Association between carotid artery and abdominal aortic aneurysm plaque
© Raz et al. 2015
Received: 14 July 2015
Accepted: 19 October 2015
Published: 15 November 2015
The correlation between AAA and carotid artery plaque is unknown and a common etiology and pathophysiology is suspected by some authors. The purpose of this work was to explore the association between the features of a) carotid artery plaque and b) abdominal aortic aneurysm (AAA) plaques using multi-detector-CT Angiography (MDCTA).
Forty-eight (32 males; median age 72 years) patients studied using a 16-detectors CT scanner were retrospectively analyzed. A region of interest (ROI) ≥ 2 mm2 was used to quantify the HU value of the plaque by two readers independently. Inter-observer reproducibility was calculated and Pearson correlation analysis was performed.
The Bland-Altman plots showed the inter-observer reproducibility to be good. The Pearson correlation was 0.224 (95 % CI = 0.071 to 0.48), without statistically significant association between HU measured in the carotid artery plaque and in the AAA plaques (p = 0.138); after exclusion of the calcified plaques from the analysis, the rho values resulted 0.494 (95 % CI = 0.187 to 0.713) with a statistically significant association (p = 0.003).
In this study, we found an association between the features of the non calcific carotid plaque and the features of AAA plaque.
KeywordsCarotid Aneurysm Plaque CTA
Atherosclerotic disease of carotid artery is considered the most important cause of cerebrovascular events [1, 2]; imaging techniques in the last years focused their attention in finding those parameters that are associated with an increased risk of stroke and transitory ischemic attacks (TIA) [3, 4]. The concept of "vulnerable plaque" has thus been introduced, focusing on those atherosclerotic plaques with a high likelihood to cause thrombotic complications [5, 6]. However, atherosclerosis is a process that may affect all the arterial vessels in the body  and, commonly, a significant target of this pathology is the abdominal aorta [8, 9].
The most prevalent pathology of the aorta is the abdominal aortic aneurysm (AAA), whose rupture has been recognized to be a significant cause of mortality for adults aged >60 years in the developed world . The pathogenesis of AAA is still poorly understood with some studies suggesting the importance of inflammatory pathways, hemodynamic forces, matrix degradation and thrombosis [11, 12]. Subjects with AAAs have frequently atherosclerosis: Cornuz et al.  showed the association of peripheral atherosclerosis with AAAs. Whether the association between atherosclerosis and AAA is simply due to common risk factors or is causal is unknown .
In the last few years MDCTA has emerged as an outstanding technique to explore the vascular system [15–18], and by using the Hounsfield Units (HU) sampling it is possible to have quantitative and reproducible information of the analyzed tissue .
The purpose of this work was to explore the association between plaques in the carotid artery and abdominal aortic aneurysm by using quantitative data obtained with MDCTA.
Forty-eight (32 males; median age 72 ± 14 years) patients studied between August 2005 and May 2011 by using a 16-detector CT scanner (Philips Brilliance, Rotterdam, Netherlands) were retrospectively analyzed. Patients with medical history of cardiac output failure, or any contraindications to iodinated contrast media did not undergo MDCTA exams. Criteria to be included in this study were: 1) Patients underwent MDCTA of carotid and abdominal aorta for AAA. 2) The time interval between the carotid and the AAA studies was not more than 3 months. Each examination was performed when clinically indicated and was ordered by the patient’s physician as part of routine clinical care. The patients were all neurologically asymptomatic, without history of TIA or stroke. In accordance with the applicable National Research Ethics Service guidance, ethical approval for the study was not required because the study was performed retrospectively on routinely acquired images and specimens.
All patients underwent MDCTA of the supra-aortic vessels using a technique previously described [blinded for peer review].
