Skip to main content

Emerging Role of Computed Tomography Angiography in the Evaluation of Coronary Atherosclerosis

  • 1152 Accesses

Part of the Contemporary Cardiology book series (CONCARD)

Abstract

Over the past decade, coronary computed tomographic angiography (CCTA) has broadened the diagnostic ability of physicians by providing a means to non-invasively image coronary atherosclerosis. It provides a robust and accurate method to assess atherosclerotic plaque burden, distribution, morphology and associated luminal stenosis. Importantly this method has provided the potential of revealing preclinical stages of the atherosclerotic disease which may have important value to improve risk stratification and to monitor the progressive course of the disease. In addition to its established role in plaque assessment, the use of CCTA is being rapidly extended to assess the haemodynamic significance of atherosclerotic plaque, associated myocardial ischaemia and to predict clinical outcomes.

Keywords

  • Myocardial Perfusion Imaging
  • Coronary Compute Tomographic Angiography
  • Suspected Coronary Artery Disease
  • Plaque Volume
  • Positive Remodelling

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-1-4939-0572-0_12
  • Chapter length: 22 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-1-4939-0572-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   149.00
Price excludes VAT (USA)
Hardcover Book
USD   149.99
Price excludes VAT (USA)
Fig. 12.1
Fig. 12.2
Fig. 12.3
Fig. 12.4
Fig. 12.5
Fig. 12.6
Fig. 12.7
Fig. 12.8
Fig. 12.9
Fig. 12.10
Fig. 12.11
Fig. 12.12
Fig. 12.13
Fig. 12.14
Fig. 12.15
Fig. 12.16
Fig. 12.17

References

  1. Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics–2012 update: a report from the American Heart Association. Circulation. 2012; 125:e2–220.

    PubMed  CrossRef  Google Scholar 

  2. Stone GW, Maehara A, Lansky AJ, et al. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364:226–35.

    CAS  PubMed  CrossRef  Google Scholar 

  3. Abbara S, Arbab-Zadeh A, Callister TQ, et al. SCCT guidelines for performance of coronary computed tomographic angiography: a report of the Society of Cardiovascular Computed Tomography Guidelines Committee. J Cardiovasc Comput Tomogr. 2009;3:1 90–204.

    Google Scholar 

  4. Miller JM, Rochitte CE, Dewey M, et al. Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med. 2008;359:2324–36.

    CAS  PubMed  CrossRef  Google Scholar 

  5. Meijboom WB, Meijs MF, Schuijf JD, et al. Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study. J Am Coll Cardiol. 2008;52:2135–44.

    PubMed  CrossRef  Google Scholar 

  6. Budoff MJ, Dowe D, Jollis JG, et al. Diagnostic performance of 64-multidetector row coronary computed tomographic angiography for evaluation of coronary artery stenosis in individuals without known coronary artery disease: results from the prospective multicenter ACCURACY (Assessment by Coronary Computed Tomographic Angiography of Individuals Undergoing Invasive Coronary Angiography) trial. J Am Coll Cardiol. 2008;52: 1724–32.

    PubMed  CrossRef  Google Scholar 

  7. Achenbach S. Cardiac CT: state of the art for the detection of coronary arterial stenosis. J Cardiovasc Comput Tomogr. 2007;1:3–20.

    PubMed  CrossRef  Google Scholar 

  8. Chun EJ, Lee W, Choi YH, et al. Effects of nitroglycerin on the diagnostic accuracy of electrocardiogram-gated coronary computed tomography angiography. J Comput Assist Tomogr. 2008;32:86–92.

    PubMed  CrossRef  Google Scholar 

  9. Bischoff B, Hein F, Meyer T, et al. Impact of a reduced tube voltage on CT angiography and radiation dose: results of the PROTECTION I study. JACC Cardiovasc Imaging. 2009;2:940–6.

    PubMed  CrossRef  Google Scholar 

  10. Hausleiter J, Meyer T, Hermann F, et al. Estimated radiation dose associated with cardiac CT angiography. JAMA. 2009;301:500–7.

