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Ascending Aorta 4D Time to Peak Distention Sexual Dimorphism and Association with Coronary Plaque Burden Severity in Women

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Abstract

Coronary artery disease (CAD) risk and plaque scores are often subjective and biased, particularly in mid-age asymptomatic women, whose CAD risk assessment has been historically underestimated. In this study, a new automatic ascending aorta time-to-peak-distention (TPD) analysis was developed for fast screening and as an independent surrogate for subclinical atherosclerosis in asymptomatic women. CCTA was obtained in 50 asymptomatic adults. Plaque burden segment involvement score (SIS) and automatic TPD were obtained from all subjects. Logistic regression analyses were performed to investigate the association between CAD risk scores and TPD with severe coronary plaque burden (SIS>5). TPD, individually, was found to be a significant predictor of SIS>5. Additionally, sex was a significant effect modifier of TPD, with a stronger statistically significant association with women. Four-dimensional aortic time-to-peak distention could supplement conventional CCTA analysis and offer a quick objective screening tool for plaque burden severity and CAD risk stratification, especially in women.

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Abbreviations

CAD:

Coronary artery disease

CCTA:

Coronary computed tomography angiography

MDCT:

Multi-detector computed tomography

AA:

Ascending aorta

TPD:

Time to peak distensibility

ROC:

Receiver operator curve

FrS:

Framingham score

ASCVD:

Atherosclerotic cardiovascular disease pooled cohort equation score

SIS:

Segment involvement score

AD:

Aortic distensibility

ECG:

Electrocardiograph

AoAd:

Diastolic aortic cross-sectional area

AoAs:

Systolic aortic cross-sectional area

Ps:

Systolic blood pressure

Pd:

Diastolic blood pressure

PWV:

Pulse wave velocity

IQR:

Interquartile range

SD:

Standard deviation

CVD:

Cardiovascular disease

References

  1. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB Sr, Gibbons R, et al. ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;63(25 Pt B):2935–59. https://doi.org/10.1016/j.jacc.2013.11.005.

    Article  PubMed  Google Scholar 

  2. Michos ED, Nasir K, Braunstein JB, Rumberger JA, Budoff MJ, Post WS, et al. Framingham risk equation underestimates subclinical atherosclerosis risk in asymptomatic women. Atherosclerosis. 2006;184(1):201–6. https://doi.org/10.1016/j.atherosclerosis.2005.04.004.

    Article  CAS  PubMed  Google Scholar 

  3. Gulati M, Shaw LJ, Bairey Merz CN. Myocardial ischemia in women: lessons from the NHLBI WISE study. Clin Cardiol. 2012;35(3):141–8. https://doi.org/10.1002/clc.21966.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Wilmot KA, O'Flaherty M, Capewell S, Ford ES, Vaccarino V. Coronary heart disease mortality declines in the United States from 1979 through 2011: evidence for stagnation in young adults, especially women. Circulation. 2015;132(11):997–1002. https://doi.org/10.1161/CIRCULATIONAHA.115.015293.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Johnson KM, Dowe DA. The detection of any coronary calcium outperforms Framingham risk score as a first step in screening for coronary atherosclerosis. AJR Am J Roentgenol. 2010;194(5):1235–43. https://doi.org/10.2214/AJR.09.2487.

    Article  PubMed  Google Scholar 

  6. Raggi P, Shaw LJ, Berman DS, Callister TQ. Gender-based differences in the prognostic value of coronary calcification. J Womens Health. 2004;13(3):273–83. https://doi.org/10.1089/154099904323016437.

    Article  Google Scholar 

  7. Redheuil A, Wu CO, Kachenoura N, Ohyama Y, Yan RT, Bertoni AG, et al. Proximal aortic distensibility is an independent predictor of all-cause mortality and incident CV events: the MESA study. J Am Coll Cardiol. 2014;64(24):2619–29. https://doi.org/10.1016/j.jacc.2014.09.060.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Nichols WW, Denardo SJ, Davidson JB, Huo T, Bairey Merz CN, Pepine CJ. Association of aortic stiffness and wave reflections with coronary flow reserve in women without obstructive coronary artery disease: an ancillary study from the National Heart, Lung, and Blood Institute-sponsored Women’s Ischemia Syndrome Evaluation (WISE). Am Heart J. 2015;170(6):1243–54. https://doi.org/10.1016/j.ahj.2015.08.019.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Siegel E, Thai WE, Techasith T, Major G, Szymonifka J, Tawakol A, et al. Aortic distensibility and its relationship to coronary and thoracic atherosclerosis plaque and morphology by MDCT: insights from the ROMICAT trial. Int J Cardiol. 2013;167(4):1616–21. https://doi.org/10.1016/j.ijcard.2012.04.107.

