Skip to main content

Advertisement

SpringerLink
Log in

Is the epicardial adipose tissue area on non-ECG gated low-dose chest CT useful for predicting coronary atherosclerosis in an asymptomatic population considered for lung cancer screening?

  • Cardiac
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objects

The purpose was to determine whether the epicardial adipose tissue (EAT) area on low-dose chest CT (LDCT) could be used to predict coronary atherosclerosis in an asymptomatic population considered for lung cancer screening.

Methods

Subjects aged 55-80 years with smoking history who underwent both LDCT and coronary CT angiography (CCTA) were retrospectively enrolled. Correlation between the EAT volume in CCTA and EAT area in LDCT was evaluated. Coronary risk factors including the body surface area (BSA) indexed EAT area were compared between coronary plaque negative and positive groups. Significant factors for predicting coronary atherosclerosis were analyzed with logistic regression analysis. Receiver-operating characteristic curve analysis was performed to determine the cutoff value.

Results

A total of 438 subjects were enrolled, including 299 subjects with coronary atherosclerosis. There was a good correlation between the EAT volume in CCTA and EAT area in LDCT (ρ = 0.712, p < 0.001). There were significant differences in age, systolic blood pressure, all BSA indexed EAT area, sex, and hypertension between plaque negative and positive groups. In multivariate logistic regression for the BSA indexed EAT area in LDCT at the RCA level, sex (OR: 11.168, 95% CI: 2.107-59.201, p = 0.005), systolic blood pressure (OR: 1.021, 95% CI: 1.005-1.036, p = 0.009), hypertension (OR: 1.723, 95% CI: 1.103-2.753, p = 0.017), and EAT area (OR: 1.273, 95% CI: 1.154-1.405, p < 0.001) were significant. The area under the curve of the BSA indexed EAT area in LDCT at the RCA level for coronary atherosclerosis was 0.657, and the cut-off value was 7.66 cm2/m2.

Conclusion

The EAT area in LDCT could be used to predict coronary atherosclerosis in an asymptomatic population considered for lung cancer screening.

Key Points

• To quantify EAT, the EAT area in LDCT can be used instead of the EAT volume in CCTA.

• The EAT area measured in LDCT can be used as a predictor of coronary artery disease.

• The extensive CAD group tended to have a greater EAT area than the non-extensive CAD group.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

A_CCTA:

EAT area in CCTA

A_LDCT:

EAT area in LDCT

ALM_LDCT:

EAT area in LDCT at LM

ARCA_LDCT:

EAT area in LDCT at RCA

AUC:

Area under the curve

BMI:

Body mass index

BSA:

Body surface area

CAD:

Coronary artery disease

CCTA:

Coronary CT angiography

CIs:

Confidence intervals

CT:

Computed tomography

DBP:

Diastolic blood pressure

EAT:

Epicardial adipose tissue

HDL:

High-density lipoprotein

HU:

Hounsfield units

IRB:

Institutional Review Board

LDCT:

Low-dose chest computed tomography

LDL:

Low-density lipoprotein

LM:

Left main coronary artery

MI:

Myocardial infarction

MRI:

Magnetic resonance imaging

NLST:

National Lung Screening Trial

OR:

Odds ratios (ORs)

RCA:

Right coronary artery

ROC:

Receiver-operating characteristic

SBP:

Systolic blood pressure

USPSTF:

US Preventive Services Task Force

V_CCTA:

EAT volume in CCTA

References

  1. Sacks HS, Fain JN (2007) Human epicardial adipose tissue: a review. Am Heart J 153:907–917

    Article  CAS  Google Scholar 

  2. Şengül C, Özveren O (2013) Epicardial adipose tissue: a review of physiology, pathophysiology, and clinical applications. Anadolu Kardiyol Derg 13:261–265

    Google Scholar 

  3. Hatem SN, Sanders P (2014) Epicardial adipose tissue and atrial fibrillation. Cardiovasc Res 102:205–213

    Article  CAS  Google Scholar 

  4. Rosito GA, Massaro JM, Hoffmann U et al (2008) Pericardial fat, visceral abdominal fat, cardiovascular disease risk factors, and vascular calcification in a community-based sample. Circulation 117:605–613

