Impact of Metabolic Syndrome on Tissue Characteristics of Angiographically Mild to Moderate Coronary Lesions

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1 Journal of the American College of Cardiology Vol. 49, No. 11, by the American College of Cardiology Foundation ISSN /07/$32.00 Published by Elsevier Inc. doi: /j.jacc CLINICAL RESEARCH Atheroma Composition and Metabolic Syndrome Impact of Metabolic Syndrome on Tissue Characteristics of Angiographically Mild to Moderate Coronary Lesions Integrated Backscatter Intravascular Ultrasound Study Tetsuya Amano, MD, PHD,* Tatsuaki Matsubara, MD, PHD, Tadayuki Uetani, MD, PHD,* Michio Nanki, MD, PHD,* Nobuyuki Marui, MD, PHD,* Masataka Kato, MD,* Kosuke Arai, MD,* Kiminobu Yokoi, MD,* Hirohiko Ando, MD,* Hideki Ishii, MD, Hideo Izawa, MD, PHD, Toyoaki Murohara, MD, PHD Nagoya, Japan Objectives Background Methods Results Conclusions We assessed the impact of metabolic syndrome (MetS) on the tissue characteristics of coronary plaques using integrated backscatter intravascular ultrasound (IB-IVUS). Metabolic syndrome is associated with the increasing risk of cardiovascular disease. We identified MetS by the definition of the National Cholesterol Education Program in Adult Treatment Panel III criterion. Non-target coronary lesions with mild to moderate stenosis were measured by conventional and IB- IVUS parameters using 40-MHz (motorized pullback 0.5 mm/s) intravascular catheter. A total of 20 IB-IVUS images were recorded at an interval of 0.5 mm for 10 mm length in each plaque. The 3-dimensional analyses were performed using commercially available software. The prevalence of MetS was 61 patients (50%) with 73 lesions (49%) among 122 patients with 148 lesions. Patients with MetS showed a significant increase in percentage lipid area (38 19% vs %, p 0.02) and percentage lipid volume (39 17% vs %, p 0.03), and they also showed a significant decrease in percentage of fibrous volume (57 14% vs %, p 0.03). Multivariate regression analysis after adjustment for potentially confounding risk factors showed that MetS remains correlated independently with the percentage of lipid volume (r 0.223, p 0.01). Logistic regression analysis after adjusting for confounding and non-mets coronary risk factors showed that MetS (odds ratio 4.00, 95% confidence interval 1.33 to 12.0, p 0.01) is proved to be an independent predictor of the lipid-rich plaque. Metabolic syndrome is associated with lipid-rich plaques, contributing to the increasing risk of plaque vulnerability. (J Am Coll Cardiol 2007;49: ) 2007 by the American College of Cardiology Foundation Metabolic syndrome (MetS) is characterized by the concurrence of cardiovascular disease (CVD) risk factors: impaired glucose tolerance, obesity, dyslipidemia, and hypertension. Recent epidemiologic studies have showed that MetS is an increasing risk factor for CVD (1,2). On the other hand, it has been reported (3,4) that disruption or erosion of vulnerable plaques and subsequent thrombosis are the most frequent causes of acute coronary syndrome (ACS) and that the culprit coronary lesion in ACS shows a relatively minor stenosis, 50% of the reference diameter (5,6). Furthermore, postmortem studies have identified several histologic From the *Department of Cardiology, Chubu-Rosai Hospital, Nagoya, Japan; Department of Internal Medicine, School of Dentistry, Aichi-Gakuin University, Nagoya, Japan; and Department of Cardiology, Nagoya University Graduate School of Medicine, Nagoya, Japan. Manuscript received August 31, 2006; revised manuscript received October 30, 2006, accepted November 6, characteristics of these vulnerable plaques, such as greater plaque burdens and greater lipid area (7). Intravascular ultrasound allows cross-sectional imaging of coronary arteries and provides more comprehensive assessment of atherosclerotic plaque in vivo. Recently, Kawasaki et al. (8) have developed an integrated backscatter intravascular ultrasound (IB-IVUS), which allows analyzing tissue components of coronary plaque in vivo and shows that vulnerable plaques caused by ACS are relevant to increase in plaque burden, including greater lipid pool (9). Regarding the association of MetS with vessel atherosclerosis, several studies have shown that the individual components of MetS are related to measurements of subclinical atherosclerosis such as carotid intima-media thickness (10,11). Few studies, however, have examined the relevance of MetS as an entity with coronary plaque, especially with its tissue components. To assess the relevant detail of MetS and coronary plaque morphology is

