The rupture of unstable plaques in the coronary artery is believed to be the main reason for acute coronary syndrome, which usually results in high mortality and morbidity.1 The rupture of unstable plaques in the carotid artery can cause transient ischaemic attacks, stroke or sudden death.2,3 In an in vitro study, numbers of macrophages determined under the microscope correlated with the target to background ratio (TBR) as estimated by positron emission tomography and computed tomography (PET CT).4 A recent study demonstrated that inflammatory mechanisms triggered by monocytes and macrophages in atherosclerotic plaques are responsible for plaque instability,5 while neovascularization of the plaques helps to deliver the inflammatory cells to the plaques.6 Additionally, the high permeability of the intimal neovascularization accelerates penetration of inflammatory cells into plaques.7 However, another in vivo study speculated that the aggregation of inflammatory cells in the plaque is not associated with neovascularisation.8 Instead, it has been proposed that the inflammatory cells migrate through the vascular adventitia.9 Despite these two hypotheses, correlation between plaque neovascularization and inflammatory cell aggregation has not been confirmed in clinical studies.
Dynamic contrast enhanced magnetic resonance imaging (DCE MRI) measures the plasma volume (Vp), which is the volume of the flowing plasma divided by the plaque volume. The flowing plasma is mainly found in the capillaries of neovascularization. The transfer constant (Ktrans) estimated by DCE MRI represents the rate at which contrast agent flows from the plasma into the interstitial space and is proportional to the permeability, to the surface area of the endothelium and to the extent of neovascularisation.10 If plaque neovascularization aids delivery of the inflammatory cells to the plaque, Vp and Ktrans should be noticeably increased when TBR increased. For these reasons, positive correlation between Vp and TBR, as well as between Ktrans and TBR, will accurately reflect the relationship between plaque neovascularization and inflammatory cell aggregation. Hence, as part of the mechanism of plaque instability we estimated the extent of these correlations.
Atherosclerotic patients hospitalized in the Chinese People's Liberation Army General Hospital between March 2011 and April 2012 were selected if they did not meet the following exclusion criterion: an intima media thickness (IMT) of <2 mm,11,12 as evaluated by ultrasound, in at least one carotid artery; patients who could not lie still in the supine position for at least 50 minutes,13 patients who could not undergo a DCE MRI examination due to presence of metal objects such as cardiac pacemakers, prosthetic valves and metal foreign bodies; allergy to gadolinium; pregnancy; serum creatinine levels greater than 110 μmol/L and patients who could not undergo a PET CT scan (due to inflammation of the throat or serum glucose levels greater than 200 mg/dl).14
Dynamic contrast enhanced magnetic resonance imaging
The patients were imaged after eight hours of fasting. All images were acquired on a Signa1.5T nuclear MRI imaging system utilizing a 4 channel, phased array carotid surface coil.15 Both carotid arteries were imaged. The relevant imaging parameters were repetition time (ms)/echo time (ms), 100/6.2; flip angle, 20°; section thickness, 2 mm; field of view, 16 cm×14 cm; and matrix, 256×256. Data were centred on the carotid bifurcation and were collected at 12 different time points, with a separation interval of 19 seconds between time points.16,17 Coincident with the acquisition of the second image in the sequence, 0.1 mmol (0.2 ml) of the gadolinium based contrast agent Magnevist (Bayer, USA) per kilogram body weight was injected at a rate of 2 ml/s using a power injector. A spatial saturation band was applied to induce a T1 dependent blood signal, which resulted in the images of blood appearing dark prior to arrival of the contrast agent.
Positron emission tomography and computed tomography
After fasting for more than six hours and quiet rest for 30 minutes, fluorine-18 fluorodeoxyglucose (18F-FDG) was injected through the cubital vein at a dose of 5.55 mBq/kg (0.15 mCi/kg). Ninety minutes later, imaging was performed using Biograph 64 HD (Siemens, Germany), with the patient in the supine position. The scanning area extended from the middle of the sternum to the upper edges of the ears. Low dose spiral CT scanning was performed using the following parameters: tube voltage, 120 kV; tube current, 180 mA; intrinsic resolution, 5 mm; section thickness, 2 mm; matrix, 512×512; field of view, 70 cm; and scanning time, 20-30 seconds.18 The PET scan area was the same as the CT scan: three minutes for each patient. Data were acquired in the three dimensional mode and analysed using the reconstruction algorithm, ordered subset expectation maximization (OSEM).14 The display matrix was 128×128, and the coronal, sagittal and transverse views were obtained from the PET images, CT images and fusion images, respectively.
