Huijun Chen1, Juan Wang2, Jie Sun3, Daniel S Hippe3, Xihai Zhao1, and Hongbing Liu2
1Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, People's Republic of, 2Cardiology, People’s Liberation Army General Hospital, Beijing, China, People's Republic of, 3Radiology, University of Washington, Seattle, WA, United States
Synopsis
Pharmacokinetic modeling of DCE-MRI
can quantify the adventitial vasa vasorum of carotid atherosclerotic lesions using the transfer constant (Ktrans). However, the relationship between the DCE-MRI quantified carotid adventitial
vasa vasorum and cardiovascular events
remains unclear. In this study, we found that the adventitial Ktrans of carotid artery measured by DCE-MRI was
associated with cardiovascular events (cerebral ischemic events and coronary artery events), suggesting that the carotid adventitial vasa vasorum is not merely a local risk factor
but also a promising systemic marker for cardiovascular risk. DCE-MRI may be valuable for identifying high risk patients in clinical
practice.Introduction
Neovasculature arising from the
vasa vasorum plays a significant role in atherosclerotic plaque progression and
destabilization (1). Dynamic contrast-enhanced (DCE) magnetic resonance
imaging (MRI) together with pharmacokinetic modeling has been validated with
histology to have the ability to characterize neovascularization and
adventitial vasa vasorum in atherosclerotic plaque by using the transfer
constant (
Ktrans) (2, 3).
However, the relationship between the DCE-MRI quantified adventitial vasa
vasorum of carotid atherosclerotic lesions and cardiovascular events (CVE)
remains unclear. Therefore, we sought to
investigate the relationship between CVE and neovasculature characteristics in
human carotid atherosclerosis quantified by DCE-MRI in this retrospective
study.
Methods
Population: After
institutional ethics approval and informed consent were obtained, seventy
patients (age: 66±12
years, 54male) with documented carotid plaque (intima-media
thickness≥2 mm) at ultrasound examination were recruited. Enrolled subjects had
their demographics and cardiovascular risk factors collected, including body
mass index (BMI), smoking, hypertension, diabetes, hypercholesterolemia. Prior
CVE were collected for each subjects, including coronary artery event (CAE) and
cerebral ischemic event (CIE). CAE was defined as
myocardial infarction or unstable angina pectoris with signs of myocardial
ischemia. CIE was defined as ischemic stroke or TIA.
Image acquisition and analysis: All subjects were
scanned on a 3.0T scanner (GE Medical Systems) with a custom designed 4-channel
carotid coil (University of Washington). Axial DCE images were acquired by a
multi-slice 2D SGRE sequence (3) centered at carotid bifurcation with parameters:
TR/TE=100/6.2ms, FA=30°, FOV=140×112mm2, matrix=256×192, slice thickness=2
mm, number of slices=6, time interval=18s. Coincident with the third phase, 0.1
mmol/kg of gadodiamide (Magnevist; Bayer Healthcare) was injected at a rate of
2 ml/s by a power injector. After bolus arrival, 10 phases were obtained. Other
than DCE-MRI, a standard 2D multi-contrast MR imaging protocol was also used to
obtain the morphological (maximum vessel wall thickness) and compositional
features (lipid rich/necrotic core (LRNC), calcification (CA), and intraplaque
hemorrhage (IPH)) of the carotid plaque (4). Blind review was performed using a
custom-designed software (CASCADE, University of Washington) (5). A
histology-validated post-processing and pharmacokinetic modeling approach was
used to obtain the adventitial transfer constant (
Ktrans) from the vasa vasorum image (Fig 1) derived from
DCE-MRI time series (2,3) for each subject.
Statistical
analysis: Variables were presented as mean±SD or n(%), and compared using Student
t-test or chi-square test as appropriate. Univariate and multivariate logistic
regression were performed to identify risk factors for CVE. The odds ratio (OR) and the 95%
confidence interval (CI) were reported for each factor.
Results
Of 70 patients, 6 (8.6%) were excluded because
of poor image quality. Of the remaining 64 patients (age: 66±12 years, 51 male), 12 (19%) had
no CVE and 52 (81%) suffered from CVE, including 32(50%) with CAE alone,
15(23%) with CIE alone, and 5 (8%) with both CAE and CIE. The characteristics of
CVE group and non-CVE group were summarized in Table 1. Among all features, patients
with CVE had higher carotid adventitial
Ktrans (0.056±0.024 min
-1) compared with subjects without CVE (0.034±0.008
min
-1) (p<0.001). The univariate and
multivariate logistic regression analysis further confirm that adventitial
Ktrans of
carotid artery was significantly and independently associated with CVE (OR: 2.8 per 0.01 min
-1 increase; 95%CI: 1.3-6.2; p=0.008), as well as smoking (OR: 8.4; 95%CI: 1.1-65; p=0.042) (Table
2). When analyzing the subgroups of CIE alone, CAE alone and CAE&CIE, the carotid
adventitial
Ktrans in patients
with both CAE and CIE (0.069±0.022 min
-1), CIE (0.056±0.018min
-1),
and established CAE (0.054±0.027min
-1) were all significantly higher
than patients without CVE (0.034±0.008 min
-1) (p<0.001,
respectively) (Fig 2).
Discussion and Conclusion
In this study, we found that the adventitial
Ktrans of carotid artery measured by DCE-MRI was
associated with cardiovascular events, including cerebral ischemic event and coronary artery event, suggesting that the neovasculature
characteristics in carotid artery is not merely a local vascular risk factor
but also a promising systemic marker for cardiovascular risk in other vascular
beds. DCE-MRI may be valuable for identifying high risk patients in clinical
practice.
Acknowledgements
This work was supported by
Army Medical Research Funds of China (11BJZ19) and Natural Science Foundation
of China (81371540).References
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