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Research Article: Observational Study

The impact of abdominal fat on abdominal aorta calcification measured on non-enhanced CT

Goldenberg, Limor MDa; Saliba, Walid MDb; Hayeq, Hashem MDc; Hasadia, Rabea MDc; Zeina, Abdel-Rauf MDd,∗

Editor(s): Lawal., Ismaheel

Author Information
doi: 10.1097/MD.0000000000013233
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1 Introduction

The burden of atherosclerotic disease is unbearably heavy as it remains a major cause of death and morbidity in industrialized societies, involved in the pathogenesis of cardiovascular (CV) events and peripheral vascular disease. Vascular calcification is a complicating factor observed in advanced atherosclerosis. The mechanism of the vascular calcification process is multifactorial and incompletely understood combing elements of inflammation, dysregulated metabolism, and osteogenesis.[1] The presence and extent of vascular calcification can be considered merely a marker for atherosclerotic load, or it may serve on its own as an agent of disease. There is vast scientific interest in the matter of vascular calcification in terms of both risk factors for its occurrence, and possible outcomes of its presence.

Scanning and scoring of coronary artery calcium (CAC) has been established as an imaging biomarker of atherosclerosis, with strong prognostic correlation.[2,3] However, research of atherosclerosis and vascular calcification includes not only the coronary arteries but also vessels such the carotids, renal arteries, and unsurprisingly—the aorta. The sclerotic process in the aorta is considered to begin with fatty streaks that are present as early as childhood, progressing to atherosclerotic lesions which appear in many young adults, and may advance further to calcified lesions and plaques.[4]

Aortic calcification is a valuable marker, as its presence and degree have been associated with the extent and severity of coronary artery calcification and disease[5,6] (absence of abdominal aortic calcification has a high negative predictive value to rule out coronary artery disease),[7] CV events,[8–10] peripheral artery disease in patients with type 2 diabetes mellitus,[6] stroke,[11] risk of fractures,[12] and all-cause mortality.

Aortic calcification can be evaluated by either plain X-Ray (chest,[9] abdomen, and lateral lumbar radiograms);[8,13] vertebral Dual-energy X-ray absorptiometry (DXA);[14] computed tomography (CT); electron beam CT (EBCT); CT angiography (CTA); 18F-NaF-PET/CT;[15] Near-infrared fluorescent imaging (tested in murine models)[16] or autopsy studies. There are several different scoring methods of calcification, of which the most vastly used is the Agatston score, combining calcified plaque area and density as derived from CT scans.[2]

Risk factors for the progression of calcified atherosclerosis in general, and specifically for aortic calcification, include age,[6,17–19] hypertension,[6] smoking,[6,20] dyslipidemia,[6] exercise level (negatively related),[17] chronic kidney disease,[21] and ethnicity.[22] Few studies examined the relation between aortic calcification and body composition: abdominal lean muscle area and visceral fat area were not generally found to be significantly associated with aortic atherosclerosis,[22–24] while gender subdivision found an association between visceral fat and abdominal aorta calcification in women only.[25] Subcutaneous fat was unexpectedly found to be inversely associated with atherosclerosis.[22,24] Therefore, the aim of this study was to examine the correlation of abdominal aortic calcium (AAC) with abdominal adipose tissue (including visceral and subcutaneous fat) and hepatosteatosis, measured on non-enhanced CT, in a large patient population.

2 Materials and methods

2.1 Study population

The study sample included 492 adult patients (age ≥18 years), who underwent non-enhanced abdominal CT scans, due to clinically suspected renal colic, in our Imaging Institute throughout the years 2013 to 2014. The only exclusion criterion was age younger than 18 years. In all CT scans reviewed, image quality was high enough to allow adequate analysis, thus there was no exclusion due to low image quality. Demographic and clinical data including the patients’ age, gender, smoking status and comorbidities, such as diabetes mellitus, hypertension, and hyperlipidemia, were collected from the medical files. Our institutional review board approved this retrospective study and waived the requirement for informed consent.