2 1150 Amano et al. JACC Vol. 49, No. 11, 2007 Metabolic Syndrome and Plaque Characteristics March 20, 2007: Abbreviations and Acronyms ACS acute coronary syndrome AMI acute myocardial infarction ATP Adult Treatment Panel CSA cross-sectional area CVD coronary vessel disease EEM external elastic membrane %FV percentage of fibrous volume IB-IVUS integrated backscatter intravascular ultrasound IVUS intravascular ultrasound LCSA lumen crosssectional area %LV percentage of lipid volume MetS metabolic syndrome NCEP National Cholesterol Education Program PCI percutaneous coronary intervention QCA quantitative coronary angiography 3D three-dimensional UAP unstable angina pectoris more important from a prevention perspective. In the present study using IB-IVUS, we assessed the impact of MetS on tissue characteristics with mild to moderate coronary lesions in patients with CVD, taking into account possible confounding factors. Methods Patients and study design. This study was a prospectively planned observational study for non-target coronary lesions with mild to moderate stenosis (percentage diameter stenosis 50%) in patients with angina pectoris recruited to undergo an elective percutaneous coronary intervention (PCI). Patients with acute myocardial infarction (AMI) were excluded. Intravascular ultrasound was performed on 126 consecutive patients with 154 coronary arteries between September 2005 and August Unstable angina pectoris (UAP) was defined as either angina with a progressive crescendo pattern or angina that occurred at rest. Various lipid and inflammatory profiles were measured by commercial radioimmunoassay kits and specific immunoradiometric assays. For this purpose, blood samples were collected from patients before PCI in a 10- to 12-h overnight fast. QCA analysis and IVUS procedure. Before performance of coronary angiography and PCI, patients were administered an intracoronary 0.5 mg of isosorbide dinitrate to prevent coronary spasm. Online quantitative coronary angiography (QCA) analysis was conducted, and reference diameter and percentage diameter stenosis were measured by a validated automated edge-detection program (CMS- MEDIS Medical Imaging System, Leiden, the Netherlands). Analysis segments, vessels narrowing at 50% for reference diameter, were selected with QCA by 2 independent observers unaware of the clinical data. Another coronary artery was analyzed when the selected segments by QCA were 20 mm from the target site of PCI and when the IVUS catheter would not cross the lesion because of severe stenosis. Intravascular ultrasound was performed to 1 or 2 arterial segments of each patient. A personal computer equipped with custom software (IB-IVUS, YD Co., Ltd., Nara, Japan) was connected to the IVUS imaging system (Clear View, Boston Scientific, Natick, Massachusetts) to obtain radio frequency signal output, signal trigger output, and video image output. Ultrasound backscattered signals were acquired using a 40 MHz (motorized pullback 0.5 mm/s) mechanically rotating IVUS catheter in order to be digitized and subjected for spectral analysis. Integrated backscatter values for each tissue component were calculated as an average power using a fast Fourier transform, measured in decibels (db), of the frequency component of backscattered signal from a small volume of tissue (8,9). A total of 20 IB-IVUS images were captured at an interval of 0.5 mm for 10 mm length at each plaque. Measurements of conventional and IB-IVUS parameters. In the conventional IVUS analysis, cross-sectional images were quantified for lumen cross-sectional area (LCSA), external elastic membrane (EEM), cross-sectional area (CSA), and plaque (P) media (M) cross-sectional area (P M CSA EEM CSA LCSA) using software built in the IVUS system. Eccentricity index of P M was calculated as: (maximum P M thickness minimum P M thickness)/maximum P M thickness. Remodeling index was defined as a ratio of EEM CSA at the measured lesion (minimum luminal site) to reference EEM CSA (average of the proximal and distal reference segments). The eccentricity index and the remodeling index were calculated in the segment with minimal luminal area. The percentage of fibrous area (fibrous area/plaque area, %FA) and the percentage