We obtained a single plaque with a complete fibrous cap from one particular slice without fusion at the axial location of carotid MRI and CT.19 The sections that best matched the two image locations in every patient were identified based on their position relative to the carotid bifurcation and the overall shape of the lumen and the plaque. Matching was accomplished prior to the quantitative analysis of the subsequent PET CT and DCE MRI scans.
Two trained reviewers, who had two years of experience in interpreting carotid MRI scans and who were blinded to clinical information and stenotic measurements, evaluated the image quality and interpreted the multicontrast images of the index carotid artery via consensus. For each index artery, an image quality rating was assigned using a 4 point scale (1=poor to 4=excellent). Arteries with an image quality of <2 points were excluded from analysis.19 For the remaining interpretable arteries, a software package (CASCADE; Seattle, USA) was used to measure the lumen area, wall area, total vessel area and mean wall thickness at each axial location.20
The presence or absence of carotid compositional features, such as calcification, lipid rich necrotic core (LRNC), intraplaque haemorrhage (IPH) and surface disruption (ulceration or fibrous cap rupture) were determined using previously published multicontrast criteria that have been validated by histological findings.21 LRNC showed a low signal in T2WI and CE T1WI, an equal or a moderately high signal in T1WI and an equal signal in 3D TOF. IPH showed a high signal in TOF and T1WI, an equal signal in CE T1WI and a high or low signal in T2WI (determined by the duration of the IPH). Calcification showed a low signal in all images. Ulceration or fibrous cap rupture showed intensified discontinuation in CE T1WI.
The cross sectional areas of the lumen and wall of the carotid artery were recorded. Normalized wall index (NWI)19 was calculated using equation 1 to obtain the mean NWI and maximum NWI (max NWI) of each artery and each plaque. Identification of the carotid artery lumen was facilitated by its transition from the region with the lowest signal intensity to the region with the highest signal intensity upon contrast agent arrival. The areas of carotid plaque calcification, LRNC, IPH and surface disruption (ulceration or fibrous cap rupture) were hand drawn on the screen.22,23 The area of carotid plaque calcification, LRNC and IPH were multiplied by the thickness of the slice to obtain the plaque volume and plaque characteristics.
We characterized the dynamics of the contrast agent using the generalized kinetic model for DCE MRI.10 This kinetic model includes an intravascular contribution and neglects the return of the contrast agent from the plaque into the blood plasma. It assumes that the total concentration of the contrast agent in a tissue is determined by the concentration in two compartments—one being the intravascular space (with Vp) and the other being the extravascular extracellular space. The signal intensity:concentration time curve of each plaque was recorded. Ktrans determines the rate at which contrast agent enters the extravascular extracellular space. The overall dynamics of the contrast agent is represented by equation 2, where Ct and Cp are the total concentration of the contrast agent in the tissue and blood plasma, respectively. Measurements of Ct and Cp over time, which are assumed linearly proportional to the change in signal intensity of the contrast agent in the tissue and blood, are sufficient to solve for Vp and Ktrans.24
A Xeleris Workstation (General Electric Medical Systems) was used to analyse the PET CT images. At each axial plane along the length of the carotid artery, regions of interest (ROIs) that were approximately 8 mm in diameter were placed within the wall of the carotid vessel for determination of the standardized uptake value (SUV).25 The SUV is defined as the decay corrected tissue concentration of 18F-FDG (in MBq/ml) divided by the injected dose per body weight (MBq/g, in equation 3). To obtain a background value for FDG uptake, the SUV was measured in a venous structure. To accomplish this, an ROI was placed within the centre of a large vein (subclavian or internal jugular) in an area without significant spill over activity. Next, TBR was calculated by dividing the carotid plaque SUV by the venous blood SUV (equation 4), and an average TBR value was determined for each patient. Tawakol et al26 suggested the following classification for the severity of inflammation: noninflammation when mean TBR <1.25, mild inflammation when mean TBR is 1.25 to 2.0, moderate inflammation when mean TBR is 2.0 to 3.2 and serious inflammation when mean TBR >3.2.
