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J Am Coll Cardiol, 2007; 49:1533-1539, doi:10.1016/j.jacc.2006.11.046 (Published online 26 March 2007).
© 2007 by the American College of Cardiology Foundation
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CLINICAL RESEARCH: ATHEROSCLEROSIS

Vascular Inflammation Evaluated by [18F]-Fluorodeoxyglucose Positron Emission Tomography Is Associated With the Metabolic Syndrome

Nobuhiro Tahara, MD, PhD*,*, Hisashi Kai, MD, PhD*, Sho-ichi Yamagishi, MD, PhD*, Minori Mizoguchi, MD*, Hiroyuki Nakaura, MD, PhD*, Masatoshi Ishibashi, MD, PhD{dagger}, Hayato Kaida, MD, PhD{dagger}, Kenkichi Baba, MD{dagger}, Naofumi Hayabuchi, MD, PhD{dagger} and Tsutomu Imaizumi, MD, PhD*

* Department of Medicine, Division of Cardio-Vascular Medicine, Kurume, Japan
{dagger} Department of Radiology, Kurume University School of Medicine, Kurume, Japan.

Manuscript received August 18, 2006; revised manuscript received September 19, 2006, accepted November 19, 2006.

* Reprints requests and correspondence: Dr. Nobuhiro Tahara, Department of Medicine, Division of Cardio-Vascular Medicine, Kurume University School of Medicine, 67 Asahimachi, Kurume 830-0011, Japan. (Email: ntahara{at}med.kurume-u.ac.jp).


    Abstract
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Objectives: We investigated factors for carotid artery inflammation by [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET).

Background: Inflammation is present in some atherosclerotic plaques. The FDG-PET is capable of identifying and quantifying vascular inflammation within atherosclerotic plaques.

Methods: The FDG-PET imaging was performed in 216 consecutive patients (63 ± 9 years, men:women 147:69) for cancer screening. Vascular inflammation in carotid atherosclerosis was quantified by measuring the standardized uptake value (SUV) of FDG into the artery.

Results: Multiple stepwise regression analysis revealed significant relationships between SUV and waist circumference (p < 0.001), hypertensive medication (p < 0.001), carotid intima-media thickness (p < 0.001), high-density lipoprotein cholesterol (p < 0.01, inversely), homeostasis model assessment of insulin resistance (p < 0.05), or high sensitivity C-reactive protein (p < 0.05). Age- and gender-adjusted SUV of FDG was significantly higher (p < 0.0001) in proportion to the accumulation of the number of the components of the metabolic syndrome. Thus, the metabolic syndrome was associated with increased FDG uptake in carotid atherosclerosis.

Conclusions: Our present study may suggest that the metabolic syndrome is associated with inflammation in carotid atherosclerosis. (Detection of Plaque Inflammation by Positron Emission Tomography (PET); http://www.clinicaltrials.gov/ct/show/NCT00114504; NCT00114504 [ClinicalTrials.gov] )

Abbreviations and Acronyms
  BMI = body mass index
  BP = blood pressure
  CAD = coronary artery disease
  CT = computed tomography
  CVD = cerebrovascular disease
  FDG = [18F]-fluorodeoxyglucose
  FPG = fasting plasma glucose
  HDL = high-density lipoprotein
  HOMA-IR = homeostasis model assessment of insulin resistance
  hsCRP = high sensitivity C-reactive protein
  IMT = intima-media thickness
  IRI = immunoreactive insulin
  LDL = low-density lipoprotein
  PET = positron emission tomography
  SUV = standardized uptake value


There is a growing body of evidence showing that vascular inflammation is involved in atherosclerosis. Some atherosclerotic plaques contain numerous inflammatory cells, particularly macrophages, which secrete several kinds of enzymes, causing the weakening of the fibrous cap of plaques (1,2). Inflammatory plaques are considered vulnerable, prone to rupture. Plaque rupture and subsequent thrombus formation lead to acute myocardial infarction (3,4). Plasma levels of high sensitivity C-reactive protein (hsCRP) were reported to be higher in patients with unstable angina than they were in patients with stable angina (5). Thus, it is desirable to identify factors responsible for vascular inflammation within atherosclerotic plaques.

