Skip to main content
SpringerLink
Log in

Absent atherosclerotic risk factors are associated with carotid stiffening quantified with ultrafast ultrasound imaging

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

Abstract

Objectives

To evaluate carotid stiffening in participants without conventional cardiovascular risk factors (CVRFs) by using ultrafast pulse wave velocity (ufPWV).

Methods

The present study enrolled 517 participants without conventional CVRFs (CVRF-Free total population). Subjects in this population were defined as current non-smokers with untreated blood pressure < 140/90 mmHg, fasting blood glucose (FBG) < 7.0 mmol/L, total cholesterol (TC) < 6.2 mmol/L, low-density lipoprotein cholesterol < 4.1 mmol/L, and high-density lipoprotein cholesterol ≥ 1.0 mmol/L. Participants in the subgroup with optimal CVRFs (CVRF-Optimal subgroup; n = 188) were defined as having blood pressure < 120/80 mmHg, TC < 5.2 mmol/L, and FBG < 5.6 mmol/L. Clinical interviews, physical examinations, serum draw, carotid intima-media thickness (cIMT), and ufPWV were evaluated. Adjusted odds ratios (ORs) with 95% confidence intervals and ordinal logistic regression models were used.

Results

Carotid stiffening was present in 46.2–54.5% of CVRF-Free subjects. Age, male sex, and body mass index (BMI) were independently associated with carotid stiffening in both the CVRF-Free total population and CVRF-Optimal subgroup (OR for age = 1.10–1.11, OR for male sex = 2.65–7.19, OR for BMI = 1.34–1.62; p < 0.05). Carotid stiffening was associated with TC only in the CVRF-Free total population (OR for TC = 1.84; p = 0.034).

Conclusions

Many CVRF-Free individuals have carotid stiffening. ufPWV for atherosclerotic stiffening aids the assessment of early atherogenesis and may further clarify the true status of healthy adults without CVRFs.

Key Points

• CVRF-Optimal individuals have a lower carotid stiffness than CVRF-Free populations.

• ufPWV is a quantitative predictor for the early assessment of AS.

• Absent major CVRFs cannot be considered low risk for carotid stiffening and atherosclerosis.

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

ACAMS:

Aixplorer cIMT automatic measure system

ALT:

Alanine aminotransferase

AS:

Atherosclerosis

BMI:

Body mass index

CCA:

Common carotid artery

cfPWV:

Carotid-femoral pulse wave velocity

CI:

Confidence interval

cIMT:

Carotid intima-media thickness

CVRF:

Cardiovascular risk factor

DBP:

Diastolic blood pressure

DICOM:

Digital Imaging and Communications in Medicine

eGFR:

Estimated glomerular filtration rate

ESC:

European Society of Cardiology

FBG:

Fasting blood glucose

HDL:

High-density lipoprotein

IMT:

Intima-media thickness

LDL:

Low-density lipoprotein

OR:

Odds ratio

PESA:

Progression of Early Subclinical Atherosclerosis

PWV:

Pulse wave velocity

PWV-BS:

Pulse wave velocity-beginning of systole

PWV-ES:

Pulse wave velocity-end of systole

ROI:

Region of interest

SBP:

Systolic blood pressure

TC:

Total cholesterol

TG:

Triglyceride

ufPWV:

Ultrafast pulse wave velocity

UUI:

Ultrafast ultrasound imaging

vEDS:

Vascular Ehlers-Danlos syndrome

References

  1. Khot UN, Khot MB, Bajzer CT et al (2003) Prevalence of conventional risk factors in patients with coronary heart disease. JAMA 290:898–904

    Article  Google Scholar 

  2. George MG, Tong X, Bowman BA (2017) Prevalence of cardiovascular risk factors and strokes in younger adults. JAMA Neurol 74:695–703

    Article  Google Scholar 

  3. Fernández-Friera L, Fuster V, López-Melgar B et al (2017) Normal LDL-cholesterol levels are associated with subclinical atherosclerosis in the absence of risk factors. J Am Coll Cardiol 70:2979–2991

    Article  Google Scholar 

  4. Piepoli MF, Hoes AW, Agewall S et al (2016) 2016 European guidelines on cardiovascular disease prevention in clinical practice: the Sixth Joint Task Force of the European Society of Cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of 10 societies and by invited experts) developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Atherosclerosis 252:207–274

    Article  CAS  Google Scholar 

  5. Mancia G, Fagard R, Narkiewicz K et al (2013) 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J 34:2159–2219

    Article  Google Scholar 

  6. Baber U, Mehran R, Sartori S et al (2015) Prevalence, impact, and predictive value of detecting subclinical coronary and carotid atherosclerosis in asymptomatic adults: the BioImage study. J Am Coll Cardiol 65:1065–1074