lipid area (lipid area/plaque area, %LA) were automatically calculated by the IB-IVUS system. The percentage of high signal area (a part of the calcification on the inner surface that could be measured with the formula of IB-IVUS/plaque area) was also automatically calculated by IB-IVUS as a high-signal area. Thrombus formation could not be differentiated and may, if present, have been included in IB-IVUS images. The technique described has not yet been modified to visualize mural or occlusive thrombus formation. Conventional 3-dimensional (3D) IVUS image analysis was conducted using commercially available software (TapeMeasure/EchoPlaque, Indec System, Mountain View, California). After digitalization of IVUS recordings at a frame rate of 30 images/s, longitudinal views of the studied segments were automatically processed by the system. The EEM CSA and LCSA were manually traced at 16-frame intervals, and interpolated measurements of the remaining frames were automatically generated. Then vessel volume, lumen volume, and total plaque volume were calculated. Three-dimensional analysis for IB-IVUS images was performed to fibrous volume, lipid volume, and high signal volume (sum of fibrous, lipid, and high signal area in each CSA at 0.5 mm axial intervals for the 20 IB-IVUS images, respectively). Then the percentage of fibrous volume (fibrous volume/plaque volume, %FV), lipid volume (lipid volume/plaque volume, %LV), and high signal volume (high signal volume/plaque volume) were calculated. The representative 3D color-coded maps of the coronary artery plaques in patients with or without MetS were also

3 JACC Vol. 49, No. 11, 2007 March 20, 2007: Amano et al. Metabolic Syndrome and Plaque Characteristics 1151 constructed as previously reported (12). In brief, the 3D IB IVUS color-coded maps consecutively connecting 20 images were digitized every 0.5 mm, and the number of voxels of lipid pool was automatically measured. The IVUS measurements were conducted independently by 2 physicians who did not recognize patient characteristics. The variability of %LV and %FV determined by 2 physicians was also considered from 30 randomly selected records. Definitions of MetS and coronary risk factors. Metabolic syndrome was defined by following criteria of the National Cholesterol Education Program (NCEP) in Adult Treatment Panel (ATP) III (13) and patients with 3 or more of the following criteria: 1) waist circumference (WC) 90 cm in women or 85 cm in men; 2) high-density lipoprotein Baseline Clinical Characteristics Table 1 Baseline Clinical Characteristics MetS ( ) (n 61) MetS ( ) (n 61) p Value Male 44 (72) 35 (57) 0.09 Age, yrs Ejection fraction, % Clinical history Hypertension 52 (85) 30 (49) Diabetes mellitus 46 (75) 24 (39) Current smoker 23 (38) 15 (25) 0.12 Unstable angina pectoris 10 (16) 11 (18) 0.81 Old myocardial infarction 14 (23) 9 (15) 0.25 Previous PCI 14 (23) 11 (18) 0.51 Previous CABG 4 (7) 3 (5) 0.70 Coronary artery disease Multiple vessel 32 (53) 31 (51) 0.86 Target plaque location Left anterior descending 37 (51) 38 (51) 0.99 Left circumflex 10 (14) 12 (16) 0.70 Right 26 (35) 25 (33) 0.77 Blood lipid levels, mg/dl Total cholesterol Triglycerides HDL cholesterol LDL cholesterol C-reactive protein, mg/dl Medication Aspirin 58 (95) 60 (98) 0.31 Ticlopidine 44 (72) 48 (79) 0.40 Statins 36 (59) 37 (61) 0.86 Fibrates 3 (5) 2 (3) 0.65 Angiotensin-converting enzyme inhibitors 12 (20) 10 (16) 0.64 Angiotensin II type 1 receptor antagonists 25 (41) 22 (36) 0.58 Nitrates 28 (46) 29 (48) 0.86 Calcium-channel 32 (53) 25 (41) 0.21 blockers Beta-blockers 35 (57) 31 (51) 0.47 Pioglitazone 7 (11) 4 (7) 0.35 Insulin 10 (16) 6 (10) 0.29 Values are mean SD or number of patients (%). CABG coronary artery bypass graft; HDL high-density lipoprotein; LDL low-density lipoprotein; MetS metabolic syndrome; PCI percutaneous coronary intervention. Data Angiography for Quantitative and Intravascular Coronary Ultrasound Table 2 Data for Quantitative Coronary Angiography and Intravascular Ultrasound MetS ( ) (n 73) MetS ( ) (n 75) p Value QCA analysis Reference diameter, mm Diameter stenosis, % Conventional IVUS analysis Vessel area, mm Lumen area, mm Plaque area, mm Plaque burden, % Eccentricity index Remodeling index Vessel volume, mm Lumen volume, mm Plaque volume, mm Plaque volume, % IB IVUS analysis Fibrous area, % Lipid area, % High signal area, % Fibrous volume, % Lipid volume, % High