Recently, Rudd et al. (6) showed that [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) was able to detect inflammatory atherosclerotic plaques in 8 patients with symptomatic carotid atherosclerosis. They first underwent PET imaging and then carotid endarterectomy (6). Histologic analysis has revealed that the most part of FDG accumulation in carotid arteries corresponds to the macrophage-rich area of the atherosclerotic plaque (6). A study in rabbits has demonstrated that the FDG uptake is attributed to infiltrating macrophages and/or smooth muscle cells within atherosclerotic lesions (7). These observations suggest that FDG-PET is capable of identifying and quantifying vascular inflammation within atherosclerotic plaques. In this study, we investigated factors for carotid inflammation by FDG-PET.


    Methods
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Design and subjects.   A total of 236 consecutive subjects who received FDG-PET for cancer screening underwent carotid artery ultrasonography and a general health check-up including blood tests. The Ethical Committee for the Clinical Research of Kurume University approved this study. All subjects gave informed consent. We excluded patients with: 1) aortitis or vasculitis; 2) active inflammatory diseases; 3) acute coronary syndrome; 4) uncontrolled hypertension; 5) uncontrolled diabetes mellitus; 6) insulin treatment for diabetes mellitus; 7) cancers; and 8) systemic disorders such as severe hepatic, renal, and hematologic diseases. Finally, we studied 216 subjects (147 men and 69 women). Of 216 subjects, 15 had history of ischemic cerebrovascular disease (CVD), including strokes and transient ischemic attacks, but they did not have episodes of cardiovascular events or receive any interventional therapy for the last 12 months.

Data collection.   A questionnaire was administered to evaluate medical history, smoking habits, and drug use. Height and weight were measured, and body mass index (BMI, kg/m2) was calculated as an index of obesity. After at least 5-min rest, blood pressure (BP) was measured in a supine position using a standard sphygmomanometer.

After overnight fast, peripheral blood was drawn from the antecubital vein for the measurements of lipid profile, fasting plasma glucose (FPG), fasting immunoreactive insulin (IRI), glycosylated hemoglobin A1c, creatinine, uric acid, and hsCRP. These chemistries were measured at a commercially available laboratory (The Kyodo Igaku Laboratory, Fukuoka, Japan). Insulin resistance was estimated using the homeostasis model assessment of insulin resistance (HOMA-IR) from FPG and IRI concentrations using the following formula: HOMA-IR = (fasting IRI [µU/ml] x FPG [mg/dl])/405. Creatinine clearance was calculated with the Cockcroft-Gault equation (8).

Metabolic syndrome.   The diagnostic criteria of metabolic syndrome according to NCEP ATP III (National Cholesterol Education Program Adult Treatment Panel III) (9) are based on specific cutoff points in the following 5 categories: 1) abdominal obesity: waist circumference >101.6 cm in men and >88.9 cm in women; 2) fasting triglycerides ≥150 mg/dl; 3) high-density lipoprotein (HDL) cholesterol <40 mg/dl in men and <50 mg/dl in women; 4) BP ≥130/85 mm Hg (either value) or use of antihypertensive medication; and 5) FPG ≥110 mg/dl or defined diabetes patients. However, Japanese are much smaller than Caucasians; therefore, it is not appropriate to use the criteria of abdominal obesity of ATP III (10). Since the International Diabetes Federation recently published new criteria that modified ATP III definition in Japanese, we adopted a waist circumference of >85 cm for men and >90 cm for women, proposed by the International Diabetes Federation (11).

Measurement of carotid intima-media thickness (IMT).   The IMT of the common carotid artery was determined using duplex ultrasonography (SSA-380A, Toshiba, Tokyo, Japan) with a 10-MHz transducer. Longitudinal B-mode images at the diastolic phase of the cardiac cycle were recorded by a single trained technician who was blinded to the subject’s background. The images were magnified and printed using a high-resolution line recorder (LSR-100A, Toshiba). Measurements of carotid IMT were made by the same technician using fine slide calipers at 3 levels of the lateral and medial walls 1 cm to 3 cm proximal to the carotid bifurcation. The mean of these 6 measurements was taken as the value for the carotid IMT (12).