    CAS  PubMed  CrossRef  Google Scholar 

  11. Chen MY, Shanbhag SM, Arai AE. Submillisievert median radiation dose for coronary angiography with a second-generation 320-detector row CT scanner in 107 consecutive patients. Radiology. 2013;267:76–85.

    PubMed Central  PubMed  CrossRef  Google Scholar 

  12. Achenbach S, Marwan M, Ropers D, et al. Coronary computed tomography angiography with a consistent dose below 1 mSv using prospectively electrocardiogram-triggered high-pitch spiral acquisition. Eur Heart J. 2010;31:340–6.

    PubMed  CrossRef  Google Scholar 

  13. Leipsic J, Labounty TM, Heilbron B, et al. Estimated radiation dose reduction using adaptive statistical iterative reconstruction in coronary CT angiography: the ERASIR study. AJR Am J Roentgenol. 2010;195: 655–60.

    PubMed  CrossRef  Google Scholar 

  14. Raff GL, Abidov A, Achenbach S, et al. SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr. 2009;3:122–36.

    PubMed  CrossRef  Google Scholar 

  15. Schuetz GM, Zacharopoulou NM, Schlattmann P, Dewey M. Meta-analysis: noninvasive coronary angiography using computed tomography versus magnetic resonance imaging. Ann Intern Med. 2010;152: 167–77.

    PubMed  CrossRef  Google Scholar 

  16. Fihn SD, Gardin JM, Abrams J, et al. 2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, and the American College of Physicians, American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J Am Coll Cardiol. 2012;60:e44–164.

    PubMed  CrossRef  Google Scholar 

  17. Montalescot G, Sechtem U, Achenbach S, et al. ESC guidelines on the management of stable coronary artery disease: The Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J. 2013;2013.

    Google Scholar 

  18. Taylor AJ, Cerqueira M, Hodgson JM et al. ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR 2010 Appropriate Use Criteria for Cardiac Computed Tomography. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the Society of Cardiovascular Computed Tomography, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the American Society of Nuclear Cardiology, the North American Society for Cardiovascular Imaging, the Society for Cardiovascular Angiography and Interventions, and the Society for Cardiovascular Magnetic Resonance. J Cardiovasc Comput Tomogr. 2010;4:407.e1–33.

    Google Scholar 

  19. Pflederer T, Schmid M, Ropers D, et al. Interobserver variability of 64-slice computed tomography for the quantification of non-calcified coronary atherosclerotic plaque. Rofo. 2007;179:953–7.

    CAS  PubMed  CrossRef  Google Scholar 

  20. Rinehart S, Vazquez G, Qian Z, Murrieta L, Christian K, Voros S. Quantitative measurements of coronary arterial stenosis, plaque geometry, and composition are highly reproducible with a standardized coronary arterial computed tomographic approach in high-quality CT datasets. J Cardiovasc Comput Tomogr. 2011;5:35–43.

    PubMed  CrossRef  Google Scholar 

  21. Lehman SJ, Schlett CL, Bamberg F, et al. Assessment of coronary plaque progression in coronary computed tomography angiography using a semiquantitative score. JACC Cardiovasc Imaging. 2009;2:1262–70.

    PubMed Central  PubMed  CrossRef  Google Scholar 

  22. Voros S, Rinehart S, Qian Z, et al. Coronary atherosclerosis imaging by coronary CT angiography: current status, correlation with intravascular interrogation and meta-analysis. JACC Cardiovasc Imaging. 2011;4:537–48.

    PubMed  CrossRef  Google Scholar 

  23. Otsuka M, Bruining N, Van Pelt NC, et al. Quantification of coronary plaque by 64-slice computed tomography: a comparison with quantitative intracoronary ultrasound. Invest Radiol. 2008;43: 314–21.

    PubMed  CrossRef  Google Scholar 

  24. Voros S, Rinehart S, Qian Z, et al. Prospective validation of standardized, 3-dimensional, quantitative coronary computed tomographic plaque measurements using radiofrequency backscatter intravascular ultrasound as reference standard in intermediate coronary arterial lesions: results from the ATLANTA (assessment of tissue characteristics, lesion morphology, and hemodynamics by angiography with fractional flow reserve, intravascular ultrasound and virtual histology, and noninvasive computed tomography in atherosclerotic plaques) I study. JACC Cardiovasc Interv. 2011; 4:198–208.