    Article  Google Scholar 

  7. Yeboah J, McClelland RL, Polonsky TS et al (2012) Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. JAMA 308:788–795

    Article  CAS  Google Scholar 

  8. Gonzalez-Cantero A, Gonzalez-Cantero J, Sanchez-Moya AI, Rodriguez-Padial L, Perez-Hortet C, Gonzalez-Calvin JL (2019) Is intima-media thickness a predictor for cardiovascular risk? Lancet 394:380–381

    Article  Google Scholar 

  9. Gepner AD, Young R, Delaney JA et al (2015) Comparison of coronary artery calcium presence, carotid plaque presence, and carotid intima-media thickness for cardiovascular disease prediction in the Multi-Ethnic Study of Atherosclerosis. Circ Cardiovasc Imaging 8:e002262

    Article  Google Scholar 

  10. Den Ruijter HM, Peters SA, Anderson TJ et al (2012) Common carotid intima-media thickness measurements in cardiovascular risk prediction: a meta-analysis. JAMA 308:796–803

    Article  Google Scholar 

  11. Lorenz MW, Polak JF, Kavousi M et al (2012) Carotid intima-media thickness progression to predict cardiovascular events in the general population (the PROG-IMT collaborative project): a meta-analysis of individual participant data. Lancet 379:2053–2062

    Article  Google Scholar 

  12. Vlachopoulos C, Aznaouridis K, Stefanadis C (2010) Prediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysis. J Am Coll Cardiol 55:1318–1327

    Article  Google Scholar 

  13. Marais L, Pernot M, Khettab H et al (2019) Arterial stiffness assessment by shear wave elastography and ultrafast pulse wave imaging: comparison with reference techniques in normotensives and hypertensives. Ultrasound Med Biol 45:758–772

    Article  Google Scholar 

  14. Mirault T, Pernot M, Frank M et al (2015) Carotid stiffness change over the cardiac cycle by ultrafast ultrasound imaging in healthy volunteers and vascular Ehlers-Danlos syndrome. J Hypertens 33:1890–1896

    Article  CAS  Google Scholar 

  15. Li X, Jiang J, Zhang H et al (2007) Measurement of carotid pulse wave velocity using ultrafast ultrasound imaging in hypertensive patients. J Med Ultrason (2001) 44:183–190

  16. Zhu ZQ, Chen LS, Wang H et al (2019) Carotid stiffness and atherosclerotic risk: non-invasive quantification with ultrafast ultrasound pulse wave velocity. Eur Radiol 29:1507–1517

    Article  Google Scholar 

  17. Pan FS, Xu M, Yu L et al (2019) Relationship between carotid intima-media thickness and carotid artery stiffness assessed by ultrafast ultrasound imaging in patients with type 2 diabetes. Eur J Radiol 111:34–40

    Article  Google Scholar 

  18. Pan FS, Yu L, Luo J et al (2018) Carotid artery stiffness assessment by ultrafast ultrasound imaging: feasibility and potential influencing factors. J Ultrasound Med 37:2759–2767

    Article  Google Scholar 

  19. Levey AS, Stevens LA, Schmid CH et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612

    Article  Google Scholar 

  20. Touboul PJ, Hennerici MG, Meairs S et al (2004) Mannheim intima-media thickness consensus. Cerebrovasc Dis 18:346–349

    Article  Google Scholar 

  21. Näslund U, Ng N, Lundgren A et al (2019) Visualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA): a pragmatic, open-label, randomised controlled trial. Lancet 393:133–142

    Article  Google Scholar 

  22. Denissen SJ, van der Aalst CM, Vonder M, Oudkerk M, de Koning HJ (2019) Impact of a cardiovascular disease risk screening result on preventive behaviour in asymptomatic participants of the ROBINSCA trial. Eur J Prev Cardiol 26:1313–1322

    Article  Google Scholar 

  23. El Jalbout R, Cloutier G, Roy-Cardinal MH et al (2019) The value of non-invasive vascular elastography (NIVE) in detecting early vascular changes in overweight and obese children. Eur Radiol 29:3854–3861

    Article  Google Scholar 

  24. Roy Cardinal MH, Durand M, Chartrand-Lefebvre C et al (2020) Increased carotid artery wall stiffness and plaque prevalence in HIV infected patients measured with ultrasound elastography. Eur Radiol 30:3178–3187

    Article  Google Scholar 

  25. Wang JC, Bennett M (2012) Aging and atherosclerosis: mechanisms, functional consequences, and potential therapeutics for cellular senescence. Circ Res 111:245–259

    Article  CAS  Google Scholar 

  26. Yu XH, Zhang DW, Zheng XL, Tang CK (2019) Cholesterol transport system: an integrated cholesterol transport model involved in atherosclerosis. Prog Lipid Res 73:65–91