2.2 CT protocols

A 64-detector row CT scanner (Brilliance-64, Philips Healthcare, Cleveland, Ohio, USA) was used to perform the abdomen-pelvis CT scan. All patients were in the supine position and were scanned from the lung base to the pubic symphysis. We performed a non-contrast scan. The scanning parameters were as follows: tube voltage, 120 kVp; collimation, 64 × 0.6 mm; rotation speed, 0.75 s; pitch, 0.8; reconstruction thickness, 3 mm. Sagittal and coronal reformatted images were generated with a thickness of 3 mm. Each CT examination was retrospectively reviewed by 2 board-certified radiologists. Image review was performed (in consensus) on a PACS workstation.

2.3 Abdominal aortic calcification scoring

Abdominal Aorta Calcium Score was obtained using Philips Brilliance Workspace Portal, Version 6.02, by Philips Medical Systems Netherlands BV. Circular regions-of-interest (ROI) were manually drawn around the aortic wall on each axial unenhanced image containing visible calcifications, defined as CT density greater than or equal to 130 Hounsfield units (HU), from the level of the celiac axis to aortic bifurcation, taking care not to include any vertebral bone area. The 130 HU threshold is recommended by the software vendor and is commonly used for CT assessment of arterial calcification.[25–27] The postprocessing software then summed the individual calcification areas and densities, calculating total calcification area and Agatston score (Fig. 1).

Figure 1
Figure 1:
Representative abdominal aorta calcium measurement using postprocessing software and calcium analysis tool (Philips Brilliance Workspace Portal, Version 6.02, by Philips Medical Systems Netherlands B.V). Axial non-enhanced CT image shows a calcified plaque (arrow) in the infrarenal abdominal aorta (A). The postprocessing software automatically highlighted the aortic calcification (color red) and a ROI was manually drawn around the aortic wall on each axial non-enhanced CT image containing visible calcifications (B), defined as CT density greater than or equal to 130 HU. The postprocessing software then summed the individual calcification areas and densities, calculating total calcification area and Agatston score (C).CT = computed tomography, HU = Hounsfield units, ROI = region of interest.

2.4 Measurement and criteria setting

2.4.1 Fat thickness measurements

Visceral fat: For the evaluation of visceral fat level, we measured the thickness (mm) of retro-renal fat. This measurement is performed at the level of the left renal vein and includes the pre-renal and para-renal fat from the surface of the kidney to the inner abdominal wall (Fig. 2A).

Figure 2
Figure 2:
Measurements of fat thickness on CT slices. Location of measurement is marked by double-headed arrow. (A) Retro-renal visceral fat: measured using the vertical distance between the left posterior renal capsule and the junction of the abdominal wall and paraspinal musculature at the level of the left renal vein (asterisk). (B) Abdominal subcutaneous fat: measured at the umbilical level, as the distance between the rectus abdominis to the skin over the anterior abdomen. (C) Pelvic subcutaneous fat: measured at the iliac crest level, as the distance between the iliac crest and the posterior skin. CT = computed tomography.

Subcutaneous abdominal fat: The thickness of subcutaneous abdominal fat was measured at the umbilical level, as the distance between the rectus abdominis to the skin over the anterior abdomen (Fig. 2B).

Subcutaneous pelvic fat: The thickness of the subcutaneous pelvic fat was measured at the iliac crest level, as the distance between the iliac crest and the posterior skin (Fig. 2C).

2.4.2 Liver density measurements

The difference between liver and spleen densities (CTL-S) was chosen as the defining criterion for hepatosteatosis in this study. Normally, liver density is higher by about 10 HU from that of the spleen. Livers were defined as fatty when the hepatic density, averaged over the 3-segment measurements, was at least 9 HU lower than that of the spleen. The specifics of liver and spleen density measurements have been described in our previous study.[28]

2.5 Statistical analysis

The statistical analysis was performed using the IBM SPSS Statistics 22.0 program. All tests are 2-tailed, with statistical significance set as P <.05. Continuous variables are reported as means and standard deviations along with medians and interquartile ranges. Categorical variables are reported as absolute values and proportion. Multiple Linear regression analysis was used to examine the univariate and multivariate relation between abdominal aorta calcium score (the dependent variable) and adiposity measures (independent variables). The unstandardized regression coefficient (B) is reported. For continuous variables, it reflects the effect on the dependent variable for each increment of 1 unit in the independent variable.