    PubMed  CrossRef  Google Scholar 

  25. Nakazato R, Shalev A, Doh JH, et al. Aggregate plaque volume by coronary computed tomography angiography is superior and incremental to luminal narrowing for diagnosis of ischemic lesions of intermediate stenosis severity. J Am Coll Cardiol. 2013; 62:460–7.

    PubMed  CrossRef  Google Scholar 

  26. Cheng VY, Nakazato R, Dey D, et al. Reproducibility of coronary artery plaque volume and composition quantification by 64-detector row coronary computed tomographic angiography: an intraobserver, interobserver, and interscan variability study. J Cardiovasc Comput Tomogr. 2009;3:312–20.

    PubMed  CrossRef  Google Scholar 

  27. Hachamovitch R, Di Carli MF. Methods and limitations of assessing new noninvasive tests: Part II: outcomes-based validation and reliability assessment of noninvasive testing. Circulation. 2008;117:2793–801.

    PubMed  CrossRef  Google Scholar 

  28. Min JK, Shaw LJ, Devereux RB, et al. Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. J Am Coll Cardiol. 2007;50:1161–70.

    PubMed  CrossRef  Google Scholar 

  29. Hulten EA, Carbonaro S, Petrillo SP, Mitchell JD, Villines TC. Prognostic value of cardiac computed tomography angiography: a systematic review and meta-analysis. J Am Coll Cardiol. 2011;57:1237–47.

    PubMed  CrossRef  Google Scholar 

  30. Min JK, Dunning A, Lin FY, 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;58:849–60.

    PubMed  CrossRef  Google Scholar 

  31. Chow BJ, Small G, Yam Y, et al. Incremental prognostic value of cardiac computed tomography in coronary artery disease using CONFIRM: COroNary computed tomography angiography evaluation for clinical outcomes: an InteRnational Multicenter registry. Circ Cardiovasc Imaging. 2011;4:463–72.

    PubMed  CrossRef  Google Scholar 

  32. Hadamitzky M, Achenbach S, Al-Mallah M, et al. Optimized Prognostic Score for Coronary Computed Tomographic Angiography: Results From the CONFIRM Registry (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter Registry). J Am Coll Cardiol. 2013;62: 468–76.

    PubMed  CrossRef  Google Scholar 

  33. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837–47.

    CAS  PubMed  CrossRef  Google Scholar 

  34. Metz LD, Beattie M, Hom R, Redberg RF, Grady D, Fleischmann KE. The prognostic value of normal exercise myocardial perfusion imaging and exercise echocardiography: a meta-analysis. J Am Coll Cardiol. 2007;49:227–37.

    PubMed  CrossRef  Google Scholar 

  35. Lin FY, Shaw LJ, Dunning AM, et al. Mortality risk in symptomatic patients with nonobstructive coronary artery disease: a prospective 2-center study of 2,583 patients undergoing 64-detector row coronary computed tomographic angiography. J Am Coll Cardiol. 2011;58:510–9.

    PubMed  CrossRef  Google Scholar 

  36. Versteylen MO, Kietselaer BL, Dagnelie PC, et al. Additive value of semiautomated quantification of coronary artery disease using cardiac computed tomographic angiography to predict future acute coronary syndrome. J Am Coll Cardiol. 2013;61:2296–305.

    PubMed  CrossRef  Google Scholar 

  37. Henneman MM, Schuijf JD, Pundziute G, et al. Noninvasive evaluation with multislice computed tomography in suspected acute coronary syndrome: plaque morphology on multislice computed tomography versus coronary calcium score. J Am Coll Cardiol. 2008;52:216–22.

    PubMed  CrossRef  Google Scholar 

  38. Hammer-Hansen S, Kofoed KF, Kelbaek H, et al. Volumetric evaluation of coronary plaque in patients presenting with acute myocardial infarction or stable angina pectoris-a multislice computerized tomography study. Am Heart J. 2009;157:481–7.