    Article  PubMed  Google Scholar 

  10. Ahmadi N, Nabavi V, Hajsadeghi F, Flores F, Azmoon S, Ismaeel H, et al. Impaired aortic distensibility measured by computed tomography is associated with the severity of coronary artery disease. Int J Cardiovasc Imaging. 2011;27(3):459–69. https://doi.org/10.1007/s10554-010-9680-6.

    Article  PubMed  Google Scholar 

  11. Okuyama T, Ehara S, Shirai N, Sugioka K, Yamashita H, Kataoka T, et al. Assessment of aortic atheromatous plaque and stiffness by 64-slice computed tomography is useful for identifying patients with coronary artery disease. Circ J. 2008;72(12):2021–7. https://doi.org/10.1253/circj.cj-08-0396.

    Article  PubMed  Google Scholar 

  12. Nichols WW, O'Rourke MF, Edelman ER, Vlachopoulos C. McDonald's blood flow in arteries : theoretical, experimental and clinical principles. Seventh edition. ed. Boca Raton, FL: CRC Press; 2022.

  13. Hashimoto J, Ito S. Aortic stiffness determines diastolic blood flow reversal in the descending thoracic aorta: potential implication for retrograde embolic stroke in hypertension. Hypertension. 2013;62(3):542–9. https://doi.org/10.1161/HYPERTENSIONAHA.113.01318.

    Article  CAS  PubMed  Google Scholar 

  14. O'Rourke MF, Hashimoto J. Mechanical factors in arterial aging: a clinical perspective. J Am Coll Cardiol. 2007;50(1):1–13. https://doi.org/10.1016/j.jacc.2006.12.050.

    Article  PubMed  Google Scholar 

  15. Dyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhall CJ, Ebbers T, et al. 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson. 2015;17(1):72. https://doi.org/10.1186/s12968-015-0174-5.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Zhang J, Fletcher JG, Vrtiska TJ, Manduca A, Thompson JL, Raghavan ML, et al. Large-vessel distensibility measurement with electrocardiographically gated multidetector CT: phantom study and initial experience. Radiology. 2007;245(1):258–66. https://doi.org/10.1148/radiol.2451060530.

    Article  PubMed  Google Scholar 

  17. Min JK, Dunning A, Lin FY, Achenbach S, Al-Mallah M, Budoff MJ, et al. Age- and sex-related differences in all-cause mortality risk based on coronary computed tomography angiography findings results from the International Multicenter CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry) of 23,854 patients without known coronary artery disease. J Am Coll Cardiol. 2011;58(8):849–60. https://doi.org/10.1016/j.jacc.2011.02.074.

    Article  PubMed  Google Scholar 

  18. Magnoni M, Andreini D, Gorini M, Moccetti T, Modena MG, Canestrari M, et al. Coronary atherosclerosis in outlier subjects at the opposite extremes of traditional risk factors: rationale and preliminary results of the Coronary Atherosclerosis in outlier subjects: Protective and novel Individual Risk factors Evaluation (CAPIRE) study. Am Heart J. 2016;173:18–26. https://doi.org/10.1016/j.ahj.2015.11.017.

    Article  PubMed  Google Scholar 

  19. Ghanem AM, Hamimi AH, Matta JR, Carass A, Elgarf RM, Gharib AM, et al. Automatic coronary wall and atherosclerotic plaque segmentation from 3D coronary CT angiography. Sci Rep. 2019;9(1):47. https://doi.org/10.1038/s41598-018-37168-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9. https://doi.org/10.1016/s0895-4356(96)00236-3.

    Article  CAS  PubMed  Google Scholar 

  21. Rylski B, Desjardins B, Moser W, Bavaria JE, Milewski RK. Gender-related changes in aortic geometry throughout life. Eur J Cardiothorac Surg. 2014;45(5):805–11. https://doi.org/10.1093/ejcts/ezt597.

