.1%, and a history of diabetes in 19.6%. The most significant physical examination finding was an increased BMI (median 29.8 kg/m2). The metabolic syndrome, defined using the guidelines of the National Cholesterol Education Program, substituting BMI >30 kg/m2 for waist circumference, was present in 41.0% of patients. Laboratory parameters included median LDL cholesterol of 147 mg/dl, median high-density lipoprotein (HDL) of 41 mg/dl, and a median CRP of 2.9 mg/dl.


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  		Table 1. Patient Characteristics (n = 654)
 

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  		Table 2. Physical Examination and Laboratory Parameters (n = 654)
 
Angiographic and IVUS disease burden.   Angiographic and IVUS measures of disease burden are summarized in Table 3. The angiogram typically contained a single lesion within the examined vessel, which averaged 39% in diameter stenosis and 62.8% in area stenosis at the most severely narrowed site. By IVUS, TAV averaged 174.5 mm3 over a median pullback length of 36 mm, and the percent of EEM area occupied by atheroma for the entire vessel averaged 38.9% (percent atheroma volume). For the entire cohort, 81.2% of all cross sections were atherosclerotic, using the pre-defined criteria of a maximum intimal thickness >0.5 mm.


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  		Table 3. Angiographic (QCA) and IVUS Measures of Disease Burden (n = 654)
 
Univariate predictors of percent atheroma volume.   Table 4 summarizes the univariate predictors of IVUS disease burden. For percent atheroma volume, there was a very strong association between presence of diabetes, male gender, and a history of prior revascularization or stroke and atherosclerotic burden. For percent atheroma volume, a history of a prior myocardial infarction or hypertension and non-Caucasian race were also predictors of more severe disease. Total cholesterol, LDL cholesterol, HDL cholesterol, CRP, and smoking were not predictors of disease severity.


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  		Table 4. Univariate Predictors of IVUS Disease Burden (n = 654)
 
Univariate predictors of normalized TAV.   Univariate predictors of normalized TAV are summarized in Table 4. There was a very strong association between male gender, non-Caucasian race, and a history of prior revascularization and atherosclerotic burden. A history of diabetes or hypertension, systolic and diastolic blood pressure, HDL cholesterol, and age were also predictors of more severe disease. Total cholesterol, LDL cholesterol, CRP, and smoking were not predictors of disease severity.

Univariate predictors of percent abnormal cross sections.   Univariate predictors of disease burden were similar, but not identical, to the parameters that were significant for percent atheroma volume (Table 4). Male gender, diabetes, HDL levels, and a history of revascularization or stroke were strong predictors. Total cholesterol, LDL cholesterol, CRP, hypertension, and smoking were not predictors of disease severity.

Univariate predictors of angiographic stenosis severity.   Results of QCA studies are summarized in Table 5. In general, there were relatively few parameters predictive of angiographic disease severity, and the associations were not as strong as observed for IVUS data. A history of prior revascularization and a history of stroke were moderately predictive of more severe stenoses. Non-Caucasian race was marginally significant, and a history of prior myocardial infarction just failed to meet statistical significance.


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  		Table 5. Univariate Predictors of Angiographic Percent Area Stenosis (n = 654)
 
Multivariate predictors of IVUS disease burden.   These findings are summarized in Table 6. Diabetes, male gender, and a history of any prior procedure remained as strong predictors of increased percent atheroma volume. Prior stroke and non-Caucasian race were weak independent predictors of more severe disease after multivariate analyses. Current smoking was also a weak independent predictor of more severe disease, despite not being a univariate predictor. For normalized TAV, age, male gender, non-Caucasian race, BMI, and a history of diabetes or prior procedures remained as predictors. For percent abnormal cross sections, only diabetes and male gender remained as predictors and having a prior procedure was borderline significant.


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  		Table 6. Multivariate Predictors of IVUS Disease Burden (n = 654)
 
Multivariate predictors of angiographic stenosis severity.   These findings are summarized in Table 7. The strongest predictor was a history of prior procedure. Non-Caucasian race remained significant in the multivariate analysis, but the association was moderate. Prior history of angina just failed to meet statistical significance.