3 Results

A total of 492 patients were included in the study. The mean age was 47.27 years (SD 14.04), and 74.8% of the participants were male. Table 1 portrays the demographic, clinical and radiological characteristics of the study population.

Table 1
Table 1:
Study population characteristics (n = 492).

Age, hypertension, diabetes mellitus, hyperlipidemia, and thickness of visceral fat were directly and significantly associated with abdominal aorta calcium score in univariate linear regression analysis, whereas a significant inverse association was found with subcutaneous pelvic fat thickness (B = −14.3, P = .006) (Table 2).

Table 2
Table 2:
Univariate linear regression analysis for the association with abdominal aorta calcium score.

Three different multivariate linear regression analyses were performed. The first model included only the four CT adiposity measures. In this model, a significant association with abdominal aorta calcium score was detected for visceral abdominal fat and subcutaneous pelvic fat, (B = 67.1, P <.001) and (B = −22.34, P <.001), respectively.

After further adjustment for demographic variables and comorbidities, the association with subcutaneous pelvic fat remained statistically significant (Table 3).

Table 3
Table 3:
Multivariate linear regression analysis for the association with abdominal aorta calcium score.

The positive association of abdominal aorta calcium score with visceral fat width remained significant in the fully adjusted model when limited to female gender only (B = 84.28, P = .001). The association with fatty liver and umbilical subcutaneous fat, however, did not reach statistical significance regardless of gender selection. A comparison between males and females in the magnitude and the direction of the association of the different adiposity measures with abdominal aorta calcium score is depicted in Figure 3.

Figure 3
Figure 3:
Multivariate B coefficient showing the magnitude and the direction of the association of the different adiposity measures with abdominal aorta calcium score among males and females.

4 Discussion

In the present study abdominal aorta calcium score was significantly associated with CV risk factors (hypertension, diabetes mellitus, hyperlipidemia) correlating to a recent meta-analysis that determine abdominal aorta calcification was an independent predictor of CV disease (CVD) events.[10] Moreover, a statistically significant positive association of visceral abdominal adipose tissue with abdominal aorta calcium score was found in both univariate and multivariate analysis. Indeed, visceral adipose tissue has been repeatedly uncovered as an important risk factor for metabolic and CV disease, including coronary atherosclerosis[29,30] and cerebrovascular lesions.[31] Lipotoxicity is a relevant term in this matter, used to describe the deleterious effect of tissue fat accumulation, initially regarding glucose metabolism, but increasingly associated with other processes, including atherosclerosis, through the possible mechanism of fat-induced chronic inflammation.[32] Positive associations between total periaortic adipose tissue volume and CV disease have been established based on data from the Framingham Heart Study and others.[33,34] Using CT for quantification of aortic adiposity and aortic dimensions, Thanassoulis et al[33] demonstrated that periaortic adipose tissue volume was associated with thoracic and abdominal aortic dimensions. This association persisted after adjustment for CVD risk factors and visceral adipose tissue volume.[33] In accordance with our results, the impact of visceral abdominal adipose tissue on abdominal aorta calcification has also been demonstrated. Studies have shown that periaortic adipose tissue volume is correlated with the quantity of visceral abdominal adipose tissue. Lehman et al[34] demonstrated that thoracic aortic adipose tissue was associated with thoracic calcification in models containing visceral abdominal tissue. Moreover, thoracic peri-aortic adipose tissue was associated with abdominal aortic calcification in models containing visceral abdominal adipose tissue and CVD risk factors.[34]

Jensky et al demonstrated a significant positive association of CT-quantified visceral fat with aortic calcification.[35] However, the current study results show in the multivariate analysis the association of visceral adipose tissue with abdominal aorta calcium score did not withhold the addition of traditional CV risk factors to the model unless the model was limited to female gender only. This gender-related observation has been noted in previous research.[25] Thus, suggesting necessity to reexamine the lipotoxic role of visceral fat in the process of abdominal aorta calcification, which specifically in women, is independent of other examined factors. Hormonal pathways and tissue-factors have been studied to explain the gender-related difference in atherosclerosis, but further research is still required.[36]