    Article  PubMed  Google Scholar 

  22. Chang HW, Kim SH, Hakim AR, Chung S, Kim DJ, Lee JH, et al. Diameter and growth rate of the thoracic aorta-analysis based on serial computed tomography scans. J Thorac Dis. 2020;12(8):4002–13. https://doi.org/10.21037/jtd-20-1275.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Crea F, Battipaglia I, Andreotti F. Sex differences in mechanisms, presentation and management of ischaemic heart disease. Atherosclerosis. 2015;241(1):157–68. https://doi.org/10.1016/j.atherosclerosis.2015.04.802.

    Article  CAS  PubMed  Google Scholar 

  24. Mileto A, Heye TJ, Makar RA, Hurwitz LM, Marin D, Boll DT. Regional mapping of aortic wall stress by using deformable, motion-coherent modeling based on electrocardiography-gated multidetector CT angiography: feasibility study. Radiology. 2016;280(1):230–6. https://doi.org/10.1148/radiol.2015151078.

    Article  PubMed  Google Scholar 

  25. Cecchi E, Giglioli C, Valente S, Lazzeri C, Gensini GF, Abbate R, et al. Role of hemodynamic shear stress in cardiovascular disease. Atherosclerosis. 2011;214(2):249–56. https://doi.org/10.1016/j.atherosclerosis.2010.09.008.

    Article  CAS  PubMed  Google Scholar 

  26. Gijsen F, van der Giessen A, van der Steen A, Wentzel J. Shear stress and advanced atherosclerosis in human coronary arteries. J Biomech. 2013;46(2):240–7. https://doi.org/10.1016/j.jbiomech.2012.11.006.

    Article  PubMed  Google Scholar 

  27. Coutinho T. Arterial stiffness and its clinical implications in women. Can J Cardiol. 2014;30(7):756–64. https://doi.org/10.1016/j.cjca.2014.03.020.

    Article  PubMed  Google Scholar 

  28. Coutinho T, Borlaug BA, Pellikka PA, Turner ST, Kullo IJ. Sex differences in arterial stiffness and ventricular-arterial interactions. J Am Coll Cardiol. 2013;61(1):96–103. https://doi.org/10.1016/j.jacc.2012.08.997.

    Article  PubMed  Google Scholar 

  29. Coutinho T, Yam Y, Chow BJW, Dwivedi G, Inacio J. Sex differences in associations of arterial compliance with coronary artery plaque and calcification burden. J Am Heart Assoc. 2017;6(8) https://doi.org/10.1161/JAHA.117.006079.

  30. Coutinho T, Mielniczuk LM, Srivaratharajah K, deKemp R, Wells GA, Beanlands RS. Coronary artery microvascular dysfunction: role of sex and arterial load. Int J Cardiol. 2018;270:42–7. https://doi.org/10.1016/j.ijcard.2018.06.072.

    Article  PubMed  Google Scholar 

  31. Gatzka CD, Cameron JD, Kingwell BA, Dart AM. Relation between coronary artery disease, aortic stiffness, and left ventricular structure in a population sample. Hypertension. 1998;32(3):575–8. https://doi.org/10.1161/01.hyp.32.3.575.

    Article  CAS  PubMed  Google Scholar 

  32. Weber T, Auer J, O'Rourke MF, Kvas E, Lassnig E, Berent R, et al. Arterial stiffness, wave reflections, and the risk of coronary artery disease. Circulation. 2004;109(2):184–9. https://doi.org/10.1161/01.CIR.0000105767.94169.E3.

    Article  PubMed  Google Scholar 

  33. Segers P, Rietzschel ER, De Buyzere ML, Vermeersch SJ, De Bacquer D, Van Bortel LM, et al. Noninvasive (input) impedance, pulse wave velocity, and wave reflection in healthy middle-aged men and women. Hypertension. 2007;49(6):1248–55. https://doi.org/10.1161/HYPERTENSIONAHA.106.085480.

    Article  CAS  PubMed  Google Scholar 

  34. Bugiardini R, Badimon L, Collins P, Erbel R, Fox K, Hamm C, et al. Angina, “normal” coronary angiography, and vascular dysfunction: risk assessment strategies. PLoS Med. 2007;4(2):e12. https://doi.org/10.1371/journal.pmed.0040012.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Ghanem AM, Matta JR, Elgarf R, Hamimi A, Muniyappa R, Ishaq H, et al. Sexual dimorphism of coronary artery disease in a low- and intermediate-risk asymptomatic population: association with coronary vessel wall thickness at MRI in women. Radiol Cardiothorac Imaging. 2019;1(1):e180007. https://doi.org/10.1148/ryct.2019180007.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Pasupathy S, Air T, Dreyer RP, Tavella R, Beltrame JF. Systematic review of patients presenting with suspected myocardial infarction and nonobstructive coronary arteries. Circulation. 2015;131(10):861–70. https://doi.org/10.1161/CIRCULATIONAHA.114.011201.