The Spearman rank correlation was used to determine statistical associations between Ktrans, Vp and TBR. Continuous data representing normal distribution were expressed as mean±standard deviation (SD), and continuous data that did not pass the normality test were expressed as median (P25, P75). The Student's t test and Wilcoxon rank sum test were used to compare the means of two groups. All analyses were performed using SPSS for Windows software (SPSS Statistics 17.0; SPSS China, Shanghai, China). A P <0.05 was considered as statistically significant.
Thirty-one patients underwent DCE MRI. One patient could not complete the imaging study because of claustrophobia. Four patients were not able to hold their bodies steady, resulting in poor quality images that could not be analysed. Thus, DCE MRI data were obtained from 26 patients (22 males and 4 females). The median age of the 26 patients was 76 (62 to 80) years. Eighteen patients were diagnosed with coronary artery disease,27 of whom, five developed acute cardiovascular or cerebrovascular events before the test. Twenty patients were treated with statin (Table 1).
Dynamic contrast enhanced magnetic resonance imaging
Twenty-four patients underwent both PET CT and DCE MRI. Excluding the plaques with poor imaging quality, 155 plaques were analysed. The mean NWI was 0.37 (0.32, 0.42) and max NWI was 0.46 (0.40, 0.56). Ninety-seven plaques showed calcification (63%), median volume of calcification of the 155 plaques was 4.36 (0.00, 19.82) mm3. One hundred and fourteen plaques had a LRNC (74%), median volume of LRNC of the 155 plaques was 26.05 (0.00, 75.55) mm3. Seventeen plaques had IPH (11%) and their median volume was 0.02 (0.00, 0.10) mm3. Two plaques had fibrous cap rupture (1%) and IPH.
The mean Ktrans value of all the plaques was 0.04 (0.02, 0.05) and their Vp was 0.06 (0.04, 0.08). Contrast intensified signals of 34 plaques (22%) were 0 and their signal intensity compared with area under curve values fluctuated around the baseline. Both Ktrans and Vp values of these plaques were 0. If these 34 plaques were excluded, the mean Ktrans value of the remaining 121 plaques was 0.04 (0.03, 0.06) and their Vp was 0.07 (0.06, 0.09).
Positron emission tomography and computed tomography
One hundred and fifty-five plaques were evaluated by PET CT. There were 2.05± 1.17 (range of 1.00-12.00) plaques in each patient's carotid artery, with a mean TBR of 1.24±0.13 (1.03-1.56). There were 94 (61%) noninflammatory plaques (TBR <1.25) and 61 (39%) inflammatory plaques (TBR ≥1.25).
Correlation between plaque parameters of PET CT and DCE MRI
The Spearman rank correlation test found the statistical associations of TBR with Ktrans and Vp to be insignificant (0.14-0.07 respectively). Thirty-four plaques without a contrast intensified, signal had a TBR of 1.24±0.13 (1.12-1.44), whereas the remaining 121 plaques had a TBR of 1.25±0.12 (1.02-1.55). There was no significant difference between the two TBR values (P=0.66).
Inflammation and plaque morphology
The plaques were divided into two groups: plaques with a TBR of <1.25 or ≥1.25. However, there was no significant difference between the two groups in terms of the plaque morphology (Table 2).
Inflammation and plaque neovascularization
There were no significant differences between the two groups in terms of Ktrans and Vp (Table 3).
Correlation analysis between inflammation and neovascularization
The statistical relationships TBR:Ktrans and TBR:Vp were determined using the Spearman rank correlations of the 94 noninflammatory plaques. Only weak and nonsignificant values were found (0.41 and 0.31 respectively). Similar correlations were found for the inflammatory plaques (-0.25 and -0.01 respectively). However, there was a significant moderate correlation between Ktrans and Vp (rs=0.75, P <0.01). A similar correlation was found for the inflammatory plaques (0.71, P <0.01).
The patients enrolled in the present study were characterized by a high coronary risk (advanced age, male predominance, high percentage of coronary artery disease, atherosclerosis and hypertension). Most of the patients received statin therapy. Ten patients had experienced either a transient ischaemic attack or stroke before. The plaques examined by MRI were relatively small and did not cause significant carotid stenosis. Overall, the plaque characteristics were not different from those reported in our previous study4 or in studies by other groups.8,28
In the present study, a noninvasive approach using PET CT and DCE MRI was employed to investigate the correlation between neovascularization and inflammation in the carotid plaque. TBR values obtained by PET CT were used to categorize inflammatory cells of the carotid plaques, whereas 18F-FDG images served as the indicator of inflammation. Neovascularization was assessed by DCE MRI. The area under the curve was constructed using the DCE MRI data, and the Vp and Ktrans values of the plaques were calculated as an indicator of neovascularization.