    Article  CAS  Google Scholar 

  27. Reimann C, Brangsch J, Colletini F et al (2017) Molecular imaging of the extracellular matrix in the context of atherosclerosis. Adv Drug Deliv Rev 113:49–60

    Article  CAS  Google Scholar 

  28. Bonnans C, Chou J, Werb Z (2014) Remodelling the extracellular matrix in development and disease. Nat Rev Mol Cell Biol 15:786–801

    Article  CAS  Google Scholar 

  29. Ahmadi A, Argulian E, Leipsic J, Newby DE, Narula J (2019) From subclinical atherosclerosis to plaque progression and acute coronary events: JACC state-of-the-art review. J Am Coll Cardiol 74:1608–1617

    Article  Google Scholar 

  30. Fernández-Friera L, Peñalvo JL, Fernández-Ortiz A et al (2015) Prevalence, vascular distribution, and multiterritorial extent of subclinical atherosclerosis in a middle-aged cohort: the PESA (Progression of Early Subclinical Atherosclerosis) study. Circulation 131:2104–2113

    Article  Google Scholar 

  31. Kassi E, Spilioti E, Nasiri-Ansari N et al (2015) Vascular inflammation and atherosclerosis: the role of estrogen receptors. Curr Med Chem 22:2651–2665

    Article  CAS  Google Scholar 

  32. Peters SAE, Muntner P, Woodward M (2019) Sex differences in the prevalence of, and trends in, cardiovascular risk factors, treatment, and control in the United States, 2001 to 2016. Circulation 139:1025–1035

    Article  CAS  Google Scholar 

  33. Chen YC, Hsu BG, Lee CJ, Ho CC, Ho GJ, Lee MC (2018) Serum adipocyte fatty acid-binding protein level is associated with arterial stiffness quantified with cardio-ankle vascular index in kidney transplant patients. Clin Exp Nephrol 22:188–195

  34. Tsiakou A, Liatis S, Alexiadou K et al (2013) Arterial stiffness is inversely related to plasma adiponectin levels in young normotensive patients with type 1 diabetes. Diabetes Care 36:734–736

    Article  CAS  Google Scholar 

  35. Borén J, Chapman MJ, Krauss RM et al (2020) Low-density lipoproteins cause atherosclerotic cardiovascular disease: pathophysiological, genetic, and therapeutic insights: a consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J. https://doi.org/10.1093/eurheartj/ehz962

Download references

Funding

This work was supported by the National Natural Science Foundation of China (grant number: 81901756), the Team Project of Jiangsu Provincial Six Talent Peaks (grant number: TD-SWYY-069), the Key Project of Jiangsu Administration of Chinese Medicine (grant number: ZD201906), the Research Project of National Administration of Chinese Medicine (grant number: YB2015020), and the Research of Jiangsu Province Hospital of Chinese Medicine (grant number: Y20044).

Author information

Author notes

  1. Zheng-Qiu Zhu and Ling-Shan Chen contributed equally to this work.

Authors and Affiliations

  1. Department of Ultrasound, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, China

    Zheng-Qiu Zhu, Yi-Yun Wu, Yun Luan, Hui Gao, Ping Dai, Xue-Hui Ma, Lin-Lin Wu, Hui-Juan Sun, Yin-Ping Wang & Hui Huang

  2. Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, China

    Ling-Shan Chen

  3. Department of Ultrasound, Jiangsu Province Geriatric Hospital, Geriatric Hospital of Nanjing Medical University, Nanjing, 210024, China

    Xue-Zhong Jiang

  4. Department of Cardiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, China

    Chong Zou, Fei Zou & Fu-Ming Liu

  5. Center of Good Clinical Practice, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, China

    Chong Zou

Authors
  1. Zheng-Qiu Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ling-Shan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xue-Zhong Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yi-Yun Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chong Zou
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yun Luan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hui Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ping Dai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Xue-Hui Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Lin-Lin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hui-Juan Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yin-Ping Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Fei Zou
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Fu-Ming Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Hui Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Fu-Ming Liu or Hui Huang.

Ethics declarations

Guarantor

The scientific guarantors of this publication are Hui Huang, M.D. (Department of Ultrasound, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, China) and Fu-Ming Liu, Ph.D. (Department of Cardiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, China).

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

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• diagnostic or prognostic study

• performed at one institution

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOC 7902 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, ZQ., Chen, LS., Jiang, XZ. et al. Absent atherosclerotic risk factors are associated with carotid stiffening quantified with ultrafast ultrasound imaging. Eur Radiol 31, 3195–3206 (2021). https://doi.org/10.1007/s00330-020-07405-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-020-07405-4

Keywords

Search

Navigation