    Article  CAS  PubMed  Google Scholar 

  37. Dean J, Cruz SD, Mehta PK, Merz CN. Coronary microvascular dysfunction: sex-specific risk, diagnosis, and therapy. Nat Rev Cardiol. 2015;12(7):406–14. https://doi.org/10.1038/nrcardio.2015.72.

    Article  PubMed  Google Scholar 

  38. Yoshino S, Cilluffo R, Prasad M, Best PJ, Atkinson EJ, Aoki T, et al. Sex-specific genetic variants are associated with coronary endothelial dysfunction. J Am Heart Assoc. 2016;5(4):e002544. https://doi.org/10.1161/JAHA.115.002544.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Ayoub C, Erthal F, Abdelsalam MA, Murad MH, Wang Z, Erwin PJ, et al. Prognostic value of segment involvement score compared to other measures of coronary atherosclerosis by computed tomography: a systematic review and meta-analysis. J Cardiovasc Comput Tomogr. 2017;11(4):258–67. https://doi.org/10.1016/j.jcct.2017.05.001.

    Article  PubMed  Google Scholar 

  40. Szilveszter B, Kolossvary M, Pontone G, Williams MC, Dweck MR, Maurovich-Horvat P. How to quantify coronary atherosclerotic plaque using computed tomography. Eur Heart J Cardiovasc Imaging. 2022;23(12):1573–5. https://doi.org/10.1093/ehjci/jeac192.

    Article  PubMed  Google Scholar 

  41. Pen A, Yam Y, Chen L, Dennie C, McPherson R, Chow BJ. Discordance between Framingham risk score and atherosclerotic plaque burden. Eur Heart J. 2013;34(14):1075–82. https://doi.org/10.1093/eurheartj/ehs473.

    Article  CAS  PubMed  Google Scholar 

  42. Li F, Wang X. Relationship between Framingham risk score and subclinical atherosclerosis in carotid plaques: an in vivo study using multi-contrast MRI. Sci China Life Sci. 2017;60(1):23–7. https://doi.org/10.1007/s11427-016-0385-5.

    Article  PubMed  Google Scholar 

  43. Seaoud E, Shawky A. Framingham risk score and extent of atherosclerosis in non-diabetic patients with suspected coronary artery disease. J Indian Coll Cardiol. 2018;8(1):18–20. https://doi.org/10.1016/j.jicc.2017.12.001.

    Article  Google Scholar 

  44. Min JK, Shaw LJ, Devereux RB, Okin PM, Weinsaft JW, Russo DJ, et al. Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. J Am Coll Cardiol. 2007;50(12):1161–70. https://doi.org/10.1016/j.jacc.2007.03.067.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors thank the participants for their time and contribution to this research endeavor.

Funding

This work was supported by the Intramural Research Program of the National Institute of Diabetes, Digestive, and Kidney Diseases at the National Institutes of Health.

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Authors and Affiliations

  1. Biomedical and Metabolic Imaging Branch (BMIB), National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), 10 Center Drive, 1C334, Bethesda, MD, 20892, USA

    Ahmed H. Hamimi, Ahmed M. Ghanem, Reham M. Elgarf, Jatin R. Matta, Ahmed M. Gharib & Khaled Z. Abd-Elmoniem

  2. Internal Medicine, Endocrinology, and Genetics, Division of Endocrinology, University of British Columbia, Vancouver, BC, Canada

    Fady Hannah-Shmouni

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  1. Ahmed H. Hamimi
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Correspondence to Ahmed M. Gharib or Khaled Z. Abd-Elmoniem.

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All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

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Hamimi, A.H., Ghanem, A.M., Hannah-Shmouni, F. et al. Ascending Aorta 4D Time to Peak Distention Sexual Dimorphism and Association with Coronary Plaque Burden Severity in Women. J. of Cardiovasc. Trans. Res. 17, 298–307 (2024). https://doi.org/10.1007/s12265-023-10422-5

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