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Fully automated pixel-wise quantitative CMR-myocardial perfusion with CMR-coronary angiography to detect hemodynamically significant coronary artery disease

  • Cardiac
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A Letter to the Editor to this article was published on 13 October 2023

Abstract

Objectives

We applied a fully automated pixel-wise post-processing framework to evaluate fully quantitative cardiovascular magnetic resonance myocardial perfusion imaging (CMR-MPI). In addition, we aimed to evaluate the additive value of coronary magnetic resonance angiography (CMRA) to the diagnostic performance of fully automated pixel-wise quantitative CMR-MPI for detecting hemodynamically significant coronary artery disease (CAD).

Methods

A total of 109 patients with suspected CAD were prospectively enrolled and underwent stress and rest CMR-MPI, CMRA, invasive coronary angiography (ICA), and fractional flow reserve (FFR). CMRA was acquired between stress and rest CMR-MPI acquisition, without any additional contrast agent. Finally, CMR-MPI quantification was analyzed by a fully automated pixel-wise post-processing framework.

Results

Of the 109 patients, 42 patients had hemodynamically significant CAD (FFR ≤ 0.80 or luminal stenosis ≥ 90% on ICA) and 67 patients had hemodynamically non-significant CAD (FFR ˃ 0.80 or luminal stenosis < 30% on ICA) were enrolled. On the per-territory analysis, patients with hemodynamically significant CAD had higher myocardial blood flow (MBF) at rest, lower MBF under stress, and lower myocardial perfusion reserve (MPR) than patients with hemodynamically non-significant CAD (p < 0.001). The area under the receiver operating characteristic curve of MPR (0.93) was significantly larger than those of stress and rest MBF, visual assessment of CMR-MPI, and CMRA (p < 0.05), but similar to that of the integration of CMR-MPI with CMRA (0.90).

Conclusions

Fully automated pixel-wise quantitative CMR-MPI can accurately detect hemodynamically significant CAD, but the integration of CMRA obtained between stress and rest CMR-MPI acquisition did not provide significantly additive value.

Key Points

• Full quantification of stress and rest cardiovascular magnetic resonance myocardial perfusion imaging can be postprocessed fully automatically, generating pixel-wise myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) maps.

• Fully quantitative MPR provided higher diagnostic performance for detecting hemodynamically significant coronary artery disease, compared with stress and rest MBF, qualitative assessment, and coronary magnetic resonance angiography (CMRA).

• The integration of CMRA and MPR did not significantly improve the diagnostic performance of MPR alone.

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Abbreviations

CAD:

Coronary artery disease

CMD:

Coronary microvascular dysfunction

CMRA:

Coronary magnetic resonance angiography

CMR-MPI:

Cardiovascular magnetic resonance myocardial perfusion imaging

FFR:

Fractional flow reserve

ICA:

Invasive coronary angiography

MBF:

Myocardial blood flow

MPR:

Myocardial perfusion reserve

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Funding

This study has received funding from the Shanghai Science and Technology Committee (grant number: 18DZ1930102), the Shanghai Municipal Key Clinical Specialty (grant number: shslczdzk03202), the Science Foundation of Shanghai Municipal Health Commission (grant numbers: 202140291 and 202040349), and the Shanghai Pujiang Program (grant number: 21PJD012).

Author information

Author notes

  1. Shi-hai Zhao and Wei-feng Guo contributed equally to this work

Authors and Affiliations

  1. Department of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China

    Shi-hai Zhao, Wei-feng Guo, Shan Yang, Hong Yun, Yin-yin Chen, Meng-su Zeng & Hang **

  2. Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China

    Shi-hai Zhao, Wei-feng Guo, Shan Yang, Hong Yun, Yin-yin Chen, Meng-su Zeng & Hang **

  3. Department of Cardiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Cardiovascular Diseases, Shanghai, China

    Zhi-feng Yao & Chen-guang Li

  4. Circle Cardiovascular Imaging, Calgary, Alberta, Canada

    Tong-tong Han

  5. MR Collaboration, Siemens Healthineers Ltd., Shanghai, China

    **ao-yue Zhou

  6. Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China

    Cai-xia Fu

  7. Department of Echocardiography, Zhongshan Hospital, Fudan University, Shanghai, China

    Cui-zhen Pan

Authors
  1. Shi-hai Zhao
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Corresponding authors

Correspondence to Meng-su Zeng, Chen-guang Li or Hang **.

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Guarantor

The scientific guarantor of this publication is Meng-su Zeng, MD, PhD.

Conflict of interest

Two authors (**ao-yue Zhou, Cai-xia Fu) are employees of Siemens. The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

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Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

No study subjects or cohorts have been previously reported.

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Zhao, Sh., Guo, Wf., Yao, Zf. et al. Fully automated pixel-wise quantitative CMR-myocardial perfusion with CMR-coronary angiography to detect hemodynamically significant coronary artery disease. Eur Radiol 33, 7238–7249 (2023). https://doi.org/10.1007/s00330-023-09689-8

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