In the present study among the examined measures of adiposity, only pelvic subcutaneous fat was found to have a solid statistically significant association with abdominal aorta calcium score. This association withstood the addition to the model of possible confounders having previously proven effects on the atherosclerotic process: age, smoking status, hypertension, hyperlipidemia, and diabetes mellitus. This association is a negative one—suggesting a protective role of subcutaneous fat on abdominal aorta calcification, as was implied in previous research.[24] Our results, however, relate to pelvic subcutaneous fat, and not abdominal subcutaneous fat as previously presented. In fact, in this study, the association of abdominal subcutaneous fat and abdominal aorta calcium score was statistically non-significant in all the univariate and multivariate analysis models, unlike the results presented by Jensky et al.[35] This may infer a variance in the calcific effect by different body fat distributions (as expressed in the traditional concept of “apple” versus “pear” body shape, and the much-studied waist-to-hip ratio).[37] Karastergiou et al review discussing “the biology of pear shape” summarizes several examples and possible mechanisms for the lower cardiometabolic risk associated with pear-shaped body fat distribution, related to gender, genetics, and microenvironment factors.[38]

Although research has tied non-alcoholic fatty liver and atherosclerosis, through possible mechanisms involving inflammatory mediators, insulin resistance, oxidative stress and endothelial damage, the specific link between fatty liver and aortic atherosclerosis has only been weakly and partially established. In this study, no significant association was found between fatty liver and abdominal aorta calcium score. Unlike previous studies, this was still the case when the model was limited to female gender only[39] and even in a univariate analysis before adjustment to other factors such as visceral fat thickness.[40] Further research will be required to determine the association and paths between these 2 conceptually related disorders.

A limitation of this study is the composition of the study population. Subjects underwent CT scanning for specific medical indications and thus limiting generalization of the findings to the general population. However, performing non-contrast CT as a means of screening and diagnosis is not rational both financially and in terms of exposure to radiation. Nonetheless, the associations derived from the study population are internally valid as measurements were standardized and consistent with accepted methods.

In conclusion: our study found a negative association between pelvic subcutaneous fat thickness and abdominal aorta calcification, and a positive association between visceral fat thickness and abdominal aorta calcification, the latter association particularly robust in women. The association between body compositions and adiposity measures with aortic calcification has not been widely investigated. Further knowledge of these associations could aid in risk stratification and identification of subsets of the population who may benefit from aortic calcification assessment and primary or secondary prevention of CV disease. These associations could also be used to identify pathogenesis mechanisms and treatment targets in atherosclerotic disease.

Author contributions

Conceptualization: Limor Goldenberg, Abdel-Rauf Zeina.

Data curation: Limor Goldenberg, Walid Saliba, Abdel-Rauf Zeina.

Formal analysis: Limor Goldenberg, Walid Saliba, Rabea Hasadia, Abdel-Rauf Zeina.

Investigation: Hashem Hayeq, Rabea Hasadia, Abdel-Rauf Zeina.

Methodology: Walid Saliba, Rabea Hasadia.

Resources: Hashem Hayeq.

Software: Walid Saliba, Hashem Hayeq, Rabea Hasadia.

Supervision: Walid Saliba.

Validation: Abdel-Rauf Zeina.

Visualization: Hashem Hayeq, Rabea Hasadia.

Writing – original draft: Limor Goldenberg, Abdel-Rauf Zeina.

Writing – review & editing: Abdel-Rauf Zeina.