    PubMed  CrossRef  Google Scholar 

  39. Motoyama S, Kondo T, Sarai M, et al. Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol. 2007;50:319–26.

    PubMed  CrossRef  Google Scholar 

  40. Pflederer T, Marwan M, Schepis T, et al. Characterization of culprit lesions in acute coronary syndromes using coronary dual-source CT angiography. Atherosclerosis. 2010;211:437–44.

    CAS  PubMed  CrossRef  Google Scholar 

  41. Imazeki T, Sato Y, Inoue F, et al. Evaluation of coronary artery remodeling in patients with acute coronary syndrome and stable angina by multislice computed tomography. Circ J. 2004;68:1045–50.

    PubMed  CrossRef  Google Scholar 

  42. Tanaka A, Shimada K, Yoshida K, et al. Non-invasive assessment of plaque rupture by 64-slice multidetector computed tomography–comparison with intravascular ultrasound. Circ J. 2008;72:1276–81.

    PubMed  CrossRef  Google Scholar 

  43. Kashiwagi M, Tanaka A, Kitabata H, et al. Feasibility of noninvasive assessment of thin-cap fibroatheroma by multidetector computed tomography. JACC Cardiovasc Imaging. 2009;2:1412–9.

    PubMed  CrossRef  Google Scholar 

  44. Madder RD, Chinnaiyan KM, Marandici AM, Goldstein JA. Features of disrupted plaques by coronary computed tomographic angiography: correlates with invasively proven complex lesions. Circ Cardiovasc Imaging. 2011;4:105–13.

    PubMed  CrossRef  Google Scholar 

  45. Motoyama S, Sarai M, Harigaya H, et al. Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol. 2009;54:49–57.

    PubMed  CrossRef  Google Scholar 

  46. Virmani R, Burke AP, Farb A, Kolodgie FD. Pathology of the vulnerable plaque. J Am Coll Cardiol. 2006; 47:C13–8.

    CAS  PubMed  CrossRef  Google Scholar 

  47. Schmid M, Achenbach S, Ropers D, et al. Assessment of changes in non-calcified atherosclerotic plaque volume in the left main and left anterior descending coronary arteries over time by 64-slice computed tomography. Am J Cardiol. 2008;101:579–84.

    PubMed  CrossRef  Google Scholar 

  48. Hamirani YS, Kadakia J, Pagali SR, et al. Assessment of progression of coronary atherosclerosis using multidetector computed tomography angiography (MDCT). Int J Cardiol. 2011;149:270–4.

    PubMed  CrossRef  Google Scholar 

  49. Burgstahler C, Reimann A, Beck T, et al. Influence of a lipid-lowering therapy on calcified and noncalcified coronary plaques monitored by multislice detector computed tomography: results of the New Age II Pilot Study. Invest Radiol. 2007;42:189–95.

    CAS  PubMed  CrossRef  Google Scholar 

  50. Hachamovitch R, Di Carli MF. Nuclear cardiology will remain the “gatekeeper” over CT angiography. J Nucl Cardiol. 2007;14:634–44.

    PubMed  CrossRef  Google Scholar 

  51. Meijboom WB, Van Mieghem CA, van Pelt N, et al. Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol. 2008;52:636–43.

    PubMed  CrossRef  Google Scholar 

  52. Sarno G, Decraemer I, Vanhoenacker PK, et al. On the inappropriateness of noninvasive multidetector computed tomography coronary angiography to trigger coronary revascularization: a comparison with invasive angiography. JACC Cardiovasc Interv. 2009;2:550–7.

    PubMed  CrossRef  Google Scholar 

  53. Tonino PA, De Bruyne B, Pijls NH, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009; 360:213–24.

    CAS  PubMed  CrossRef  Google Scholar 

  54. De Bruyne B, Pijls NH, Kalesan B, et al. Fractional flow reserve-guided PCI versus medical therapy in stable coronary disease. N Engl J Med. 2012;367: 991–1001.