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  		Table 7. Multivariate Predictors of QCA Disease Burden (n = 654)
 
Diabetes and metabolic syndrome.   Tables 8 and 9Go summarize the relationships between key measures of disease burden and the presence or absence of diabetes or the metabolic syndrome. All IVUS measures of disease burden were more severe in patients with diabetes, including both measures of atheroma burden and stenosis severity. However, measures of minimum luminal diameter or percent narrowing by angiography were no different in patients with or without diabetes. In comparison with the cohort with diabetes, the relationship between the metabolic syndrome and IVUS disease burden was weaker, with no measure showing a significant relationship. Neither the presence of diabetes nor the metabolic syndrome showed a statistically significant relationship to angiographic measures of disease burden.


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  		Table 8. Disease Burden in Patients With Diabetes Versus Patients Without Diabetes
 

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  		Table 9. Disease Burden in the Metabolic Syndrome
 

   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
Epidemiologic data suggest a complex relationship between cardiovascular risk factors and clinical events in coronary disease patients (16). However, the relationship between cardiovascular risk factors and atherosclerotic disease burden is more difficult to evaluate. Data from necropsy studies only describe the extent of disease in patients who succumb to their disease or suffer from fatal trauma (1–3). Investigators have correlated risk factors with indirect measures of atherosclerotic burden, including carotid intimal-medial thickness, coronary calcification, or measures of stenosis severity, such as angiography (6–8). These approaches have important limitations. The risk factors associated with carotid atherosclerosis are different from those linked to coronary disease (17). Coronary calcification occurs late in atherogenesis, and angiography describes only luminal narrowing, not the true extent of atherosclerosis (18).

Intravascular ultrasound provides a high-resolution technique for quantitative assessment of vessel wall anatomy in living patients. Intravascular ultrasound provides a unique opportunity to study the interaction of risk factors with plaque burden. This study is the first large-scale IVUS trial measuring coronary atherosclerosis in hyperlipidemic patients. Diabetes, male gender, and a history of prior revascularization were particularly strong predictors of atheroma burden. Non-Caucasian race and a history of stroke also remained significant in multivariate analysis. In contrast, several risk factors, including hypertension, hyperlipidemia, and CRP, were less important than expected.

The absence of a strong association between cholesterol levels and IVUS measures of disease burden requires additional comment. Although HDL levels were predictive in univariate analysis, in terms of their association with TAV and the percentage of abnormal sections, none of the traditionally measured lipid values were independently predictive of disease burden. The apparent lack of association between lipids and atheroma burden is consistent with other available data. The high degree of overlap between cholesterol levels in patients with and without CAD is well established (19). These findings suggest that the interaction between lipid levels and other risk factors, such as inflammation or genetic susceptibility, determines whether abnormalities of lipid metabolism are expressed as atherosclerotic disease. This is in contrast to previous reports of a strong correlation between LDL levels and serial accumulation of atheroma (4). However, that study involved IVUS assessment of only one slice of the left main coronary artery in a small cohort of subjects. Given the multitude of etiologic factors that promote atherogenesis, it is not all that surprising that the degree of correlation between LDL levels and plaque burden is not particularly high. The current findings do not exclude the hypothesis that lipid levels play a role in determining atheroma vulnerability, but suggest that these effects may be independent of their impact on atheroma volume.

It was also intriguing that CRP, an emerging biomarker that predicts cardiovascular risk, was not associated with baseline measures of atherosclerotic burden. Reductions in CRP, in response to statin therapy, were recently demonstrated to correlate with both a reduction in clinical events and inhibition of plaque progression (20,21). This finding suggests that CRP may not be mechanistically linked to atheroma development, although reductions in its levels are beneficial. Combining the current and recently reported data suggests that the degree of reduction of both LDL and CRP with statin therapy has a greater influence on change in plaque burden, rather than their absolute levels at baseline. While evidence continues to emerge implicating a pivotal role for inflammatory events in CAD, it would appear that this association is related predominantly to promoting plaque vulnerability.