Theoretically, Ktrans is proportional to the permeability and surface area of the endothelium and proportional to neovascularization. The inflammatory process can also increase the permeability of the endothelium. Therefore, both the monocytes/macrophages and neovascularization are capable of increasing the Ktrans.10,29 If neovascularization of the plaques helps deliver the inflammatory cells to the plaque, then aggregation of the inflammatory cells would be accompanied by the development of neovascularization. When inflammation increases, Ktrans is also expected to increase.
However, in the present study, Ktrans did not differ between the inflammatory and noninflammatory plaques. As a result, neovascularization did not lead to an increase in inflammation. Vp of the plaque is calculated by dividing the volume of flowing plasma by the plaque volume. The flowing plasma is mainly found in the capillaries of neovascularization. Pathological findings suggest that Vp is a better marker of neovascularization than Ktrans.20 In our study, there was no significant difference in Vp values between the inflammatory (TBR ≥1.25) and noninflammatory plaques (TBR <1.25). In the 34 plaques without contrast enhancement showing a Ktrans and Vp value of 0, the TBR did not differ significantly from the other plaques. In other words, the inflammatory cells still accumulated, although there was little neovascularization.
Our results suggest that neovascularization does not help in the delivery of the inflammatory cells into the plaque. Tawakol et al26 have categorized the severity of inflammation as mild (CD68 cells: <5%) for a mean TBR of 1.25; moderate (CD68 cells: 5%-15%) for a mean TBR of 2.0 and serious (CD68 cells: >15%) for a mean TBR of 3.2, which categorisation forms the basis of ours. We compared the plaque parameters (Ktrans and Vp) between plaques with a TBR of ≥1.25 (inflammatory) and plaques with a TBR of <1.25 (noninflammatory). No significant differences were found between the two groups. Because an increase in Ktrans and Vp was not seen in the inflammatory plaques, our results do not support the hypothesis that neovascularization helps to deliver inflammatory cells into carotid atherosclerotic plaques.
It seems that our results are contradictory to those of previous studies. Kerwin et al24 showed that the number of monocytes/macrophages cells and neovascularization of the carotid plaque were moderately correlated with Ktrans and Vp. In another clinical study, the same correlation was established for inflammatory cells and neovascularization of human carotid plaques removed by carotid endarterectomy, which closely correlated with cerebrovascular events.30 In a study by Calcagno et al,11 the location and number of monocytes/macrophages cells, as seen under the microscope, correlated well with TBR obtained by PET CT. This indicates that DCE MRI can be reliably used to evaluate both the inflammation and neovascularization of the carotid plaque.
According to the theory put forth by O'Brien et al,6 the more neovascularization, the more monocytes/macrophages. However, no useful correlation was found between Ktrans or Vp and TBR in the 61 inflammatory plaques, the 94 noninflammatory plaques or both groups combined. This means that when plaque shows very little aggregation of inflammatory cells, neovascularization does not change much and the surface area of the endothelium does not increase: however, the increased permeability of endothelium increases the Ktrans. A possible explanation for this result would be that not all of the inflammatory cells in plaque are transferred by neovascularization. Some of them probably migrate through the vascular adventitia9,31 thus therapies to suspend neovascularization are not enough for stabilizing the plaques in carotid or coronary artery. If this is the case, there should be no significant correlation between the number of neovascularization and inflammatory cells and our results hold true.
Limitations of the study
Our study was unable to demonstrate a significant correlation between inflammatory cell aggregation and neovascularization of the carotid atherosclerotic plaque. This could be partly due to the limited sample size of our study. Thus, future correlation studies will be conducted on a larger patient sample. Our previous study indicates that the resolution of PET CT may not be high enough to detect small extents of inflammation.4 Hence, a more sensitive technique is necessary to detect accurately, low levels of inflammation.32
In conculsions, our study did not find a statistically significant correlation between plaque neovascularization and the aggregation of inflammatory cells.