FDG-PET imaging.   After at least 12 h of fasting, the study patients received an intravenous administration of 4.2 MBq (0.12 mCi) of FDG per kg of body weight. One hour after FDG injection, 3-dimensional whole-body PET imaging was carried out using a PET scanner (Allegro, Philips Medical Systems [Cleveland], Inc., Cleveland, Ohio). We performed an attenuation correction for the PET imaging by a rotating rod of activity in the PET scanner. Contrast enhanced computed tomography (CT) images were also taken from the skull base to the diaphragm using Light Speed Ultra 16 (GE Healthcare, Milwaukee, Wisconsin). Positron emission tomography has spatial resolution limitations. The average transverse spatial resolution is about 5 mm (National Electrical Manufacturers Association standard), which may be too large to dissect plaques from other tissues. To overcome spatial resolution limitations of PET in this study, co-registration of PET and CT imaging (PET/CT imaging) was performed for review on a workstation (Sun Microsystems, Inc., Santa Clara, California), as described previously (6). The intensity of FDG uptake was quantified by measuring the standardized uptake value (SUV) corrected for total body weight. The SUV was calculated by using the maximum pixel activity value within the region of interest placed on the vascular wall of the transaxial PET/CT image of the common carotid artery. The SUV score was determined as the average of the SUVs of both the common carotid arteries obtained from 10 consecutive PET/CT images, each separated by 4 mm in length with the most cranial site starting at the carotid bifurcation. Two blinded radiologists measured the SUV, and the measurements were averaged. The intraobserver or interobserver variability of SUV measurements was <5%.

Statistical analysis.   Data were described as mean ± SD. Discontinuous variables were coded as dummy variables. Because of skewed distributions, the natural logarithmic transformations were performed for triglycerides, FPG, HOMA-IR, and hsCRP before data analyses. The univariate correlation between SUV of FDG and the values of each risk factor were assessed by dividing patients into quartiles on the basis of SUV of FDG, and analyzed with analysis of variance or chi-square test. To determine final parameters related to the carotid FDG levels, multiple stepwise regression analysis was performed. Carotid FDG levels stratified by the number of the metabolic syndrome were compared using analysis of covariance, adjusted for age and gender. Values of <0.05 were considered to indicate statistical significance.


    Results
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Clinical characteristics.   The age of the subjects enrolled ranged from 39 to 80 years with a mean of 63 ± 9 years of age. One hundred seventy-four subjects were non-smokers, and 42 were smokers. Systolic and diastolic BP were 136 ± 18 mm Hg and 82 ± 12 mm Hg, respectively. Average total cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides, and HDL cholesterol levels were 216 ± 38 mg/dl, 130 ± 31 mg/dl, 123 ± 7 mg/dl, and 55 ± 16 mg/dl, respectively. Mean FPG, HOMA-IR, and hemoglobin A1c levels were 104 ± 6 mg/dl, 1.42 ± 0.08, and 5.6 ± 0.7%, respectively. Mean creatinine clearance was 82 ± 27 ml/min. Mean BMI was 24 ± 3 kg/m2. The mean number of components of the metabolic syndrome was 2.0 ± 1.3. The prevalence of medication for hypertension, hypercholesterolemia, and diabetes mellitus was 41.7%, 11.1%, and 7.9 %, respectively. Mean SUV of FDG in the carotid artery was 1.38 ± 0.19.

Table 1 shows the clinical variables stratified by quartiles of SUV of FDG. A significant correlation between SUV of FDG and BMI (p < 0.001), waist circumference (p < 0.001), carotid IMT (p < 0.001), systolic BP (p < 0.05), HDL cholesterol (p < 0.001, inversely), HOMA-IR (p < 0.001), uric acid (p < 0.001), hsCRP (p < 0.01), or medication for hypertension (p < 0.001) existed. Standardized uptake value of FDG was not correlated with current smoking, heart rate, diastolic BP, total cholesterol, LDL cholesterol, and creatinine clearance.


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Table 1 Clinical Variables Stratified by Quartiles of SUV
 
For the significant factors shown in Table 1, we performed multiple stepwise regression analysis (Table 2). Waist circumference (p < 0.001), hypertensive medication (p < 0.001), carotid IMT (p < 0.001), HDL cholesterol (p < 0.01, inversely), HOMA-IR (p < 0.05), and hsCRP (p < 0.05) remained significant and were independently related to carotid FDG levels. Thus, factors of the metabolic syndrome were associated with carotid FDG uptake. Furthermore, age- and gender-adjusted SUV of FDG increased in proportion to the accumulation of the number of the components of the metabolic syndrome (p < 0.0001) (Fig. 1).


