Abstract
Objective
To evaluate the diagnostic performance of automated coronary atherosclerotic plaque quantification (QCT) by different users (expert/non-expert/automatic).
Methods
One hundred fifty coronary artery segments from 142 patients who underwent coronary computed tomography angiography (CCTA) and intravascular ultrasound (IVUS) were analyzed. Minimal lumen area (MLA), maximal lumen area stenosis percentage (%AS), mean plaque burden percentage (%PB), and plaque volume were measured semi-automatically by expert, non-expert, and fully automatic QCT analyses, and then compared to IVUS.
Results
Between IVUS and expert QCT analysis, the correlation coefficients (r) for the MLA, %AS, %PB, and plaque volume were excellent: 0.89 (p < 0.001), 0.84 (p < 0.001), 0.91 (p < 0.001), and 0.94 (p < 0.001), respectively. There were no significant differences in the mean parameters (all p values >0.05) except %AS (p = 0.01). The automatic QCT analysis showed comparable performance to non-expert QCT analysis, showing correlation coefficients (r) of the MLA (0.80 vs. 0.82), %AS (0.82 vs. 0.80), %PB (0.84 vs. 0.73), and plaque volume (0.84 vs. 0.79) when they were compared to IVUS, respectively.
Conclusion
Fully automatic QCT analysis showed clinical utility compared with IVUS, as well as a compelling performance when compared with semiautomatic analyses.
Key Points
• Coronary CTA enables the assessment of coronary atherosclerotic plaque.
• High-risk plaque characteristics and overall plaque burden can predict future cardiac events.
• Coronary atherosclerotic plaque quantification is currently unfeasible in practice.
• Quantitative computed tomography coronary plaque analysis software (QCT) enables feasible plaque quantification.
• Fully automatic QCT analysis shows excellent performance.
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Abbreviations
- CCTA:
-
Coronary computed tomography angiography
- QCT:
-
Quantitative computed tomography
- ICA:
-
Invasive coronary angiography
- IVUS:
-
Intravascular ultrasound
- CAD:
-
Coronary artery disease
- CI:
-
Confidence interval
- MLA:
-
Minimal lumen area
- MLD:
-
Minimal lumen diameter
- %DS:
-
Maximal lumen diameter stenosis percentage
- %AS:
-
Maximal lumen area stenosis percentage
- %PB:
-
Mean plaque burden percentage
References
Miller JM, Rochitte CE, Dewey M et al (2008) Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med 359:2324–2336
Hoffmann MH, Shi H, Schmitz BL et al (2005) Noninvasive coronary angiography with multislice computed tomography. JAMA 293:2471–2478
Cordeiro MA, Lima JA (2006) Atherosclerotic plaque characterization by multidetector row computed tomography angiography. J Am Coll Cardiol 47:C40–C47
Hoffmann U, Moselewski F, Nieman K et al (2006) Noninvasive assessment of plaque morphology and composition in culprit and stable lesions in acute coronary syndrome and stable lesions in stable angina by multidetector computed tomography. J Am Coll Cardiol 47:1655–1662
Motoyama S, Kondo T, Sarai M et al (2007) Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol 50:319–326
Motoyama S, Sarai M, Harigaya H et al (2009) Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol 54:49–57
Stone GW, Maehara A, Lansky AJ et al (2011) A prospective natural-history study of coronary atherosclerosis. N Engl J Med 364:226–235
Nakazato R, Shalev A, Doh JH et al (2013) 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 62:460–467
Narula J, Garg P, Achenbach S, Motoyama S, Virmani R, Strauss HW (2008) Arithmetic of vulnerable plaques for noninvasive imaging. Nat Clin Pract Cardiovasc Med 5(Suppl 2):S2–S10
Bischoff B, Meinel FG, Del Prete A, Reiser MF, Becker HC (2013) High-pitch coronary CT angiography in dual-source CT during free breathing vs. breath holding in patients with low heart rates. Eur J Radiol. doi:10.1016/j.ejrad.2013.09.003
Min JK, Arsanjani R, Kurabayashi S et al (2013) Rationale and design of the ViCTORY (Validation of an Intracycle CT Motion CORrection Algorithm for Diagnostic AccuracY) trial. J Cardiovasc Comput Tomogr 7:200–206
Schaap M, Metz CT, van Walsum T et al (2009) Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms. Med Image Anal 13:701–714
Boogers MJ, Broersen A, van Velzen JE et al (2012) Automated quantification of coronary plaque with computed tomography: comparison with intravascular ultrasound using a dedicated registration algorithm for fusion-based quantification. Eur Heart J 33:1007–1016
de Graaf MA, Broersen A, Kitslaar PH et al (2013) Automatic quantification and characterization of coronary atherosclerosis with computed tomography coronary angiography: cross-correlation with intravascular ultrasound virtual histology. Int J Cardiovasc Imaging 29:1177–1190
Heo JH, Brugaletta S, Garcia-Garcia HM et al (2011) Reproducibility of intravascular ultrasound iMAP for radiofrequency data analysis: Implications for design of longitudinal studies. Catheter Cardiovasc Interv. doi:10.1002/ccd.23335
Bruining N, Roelandt JR, Palumbo A et al (2007) Reproducible coronary plaque quantification by multislice computed tomography. Catheter Cardiovasc Interv 69:857–865
Hoffmann U, Bamberg F, Chae CU et al (2009) Coronary computed tomography angiography for early triage of patients with acute chest pain: the ROMICAT (Rule Out Myocardial Infarction using Computer Assisted Tomography) trial. J Am Coll Cardiol 53:1642–1650
Kang KW, Chang HJ, Shim H et al (2012) Feasibility of an automatic computer-assisted algorithm for the detection of significant coronary artery disease in patients presenting with acute chest pain. Eur J Radiol 81:e640–e646
Anders K, Achenbach S, Petit I, Daniel WG, Uder M, Pflederer T (2013) Accuracy of automated software-guided detection of significant coronary artery stenosis by CT angiography: comparison with invasive catheterisation. Eur Radiol 23:1218–1225
Rajiah P, Schoenhagen P (2013) Automated interpretation and reporting of coronary CT coronary angiography. Curr Cardiovasc Imaging Rep 6:282
Acknowledgments
The scientific guarantor of this publication is Hyuk-Jae Chang. 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. This research was supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (MSIP) (No. 2012027176). No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Methodology: retrospective, diagnostic or prognostic study, multicenter study.
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Park, HB., Lee, B.K., Shin, S. et al. Clinical Feasibility of 3D Automated Coronary Atherosclerotic Plaque Quantification Algorithm on Coronary Computed Tomography Angiography: Comparison with Intravascular Ultrasound. Eur Radiol 25, 3073–3083 (2015). https://doi.org/10.1007/s00330-015-3698-z
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DOI: https://doi.org/10.1007/s00330-015-3698-z