    Article  Google Scholar 

  5. Wang T-D, Lee W-J, Shih F-Y et al (2010) Association of epicardial adipose tissue with coronary atherosclerosis is region-specific and independent of conventional risk factors and intra-abdominal adiposity. Atherosclerosis 213:279–287

    Article  CAS  Google Scholar 

  6. Kim S-H, Chung J-H, Kwon B-J, Song S-W, Choi W-S (2013) The associations of epicardial adipose tissue with coronary artery disease and coronary atherosclerosis. Int Heart J 55:197–203

    Article  Google Scholar 

  7. Marwan M, Achenbach S (2013) Quantification of epicardial fat by computed tomography: why, when and how? J Cardiovasc Comput Tomogr 7:3–10

    Article  Google Scholar 

  8. Hajsadeghi F, Nabavi V, Bhandari A et al (2014) Increased epicardial adipose tissue is associated with coronary artery disease and major adverse cardiovascular events. Atherosclerosis 237:486–489

    Article  CAS  Google Scholar 

  9. Saad Z, El-Rawy M, Donkol RH, Boghattas S (2015) Quantification of epicardial fat: Which method can predict significant coronary artery disease? World J Cardiol 7:287

    Article  Google Scholar 

  10. Eroglu S, Sade LE, Yildirir A et al (2009) Epicardial adipose tissue thickness by echocardiography is a marker for the presence and severity of coronary artery disease. Nutr Metab Cardiovasc Dis 19:211–217

    Article  CAS  Google Scholar 

  11. Picard FA, Gueret P, Laissy J-P et al (2014) Epicardial adipose tissue thickness correlates with the presence and severity of angiographic coronary artery disease in stable patients with chest pain. PLoS One 9:e110005

    Article  Google Scholar 

  12. Wang T, Liu Q, Liu C et al (2014) Correlation of echocardiographic epicardial fat thickness with severity of coronary artery disease in patients with acute myocardial infarction. Echocardiography 31:1177–1181

    Article  CAS  Google Scholar 

  13. Sicari R, Sironi AM, Petz R et al (2011) Pericardial rather than epicardial fat is a cardiometabolic risk marker: an MRI vs echo study. J Am Soc Echocardiogr 24:1156–1162

    Article  Google Scholar 

  14. Team NLSTR (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011:395–409

  15. Moyer VA (2014) Screening for lung cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med 160:330–338

    Google Scholar 

  16. Greenland P, Alpert JS, Beller GA et al (2010) 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association task force on practice guidelines developed in collaboration with the American Society of Echocardiography, American Society of Nuclear Cardiology, Society of Atherosclerosis Imaging and Prevention, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance. J Am Coll Cardiol 56:e50–e103

    Article  Google Scholar 

  17. Hecht HS, Cronin P, Blaha MJ et al (2017) 2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: A report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology. J Cardiovasc Comput Tomogr 11:74–84

    Article  Google Scholar 

  18. Leber AW, Becker A, Knez A et al (2006) Accuracy of 64-slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound. J Am Coll Cardiol 47:672–677

    Article  Google Scholar 

  19. Yong HS, Kim EJ, Seo HS et al (2010) Pericardial fat is more abundant in patients with coronary atherosclerosis and even in the non-obese patients: evaluation with cardiac CT angiography. Int J Card Imaging 26:53–62

    Article  Google Scholar 

  20. Habets J, van den Brink RB, Uijlings R et al (2012) Coronary artery assessment by multidetector computed tomography in patients with prosthetic heart valves. Eur Radiol 22:1278–1286

    Article  Google Scholar 

  21. Austen WG, Edwards JE, Frye RL et al (1975) A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation 51:5–40

    Article  CAS  Google Scholar 

  22. Hulten E, Bittencourt MS, Singh A et al (2014) Coronary artery disease detected by coronary computed tomographic angiography is associated with intensification of preventive medical therapy and lower low-density lipoprotein cholesterol. Circ Cardiovasc Imaging 7:629–638