In our protocol for the analysis of carotid arteries, the angiographic phase is obtained by injecting 80-110 mL of contrast using a power injector at a flow rate of 5 mL/s. A bolus tracking technique is used to calculate the correct timing of the scan. Dynamic monitoring scanning begins 6 s after the beginning of the intravenous injection of contrast material. The trigger threshold inside the ROI is set at + 90 HU above the baseline. The delay between the acquisitions of each monitoring scan is 1 s. CT technical parameters include: matrix 512x512, field of view (FOV) 14–19 cm; mAs 180–220; kV 120–140.
For the analysis of AAA, the angiographic phase is obtained by injecting 80-110 mL of contrast medium into a cubital vein (usually the left side was used), using a power injector at a flow rate of 4-5 mL/s and an 18-gauge intravenous catheter. The scan starts at the level of the diaphragm up to the pubic symphysis. For the study of AAA a bolus tracking technique similar to the procedure described for the carotid arteries is used.
Window parameters (width and level) were freely modifiable but the parameters from another article  were followed. To quantifiy the HU value, a circular or elliptical region of interest cursor in the predominant area of plaque was used. Regions of beam hardening in calcified areas were excluded and areas showing contamination by contrast material or calcification were avoided.
Continuous data were described as the mean value ± standard deviation (SD). In order to evaluate the inter-observer reproducibility in HU quantification, Bland-Altman analysis with 95 % limits of agreement (mean difference ± 1.96 SDs) was performed and the differences between the measured values were plotted against the mean of the 2 measurements to assess the relationship between the difference and the magnitude of the measurement. Mann-Whitney test was used to test the differences between groups. For the analysis of correlation (Pearson Rho correlation) between HU measured in the carotid artery and AAA plaques, the HU values between the 2 observers were averaged. R software (www.r-project.org) was employed for statistical analyses.
72 y (SDb 13 y)
65 % (n = 31)
53 % (n = 25)
62 % (n = 30)
59 % (n = 28)
15 % (n = 7)
61 % (n = 29)
HU carotid artery plaque
HU AAA plaque
95 % CI for the median
54.88 to 67
57 to 66.12
35.27 to 46.1
40 to 49
45 to 82.75
49.5 to 76.75
32 to 49
34.5 to 52
Pearson correlation analysis
In the last few years several papers demonstrated that the plaque composition of the carotid arteries plays a significant role in the “vulnerability” of the plaque and in the risk of develop cerebrovascular events.
In the carotid artery (as well as in the coronary arteries), it is possible to find different types of plaque [3, 4] and the very hypodense regions (<30 HU) in the center of atherosclerotic carotid plaque are associated with the presence of a lipid core (i.e., lipid, hemorrhage, or necrotic debris) [21, 22]; this kind of plaques are associated with the development of cerebrovascular events .
The presence of atherosclerotic pathology and plaque development in the AAA is well described but if this association is simply due to common risk factors or is causal, is still unknown . In this study, our purpose was to evaluate whether there was an association between the HU values measured in the carotid artery plaque and the HU values measured in the AAA plaque.
By analyzing the correlation between HU values in carotid plaques and AAA plaques a rho value of 0.224 (95 % CI = 0.071 to 0.48) was found with the absence of significant p-value (p = 0.138). We analyzed the morphology of the scatter-plot and we found that the calcified plaques of carotid plaques represent, for this kind of analysis, a confounding factor. In the Fig. 3a the calcified plaques of carotid are clearly visible (dotted circle) and by excluding this kind of plaques the coefficient rho changed to 0.494 (95 % CI = 0.187 to 0.713) with the presence of a statistically significant association (p = 0.003). This is an interesting point to discuss because the presence of carotid calcified plaques are considered a protective factor for the development of cerebrovascular events [23, 24]. Nandalur et al. , demonstrated that calcified plaques are 21 times less likely to be symptomatic than non-calcified plaques (p = 0.030) whereas no significant predictive value was found between fatty (p = 0.23) or mixed (p = 0.18) plaque type for the occurrence of symptoms. The results of this study were further confirmed by Saba et al.  that showed that carotid calcified plaques are less frequently associated with cerebrovascular symptoms. In that paper the non calcified plaques were found to be associated with the presence of stroke-TIA.