signal volume, % Values are mean SD. Data for the percentage diameter stenosis and for cross-sectional area analysis were calculated at the site of minimum luminal area. IB integrated backscatter; IVUS intravascular ultrasound; MetS metabolic syndrome; QCA quantitative coronary angiography. cholesterol 40 mg/dl; 3) serum triglycerides 150 mg/dl; 4) known hypertensives or blood pressure 130/85 mm Hg; and 5) fasting glucose 110 mg/dl. The cutoff values for WC were modified with the values used in Japanese populations (14). Diabetes mellitus was defined as using any anti-hyperglycemic medication and was counted as meeting the glucose criterion. Patients taking antihypertensive medication were not counted as meeting the blood pressure criterion because many CVD patients with normal blood pressure were receiving beta-blockers or calcium-channel antagonists to control angina, or they were receiving angiotensin-converting enzyme inhibitors to decrease cardiovascular risk. Smoking status was defined as current or quit within a year at baseline. All patients were given informed consent, and the study was approved by the Committee for Human Investigation of the investigator s institution. Statistical analysis. Statistical analysis was performed by the SAS statistical software package (version 8.02, SAS Institute, Inc., Cary, North Carolina). Continuous and categorical variables were expressed as mean SD and proportions, respectively. Univariate analysis was applied to compare clinical, laboratory, and ultrasound parameters between MetS and non-mets, by use of chi-square test and Fisher exact tests when appropriate for categorical variables and by unpaired Student t test for continuous normally distributed variables and Mann-Whitney U tests for nonnormally distributed variables. To account for repeated

4 1152 Amano et al. Metabolic Syndrome and Plaque Characteristics assessments to one patient, generalized estimation equations (GEE) linear regression (for continuous outcomes) or GEE logistic regression (for binary outcomes) was performed to estimate corrected probability values. In the present study, we performed a receiver operating characteristic curve analysis to assess the optimal cutoff values of %LV and %FV for the prediction of UAP. The lipid-rich plaque was defined as both an increase in %LV ( 52%) and a decrease in %FV ( 47%). We used linear regression analysis to examine the relationship of MetS with %LV and %FV adjusting for confounding (age, gender, and body mass index) and various non-mets risk factors (smoking, low-density lipoprotein [LDL] cholesterol, multivessel disease, and history of old myocardial infarction). Logistic regression analysis was applied to study for best predictors of the lipid-rich plaque after adjusting for confounding and various risk factors. Univariate predictors of %LV or %FV with a p value 0.2 were also entered into the model. Three groupings of individual components of MetS (risk 0 to 2, 3, and 4 to 5) Figure 1 JACC Vol. 49, No. 11, 2007 March 20, 2007: were evaluated using analysis of variance. Bonferroni test for multiple comparisons to determine their associations with the lipid-rich plaque rate was used with analysis of variance. A p value 0.05 was considered statistically significant. Results Study populations and baseline characteristics. One hundred and twenty-two patients with 148 anginaunrelated coronary lesions (a total of 2,960 IB-IVUS images) were evaluated in the present study. Four patients (2 patients with MetS) were excluded because IB-IVUS data were not available. The prevalence of MetS was 61 patients (50%), with 73 lesions (49%) among these patients. The mean values of continuous variables with normal distribution, including age, ejection fraction, total cholesterol, LDL cholesterol, and high-density lipoprotein cholesterol were compared between the 2 groups by use of unpaired Student t test. Mann-Whitney U tests were used Representative Images of Conventional Intravascular Ultrasound and 2-Dimensional Integrated Backscatter Intravascular Ultrasound Color-Coded Maps of Coronary Artery Plaques in Patients With or Without MetS (A) Patients with ( ) metabolic syndrome (MetS); (B) patients without ( ) MetS. The percentage of lipid area and the percentage of fibrous area were 46.1% and 50.1% in panel A, and 12.1% and 80.9% in panel B, respectively. Blue lipid pool; green yellow fibrous lesion; red high signal lesion.

