European Radiology

, Volume 17, Issue 6, pp 1445–1451 | Cite as

Visual and automatic grading of coronary artery stenoses with 64-slice CT angiography in reference to invasive angiography

  • Stephanie Busch
  • Thorsten R. C. Johnson
  • Konstantin Nikolaou
  • Franz von Ziegler
  • Andreas Knez
  • Maximilian F. Reiser
  • Christoph R. Becker
Cardiac

Abstract

The aim of this study was to assess the performance of a software tool for quantitative coronary artery analysis of computed tomography coronary angiography (CT-QCA) in comparison with invasive coronary angiography with quantitative analysis (CAG-QCA) as standard of reference. Two radiologists reviewed the CT angiography data sets (Siemens Sensation 64) of 25 patients, grading coronary artery stenoses visually and with a software tool (Circulation, Siemens). Twenty-three data sets with sufficient image quality were included in the final analysis. CAG revealed a total of 30 wall irregularities and 28 stenoses, of which 17 were graded as moderate and nine as hemodynamically significant. CT-QCA showed a better agreement to CAG-QCA, with a systematic overestimation of the degree of stenosis of 6.1% and limits of agreement of +36.1% and −23.9; the correlation coefficient was 0.82 (p < 0.0001). Using CT-QCA, sensitivity, specificity, and positive and negative predictive value were 89%, 100%, 89%, and 100%, respectively, for significant area stenoses greater than 75%. The positive predictive value for the visual assessment amounted to 53%. Interobserver variability between CT-QCA and visual assessment showed a kappa value of 0.72. In conclusion, software-supported CT-QCA makes it possible to quantify significant coronary artery stenoses automatically, with good agreement to CAG-QCA.

Keywords

Coronary angiography Computed tomography Coronary stenosis Computer aided diagnosis 