[1]. Abedin M, Tintut Y, Demer LL. Vascular calcification: mechanisms and clinical ramifications. Arterioscler Thromb Vasc Biol 2004;24:1161–70.
[2]. Nezarat N, Kim M, Budoff M. Role of coronary calcium for risk stratification and prognostication. Curr Treat Options Cardiovasc Med 2017;8:19.
[3]. Detrano R, Guerci AD, Carr JJ, et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med 2008;358:1336–45.
[4]. McMahan CA, Gidding SS, Malcom GT, et al. Pathobiological determinants of atherosclerosis in youth risk scores are associated with early and advanced atherosclerosis. Pediatrics 2006;118:1447–55.
[5]. Yamamoto H, Shavelle D, Takasu J, et al. Valvular and thoracic aortic calcium as a marker of the extent and severity of angiographic coronary artery disease. Am Heart J 2003;146:153–9.
[6]. Churchill TW, Rasania SP, Rafeek H, et al. Ascending and descending thoracic aorta calcification in type 2 diabetes mellitus. J Cardiovasc Comput Tomogr 2015;9:373–81.
[7]. Zweig BM, Sheth M, Simpson S, et al. Association of abdominal aortic calcium with coronary artery calcium and obstructive coronary artery disease: a pilot study. Int J Cardiovasc Imaging 2012;28:399–404.
[8]. Wilson PWF, Kauppila LI, O’Donnell CJ, et al. Abdominal aortic calcific deposits are an important predictor of vascular morbidity and mortality. Circulation 2001;103:1529–34.
[9]. Iijima K, Hashimoto H, Hashimoto M, et al. Aortic arch calcification detectable on chest X-ray is a strong independent predictor of cardiovascular events beyond traditional risk factors. Atherosclerosis 2010;210:137–44.
[10]. Gonçalves FB, VoÛte MT, Hoeks SE, et al. Calcification of the abdominal aorta as an independent predictor of cardiovascular events: a meta-analysis. Heart 2012;98:988–94.
[11]. Hermann DM, Lehmann N, Gronewold J, et al. Thoracic aortic calcification is associated with incident stroke in the general population in addition to established risk factors. Eur Heart J Cardiovasc Imaging 2015;16:684–90.
[12]. Chen Z, Yu Y. Aortic calcification was associated with risk of fractures: a meta-analysis. J Back Musculoskelet Rehabil 2016;29:635–42.
[13]. de Bie MK, Buiten MS, Rotmans JI, et al. Abdominal aortic calcification on a plain X-ray and the relation with significant coronary artery disease in asymptomatic chronic dialysis patients. BMC Nephrol 2017;18:82.
[14]. Schousboe JT, Lewis JR, Kiel DP. Abdominal aortic calcification on dual-energy X-ray absorptiometry: methods of assessment and clinical significance. Bone 2017.
[15]. Beheshti M, Saboury B, Mehta MN, et al. Detection and global quantification of cardiovascular molecular calcification by fluoro18-fluoride positron emission tomography/computed tomography—a novel concept. Hell J Nucl Med 2011;14:114–20.
[16]. Lu T, Wen S, Cui Y, et al. Near-infrared fluorescence imaging of murine atherosclerosis using an oxidized low density lipoprotein-targeted fluorochrome. Int J Cardiovasc Imaging 2014;30:221–31.
[17]. Kim E-D, Kim JS, Kim S-S, et al. Association of abdominal aortic calcification with lifestyle and risk factors of cardiovascular disease. Korean J Fam Med 2013;34:213–20.
[18]. Allison MA, Criqui MH, Wright CM. Patterns and risk factors for systemic calcified atherosclerosis. Arterioscler Thromb Vasc Biol 2004;24:331–6.
[19]. Günenç Beşer C, Karcaaltincaba M, Çelik HH, et al. The prevalence and distribution of the atherosclerotic plaques in the abdominal aorta and its branches. Folia Morphol 2016;75:364–75.
[20]. Hirooka N, Kadowaki T, Sekikawa A, et al. Influence of cigarette smoking on coronary artery and aortic calcium among random samples from populations of middle-aged Japanese and Korean men. J Epidemiol Community Health 2013;67:119–24.
[21]. Benz K, Varga I, Neureiter D, et al. Vascular inflammation and media calcification are already present in early stages of chronic kidney disease, Cardiovasc. Pathol Off J Soc Cardiovasc Pathol 2017;27:57–67.