5 JACC Vol. 49, No. 11, 2007 March 20, 2007: Amano et al. Metabolic Syndrome and Plaque Characteristics 1153 to evaluate differences in triglycerides and C-reactive protein. The frequency of gender, hypertension, diabetes mellitus, smoking, unstable angina pectoris, old myocardial infarction, previous PCI, previous coronary artery bypass graft, multi-vessel disease, target plaque location, and medication therapy was compared between the groups by chisquare analysis. There were no significant differences between the groups except for the MetS components (Table 1). Quantitative parameters of QCA and IVUS. In the QCA and IVUS parameters, vessel volume and plaque volume were compared between the 2 groups by the Mann-Whitney U test and the other parameters by unpaired Student t test. Table 2 shows quantitative QCA and IVUS findings. There were no significant differences in reference diameter ( mm vs mm, p 0.53) and percentage of diameter stenosis (24 9% vs. 22 7%, p 0.43) between patients with or without MetS. Also, in the conventional IVUS analysis, there were no significant differences in various parameters between the 2 groups. However, IB-IVUS analysis indicated that the patients with MetS were significantly increased in %LA (38 19% vs %, p 0.02) and %LV (39 17% vs %, p 0.03) and significantly decreased in %FV (57 14% vs %, p 0.03). Figure 1 shows the representative images of conventional IVUS and 2- dimensional IB-IVUS color-coded maps of coronary artery plaques in patients with MetS (Fig. 1A) or in patients without MetS (Fig. 1B). The %LA and %FA were 46.1% and 50.1% in (Fig. 1A) and 12.1% and 80.9% in (Fig. 1B), respectively. Figure 2 shows the representative images of 3D IB-IVUS color-coded maps of coronary artery plaques in the patients with MetS (Fig. 2A) and in the patients without MetS (Fig. 2B). The %LV and %FV were 52.7% Figure 2 Representative Images of the 3-Dimensional Integrated Backscatter Intravascular Ultrasound in Patients With or Without MetS (A) Patients with ( ) metabolic syndrome (MetS); (B) patients without ( ) MetS. The percentage of lipid volume was 52.7% in panel A and 23.0% in panel B. Blue and light blue lipid pool; green and yellow fibrous lesion; red high signal lesion.

6 1154 Amano et al. JACC Vol. 49, No. 11, 2007 Metabolic Syndrome and Plaque Characteristics March 20, 2007: and 43.8% in (Fig. 2A) and 23.2% and 71.2% in (Fig. 2B), respectively. The correlation of %LV and %FV measured by 2 physicians who conducted IVUS measurement independently was r 0.95 (p 0.01) and r 0.93 (p 0.01), respectively. Association of MetS with tissue characteristics of coronary plaque. On simple regression analysis, %LV and %FV were significantly correlated with UAP (r 0.197, p 0.02 and r 0.196, p 0.02), MetS (r 0.178, p 0.03 and r 0.179, p 0.03), and CRP levels (r 0.182, p 0.03 and r 0.184, p 0.03) (Table 3). A recent ACS is the typical clinical presentation of vulnerable plaques (3,4,9). Also, the increase in %LA and the decrease in %FA have been reported as an important prerequisite for ACS (9). The optimal cutoff values of %LV and %FV for predicting prevalence of UAP by receiver operating characteristic analysis were 52% and 47%, respectively. In the present study, the lipid-rich plaque was thus clarified as both increase in %LV ( 52%) and decrease in %FV Simple Volume Dependent Regression or Percentage VariableAnalysis Fibrous With Volume Percentage As thelipid Table 3 Simple Regression Analysis With Percentage Lipid Volume or Percentage Fibrous Volume As the Dependent Variable Variable Beta Coefficient t Ratio p Value Percentage lipid volume Unstable angina C-reactive protein Metabolic syndrome Multivessel disease Old myocardial infarction Statins LDL cholesterol Waist circumference Age Hypertension Smoke Triglycerides Male HDL cholesterol Diabetes mellitus Percentage fibrous volume Unstable angina C-reactive protein Metabolic syndrome Multivessel disease Statins Waist circumference Old myocardial infarction LDL cholesterol Triglycerides Age Hypertension Diabetes mellitus Smoke Male HDL cholesterol HDL high-density lipoprotein; LDL low-density lipoprotein. Variable Volume Multiple (r Regression 0.37, 0.40, p Analysis 0.03) 0.01) With as or Percentage the Dependent Fibrous Lipid Table 4 ( 47%), which gave the significant association with the incidence of