Previous studies have attributed the development of AAA to atherosclerosis  because these conditions share risk factors, such as hypertension, smoking, and hypercholesterolemia [26, 27]. The presence of atherosclerotic process in the aneurismal wall is a common finding in AAA patients but several patients with advanced atherosclerosis do not develop AAA [28, 29].
The results of this study suggest that the atherosclerotic process involved in the carotid artery plaques and in the wall of the AAA is of a different nature: in fact in the carotid plaques may show a calcified type (HU value > 130) that is not present in the AAA. Nonetheless, when the carotid calcified plaques are excluded, a significant correlation is found between the HU values in the carotid and in the AAA.
From a pathological point of view authors reported that AAA is characterized by transmural infiltration of lymphocytes and macrophages and by the destruction of elastin and collagen in the media and adventitia loss of medial smooth muscle cells with thinning of the vessel wall [30, 31] and these pathological elements are quite similar in those found in the carotid (and coronary) artery “vulnerable” plaques [3, 4, 32, 33]. A study by Zweig et al., demonstrated that the calcifications of the abdominal aorta correlated with the presence of calcifications in the coronary arteries and even suggested abdominal aortic as a possible tool to help exclude obstructive coronary disease and improve the selection of patients that may benefit from further risk stratification .
In this type of study the analysis of reproducibility in the HU measurement is important and Bland-Altman plot analysis showed that the inter-observer reproducibility is good for both analysis and the best agreement is obtained in the carotid artery plaque HU quantification (with 95 % CI from −25.5 % to 20.3 %. In the HU quantification of the carotid artery plaque our results are concordant with previous observations [35, 36] whereas, on the best of our knowledge no previous analysis of concordance in the HU quantification of AAA plaque was found. These results were also confirmed by the Mann-Whitney test where we found no differences in HU analysis between the two observers in the carotids (p = 0.836) and in the AAA (p = 0.353).
In this paper there are some limitations. First, we quantified the HU values in the carotid and AAA by using a circular ROI; a more precise system like manual drawing of the plaque would be more reliable and this fact may introduce a bias in the data analysis: however we think that this can be considered a minor limitation because the predominant area of the plaque was selected. Second, the total number of analysed patients was forty-five and this represents a relative small population: therefore the obtained results should be further verified in larger cohort.
In this study, we found an association between the features of the non calcific carotid plaque and the features of AAA plaque.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Sadat U, Teng Z, Young VE, Graves MJ, Gaunt ME, Gillard JH. High-resolution magnetic resonance imaging-based biomechanical stress analysis of carotid atheroma: a comparison of single transient ischaemic attack, recurrent transient ischaemic attacks, non-disabling stroke and asymptomatic patient groups. Eur J Vasc Endovasc Surg. 2011;41(1):83–90.View ArticlePubMedGoogle Scholar
- U-King-Im JM, Young V, Gillard JH. Carotid-artery imaging in the diagnosis and management of patients at risk of stroke. Lancet Neurol. 2009;8(6):569–80.View ArticlePubMedGoogle Scholar
- Naghavi M, Libby P, Falk E, Casscells SW, Litovsky S, Rumberger J, et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part I. Circulation. 2003;108(14):1664–72.View ArticlePubMedGoogle Scholar
- Naghavi M, Libby P, Falk E, Casscells SW, Litovsky S, Rumberger J, et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part II. Circulation. 2003;108(15):1772–8.View ArticlePubMedGoogle Scholar
- Naghavi M, Falk E, Hecht HS, Shah PK. The first SHAPE (Screening for Heart Attack Prevention and Education) guideline. Crit Pathw Cardiol. 2006;5(4):187–90.View ArticlePubMedGoogle Scholar
- Casscells W, Naghavi M, Willerson JT. Vulnerable atherosclerotic plaque: a multifocal disease. Circulation. 2003;107(16):2072–5.View ArticlePubMedGoogle Scholar
- Curtiss LK. Reversing atherosclerosis? N Engl J Med. 2009;360(11):1144–6.View ArticlePubMedGoogle Scholar
- Biros E, Norman PE, Jones GT, van Rij AM, Yu G, Moxon JV, et al. Meta-analysis of the association between single nucleotide polymorphisms in TGF-β receptor genes and abdominal aortic aneurysm. Atherosclerosis. 2011;219(1):218–23.View ArticlePubMedGoogle Scholar
- Desai MY, Lima JA. Imaging of atherosclerosis using magnetic resonance: state of the art and future directions. Curr Atheroscler Rep. 2006;8(2):131–9.View ArticlePubMedGoogle Scholar
- U.S. Department of Health and Human Services Centers for Disease Control and Prevention National Center for Health Statistics. MD LCWK1. Deaths, percent of total deaths, and death rates for the 15 leading causes of death in 5-year age groups, by race and sex: United States, 2006, 2009:7–9. http://www.cdc.gov/nchs/data/dvs/LCWK1_2006.pdf.
- Golledge J, Muller J, Daugherty A, Norman P. Abdominal aortic aneurysm: pathogenesis and implications for management. Arterioscler Thromb Vasc Biol. 2006;26:2605–13.View ArticlePubMedGoogle Scholar
- Golledge J, Norman PE. Pathophysiology of abdominal aortic aneurysm relevant to improvements in patients’ management. Curr Opin Cardiol. 2009;24:532–8.View ArticlePubMedGoogle Scholar
- Cornuz J, Sidoti Pinto C, Tevaearai H, Egger M. Risk factors for asymptomatic abdominal aortic aneurysm: systematic review and meta-analysis of population-based screening studies. Eur J Public Health. 2004;14:343–9.View ArticlePubMedGoogle Scholar
- Golledge J, Norman PE. Atherosclerosis and abdominal aortic aneurysm: cause, response, or common risk factors? Arterioscler Thromb Vasc Biol. 2010;30(6):1075–7.PubMed CentralView ArticlePubMedGoogle Scholar
- Saba L, Pascalis L, Sanfilippo R, Anzidei M, Bura R, Montisci R, et al. Carotid artery wall thickness and leukoaraiosis: preliminary results using multidetector row CT angiography. AJNR Am J Neuroradiol. 2011;32(5):955–61.View ArticlePubMedGoogle Scholar
- Saba L, Sanfilippo R, Montisci R, Mallarini G. Associations between carotid artery wall thickness and cardiovascular risk factors using multidetector CT. AJNR Am J Neuroradiol. 2010;31(9):1758–63.View ArticlePubMedGoogle Scholar
- Fraioli F, Catalano C, Napoli A, Francone M, Venditti F, Danti M, et al. Low-dose multidetector-row CT angiography of the infra-renal aorta and lower extremity vessels: image quality and diagnostic accuracy in comparison with standard DSA. Eur Radiol. 2006;16(1):137–46.View ArticlePubMedGoogle Scholar
- Catalano C, Fraioli F, Laghi A, Napoli A, Bezzi M, Pediconi F, et al. Infrarenal aortic and lower-extremity arterial disease: diagnostic performance of multi-detector row CT angiography. Radiology. 2004;231(2):555–63.View ArticlePubMedGoogle Scholar
- Saba L, Montisci R, Sanfilippo R, Mallarini G. Multidetector row CT of the brain and carotid artery: a correlative analysis. Clin Radiol. 2009;64(8):767–78.View ArticlePubMedGoogle Scholar
- Saba L, Mallarin G. Window settings for the study of calcified carotid plaques with multidetector CT angiography. AJNR Am J Neuroradiol. 2009;30(7):1445–50.View ArticlePubMedGoogle Scholar
- Saba L, Caddeo G, Sanfilippo R, Montisci R, Mallarini G. CT and US in the study of ulcerated carotid plaque compared with surgical results. Advantages of multi-detector-row CT angiography. Am J Neuroradiol. 2007;28:1061–66.View ArticlePubMedGoogle Scholar
- Saba L, Caddeo G, Sanfilippo R, Montisci R, Mallarini G. Efficacy and Sensitivity of axial scans and different reconstruction methods in the study of the ulcerated carotid plaque by using multi-detector-row CT angiography. Comparison with surgical results. Am J Neuroradiol AJNR. 2007;28:716–23.View ArticlePubMedGoogle Scholar