[22]. Yuan M, Hsu F-C, Bowden DW, et al. Relationships between measures of adiposity with subclinical atherosclerosis in patients with type 2 diabetes. Obesity 2016;24:1810–8.
[23]. Jensky NE, Allison MA, Loomba R, et al. Null association between abdominal muscle and calcified atherosclerosis in community-living persons without clinical cardiovascular disease: the multi-ethnic study of atherosclerosis. Metabolism 2013;62:1562–9.
[24]. Narumi H, Yoshida K, Hashimoto NI, et al. Increased subcutaneous fat accumulation has a protective role against subclinical atherosclerosis in asymptomatic subjects undergoing general health screening. Int J Cardiol 2009;135:150–5.
[25]. Ditomasso D, Carnethon MR, Wright CM, et al. The associations between visceral fat and calcified atherosclerosis are stronger in women than men. Atherosclerosis 2010;208:531–6.
[26]. Wu E-H, Wojciechowski D, Chandran S, et al. Prevalence of abdominal aortic calcifications in older living renal donors and its effect on graft function and histology. Transpl Int Off J Eur Soc Organ Transplant 2015;28:1172–8.
[27]. Yun C-H, Longenecker CT, Chang H-R, et al. The association among peri-aortic root adipose tissue, metabolic derangements and burden of atherosclerosis in asymptomatic population. J Cardiovasc Comput Tomogr 2016;10:44–51.
[28]. Zeina A-R, Goldenberg L, Nachtigal A, et al. Association between nephrolithiasis and fatty liver detected on non-enhanced CT for clinically suspected renal colic. Clin Imaging 2017;43:148–52.
[29]. Sato F, Maeda N, Yamada T, et al. Association of epicardial, visceral, and subcutaneous fat with cardiometabolic diseases. Circ J Off J Japanese Circ Soc 2017.
[30]. Mongraw-Chaffin ML, Allison MA, Burke GL, et al. CT derived body fat distribution and incident cardiovascular disease: the multi-ethnic study of atherosclerosis. J Clin Endocrinol Metab 2017.
[31]. Higuchi S, Kabeya Y, Kato K. Visceral-to-subcutaneous fat ratio is independently related to small and large cerebrovascular lesions even in healthy subjects. Atherosclerosis 2017;259:41–5.
[32]. Yazici D, Sezer H. Insulin resistance, obesity and lipotoxicity. Adv Exp Med Biol 2017;960:277–304.
[33]. Thanassoulis G, Massaro JM, Corsini E, et al. Periaortic adipose tissue and aortic dimensions in the Framingham Heart Study. J Am Heart Assoc 2012;1:e000885.
[34]. Lehman SJ, Massaro JM, Schlett CL, et al. Peri-aortic fat, cardiovascular disease risk factors, and aortic calcification: the framingham heart study. Atherosclerosis 2010;210:656–61.
[35]. Jensky NE, Criqui MH, Wright CM, et al. The association between abdominal body composition and vascular calcification. Obes Silver Spring Md 2011;19:2418–24.
[36]. Mathur P, Ostadal B, Romeo F, et al. Gender-related differences in atherosclerosis. Cardiovasc Drugs Ther 2015;29:319–27.
[37]. Shungin D, Winkler TW, Croteau-Chonka DC, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature 2015;518:187–96.
[38]. Karastergiou K, Smith SR, Greenberg AS, et al. Sex differences in human adipose tissues—the biology of pear shape. Biol Sex Differ 2012;3:13.
[39]. Remigio-Baker RA, Allison MA, Forbang NI, et al. Race/ethnic and sex disparities in the non-alcoholic fatty liver disease-abdominal aortic calcification association: the multi-ethnic study of atherosclerosis. Atherosclerosis 2017;258:89–96.
[40]. VanWagner LB, Ning H, Lewis CE, et al. Associations between nonalcoholic fatty liver disease and subclinical atherosclerosis in middle-aged adults: the coronary artery risk development in young adults study. Atherosclerosis 2014;235:599–605.

abdominal visceral fat; aortic calcification; atherosclerosis; calcium score; non-enhanced CT

Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc.