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Quantification of the myocardial area at risk using coronary CT angiography and Voronoi algorithm-based myocardial segmentation

  • Cardiac
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Abstract

Objectives

The purpose of this study was to estimate the myocardial area at risk (MAAR) using coronary computed tomography angiography (CTA) and Voronoi algorithm-based myocardial segmentation in comparison with single-photon emission computed tomography (SPECT).

Methods

Thirty-four patients with coronary artery disease underwent 128-slice coronary CTA, stress/rest thallium-201 SPECT, and coronary angiography (CAG). CTA-based MAAR was defined as the sum of all CAG stenosis (>50 %) related territories (the ratio of the left ventricular volume). Using automated quantification software (17-segment model, 5-point scale), SPECT-based MAAR was defined as the number of segments with a score above zero as compared to the total 17 segments by summed stress score (SSS), difference (SDS) score map, and comprehensive SPECT interpretation with either SSS or SDS best correlating CAG findings (SSS/SDS). Results were compared using Pearson's correlation coefficient.

Results

Forty-nine stenoses were observed in 102 major coronary territories. Mean value of CTA-based MAAR was 28.3 ± 14.0 %. SSS-based, SDS-based, and SSS/SDS-based MAAR was 30.1 ± 6.1 %, 20.1 ± 15.8 %, and 26.8 ± 15.7 %, respectively. CTA-based MAAR was significantly related to SPECT-based MAAR (r = 0.531 for SSS; r = 0.494 for SDS; r = 0.814 for SSS/SDS; P < 0.05 in each).

Conclusions

CTA-based Voronoi algorithm myocardial segmentation reliably quantifies SPECT-based MAAR.

Key points

• Voronoi algorithm allows for three-dimensional myocardial segmentation of coronary CT angiography

• Stenosis-related CT myocardial territories correlate to SPECT based area at risk

• CT angiography myocardial segmentation may assist in clinical decision-making

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Abbreviations

CABG:

Coronary artery bypass grafting

CAD:

Coronary artery disease

CTA:

CT angiography

LV:

Left ventricle (ventricular)

MDCT:

Multidetector-row computed tomography

MPI:

Myocardial perfusion imaging

MAAR:

Myocardial area at risk

PCI:

Percutaneous coronary intervention

QCA:

Quantitative coronary analysis

SPECT:

Single-photon emission computed tomography

3-D:

Three-dimensional

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Acknowledgements

The scientific guarantor of this publication is Koen Nieman. 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. The authors state that this work has not received any funding. 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 observational multicenter study.

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Authors and Affiliations

  1. Department of Radiology, Erasmus University Medical Center, ‘s-Gravendijkwal 230, Rotterdam, 3015CE, The Netherlands

    Akira Kurata, Atsushi Kono, Adriaan Coenen, Raluca G. Saru-Chelu, Pim J. de Feyter, Gabriel P. Krestin & Koen Nieman

  2. Department of Cardiology, Erasmus University Medical Center, Rotterdam, The Netherlands

    Pim J. de Feyter & Koen Nieman

  3. Development Division, AZE inc, Chiyoda, Tokyo, Japan

    Tsuyoshi Sakamoto

  4. Department of Radiology, Ehime University Graduate School of Medicine, Toon, Ehime, Japan

    Teruhito Kido & Teruhito Mochizuki

  5. Department of Radiology, Yotsuba Circulation Clinic, Matsuyama, Ehime, Japan

    Hiroshi Higashino

  6. Department of Cardiology, Yotsuba Circulation Clinic, Matsuyama, Ehime, Japan

    Mitsunori Abe

Authors
  1. Akira Kurata
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  2. Atsushi Kono
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  3. Tsuyoshi Sakamoto
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  4. Teruhito Kido
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  6. Hiroshi Higashino
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  7. Mitsunori Abe
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  8. Adriaan Coenen
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  9. Raluca G. Saru-Chelu
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  11. Gabriel P. Krestin
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  12. Koen Nieman
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Corresponding author

Correspondence to Akira Kurata.

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Kurata, A., Kono, A., Sakamoto, T. et al. Quantification of the myocardial area at risk using coronary CT angiography and Voronoi algorithm-based myocardial segmentation. Eur Radiol 25, 49–57 (2015). https://doi.org/10.1007/s00330-014-3388-2

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  • DOI: https://doi.org/10.1007/s00330-014-3388-2

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