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Clinical Feasibility of 3D Automated Coronary Atherosclerotic Plaque Quantification Algorithm on Coronary Computed Tomography Angiography: Comparison with Intravascular Ultrasound

  • Cardiac
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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

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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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Authors and Affiliations

  1. Yonsei-Cedar Sinai Integrative Cardiovascular Imaging Research Center, Yonsei University Health System, Seoul, South Korea

    Hyung-Bok Park, Sanghoon Shin, Ran Heo, Hyuk-Jae Chang & Namsik Chung

  2. Division of Cardiology, Cardiovascular Center, Myongji Hospital, Goyang, South Korea

    Hyung-Bok Park

  3. Division of Cardiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea

    Byoung Kwon Lee

  4. Division of Cardiology, National Health Insurance Corporation Ilsan Hospital, Goyang, South Korea

    Sanghoon Shin

  5. Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University Health System, 50 Yonsei-ro, Seodaemun-gu, Seoul, South Korea, 120-752

    Ran Heo, Hyuk-Jae Chang, Myeong-Ki Hong, Yangsoo Jang & Namsik Chung

  6. Departments of Imaging and Medicine, Cedars-Sinai Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Reza Arsanjani

  7. Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands

    Pieter H. Kitslaar, Alexander Broersen & Jouke Dijkstra

  8. Medis medical Imaging Systems B.V., Leiden, The Netherlands

    Pieter H. Kitslaar

  9. Division of Cardiology, Yonsei University Wonju Severance Christian Hospital, Wonju, South Korea

    Sung Gyun Ahn

  10. Institute for Cardiovascular Imaging, Weill-Cornell Medical College, New York-Presbyterian Hospital, New York, NY, USA

    James K. Min

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  1. Hyung-Bok Park
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Corresponding author

Correspondence to Hyuk-Jae Chang.

Appendix

Appendix

Table 5 Mean and SD measurements of IVUS and QCT (Expert/Non-expert/Automatic)
Full size table
Table 6 Correlation coefficient (r) between IVUS and QCT (Expert/Non-expert/Automatic)
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Fig. 4
figure 4

Bland–Altman analyses of minimal lumen area between IVUS and QCT (expert (a) /non-expert (c) /automatic (e)). Abbreviations as in Fig. 1

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Fig. 5
figure 5

Bland–Altman analyses of maximal lumen area stenosis percentage between IVUS and QCT (expert (a, b) /non-expert (c, d) /automatic (e, f)). Abbreviations as in Fig. 1

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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

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