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Table 2 Multiple Stepwise Regression Analysis for Factors Associated With SUV of FDG Levels in Carotid Artery
 

Figure 1
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Figure 1 Age- and Gender-Adjusted Mean SUV of [18F]-Fluorodeoxyglucose Levels

SUV = standardized uptake value.

 
FDG-PET imaging.   Figure 2A shows representative images of FDG-PET in carotid artery of a normal subject and a patient with the metabolic syndrome. Figure 2B shows representative transaxial carotid artery images of FDG-PET and CT in a patient with the metabolic syndrome. Co-registration of FDG-PET and CT revealed that FDG was uptaken into the plaque of carotid artery.


Figure 2
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Figure 2 Representative Coronal Images of FDG-PET in the Carotid Arteries of a Normal Subject and a Patient With the Metabolic Syndrome

Red arrows indicate vascular [18F]-fluorodeoxyglucose (FDG) uptake within the carotid arteries in a patient with the metabolic syndrome (right, A). Representative transaxial images of FDG positron emission tomography (PET), contrast enhanced computed tomography (CT), and the co-registration of PET and CT (PET/CT), showing FDG uptake within the carotid artery in the patient with metabolic syndrome (B). Black arrow-arrowhead denotes vessel wall or atherosclerotic plaque. Red arrow-arrowhead indicates FDG vascular uptake.

 

    Discussion
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To our knowledge, the present study provides the first evidence showing the positive association of components of the metabolic syndrome with FDG uptake in carotid atherosclerosis detected by PET imaging. Further, in this study, we found that the FDG accumulation in carotid artery was significantly higher in proportion to the increased number of the components of the metabolic syndrome. These observations may suggest that the metabolic syndrome is associated with inflammation in carotid atherosclerosis.

Methodologic consideration.   In the present study, we enrolled a population who had no clinical evidence of active inflammation of vessels such as aortitis syndrome and collagen disease. The low levels of hsCRP preclude such diseases as well. We also excluded patients with a recent episode of cerebrovascular events. These strict exclusion criteria obviated the influence of these disorders on vascular inflammation in carotid artery detected by FDG-PET imaging. We did not exclude patients on the use of small doses of aspirin or statin, which may decrease inflammation because it is not ethically feasible to stop these medications.

We simultaneously performed contrast-enhanced CT and obtained PET/CT images in order to clarify whether FDG accumulated in the vessel wall or arterial lumen. As shown in the representative Figure 2, FDG accumulated in the vessel wall. Blood pool activity may be a source of FDG uptake. However, this possibility was unlikely for the following reasons. First, FDG uptake was not uniformly distributed along the course of carotid artery. Second, the jugular vein did not show any uptake of FDG. Third, the clearance of FDG is too rapid to stay in the circulation 1 h after injection of the tracer. Because of the problem of spatial resolution, we did not determine the exact location of FDG accumulation in the vessel wall or in the plaque. However, as shown in the representative image of Figure 2B, strong FDG accumulation was observed in the lesion that protruded into the lumen, thus suggesting FDG accumulation within the atherosclerotic plaque. In conjunction with our hypothesis, Rudd et al. (6) found histologically that FDG accumulation was located within the atherosclerotic plaques in 8 human specimens.

For quantitative analysis of inflammation, we evaluated SUV in the carotid arteries. The SUV is a quantitative parameter of glucose metabolic rate, and thus high SUV indicates inflammation. In this study, the mean SUV of carotid arteries was 1.38 ± 0.19 (ranging from 1.00 to 1.93). Although mean SUV was not so high, some patients (n = 30) had SUV >1.6, a figure that has been reported for some types of malignancies (13,14). It is interesting to note that the SUV level (marker of local inflammation) was significantly correlated with hsCRP (marker of systemic inflammation).

High FDG uptake of the carotid artery in metabolic syndrome.   Atherosclerosis is now widely accepted as a vascular inflammatory disorder. In this study, we could not only visualize the inflammation within carotid atherosclerosis, but also quantitatively estimate inflammation by SUV of FDG uptake. The most novel finding of the present study is that increased FDG uptake of the carotid artery is associated with the metabolic syndrome.