    Article  Google Scholar 

  23. Lu MT, Park J, Ghemigian K et al (2016) Epicardial and paracardial adipose tissue volume and attenuation–Association with high-risk coronary plaque on computed tomographic angiography in the ROMICAT II trial. Atherosclerosis 251:47–54

    Article  CAS  Google Scholar 

  24. Mancio J, Pinheiro M, Ferreira W et al (2017) Gender differences in the association of epicardial adipose tissue and coronary artery calcification: EPICHEART study: EAT and coronary calcification by gender. Int J Cardiol 249:419–425

    Article  Google Scholar 

  25. Djaberi R, Schuijf JD, van Werkhoven JM, Nucifora G, Jukema JW, Bax JJ (2008) Relation of epicardial adipose tissue to coronary atherosclerosis. Am J Cardiol 102:1602–1607

    Article  Google Scholar 

  26. Jang H-C, Lee H-K, Lee H, Cha J-G, Kim Y-S, Cho J-H (2015) Analyzing correlation between epicardial fat area and metabolic syndrome risk factor by using low-dose Lung CT. Pak J Med Sci 31:1207

    Article  Google Scholar 

  27. Anderson KM, Wolson P, Odell PM, Kannel WB (1991) An updated coronary risk profile: a statement for health professionals. Circulation 83:356–362

    Article  CAS  Google Scholar 

  28. Oyama N, Goto D, Ito YM et al (2011) Single-slice epicardial fat area measurement: do we need to measure the total epicardial fat volume? Jpn J Radiol 29:104–109

    Article  Google Scholar 

  29. Simon-Yarza I, Viteri-Ramírez G, Saiz-Mendiguren R, Slon-Roblero PJ, Paramo M, Bastarrika G (2012) Feasibility of epicardial adipose tissue quantification in non-ECG-gated low-radiation-dose CT: comparison with prospectively ECG-gated cardiac CT. Acta Radiol 53:536–540

    Article  Google Scholar 

  30. Tanami Y, Jinzaki M, Kishi S et al (2015) Lack of association between epicardial fat volume and extent of coronary artery calcification, severity of coronary artery disease, or presence of myocardial perfusion abnormalities in a diverse, symptomatic patient population. Clin Perspect Circ Cardiovasc Imaging 8:e002676

    Google Scholar 

  31. Forouzandeh F, Chang SM, Muhyieddeen K et al (2012) Does quantifying epicardial and intrathoracic fat with noncontrast computed tomography improve risk stratification beyond calcium scoring alone? Circ Cardiovasc Imaging: CIRCIMAGING 976316:112

    Google Scholar 

  32. Khawaja T, Greer C, Thadani SR et al (2015) Increased regional epicardial fat volume associated with reversible myocardial ischemia in patients with suspected coronary artery disease. J Nucl Cardiol 22:325–333

    Article  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Departments of Radiology, College of Medicine, Korea University, Seoul, Korea

    Kyu-Chong Lee, Hwan Seok Yong, Jaewook Lee & Eun-young Kang

  2. Korea University Guro Hospital, Gurodong-ro 148, Guro-gu, Seoul, 08308, Korea

    Hwan Seok Yong

  3. Departments of cardiology, College of Medicine, Korea University, Seoul, Korea

    Jin Oh Na

Authors
  1. Kyu-Chong Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hwan Seok Yong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaewook Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Eun-young Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jin Oh Na
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hwan Seok Yong.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Hwan Seok Yong.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Case-control study

• Performed at one institution

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, KC., Yong, H.S., Lee, J. et al. Is the epicardial adipose tissue area on non-ECG gated low-dose chest CT useful for predicting coronary atherosclerosis in an asymptomatic population considered for lung cancer screening?. Eur Radiol 29, 932–940 (2019). https://doi.org/10.1007/s00330-018-5562-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-018-5562-4

Keywords

Search

Navigation