UAP (odds ratio 10.1, 95% confidence interval 2.98 to 34.2, p ). Multivariate regression analysis after adjustment for confounding and non-mets risk factors showed that the prevalence of UAP and MetS remain correlated independently with %LV (r 0.314, p and r 0.223, p 0.01) and %FV (r 0.273, p and r 0.206, p 0.02) (Table 4). On logistic regression analysis, individual risk factors of CVD did not show the statistical power to predict the lipid-rich plaque (data not shown). Nevertheless, even after adjustment for confounding and non-mets risk factors, MetS identified by NCEP ATP III criteria (odds ratio 4.00, 95% confidence interval 1.33 to 12.0, p 0.01) was proved to be an independent predictor of the lipid-rich plaque (Table 5). Figure 3 shows the lipid-rich plaque rate for individual risks with 0 to 2, 3 and 4, or 5 component groupings of MetS. The lipid-rich plaque rate was significantly associated with an increasing number of MetS components in the grouping (p 0.002). Discussion Multiple Regression Analysis With Percentage Lipid Volume (r 0.40, p 0.01) or Percentage Fibrous Volume (r 0.37, p 0.03) as the Dependent Variable Variable Beta Coefficient t Ratio p Value Percentage lipid volume ( 52%) Unstable angina Metabolic syndrome Statins C-reactive protein Percentage fibrous volume ( 47%) Unstable angina Metabolic syndrome Statins C-reactive protein After adjusting for confounding (age, gender, and body mass index), predefined (multivessel disease and old myocardial infarction), and non-metabolic syndrome risk factors (smoking status and low-density lipoprotein cholesterol). Metabolic syndrome, a common clinical problem with high prevalence, has been associated with adverse cardiovascular risk and mortality, where ACS significantly affects mortal- Logistic for Prediction Regression of Lipid-Rich Model Plaque Table 5 Logistic Regression Model for Prediction of Lipid-Rich Plaque Variable Odds Ratio 95% CI p Value Unstable angina Metabolic syndrome Statins C-reactive protein After adjusting for confounding (age, gender, and body mass index), pre-defined (multivessel disease and old myocardial infarction), and non-metabolic syndrome risk factors (smoking status and low-density lipoprotein cholesterol). CI confidence interval.

7 JACC Vol. 49, No. 11, 2007 March 20, 2007: Amano et al. Metabolic Syndrome and Plaque Characteristics 1155 Figure 3 The Lipid-Rich Plaque Rate According to Increasing Numbers of MetS Components The lipid-rich plaque rate was significantly associated with an increasing number of metabolic syndrome (MetS) components in the grouping. p by analysis of variance (ANOVA). ity, morbidity and quality of life in these patients (1,2). On the other hand, evidence has accumulated that the lipid-rich plaque plays a critical role in the prevalence of ACS (3,4,9). Also, the culprit lesion in patients with ACS has reportedly shown to be a relatively minor stenosis ( 50% of the percentage diameter stenosis) (5,6). In the present study using IB-IVUS, the impact of MetS on tissue characteristics of the coronary plaques with angiographically mild to moderate coronary lesions was assessed, and our study found that MetS identified by NCEP ATP III criteria was significantly associated with an increase in %LV and a decrease in %FV. The result suggested a high prevalence of the lipid-rich plaque in these patients. Furthermore, MetS was proved to be an independent predictor of lipid-rich plaque even after adjustment for confounding and non- MetS risk factors. Individual risk factors and coronary plaque characteristics. The association of MetS with increasing atherosclerotic plaques is not surprising because individual components of MetS have been well established as risk factors for CVD (15). However, few data are available for assessing the correlation between these risk factors and tissue characteristics of coronary plaques. In the present study, individual risk factors were not relevant to the lipid-rich plaque. Nevertheless, patients with more than 3 clustering risks had significantly increased lipid-rich plaque rates, which is consistent with a previous report (10) showing the synergistic effects of risk factors on atherosclerosis. In keeping with the building evidence on the role of inflammation in CVD, inflammatory factors have been shown as significant predictors of atherosclerotic plaques (16 18). Nevertheless, CRP concentration was not significantly associated with the lipid-rich plaque. Conversely, statin use was negatively correlated with the lipid-rich plaque, consistent with previous reports (19,20) showing the beneficial effects of this drug on plaque stability. Consequently, the lack of correlation of lipid-rich plaque with CRP concentration suggests either that most of our included patients had ACS or that they were well treated with statins before the procedure. Impact of MetS on coronary plaque characteristics. In the present study, significant differences in the reference diameter and the percentage diameter stenoses measured by QCA were not recognized between patients with and without MetS. However, vessel volume and plaque volume in the conventional IVUS analysis showed a tendency to increase in patients with MetS compared with patients without MetS. These results suggest that vessels in patients with MetS might be compensatorily enlarged to prevent building atheroma from encroaching in lumen, thereby concealing the presence of a lesion when angiography is performed (21). In the IB-IVUS analysis, vessels in patients with MetS significantly increased in %LV and significantly decreased in %FV. This finding suggests the incidence of lipid-rich plaque. Furthermore, on logistic regression, the prevalence of MetS was independently associated with lipid-rich plaque. It has been reported that greater plaque volume, including lipid-rich components, is relevant to plaque vulnerability, resulting in increasing coronary events. Taken together, these findings might explain the mechanisms of MetS contributing to the increasing risk of cardiovascular events. Study limitations. This study has several limitations. First, the lipid-rich plaque defined in the present study might not be considered as a predominant marker of plaque vulnerability. In addition, this definition was performed in the study patients rather than a validation sample, raising the likelihood of a systematic error. Thus, we also arbitrarily defined the cutoff point for the lipid-rich plaque as shown in the previous report (22). Furthermore, the cutoff points were 49.3% for %LV and 49.2% for %FV, which were the 75th percentile of %LV and 25th percentile of %FV in the present study population. Following this definition, even after adjustment for confounding and non-mets risk factors, MetS was again significantly correlated with %LV (r 0.232, p 0.009) and %FV (r 0.225, p 0.01). Second, the thrombus formation, which is often not detected even with gray-scale ultrasound, was not color coded and analyzed by IB-IVUS. Angioscopic studies have revealed that plaque rupture and thrombus are present in 70% to 95% of patients with ACS and 20% of those with stable angina (23,24). Thus, a combination of these modalities should be tested to identify the vulnerable plaques in the future. Third, the study sample was relatively small, and patients with AMI were not included. The prevalence of coronary plaque characteristics in patients with AMI or in patients without CVD remains to be evaluated. Fourth, data on cardiac events should be collected in future studies, because we used a cross-sectional study design. Together with other results, our findings need further study to answer a number of questions definitively.

8 1156 Amano et al. JACC Vol. 49, No. 11, 2007 Metabolic Syndrome and Plaque Characteristics March 20, 2007: Conclusions Our findings indicate that MetS is significantly associated with lipid-rich plaque with mild to moderate coronary lesions. Furthermore, the prevalence of MetS has been proved to be an independent predictor of the lipid-rich plaque even after adjustment for confounding and traditional and non-mets risk factors. Together with other results, the study findings suggest that MetS identified by following NCEP ATP III criteria might be considered a surrogate maker for early stages of coronary atherosclerosis, especially in lipid-rich plaques, contributing to the increasing risk of plaque vulnerability. Reprint requests and correspondence: Dr. Tetsuya Amano, Chubu-Rosai Hospital, Cardiology, Kohmei , Minato-ku, Nagoya , Japan. amanot@med.nagoya-u.ac.jp. REFERENCES 1. Lakka HM, Laaksonen DE, Lakka TA, et al. 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