Multiple stepwise regression analysis revealed significant relationships between SUV and waist circumference, hypertensive medication, carotid IMT, HDL cholesterol, HOMA-IR, or hsCRP. Among them, the strongest determinant of SUV was waist circumference; HOMA-IR was also significant. These findings suggest that visceral obesity or insulin resistance is a strong determinant of SUV of the carotid artery. Accordingly, we investigated the relationship between SUV of the carotid artery and metabolic syndrome. As shown in Figure 1, SUV was significantly higher in patients with metabolic syndrome (components ≥3) than it was in those without, suggesting the role of metabolic syndrome in vessel inflammation.

We reanalyzed the data in the population without coronary artery disease (CAD) or CVD. Standardized uptake value of FDG in patients with CAD or CVD was also significantly higher than SUV of patients without CAD and CVD (1.47 ± 0.21 vs. 1.36 ± 0.18, p < 0.01). Again, age- and gender-adjusted SUV of FDG in patients without CAD or CVD was also significantly higher (p < 0.0001) in proportion to the accumulation of the number of the components of the metabolic syndrome. These results suggest that the increased carotid artery FDG uptake is associated with the metabolic syndrome, independent of vascular disease.

Interestingly, HDL cholesterol, an antiatherogenic and anti-inflammatory lipoprotein, was negatively correlated with SUV. In our recent study, we found by FDG-PET that the decrease of SUV of the carotid artery by the treatment with simvastatin, a 3-hydroxy-3-methylglutarylcoenzyme A reductase inhibitor, was correlated to the increase in HDL cholesterol level in plasma (15). Taken together, by FDG-PET, we were able to demonstrate the negative impact of HDL cholesterol on vessel inflammation in humans. A couple of investigators have previously reported that the FDG accumulation in human aorta and ilio-femoral artery are independently associated with age and hypercholesterolemia (16,17). However, in this study, age and cholesterol were not related to inflammation of the carotid artery. Several reasons are considered. First, they evaluated the inflammation visually and semiquantitatively; we evaluated it quantitatively by the use of SUV. Second, the backgrounds of the subject population are different; our subjects were much younger and not so hypercholesterolemic compared with the previous studies.

It is not clear from our study why waist circumference was the strongest determinant of vascular inflammation in carotid atherosclerosis. It is well recognized that visceral obesity, a key player in the development of the metabolic syndrome, may cause inflammation (18–20). Indeed, adipose tissues secrete various types of proinflammatory adipocytokines such as monocyte chemoattractant protein-1 and tumor necrosis factor-alpha (21,22). In supporting this, hsCRP levels were significantly associated with carotid FDG uptake. Unfortunately, we did not measure blood levels of these adipocytokines.

Study limitations.   This study was cross-sectional and thus could not assess the question of whether vascular inflammation detected by FDG-PET was a cause or consequence of the metabolic syndrome. Future longitudinal studies are needed to determine whether therapeutic lifestyle change and/or pharmacologic therapy of abdominal obesity or insulin resistance could decrease the SUV of FDG in carotid arteries and subsequently reduce the risk of future cardiovascular events in our subjects. Although we were able to visualize the inflammation, it is unknown for sure whether the plaques with FDG accumulation are really unstable; in other words, we could not assess whether patients with high accumulation of FDG in carotid arteries would develop ischemic vascular events and whether FDG-PET is really useful for risk stratification. Prospective studies are needed to address these issues.

The lack of use of a hybrid PET-CT is another limitation. In this study, software fusion of PET and CT images was carefully performed at the denoted level of spinal cord by 3 radiologists blinded to clinical information. Under these conditions, we could clearly separate uptake in the carotids from uptake in muscle or other tissues in the neck.


    Conclusions
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 Abstract
 Methods
 Results
 Discussion
 Conclusions
 References
 
Waist circumference was the strongest determinant of carotid FDG uptake detected by PET imaging, and FDG uptake was higher in proportion to the accumulation to the number of the components of the metabolic syndrome. Our results may suggest that metabolic syndrome is associated with inflammation in carotid atherosclerosis.


    Footnotes
 
This study was supported, in part, by a research grant from the Kimura Memorial Foundation to Dr. Imaizumi; by a grant from the Ishibashi Foundation for the Promotion of Science to Dr. Tahara; by a grant from Fukuda Foundation for Medical Technology to Dr. Tahara; by a grant from Mitsui Life Social Welfare Foundation to Dr. Tahara; and by a grant for the Academic Frontier Project from the Ministry of Education, Science, Sports, Culture, and Technology, Japan (Cardiovascular Research Institute, Kurume University).


    References
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