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Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics

  • Cardiac
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Abstract

Objective

To determine whether radiomics analysis of pericoronary adipose tissue (PCAT) captured by coronary computed tomography angiography (CCTA) could discriminate acute myocardial infarction (MI) from unstable angina (UA).

Methods

In a single-center retrospective case-control study, patients with acute MI (n = 105) were matched to patients with UA (n = 105) and all patients were randomly divided into training and validation cohorts with a ratio of 7:3. Fat attenuation index (FAI) and PCAT radiomics features selected by Max-Relevance and Min-Redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) around the proximal three major epicardial coronary vessels (LAD [left anterior descending artery], LCx [left circumflex artery], and RCA [right coronary artery]) were used to build logistic regression models. Finally, a FAI model, three radiomics models of PCAT (LAD, LCx, and RCA), and a combined model that used the scores of these independent models were constructed. The performance of the models was evaluated by identification, calibration, and clinical application.

Results

In training and validation cohorts, compared with the FAI model (AUC = 0.53, 0.50), the combined model achieved superior performance (AUC = 0.97, 0.95) while there was a significant difference of AUC between two models (p < 0.05). The calibration curves of the combined model demonstrated the smallest Brier score loss. Decision curve analysis suggested that the combined model provided higher clinical benefit than the FAI model.

Conclusions

The CCTA–based radiomics phenotype of PCAT outperforms the FAI model in discriminating acute MI from UA. The combination of PCAT radiomics and FAI could further enhance the performance of acute MI identification.

Key Points

• Fat attenuation index based on CCTA can detect inflammation-induced changes in the ratio of lipid to aqueous phase in pericoronary adipose tissue.

• Fat attenuation index cannot distinguish acute MI patients from UA patients, suggesting that the two groups have the same degree of ratio of lipid to aqueous phase in pericoronary adipose tissue.

• Radiomics features of PCAT have the potential to distinguish acute MI patients from UA patients.

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Abbreviations

ACE-I:

Angiotensin-converting enzyme inhibitor

ACS:

Acute coronary syndrome

ARB:

Angiotensin receptor blocker

BMI:

Body mass index

BP:

Blood pressure

CAD:

Coronary artery disease

CCTA:

Coronary computed tomography angiography

DLP:

Dose-length product

ECG:

Electrocardiogram

FAI:

Fat attenuation index

HDL:

High-density lipoprotein

HIS:

Hospital information system

LAD:

Left anterior descending artery

LASSO:

Least absolute shrinkage and selection operator

LCx:

Left circumflex artery

LDL:

Low-density lipoprotein

MI:

Myocardial infarction

mRMR:

Max-Relevance and Min-Redundancy

PCAT:

Pericoronary adipose tissue

RCA:

Right coronary artery

UA:

Unstable angina

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Acknowledgements

Thanks to **g**g Cui and Fan Yang for their help in the processing of PCAT segmentation and radiomics feature extraction.

Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Department of Radiology, Fourth Affiliated Hospital of Harbin Medical University, No. 37, YiYuan Street, NanGang District, Harbin, 150001, HeiLongJiang Province, China

    Nuo Si, Ke Shi, Na Li, **aolin Dong, Chentao Zhu & Tong Zhang

  2. GE Healthcare, No. 1, TongJi South Road, Daxing District, Bei**g, China

    Yan Guo & Jiesi Hu

  3. Department of Research and Development, Shanghai United Imaging Intelligence, Co., Ltd., No. 2258, ChengBei Road, JiaDing District, Shanghai, 201807, China

    **g**g Cui & Fan Yang

Authors
  1. Nuo Si
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  10. Tong Zhang
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Corresponding author

Correspondence to Tong Zhang.

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Guarantor

The scientific guarantor of this publication is Tong Zhang.

Conflict of interest

Two of the authors of this manuscript (Yan Guo, Jiesi Hu) are employees of GE Healthcare. Two of the authors of this manuscript (**g**g Cui, Fan Yang) are employees of Shanghai United Imaging Intelligence, Co., Ltd. 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

Yan Guo and Jiesi Hu kindly provided statistical advice for this manuscript.

Informed consent

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

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• case-control study

• performed at one institution

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Si, N., Shi, K., Li, N. et al. Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics. Eur Radiol 32, 6868–6877 (2022). https://doi.org/10.1007/s00330-022-08812-5

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  • DOI: https://doi.org/10.1007/s00330-022-08812-5

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