The findings in patients with diabetes and the metabolic syndrome are particularly noteworthy. Every IVUS measure of atherosclerotic burden showed more disease in patients with diabetes. While increased cardiovascular event rates in patients with diabetes has been described, the underlying pathophysiology remains incompletely defined. Many abnormalities in vascular and hematologic function have been described in diabetes resulting in endothelial dysfunction, defective thrombolysis, and enhanced platelet activity (22). The current study directly supports the conclusion that the diabetic state promotes atherosclerotic plaque development and suggests that enhanced atheroma burden may explain a significant proportion of the increased event rates noted in morbidity and mortality trials. Interestingly, there was a non-significant trend for an association between the metabolic syndrome and a greater TAV, but not percent volume, suggesting that the increases in atheroma volume were somewhat accommodated by adaptive coronary remodeling (23).

The relationship between cardiovascular risk factors and angiographic measures of disease burden is also intriguing. Only history of prior revascularization was a strong independent predictor of angiographic stenosis severity. Non-Caucasian race remained a less strong predictor in the multivariate analysis. In contrast with the IVUS findings, there was, remarkably, no relationship between diabetes or metabolic syndrome and angiographic stenosis severity. The limited correlation between risk factors and angiographic disease severity as monitored by QCA suggests two possible explanations. Focal angiographic stenoses may be produced by a different pattern of risk factors than global atheroma burden. Alternatively, the dissociation between IVUS and angiographic measures of disease burden more likely reflects the marked discrepancy in what each imaging modality measures (i.e., the size of the doughnut vs. the size of the doughnut hole). For vessels with diffuse narrowing, the "normal" reference segment may also contain substantial atheroma burden, and, consequently, percent stenosis by angiography will systematically underestimate disease burden (18).

A number of potential limitations of this analysis should be noted. While all subjects had angiographic disease, the observations cannot be extrapolated to distinguish the ability of risk factors to predict the presence or absence of CAD. The presence of a lipid range for inclusion in the study introduces a potential bias in the assessment of a relationship between lipid levels and plaque burden. It is uncertain whether a relationship does in fact exist at levels of LDL cholesterol that fall outside of this range. Assessment of plaque burden was made by performing a volumetric measurement of plaque through a segment of coronary artery. While atherosclerosis is a diffuse process, it is possible that within a particular subject the extent of atheroma within the studied segment does not reflect the disease contained in the remainder of that artery or coronary arterial tree in general. The cohort is relatively young, and it is uncertain whether similar relationships between risk factors and plaque burden are seen in an older population. Finally, it should be noted that, due to the absence of abdominal girth measurements, an amended definition was used for metabolic syndrome that may have influenced its incidence and, therefore, its potential relationship with plaque burden.

In conclusion, the present data demonstrate greater atheroma burden in patients with diabetes, men, and patients with a history of prior revascularization. In comparison with IVUS, there was a more limited relationship between risk factors and angiographic measures of disease severity. These findings further highlight the complex relationship promoting the translation of traditional and emerging risk factors and the incidence of cardiovascular disease.


   Footnotes
 
The REVERSAL study was funded by Pfizer. This work was supported in part by grants P01 HL 076491 and HL077692 from the National Institutes of Health. Neil Weissman acted as guest editor for this paper.

1 Dr. Nicholls is supported by a Ralph Reader Overseas Research Fellowship from the National Heart Foundation of Australia. Back

2 Dr. Sipahi has received an educational grant from Pfizer. Back

3 Drs. Nissen, Tuzcu, and Hazen have each received research support from Pfizer. Back

4 Drs. Nicholls, Nissen, Tuzcu, and Hazen have received speaking honoraria from Pfizer. Back


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

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S. J. Nicholls, E. M. Tuzcu, and S. E. Nissen
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J. Am. Coll. Cardiol., November 7, 2006; 48(9): 1915 - 1916.
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C. von Birgelen and M. Hartmann
Coronary Plaque Burden and Cardiovascular Risk Factors: Single-Point Versus Serial Assessment
J. Am. Coll. Cardiol., November 7, 2006; 48(9): 1914 - 1915.
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