1. Schoenenberger AW, Jamshidi P, Kobza R, Zuber M, Stuck AE, Pfisterer M, et al. Progression of coronary artery disease during long term follow up of the Swiss Interventional Study on Silent Ischaemia Type II (SWISSI II). Clin Cardiol 2010; 33: 289-295.
2. Hollander M, Bots ML, Del SA, Koudstaal PJ, Witteman JC, Grobbee DE, et al. Carotid plaques increase the risk of stroke and subtypes of cerebral infarction in asymptomatic elderly: the Rotterdam study. Circulation 2002; 105: 2872-2877.
3. Cao JJ, Thach C, Manolio TA, Psaty BM, Kuller LH, Chaves PH, et al. C reactive protein, carotid intima media thickness, and incidence of ischaemic stroke in the elderly: the Cardiovascular Health Study. Circulation 2003; 108: 166-170.
4. Wang XN, Liu HB, Li J, Chen YD, Zhang JM, Wang GW. Application of 18
F FDG nuclide imaging of atherosclerotic plaques in apolipoprotein E deficient mice. J Chinese PLA Postgrad Med Sch (Chin) 2011; 32: 645-647.
5. Celletti FL, Waugh JM, Amabile PG, Brendolan A, Hilfiker PR, Dake MD. Vascular endothelial growth factor enhances atherosclerotic plaque progression. Nat Med 2001; 7: 425-429.
6. O'Brien KD, McDonald TO, Chait A, Allen MD, Alpers CE. Neovascular expression of E selectin, intercellular adhesion molecule 1, and vascular cell adhesion molecule 1 in human atherosclerosis and their relation to intimal leukocyte content. Circulation 1996; 93: 672-682.
7. Frantz S, Vincent KA, Feron O, Kelly RA. Innate immunity and angiogenesis. Circ Res 2005; 96: 15-26.
8. Camici PG, Rimoldi OE, Gaemperli O, Libby P. Non invasive anatomic and functional imaging of vascular inflammation and unstable plaque. Eur Heart J 2012; 33: 1309-1317.
9. Maiellaro K, Taylor WR. The role of the adventitia in vascular inflammation. Cardiovasc Res 2007; 75: 640-648.
10. Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, et al. Estimating kinetic parameters from dynamic contrast enhanced T(1) weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 1999; 10: 223-232.
11. Calcagno C, Mani V, Ramachandran S, Fayad ZA. Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) of atherosclerotic plaque angiogenesis. Angiogenesis 2010; 13: 87-99.
12. Brott TG, Halperin JL, Abbara S, Bacharach JM, Barr JD, Bush RL, et al. 2011 ASA/ACCF/AHA/AANN/AANS/ACR/ASNR/CNS/SAIP/SCAI/SIR/SNIS/SVM/SVS guideline on the management of patients with extracranial carotid and vertebral artery disease. A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, and the American Stroke Association, American Association of Neuroscience Nurses, American Association of Neurological Surgeons, American College of Radiology, American Society of Neuroradiology, Congress of Neurological Surgeons, Society of Atherosclerosis Imaging and Prevention, Society for Cardiovascular Angiography and Interventions, Society of Interventional Radiology, Society of NeuroInterventional Surgery, Society for Vascular Medicine, and Society for Vascular Surgery. Circulation 2011; 124: e54-e130.
13. Lythgoe DJ, Ostergaard L, William SC, Cluckie A, Buxton Thomas M, Simmons A, et al. Quantitative perfusion imaging in carotid artery stenosis using dynamic susceptibility contrast enhanced magnetic resonance imaging. Magn Reson Imaging 2000; 18: 1-11.
14. Rudd JH, Warburton EA, Fryer TD, Jones HA, Clark JC, Antoun N, et al. Imaging atherosclerotic plaque inflammation with [18F] fluorodeoxyglucose positron emission tomography
. Circulation 2002; 105: 2708-2711.
15. Wang Y, Wang QJ, Cai YQ, Ma L, Cai JM. Evaluation of atherosclerotic carotid plaque composition with magnetic resonance imaging using different sequences. J South Med Univ (Chin) 2011; 31: 299-303.
16. Yarnykh VL, Yuan C. Multislice double inversion recovery black blood imaging with simultaneous slice reinversion. J Magn Reson Imaging 2003; 17: 478-483.
17. Yarnykh VL, Yuan C. T1 insensitive flow suppression using quadruple inversion recovery. Magn Reson Med 2002; 48: 899-905.