    PubMed  CrossRef  Google Scholar 

  55. Hachamovitch R, Berman DS, Kiat H, et al. Incremental prognostic value of adenosine stress myocardial perfusion single-photon emission computed tomography and impact on subsequent management in patients with or suspected of having myocardial ischemia. Am J Cardiol. 1997;80:426–33.

    CAS  PubMed  CrossRef  Google Scholar 

  56. Ko BS, Cameron JD, Meredith IT, et al. Computed tomography stress myocardial perfusion imaging in patients considered for revascularization: a comparison with fractional flow reserve. Eur Heart J. 2012; 33:67–77.

    PubMed  CrossRef  Google Scholar 

  57. Bettencourt N, Chiribiri A, Schuster A, et al. Direct comparison of cardiac magnetic resonance and multidetector computed tomography stress-rest perfusion imaging for detection of coronary artery disease. J Am Coll Cardiol. 2013;61:1099–107.

    PubMed  CrossRef  Google Scholar 

  58. Wong DT, Ko BS, Cameron JD, et al. Transluminal attenuation gradient in coronary computed tomography angiography is a novel noninvasive approach to the identification of functionally significant coronary artery stenosis: a comparison with fractional flow reserve. J Am Coll Cardiol. 2013;61(12):1271–9.

    PubMed  CrossRef  Google Scholar 

  59. Koo BK, Erglis A, Doh JH, et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol. 2011;58:1989–97.

    PubMed  CrossRef  Google Scholar 

  60. Taylor CA, Fonte TA, Min JK. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. 2013;61:2233–41.

    PubMed  CrossRef  Google Scholar 

  61. Min JK, Berman DS, Budoff MJ, et al. Rationale and design of the DeFACTO (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic AngiOgraphy) study. J Cardiovasc Comput Tomogr. 2011;5:301–9.

    PubMed  CrossRef  Google Scholar 

  62. Min JK, Leipsic J, Pencina MJ, et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012;308(12):1237–45.

    CAS  PubMed  CrossRef  Google Scholar 

  63. Choi JH, Min JK, Labounty TM, et al. Intracoronary transluminal attenuation gradient in coronary CT angiography for determining coronary artery stenosis. JACC Cardiovasc Imaging. 2011;4:1149–57.

    PubMed  CrossRef  Google Scholar 

  64. Kurata A, Mochizuki T, Koyama Y, et al. Myocardial perfusion imaging using adenosine triphosphate stress multi-slice spiral computed tomography: alternative to stress myocardial perfusion scintigraphy. Circ J. 2005;69:550–7.

    PubMed  CrossRef  Google Scholar 

  65. George RT, Arbab-Zadeh A, Miller JM, et al. Adenosine stress 64- and 256-row detector computed tomography angiography and perfusion imaging: a pilot study evaluating the transmural extent of perfusion abnormalities to predict atherosclerosis causing myocardial ischemia. Circ Cardiovasc Imaging. 2009; 2:174–82.

    PubMed Central  PubMed  CrossRef  Google Scholar 

  66. Ko BS, Cameron JD, Leung M, et al. Combined CT coronary angiography and stress myocardial perfusion imaging for hemodynamically significant stenoses in patients with suspected coronary artery disease: a comparison with fractional flow reserve. JACC Cardiovasc Imaging. 2012;5: 1097–111.

    PubMed  CrossRef  Google Scholar 

  67. Bamberg F, Becker A, Schwarz F, et al. Detection of hemodynamically significant coronary artery stenosis: incremental diagnostic value of dynamic CT-based myocardial perfusion imaging. Radiology. 2011;260: 689–98.

    PubMed  CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dennis T. L. Wong BSc (Med), MBBS (Hons), PhD, FRACP .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this chapter

Cite this chapter

Ko, B.S.H., Seneviratne, S.K., Wong, D.T.L. (2014). Emerging Role of Computed Tomography Angiography in the Evaluation of Coronary Atherosclerosis. In: Nicholls, S., Crowe, T. (eds) Imaging Coronary Atherosclerosis. Contemporary Cardiology. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0572-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-0572-0_12

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0571-3

  • Online ISBN: 978-1-4939-0572-0

  • eBook Packages: MedicineMedicine (R0)