- Nandalur KR, Baskurt E, Hagspiel KD, Phillips CD, Kramer CM. Calcified carotid atherosclerotic plaque is associated less with ischemic symptoms than is noncalcified plaque on MDCT. AJR Am J Roentgenol. 2005;184(1):295–8.PubMed CentralView ArticlePubMedGoogle Scholar
- Nandalur KR, Hardie AD, Raghavan P, Schipper MJ, Baskurt E, Kramer CM. Composition of the stable carotid plaque: insights from a multidetector computed tomography study of plaque volume. Stroke. 2007;38(3):935–40.PubMed CentralView ArticlePubMedGoogle Scholar
- Tilson MD. Atherosclerosis and aneurysm disease. J Vasc Surg. 1990;12:371–2.View ArticlePubMedGoogle Scholar
- Forsdahl SH, Singh K, Solberg S, Jacobsen BK. Risk factors for abdominal aortic aneurysms: a 7-year prospective study: the Tromsø study, 1994–2001. Circulation. 2009;119:2202–8.View ArticlePubMedGoogle Scholar
- Blanchard JF, Armenian HK, Friesen PP. Risk factors for abdominal aortic aneurysm: results of a case-control study. Am J Epidemiol. 2000;151:575–83.View ArticlePubMedGoogle Scholar
- Reed D, Reed C, Stemmermann G, Hayashi T. Are aortic aneurysms caused by atherosclerosis? Circulation. 1992;85:205–11.View ArticlePubMedGoogle Scholar
- Sterpetti AV, Feldhaus RJ, Schultz RD, Blair EA. Identification of abdominal aortic aneurysm patients with different clinical features and clinical outcomes. Am J Surg. 1988;156:466–9.View ArticlePubMedGoogle Scholar
- Davies MJ. Aortic aneurysm formation: lessons from human studies and experimental models. Circulation. 1998;98:193–5.View ArticlePubMedGoogle Scholar
- Freestone T, Turner RJ, Coady A, Higman DJ, Greenhalgh RM, Powell JT. Inflammation and matrix metalloproteinases in the enlarging abdominal aortic aneurysm. Arterioscler Thromb Vasc Biol. 1995;15:1145–51.View ArticlePubMedGoogle Scholar
- Redgrave JN, Lovett JK, Gallagher PJ, Rothwell PM. Histological assessment of 526 symptomatic carotid plaques in relation to the nature and timing of ischemic symptoms: the Oxford plaque study. Circulation. 2006;113(19):2320–8.View ArticlePubMedGoogle Scholar
- Redgrave JN, Lovett JK, Rothwell PM. Histological features of symptomatic carotid plaques in relation to age and smoking: the oxford plaque study. Stroke. 2010;41(10):2288–94.View ArticlePubMedGoogle Scholar
- Zweig BM, Sheth M, Simpson S, Al-Mallah MH. Association of abdominal aortic calcium with coronary artery calcium and obstructive coronary artery disease: a pilot study. Int J Cardiovasc Imaging. 2012;28(2):399–404.View ArticlePubMedGoogle Scholar
- Saba L, Mallarini G. Carotid Plaque Enhancement and Symptom Correlations: An Evaluation by Using Multidetector Row CT Angiography. AJNR Am J Neuroradiol. 2011;32(10):1919–25.View ArticlePubMedGoogle Scholar
- de Weert TT, de Monyé C, Meijering E, Booij R, Niessen WJ, Dippel DW, et al. Assessment of atherosclerotic carotid plaque volume with multidetector computed tomography angiography. Int J Cardiovasc Imaging. 2008;24(7):751–9.PubMed CentralView ArticlePubMedGoogle Scholar