References

  1. 1.
    Greuter MJ, Dorgelo J, Tukker WG, Oudkerk M (2005) Study on motion artifacts in coronary arteries with an anthropomorphic moving heart phantom on an ECG-gated multidetector computed tomography unit. Eur Radiol 15:995–1007PubMedCrossRefGoogle Scholar
  2. 2.
    Horiguchi J, Fukuda H, Yamamoto H, Hirai N, Alam F, Kakizawa H, Hieda M, Tachikake T, Marukawa K, Ito K (2006) The impact of motion artifacts on the reproducibility of repeated coronary artery calcium measurements. Eur Radiol DOI 10.1007/s00330-006-0278-2
  3. 3.
    Knez A, Becker C, Ohnesorge B, Haberl R, Reiser M, Steinbeck G (2000) Noninvasive detection of coronary artery stenosis by multislice helical computed tomography. Circulation 101:E221–E222PubMedGoogle Scholar
  4. 4.
    Flohr TG, McCollough CH, Bruder H, Petersilka M, Gruber K, Suss C, Grasruck M, Stierstorfer K, Krauss B, Raupach R, Primak AN, Kuttner A, Achenbach S, Becker C, Kopp A, Ohnesorge BM (2006) First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol 16:256–268PubMedCrossRefGoogle Scholar
  5. 5.
    Johnson TR, Nikolaou K, Wintersperger BJ, Leber AW, von Ziegler F, Rist C, Buhmann S, Knez A, Reiser MF, Becker CR (2006) Dual-source CT cardiac imaging: initial experience. Eur Radiol 16:1409–1415PubMedCrossRefGoogle Scholar
  6. 6.
    Knez A, Becker CR, Leber A, Ohnesorge B, Becker A, White C, Haberl R, Reiser MF, Steinbeck G (2001) Usefulness of multislice spiral computed tomography angiography for determination of coronary artery stenoses. Am J Cardiol 88:1191–1194PubMedCrossRefGoogle Scholar
  7. 7.
    Leber AW, Knez A, von Ziegler F, Becker A, Nikolaou K, Paul S, Wintersperger B, Reiser M, Becker CR, Steinbeck G, Boekstegers P (2005) Quantification of obstructive and nonobstructive coronary lesions by 64-slice computed tomography: a comparative study with quantitative coronary angiography and intravascular ultrasound. J Am Coll Cardiol 46:147–154PubMedCrossRefGoogle Scholar
  8. 8.
    Achenbach S, Ropers D, Hoffmann U, MacNeill B, Baum U, Pohle K, Brady TJ, Pomerantsev E, Ludwig J, Flachskampf FA, Wicky S, Jang IK, Daniel WG (2004) Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol 43:842–847PubMedCrossRefGoogle Scholar
  9. 9.
    Ferencik M, Nomura CH, Maurovich-Horvat P, Hoffmann U, Pena AJ, Cury RC, Abbara S, Nieman K, Fatima U, Achenbach S, Brady TJ (2006) Quantitative parameters of image quality in 64-slice computed tomography angiography of the coronary arteries. Eur J Radiol 57:373–379PubMedCrossRefGoogle Scholar
  10. 10.
    Cury RC, Pomerantsev EV, Ferencik M, Hoffmann U, Nieman K, Moselewski F, Abbara S, Jang IK, Brady TJ, Achenbach S (2005) Comparison of the degree of coronary stenoses by multidetector computed tomography versus by quantitative coronary angiography. Am J Cardiol 96:784–787PubMedCrossRefGoogle Scholar
  11. 11.
    Gerber TC, Breen JF, Kuzo RS, Kantor B, Williamson EE, Safford RE, Morin RL (2006) Computed tomographic angiography of the coronary arteries: techniques and applications. Semin Ultrasound CT MR 27:42–55PubMedCrossRefGoogle Scholar
  12. 12.
    Kyriakou Y, Kachelriess M, Knaup M, Krause JU, Kalender WA (2006) Impact of the z-flying focal spot on resolution and artifact behavior for a 64-slice spiral CT scanner. Eur Radiol 16:1206–1215PubMedCrossRefGoogle Scholar
  13. 13.
    Austen WG, Edwards JE, Frye RL, Gensini GG, Gott VL, Griffith LS, McGoon DC, Murphy ML, Roe BB (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 51:5–40PubMedGoogle Scholar
  14. 14.
    Moselewski F, Ferencik M, Achenbach S, Abbara S, Cury RC, Booth SL, Jang IK, Brady TJ, Hoffmann U (2006) Threshold-dependent variability of coronary artery calcification measurements – implications for contrast-enhanced multi-detector row-computed tomography. Eur J Radiol 57:390–395PubMedCrossRefGoogle Scholar
  15. 15.
    Mollet NR, Cademartiri F, Nieman K, Saia F, Lemos PA, McFadden EP, Pattynama PM, Serruys PW, Krestin GP, de Feyter PJ (2004) Multislice spiral computed tomography coronary angiography in patients with stable angina pectoris. J Am Coll Cardiol 43:2265–2270PubMedCrossRefGoogle Scholar
  16. 16.
    Herrington DM, Siebes M, Sokol DK, Siu CO, Walford GD (1993) Variability in measures of coronary lumen dimensions using quantitative coronary angiography. J Am Coll Cardiol 22:1068–1074PubMedCrossRefGoogle Scholar
  17. 17.
    Achenbach S, Moselewski F, Ropers D, Ferencik M, Hoffmann U, MacNeill B, Pohle K, Baum U, Anders K, Jang IK, Daniel WG, Brady TJ (2004) Detection of calcified and noncalcified coronary atherosclerotic plaque by contrast-enhanced, submillimeter multidetector spiral computed tomography: a segment-based comparison with intravascular ultrasound. Circulation 109:14–17PubMedCrossRefGoogle Scholar
  18. 18.
    Mahnken AH, Wildberger JE, Sinha AM, Dedden K, Stanzel S, Hoffmann R, Schmitz-Rode T, Gunther RW (2003) Value of 3D-volume rendering in the assessment of coronary arteries with retrospectively ECG-gated multislice spiral CT. Acta Radiol 44:302–309PubMedCrossRefGoogle Scholar
  19. 19.
    Escaned J, Baptista J, Di Mario C, Haase J, Ozaki Y, Linker DT, de Feyter PJ, Roelandt JR, Serruys PW (1996) Significance of automated stenosis detection during quantitative angiography. Insights gained from intracoronary ultrasound imaging. Circulation 94:966–972PubMedGoogle Scholar
  20. 20.
    Swallow RA, Court IA, Calver AL, Curzen NP (2006) The limitations of coronary angiography: identification of a critical coronary stenosis using intravascular ultrasound. Int J Cardiol 106:123–125PubMedCrossRefGoogle Scholar
  21. 21.
    Martuscelli E, Romagnoli A, D’Eliseo A, Razzini C, Tomassini M, Sperandio M, Simonetti G, Romeo F (2004) Accuracy of thin-slice computed tomography in the detection of coronary stenoses. Eur Heart J 25:1043–1048PubMedCrossRefGoogle Scholar
  22. 22.
    Brown MS, Goldin JG, Rogers S, Kim HJ, Suh RD, McNitt-Gray MF, Shah SK, Truong D, Brown K, Sayre JW, Gjertson DW, Batra P, Aberle DR (2005) Computer-aided lung nodule detection in CT: results of large-scale observer test. Acad Radiol 12:681–686PubMedCrossRefGoogle Scholar
  23. 23.
    Hermiller JB, Cusma JT, Spero LA, Fortin DF, Harding MB, Bashore TM (1992) Quantitative and qualitative coronary angiographic analysis: review of methods, utility, and limitations. Cathet Cardiovasc Diagn 25:110–131PubMedCrossRefGoogle Scholar
  24. 24.
    Cademartiri F, Mollet NR, Runza G, Bruining N, Hamers R, Somers P, Knaapen M, Verheye S, Midiri M, Krestin GP, de Feyter PJ (2005) Influence of intracoronary attenuation on coronary plaque measurements using multislice computed tomography: observations in an ex vivo model of coronary computed tomography angiography. Eur Radiol 15:1426–1431PubMedCrossRefGoogle Scholar
  25. 25.
    Nikolaou K, Flohr T, Knez A (2004) Advances in cardiac CT imaging: 64-slice scanner. Int J Cardiovasc Imaging.20:535–540PubMedCrossRefGoogle Scholar
  26. 26.
    Nikolaou K, Knez A, Rist C (2006) Accuracy of 64-MDCT in the diagnosis of ischemic heart disease. AJR Am J Roentgenol 187:111–117PubMedCrossRefGoogle Scholar
  27. 27.
    Nikolaou K, Rist C, Wintersperger BJ (2006) Clinical value of MDCT in the diagnosis of coronary artery disease in patients with a low pretest likelihood of significant disease. AJR Am J Roentgenol 186:1659–1668PubMedCrossRefGoogle Scholar
  28. 28.
    Nikolaou K, Becker CR, Wintersperger BJ, Rist C (2004) Evaluating multislice computed tomography for imaging coronary atherosclerosis. Radiologe 44(2):130–139PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Stephanie Busch
    • 1
  • Thorsten R. C. Johnson
    • 1
  • Konstantin Nikolaou
    • 1
  • Franz von Ziegler
    • 2
  • Andreas Knez
    • 2
  • Maximilian F. Reiser
    • 1
  • Christoph R. Becker
    • 1
  1. 1.Department of Clinical RadiologyUniversity of MunichMunichGermany
  2. 2.Department of Cardiology, Medical Clinic IUniversity of MunichMunichGermany

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