18. Xing XW, Zhang JT, Zhu F, Ma L, Yin DY, Jia WQ, et al. Comparison of diffusion weighted MRI with 18
F-fluoro-deoxyglucose positron emission tomography
/CT and electroencephalography in sporadic Creutzfeldt Jakob disease. J Clin Neurosci 2012; 19: 1354-1357.
19. Zhao X, Underhill HR, Zhao Q, Cai J, Li F, Oikawa M, et al. Discriminating carotid atherosclerotic lesion severity by luminal stenosis and plaque burden: a comparison utilizing high resolution magnetic resonance imaging at 3.0 Tesla. Stroke 2011; 42: 347-353.
20. Kerwin W, Xu D, Liu F, Saam T, Underhill H, Takaya N, et al. Magnetic resonance imaging of carotid atherosclerosis
: plaque analysis. Top Magn Reson Imaging 2007; 18: 371-378.
21. Hatsukami TS, Yuan C. MRI in the early identification and classification of high risk atherosclerotic carotid plaques. Imaging Med 2010; 2: 63-75.
22. Cai JM, Hatsukami TS, Ferguson MS, Small R, Polissar NL, Yuan C. Classification of human carotid atherosclerotic lesions with in vivo
multicontrast magnetic resonance imaging. Circulation 2002; 106: 1368-1373.
23. Cai J, Hatsukami TS, Ferguson MS, Kerwin WS, Saam T, Chu B, et al. In vivo
quantitative measurement of intact fibrous cap and lipid rich necrotic core size in atherosclerotic carotid plaque: comparison of high resolution, contrast enhanced magnetic resonance imaging and histology. Circulation 2005; 112: 3437-3444.
24. Kerwin WS, O'Brien KD, Ferguson MS, Polissar N, Hatsukami TS, Yuan C. Inflammation in carotid atherosclerotic plaque: a dynamic contrast enhanced MR imaging study. Radiology 2006; 241: 459-468.
25. Davies JR, Rudd JH, Fryer TD, Graves MJ, Clark JC, Kirkpatrick PJ, et al. Identification of culprit lesions after transient ischaemic attack by combined 18
F fluorodeoxyglucose positron emission tomography
and high resolution magnetic resonance imaging. Stroke 2005; 36: 2642-2647.
26. Tawakol A, Migrino RQ, Bashian GG, Bedri S, Vermylen D, Cury RC, et al. In vivo18
F fluorodeoxyglucose positron emission tomography
imaging provides a noninvasive measure of carotid plaque inflammation in patients. J Am Coll Cardiol 2006; 48: 1818-1824.
27. Levine GN, Bates ER, Blankenship JC, Bailey SR, Bittl JA, Cercek B, et al. 2011 ACCF/AHA/SCAI Guideline for Percutaneous Coronary Intervention. A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines and the Society for Cardiovascular Angiography and Interventions. J Am Coll Cardiol 2011; 58: e44-e122.
28. Chen H, Cai J, Zhao X, Underhill H, Ota H, Oikawa M, et al. Localized measurement of atherosclerotic plaque inflammatory burden with dynamic contrast enhanced MRI. Magn Reson Med 2010; 64: 567-573.
29. Pfluger M, Kapuscik A, Lucas R, Koppensteiner A, Katzlinger M, Jokela J, et al. A combined impedance and AlphaLISA based approach to identify anti inflammatory and barrier protective compounds in human endothelium. J Biomol Screen 2013; 18: 67-74.
30. Teng Z, Sadat U, Huang Y, Young VE, Graves MJ, Lu J, et al. In vivo
MRI based 3D mechanical stress strain profiles of carotid plaques with juxtaluminal plaque haemorrhage: an exploratory study for the mechanism of subsequent cerebrovascular events. Eur J Vasc Endovasc Surg 2011; 42: 427-433.
31. Xu X, Lu H, Lin H, Ni M, Sun H, Li C, et al. Lymphangiogenesis promotes inflammation and neointimal hyperplasia after adventitia removal in the rat carotid artery. Int J Cardiol 2009; 134: 426-427.
32. Li D, Xu Y, Wang Q, Wu H, Li H. 11
C-methionine and 18
F-fluorodeoxyglucose positron emission tomography
/CT in the evaluation of patients with suspected primary and residual/recurrent gliomas. Chin Med J 2012; 125: 91-96.